From 7b153e0857780844626b4e28104f8096736b5992 Mon Sep 17 00:00:00 2001 From: Borja Perez I Guasch Date: Mon, 15 Nov 2021 14:52:45 +0100 Subject: [PATCH 1/7] Corrected typos --- content/rendering-with-batch/_index.md | 8 +++---- content/rendering-with-batch/batch/_index.md | 8 +++---- .../batch/compute_environment.md | 4 ++-- .../batch/job_definition.md | 4 ++-- .../rendering-with-batch/batch/job_queue.md | 4 ++-- .../rendering-with-batch/batch/submit_job.md | 4 ++-- content/rendering-with-batch/cleanup.md | 4 ++-- .../rendering-with-batch/ecr-repository.md | 23 +++++++++---------- .../rendering-with-batch/final_thoughts.md | 4 ++-- content/rendering-with-batch/monitor_job.md | 7 +++--- .../rendering_pipeline.md | 2 +- content/rendering-with-batch/start/_index.md | 2 +- .../start/review-outputs.md | 4 ++-- 13 files changed, 38 insertions(+), 40 deletions(-) diff --git a/content/rendering-with-batch/_index.md b/content/rendering-with-batch/_index.md index d63a32cc..978fa092 100644 --- a/content/rendering-with-batch/_index.md +++ b/content/rendering-with-batch/_index.md @@ -7,17 +7,17 @@ pre: "8. " --- {{% notice info %}} -The estimated completion time of this lab is **60 minutes**. Please note Rendering the animation presented below can incur in costs up to **$15**. +The estimated completion time of this lab is **60 minutes**. Please note that rendering the animation presented below can incur in costs up to **$15**. {{% /notice %}} ## Overview In this workshop you will learn to submit jobs with [AWS Batch](https://aws.amazon.com/batch/) following Spot best practices to [render](https://en.wikipedia.org/wiki/Rendering_(computer_graphics)) a [Blender](https://www.blender.org/) file in a distributed way. You will be creating a docker container and publishing it in Amazon Elastic Container Registry (ECR). Then you will use that container in AWS Batch using a mix of EC2 On-Demand and Spot instances. [Spot instances](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-spot-instances.html) are EC2 spare capacity offered at steep discounts compared to On-Demand instances and are a cost-effective choice for applications that can be interrupted, what makes them well-suited for the batch processing that we will run. After going through all the sections, you will have the following pipeline created: -1. A python script downloads the Blender file from S3 to extract the number of frames from the Blender project. -2. The script submits a batch using an `array job` with as many tasks as number of frames. It also submits a single stitching job using [FFmpeg](https://ffmpeg.org/) to create a final video file. +1. A python script downloads the Blender file from S3 to extract the number of frames from the Blender project. +2. The script submits a batch job using an `array job` with as many tasks as number of frames. It also submits a single stitching job using [FFmpeg](https://ffmpeg.org/) to create a final video file. 3. Each of the jobs in the rendering job array run a Docker container that executes Blender to render a slice of frames, and after uploads them to S3. -The outcome of the workshop would be the following animation. +The outcome of the workshop would be the following animation: ![Pottery output](/images/rendering-with-batch/animation_example.gif) diff --git a/content/rendering-with-batch/batch/_index.md b/content/rendering-with-batch/batch/_index.md index 947c30a1..d3f6fde3 100644 --- a/content/rendering-with-batch/batch/_index.md +++ b/content/rendering-with-batch/batch/_index.md @@ -22,12 +22,12 @@ If you want to learn in detail all its capabilities, visit [this web page](https ## Understanding Batch components -In this section we will go through each individual AWS Batch architecture component, starting with the typical AWS Batch job architecture. In the diagram below you can see how +In this section we will go through each individual AWS Batch architecture component, starting with the typical AWS Batch job architecture. In the diagram below you can see how: -1. The user start triggering an event by uploading a S3 object -2. You can automate and trigger the submission of one or more jobs using [AWS Lambda](https://aws.amazon.com/lambda/) or manage [AWS Batch with Step functions](https://docs.aws.amazon.com/step-functions/latest/dg/connect-batch.html). The job gets submitted to a **Job queue** using a **Job Definition**. +1. The user starts triggering an event by uploading a S3 object. +2. You can automate and trigger the submission of one or more jobs using [AWS Lambda](https://aws.amazon.com/lambda/) or manage [AWS Batch with Step functions](https://docs.aws.amazon.com/step-functions/latest/dg/connect-batch.html). The job gets submitted to a **Job queue** using a **Job Definition**. 3. AWS Batch will schedule the jobs submitted using **Compute Environments**. It will procure new resources when needed and allocate the job accordingly. -4. The Compute Environment resources (EC2 Instances or Fargate) will run the job and in this workshop and example, it will store the output of into S3. +4. The Compute Environment resources (EC2 Instances or Fargate) will run the job and store the output in S3 (as in this workshop). ![Batch components](/images/rendering-with-batch/batch_architecture.png) diff --git a/content/rendering-with-batch/batch/compute_environment.md b/content/rendering-with-batch/batch/compute_environment.md index 61d567e2..7b7cfb8e 100644 --- a/content/rendering-with-batch/batch/compute_environment.md +++ b/content/rendering-with-batch/batch/compute_environment.md @@ -6,7 +6,7 @@ weight: 90 ![Compute environment](/images/rendering-with-batch/CE.png) -We are going to create two compute environments: one using **Spot** instances and the other using **On-Demand** instances. That way if your job need to comply with an SLAs the On-Demand proportion can be used to ensure a timely completion, while the Spot will be used to accelerate the run and reduce the overall cost. +We are going to create two compute environments: one using **Spot** instances and another one using **On-Demand** instances. That way, if your job needs to comply with SLAs, the On-Demand proportion can be used to ensure a timely completion while the Spot will be used to accelerate the run and reduce the overall cost. ### Spot Compute environment creation @@ -86,7 +86,7 @@ cat < ondemand-compute-environment-config.json EoF ``` -Lets explore the configuration parameters in the `computeResources` structure that differ from the previous Compute environment: +Let's explore the configuration parameters in the `computeResources` structure that differ from the previous Compute environment: - **type**: specifies the compute resource type to use. This compute environment will use On-demand instances, hence the `EC2` value. The other possible values are `SPOT`, `FARGATE` and `FARGATE_SPOT`. - **allocationStrategy**: the allocation strategy to use for the compute resource if not enough instances of the best fitting instance type can be allocated. By specifying `BEST_FIT_PROGRESSIVE`, AWS Batch selects an instance type that best fits the needs of the jobs with a preference for the lowest-cost instance type. diff --git a/content/rendering-with-batch/batch/job_definition.md b/content/rendering-with-batch/batch/job_definition.md index 50203a43..8606d1a3 100644 --- a/content/rendering-with-batch/batch/job_definition.md +++ b/content/rendering-with-batch/batch/job_definition.md @@ -30,9 +30,9 @@ cat < job-definition-config.json EoF ``` -Lets explore the configuration parameters in the structure: +Let's explore the configuration parameters in the structure: -- **type**: `container` is the default type and allows to run loosely coupled HPC workloads at scale. The type is `multinode`. With AWS Batch multi-node you can run large-scale, tightly coupled, high performance computing applications. Note `multi-node` jobs are not supported with Spot instances. To learn more about `multi-node` jobs, visit [multi-node parallel jobs](https://docs.aws.amazon.com/batch/latest/userguide/multi-node-parallel-jobs.html). +- **type**: `container` is the default type and allows to run loosely coupled HPC workloads at scale. The other available type is `multi-node`. With AWS Batch multi-node you can run large-scale, tightly coupled, high performance computing applications. Note `multi-node` jobs are not supported with Spot instances. To learn more about `multi-node` jobs, visit [multi-node parallel jobs](https://docs.aws.amazon.com/batch/latest/userguide/multi-node-parallel-jobs.html). - **image**: the image used to start a container, this value is passed directly to the Docker daemon. - **vcpus**: The number of vCPUs reserved for the job. Each vCPU is equivalent to 1,024 CPU shares. - **memory**: hard limit (in MiB) for a container. If your container attempts to exceed the specified number, it's terminated. diff --git a/content/rendering-with-batch/batch/job_queue.md b/content/rendering-with-batch/batch/job_queue.md index 6714a7a3..ddbe61b4 100644 --- a/content/rendering-with-batch/batch/job_queue.md +++ b/content/rendering-with-batch/batch/job_queue.md @@ -4,7 +4,7 @@ date: 2021-09-06T08:51:33Z weight: 100 --- -You are now going to create a Job Queue. The Job Queue is going to be associated with the two compute environments that we just created. We will assign an order of use for the Compute Environments using first the OnDemand environment and then the Spot. +You are now going to create a Job Queue. The Job Queue is going to be associated with the two compute environments that we just created. We will assign an order of use for the Compute Environments using first the OnDemand environment and then the Spot. Run the following to generate the configuration file that will be used to create the job queue: @@ -30,7 +30,7 @@ cat < job-queue-config.json EoF ``` -Lets explore the configuration parameters in the structure: +Let's explore the configuration parameters in the structure: - **priority**: job queues with a higher priority are evaluated first when associated with the same compute environment. Priority is determined in descending order. - **computeEnvironmentOrder**: the set of compute environments mapped to a job queue and their order relative to each other. A compute environment with a **lower** value of `order` is tried for job placement first. We specify the On-demand compute environment to be tried first to ensure that we have compute capacity throughout the whole execution, thus being able to comply with SLAs should there be any. diff --git a/content/rendering-with-batch/batch/submit_job.md b/content/rendering-with-batch/batch/submit_job.md index c3763eb0..e237b538 100644 --- a/content/rendering-with-batch/batch/submit_job.md +++ b/content/rendering-with-batch/batch/submit_job.md @@ -22,7 +22,7 @@ This script needs a couple of command line arguments as input, execute the follo python3 job_submission.py -h ``` -The script needs: (a) the location of the blender file, (b) the location where results will be uploaded, (c) as well as the the Job Definition that will be used to submit the job, (d) the Job Queue where it will be placed and the name that will be used to submit it. +The script needs: (a) the location of the blender file, (b) the location where results will be uploaded, \(c\) the Job Definition that will be used to submit the job, (d) the Job Queue where it will be placed and (e) the name that will be used to submit it. Additionally, there's an extra argument `-f` that needs to be passed. The `-f` argument can be used to specify how many frames each job should render. This will have a direct impact on the size of the array job that is submitted. E.g.: if you want to render a file that has 250 frames and you specify a value of 1 for that argument, the size of the array job will be 250. If you specify a value of 5, the size will be 50 and so on. As you can imagine, the less the frames each job has to render, the less the time it will take for the job to complete. @@ -42,7 +42,7 @@ At this point the jobs have been submitted and you are ready to monitor them. ## Optional: understanding the script -We have used a python program to programmatically submit the jobs to AWS Batch. Feel free to move to the next section and monitor the execution of your AWS Batch job. If at some point you are interested to know the details of how the `job_submission.py` python job submits the job, you can read the sections below. +We have used a python program to submit the jobs to AWS Batch. Feel free to move to the next section and monitor the execution of your AWS Batch job. If at some point you are interested in knowing the details of how the `job_submission.py` python job submits the job, you can read the sections below. ### Method submit_rendering_job diff --git a/content/rendering-with-batch/cleanup.md b/content/rendering-with-batch/cleanup.md index cc67d9c2..54f65383 100644 --- a/content/rendering-with-batch/cleanup.md +++ b/content/rendering-with-batch/cleanup.md @@ -19,7 +19,7 @@ To learn more about these APIs, see [Emptying a bucket](https://docs.aws.amazon. ## AWS Batch -When deleting Batch components, the order matters; a CE cannot be deleted if it is associated to a valid queue, so we have to start by deleting the queue. Job queues and compute environments have to be disabled bore deleting them. +When deleting AWS Batch components, the order matters; a CE cannot be deleted if it is associated to a valid queue, so we have to start by deleting the queue. Job queues and compute environments have to be disabled bore deleting them. To disable the components: @@ -32,7 +32,7 @@ aws batch update-compute-environment --compute-environment "${ONDEMAND_COMPUTE_E To learn more about these APIs, see [update-job-queue CLI Command Reference](https://docs.aws.amazon.com/cli/latest/reference/batch/update-job-queue.html) and [update-compute-environment CLI Command Reference](https://docs.aws.amazon.com/cli/latest/reference/batch/update-compute-environment.html). {{% notice info %}} -The previous operation may take up to 2 minutes. Job queues and compute environments cannot be deleted while being modified, so running the commands below while the compute environments and job queue are being disabled might result in an error with the message "resource is being modified" +The previous operation may take up to 2 minutes. Job queues and compute environments cannot be deleted while being modified, so running the commands below while the compute environments and job queue are being disabled might result in an error with the message "resource is being modified". {{% /notice %}} To delete the components: diff --git a/content/rendering-with-batch/ecr-repository.md b/content/rendering-with-batch/ecr-repository.md index e75ec2d7..81c80ca9 100644 --- a/content/rendering-with-batch/ecr-repository.md +++ b/content/rendering-with-batch/ecr-repository.md @@ -60,37 +60,36 @@ You are now done with the container part. Next, you will configure some environm ## Optional: understanding the render.sh script -When we send a batch job, the container that we just created will be executed. The -Entrypoint of the container is the bash script `render.sh`. The scripts just takes -a few arguments that AWS Batch will pass to each task and does run either blender when a environment variable named `ACTION` is set to `render` or or ffmpeg when is set to `stitch`. +When we send a batch job, the container that we just created will be executed. The entry point of the container is the bash script `render.sh`. The script just takes +a few arguments that AWS Batch will pass to each task and does run either blender when an environment variable named `ACTION` is set to `render` or or ffmpeg when is set to `stitch`. -The following section describes the `render.sh` script in more detail. You don't need to go through this to run this workshop, but if you are interested in fully understanding how Blender and Stitch are called it will give you a clear description. +The following section describes the `render.sh` script in more detail. You don't need to go through this to run this workshop, but if you are interested in fully understanding how Blender and FFmpeg are called it will give you a clear description. #### Method parse_argument: -1. Downloads the blender file from S3. - Read the environment variable `ACTION`and decide from it what's the type of job to run, either blender or ffmpeg. It also takes other arguments such as the the *input*, *output* - - {{< highlight go "linenos=table, linenostart=6" >}} + +Reads the environment variable `ACTION` and decides from it what's the type of job to run, either render or stitch. It also takes other arguments such as the the *input*, *output* + +{{< highlight go "linenos=table, linenostart=6" >}} ACTION=$1 if [ "${ACTION}" != "render" ] && [ "${ACTION}" != "stitch" ] ; then echo "Unrecognised action" exit 2 fi - ... + {{< / highlight >}} #### Method render: -2. Downloads the blender file from S3. +1. Downloads the blender file from S3. {{< highlight go "linenos=table, linenostart=57" >}} aws s3 cp "${INPUT_URI}" file.blend {{< / highlight >}} -3. Calculates the slice of frames that has to render (we will se how in more detail when we talk about AWS Batch). +2. Calculates the slice of frames that has to render (we will se how in more detail when we talk about AWS Batch). {{< highlight go "linenos=table, linenostart=43" >}} if [[ -z "${AWS_BATCH_JOB_ARRAY_INDEX}" ]]; then @@ -102,7 +101,7 @@ else fi {{< / highlight >}} -4. Executes Blender. +3. Executes Blender. {{< highlight go "linenos=table, linenostart=63, hl_lines=3" >}} mkdir frames diff --git a/content/rendering-with-batch/final_thoughts.md b/content/rendering-with-batch/final_thoughts.md index be2c9a20..c1b58055 100644 --- a/content/rendering-with-batch/final_thoughts.md +++ b/content/rendering-with-batch/final_thoughts.md @@ -9,8 +9,8 @@ weight: 160 1. Learned about AWS Batch, its use cases and components. 2. Seen how easy it is to adopt Spot best practices when using AWS Batch, by defining several compute environments with the appropriate allocation strategies. 3. Learned the different types of jobs you find in AWS Batch (array and single). Also, you have learned how to define dependencies between them and how to work with the AWS_BATCH_JOB_ARRAY_INDEX environment variable. -4. You learned the concepts required to create a rendering pipeline using Blender and ffmpeg. -5. Built and published in ECR a Docker image that runs Blender and ffmpeg. +4. Learned the concepts required to create a rendering pipeline using Blender and FFmpeg. +5. Built and published in ECR a Docker image that runs Blender and FFmpeg. ## Savings diff --git a/content/rendering-with-batch/monitor_job.md b/content/rendering-with-batch/monitor_job.md index 58e1e0ad..dcbd9bd3 100644 --- a/content/rendering-with-batch/monitor_job.md +++ b/content/rendering-with-batch/monitor_job.md @@ -26,24 +26,23 @@ done ``` {{% notice tip %}} -This operation will take about 5 minutes. While it progresses, go to the AWS Batch Console, and explore the state of: (a) Compute Environments, (b) Jobs. You can also check in the EC2 Console the : \(c\) EC2 Instances, (d) Auto Scaling groups defined. +This operation will take about 5 minutes. While it progresses, go to the AWS Batch Console, and explore the state of: (a) Compute Environments, (b) Jobs. You can also check in the EC2 Console the: \(c\) EC2 Instances and (d) Auto Scaling groups defined. {{% /notice %}} - When the progress reaches 100%, the output video will be available in the following URL: ``` echo "Output url: https://s3.console.aws.amazon.com/s3/buckets/${BucketName}?region=${AWS_DEFAULT_REGION}&prefix=${JOB_NAME}/output.mp4" ``` -Copy the output of the command into your browser. It will take you to the S3 page where the output file `output.mp4` has been stored. You can just click on the **Download** button to download it to your own computer and play it. +Copy the output of the command into your browser. It will take you to the S3 page where the output file `output.mp4` has been stored. You can just click on the **Download** button to download it to your own computer and play it. {{% notice warning %}} You will need the appropriate program and video codecs to watch the mp4 generated video. You can use [VLC media player](https://www.videolan.org/vlc/). {{% /notice %}} {{% notice tip %}} -Explore also the rest of the S3 folders and check the frames that were created. +Explore also the rest of the S3 folders and check the frames that were created. {{% /notice %}} diff --git a/content/rendering-with-batch/rendering_pipeline.md b/content/rendering-with-batch/rendering_pipeline.md index 30d02c04..b6b76992 100644 --- a/content/rendering-with-batch/rendering_pipeline.md +++ b/content/rendering-with-batch/rendering_pipeline.md @@ -37,7 +37,7 @@ If you want to learn more about Blender's command line rendering, visit [this we ### Gathering a Blender file -We will use a Blender file from [BlendSwap](https://blendswap.com/categories). **BlenderSwap** is a site where Blender-powered 3D artists can share, exchange, collaborate, and learn from other artists. We will work with [the same file](https://blendswap.com/blend/28661) that was used to create the animation in the landing page. That file was created by [Prokster](https://blendswap.com/profile/1012752) and is licensed under [Creative Commons 0](https://creativecommons.org/share-your-work/public-domain/cc0/). If you want to use a different one, feel free to do so! Just take into account the following: +We will use a Blender file from [BlendSwap](https://blendswap.com/categories). **BlenderSwap** is a site where Blender-powered 3D artists can share, exchange, collaborate, and learn from other artists. We will work with [the same file](https://blendswap.com/blend/28661) that was used to create the animation from the landing page. That file was created by [Prokster](https://blendswap.com/profile/1012752) and is licensed under [Creative Commons 0](https://creativecommons.org/share-your-work/public-domain/cc0/). If you want to use a different one, feel free to do so! Just take into account the following: - The file must be configured to render the frames as .png files. - The file must be named **blendfile.blend**. diff --git a/content/rendering-with-batch/start/_index.md b/content/rendering-with-batch/start/_index.md index 76b74a06..6e2d7a9d 100644 --- a/content/rendering-with-batch/start/_index.md +++ b/content/rendering-with-batch/start/_index.md @@ -11,5 +11,5 @@ To start the workshop head to one of the following pages, depending whether you When you finish the workshop, don't forget to execute the commands described in [**Clean up**](/rendering-with-batch/cleanup.html) to prevent incurring in additional charges. {{% notice info %}} -The estimated completion time of this lab is **60 minutes**. Rendering the animation that in this workshop you will incur in an estimated cost of up to **$15**. +The estimated completion time of this lab is **60 minutes**. Rendering the animation presented in the initial page of this workshop, you will incur in an estimated cost of up to **$15**. {{% /notice %}} diff --git a/content/rendering-with-batch/start/review-outputs.md b/content/rendering-with-batch/start/review-outputs.md index 4f99a714..7f402aea 100644 --- a/content/rendering-with-batch/start/review-outputs.md +++ b/content/rendering-with-batch/start/review-outputs.md @@ -1,8 +1,8 @@ ## Reviewing the Launch Template -You can check the CloudFormation stack by downloading the following file: [CloudFormation stack](https://raw.githubusercontent.com/awslabs/ec2-spot-workshops/master/content/rendering-with-batch/rendering-with-batch.files/stack.yaml) +You can check the CloudFormation stack by downloading the following file: [CloudFormation stack](https://raw.githubusercontent.com/awslabs/ec2-spot-workshops/master/content/rendering-with-batch/rendering-with-batch.files/stack.yaml) -Note the `UserData` of the created Launch Template contains the following script: +Note that the `UserData` of the created Launch Template contains the following script: ```bash MIME-Version: 1.0 From fd3dfc0a5487e83e2f43d5956816a9e3285c7b39 Mon Sep 17 00:00:00 2001 From: Borja Perez I Guasch Date: Mon, 15 Nov 2021 14:57:23 +0100 Subject: [PATCH 2/7] Solved navigation issues --- content/rendering-with-batch/start/on-your-own.md | 2 +- content/rendering-with-batch/start/review-outputs.md | 5 +++++ 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/content/rendering-with-batch/start/on-your-own.md b/content/rendering-with-batch/start/on-your-own.md index 79bf0b3f..e9b15d11 100644 --- a/content/rendering-with-batch/start/on-your-own.md +++ b/content/rendering-with-batch/start/on-your-own.md @@ -24,4 +24,4 @@ After downloading the template, open the [CloudFormation console](https://consol The stack creation process will begin. All the resources will be ready to use when the status of the stack is `CREATE_COMPLETE`. -{{% insert-md-from-file file="rendering-with-batch/start/review-outputs.md" %}} \ No newline at end of file +{{% insert-md-from-file file="rendering-with-batch/start/review-outputs.md" %}} diff --git a/content/rendering-with-batch/start/review-outputs.md b/content/rendering-with-batch/start/review-outputs.md index 7f402aea..b4f277ba 100644 --- a/content/rendering-with-batch/start/review-outputs.md +++ b/content/rendering-with-batch/start/review-outputs.md @@ -1,3 +1,8 @@ +--- +disableToc: true +hidden: true +--- + ## Reviewing the Launch Template You can check the CloudFormation stack by downloading the following file: [CloudFormation stack](https://raw.githubusercontent.com/awslabs/ec2-spot-workshops/master/content/rendering-with-batch/rendering-with-batch.files/stack.yaml) From a58a89062597b7b685a9d80e33743aa2f84a7525 Mon Sep 17 00:00:00 2001 From: Borja Perez I Guasch Date: Tue, 28 Dec 2021 13:38:13 +0100 Subject: [PATCH 3/7] Integrated AWS Step functions for workflow orchestration. Minor changes based on the received feedback --- content/rendering-with-batch/_index.md | 8 +- .../batch/batch.files/job_submission.py | 257 ------------------ .../batch/job_definition.md | 4 +- .../rendering-with-batch/batch/job_queue.md | 3 +- .../rendering-with-batch/batch/submit_job.md | 171 ++++++++---- .../rendering-with-batch/ecr-repository.md | 2 +- .../rendering-with-batch/final_thoughts.md | 3 +- content/rendering-with-batch/monitor_job.md | 35 ++- .../diagrams.drawio | 2 +- .../verifying_resilience.py | 58 ---- .../rendering_pipeline.md | 9 +- .../rendering-with-batch/start/at-an-event.md | 3 +- .../rendering-with-batch/start/on-your-own.md | 5 + .../start/review-outputs.md | 2 - .../rendering-with-batch/architecture.png | Bin 135539 -> 138667 bytes .../rendering-with-batch/state_machine.png | Bin 0 -> 51172 bytes .../rendering-with-batch/step-functions.png | Bin 0 -> 85167 bytes 17 files changed, 165 insertions(+), 397 deletions(-) delete mode 100644 content/rendering-with-batch/batch/batch.files/job_submission.py delete mode 100644 content/rendering-with-batch/rendering-with-batch.files/verifying_resilience.py create mode 100644 static/images/rendering-with-batch/state_machine.png create mode 100644 static/images/rendering-with-batch/step-functions.png diff --git a/content/rendering-with-batch/_index.md b/content/rendering-with-batch/_index.md index 978fa092..7834b54a 100644 --- a/content/rendering-with-batch/_index.md +++ b/content/rendering-with-batch/_index.md @@ -11,11 +11,11 @@ The estimated completion time of this lab is **60 minutes**. Please note that re {{% /notice %}} ## Overview -In this workshop you will learn to submit jobs with [AWS Batch](https://aws.amazon.com/batch/) following Spot best practices to [render](https://en.wikipedia.org/wiki/Rendering_(computer_graphics)) a [Blender](https://www.blender.org/) file in a distributed way. You will be creating a docker container and publishing it in Amazon Elastic Container Registry (ECR). Then you will use that container in AWS Batch using a mix of EC2 On-Demand and Spot instances. [Spot instances](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-spot-instances.html) are EC2 spare capacity offered at steep discounts compared to On-Demand instances and are a cost-effective choice for applications that can be interrupted, what makes them well-suited for the batch processing that we will run. After going through all the sections, you will have the following pipeline created: +In this workshop you will learn to submit jobs with [AWS Batch](https://aws.amazon.com/batch/) following Spot best practices to [render](https://en.wikipedia.org/wiki/Rendering_(computer_graphics)) a [Blender](https://www.blender.org/) file in a distributed way. You will be creating a docker container and publishing it in Amazon Elastic Container Registry (ECR). Then you will use that container in AWS Batch using a mix of EC2 On-Demand and Spot instances. [Spot instances](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-spot-instances.html) are EC2 spare capacity offered at steep discounts compared to On-Demand instances and are a cost-effective choice for applications that can be interrupted, what makes them well-suited for the batch processing that we will run. After going through all the sections, you will have the following pipeline created, orchestrated by AWS Step Functions: -1. A python script downloads the Blender file from S3 to extract the number of frames from the Blender project. -2. The script submits a batch job using an `array job` with as many tasks as number of frames. It also submits a single stitching job using [FFmpeg](https://ffmpeg.org/) to create a final video file. -3. Each of the jobs in the rendering job array run a Docker container that executes Blender to render a slice of frames, and after uploads them to S3. +1. A Lambda function downloads the Blender file from S3 to read the number of frames it has. +2. An AWS Batch `array job` (rendering) is submitted with as many tasks as number of frames. Each of the jobs in the array job run a Docker container that executes Blender to render a slice of frames, and after uploads them to S3. +3. An AWS Batch single job (stitching) is submitted to run a Docker container that executes [FFmpeg](https://ffmpeg.org/) to concatenate the frames and create a final video file that it's uploaded to S3. The outcome of the workshop would be the following animation: diff --git a/content/rendering-with-batch/batch/batch.files/job_submission.py b/content/rendering-with-batch/batch/batch.files/job_submission.py deleted file mode 100644 index 7a000dc6..00000000 --- a/content/rendering-with-batch/batch/batch.files/job_submission.py +++ /dev/null @@ -1,257 +0,0 @@ -#!/usr/bin/env python3 - -import sys, getopt, math, boto3, argparse, json, struct, gzip - - -INPUT_URI = '' # S3 URI where the blender file is located -OUTPUT_URI = '' # S3 URI where to upload the rendered file -F_PER_JOB = 0 # Number of frames that each job has to render -JOB_NAME = '' # Name of the job that will be submitted to Batch -JOB_QUEUE = '' # Queue to which the job is submitted -JOB_DEFINITION = '' # Job definition used by the submitted job -FILE_NAME = '' # Name of the blender file - - -# ##### BEGIN GPL LICENSE BLOCK ##### -# -# Extract from Blender's script library included in scripts/modules. -# -# This program is free software; you can redistribute it and/or -# modify it under the terms of the GNU General Public License -# as published by the Free Software Foundation; either version 2 -# of the License, or (at your option) any later version. -# -# This program is distributed in the hope that it will be useful, -# but WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# ##### END GPL LICENSE BLOCK ##### -def read_blend_rend_chunk(path): - """Extract from Blender's script library included in scripts/modules. - Reads the header of a blend file and returns scenes' information. - - Keyword arguments: - path -- path where the blend file is located - """ - - blendfile = open(path, "rb") - - head = blendfile.read(7) - - if head[0:2] == b'\x1f\x8b': # gzip magic - blendfile.seek(0) - blendfile = gzip.open(blendfile, "rb") - head = blendfile.read(7) - - if head != b'BLENDER': - print("not a blend file:", path) - blendfile.close() - return [] - - is_64_bit = (blendfile.read(1) == b'-') - - # true for PPC, false for X86 - is_big_endian = (blendfile.read(1) == b'V') - - # Now read the bhead chunk!!! - blendfile.read(3) # skip the version - - scenes = [] - - sizeof_bhead = 24 if is_64_bit else 20 - - while blendfile.read(4) == b'REND': - sizeof_bhead_left = sizeof_bhead - 4 - - struct.unpack('>i' if is_big_endian else '2i' if is_big_endian else '<2i', blendfile.read(8)) - - scene_name = blendfile.read(64) - - scene_name = scene_name[:scene_name.index(b'\0')] - - try: - scene_name = str(scene_name, "utf8") - except TypeError: - pass - - scenes.append((start_frame, end_frame, scene_name)) - - blendfile.close() - - return scenes - -def parse_arguments(): - """Parses the command line arguments and stores the values in global variables. - """ - - parser = argparse.ArgumentParser(description='Submit an AWS Batch job that will render a Blender file in a distributed fashion.') - parser.add_argument('-i', dest='input_uri', type=str, required=True, help='S3 URI where the blender file is located') - parser.add_argument('-o', dest='output_uri', type=str, required=True, help='S3 URI where to upload the rendered file') - parser.add_argument('-f', dest='f_per_job', type=int, required=True, help='Number of frames that each job has to render') - parser.add_argument('-n', dest='job_name', type=str, required=True, help='Name of the job that will be submitted to Batch') - parser.add_argument('-q', dest='job_queue', type=str, required=True, help='Queue to which the job is submitted') - parser.add_argument('-d', dest='job_definition', type=str, required=True, help='Job definition used by the submitted job') - args = parser.parse_args() - - if args.f_per_job < 1: - print('F_PER_JOB must be a positive integer') - sys.exit(2) - - global INPUT_URI - INPUT_URI = args.input_uri - global OUTPUT_URI - OUTPUT_URI = args.output_uri - global F_PER_JOB - F_PER_JOB = args.f_per_job - global JOB_NAME - JOB_NAME = args.job_name - global JOB_QUEUE - JOB_QUEUE = args.job_queue - global JOB_DEFINITION - JOB_DEFINITION = args.job_definition - global FILE_NAME - FILE_NAME = INPUT_URI.split('/')[-1] - -def download_blender_file_from_s3(): - """Downloads the blend file from S3 and stores it locally. - """ - - bucket = INPUT_URI.split('s3://')[1].split('/')[0] - - s3 = boto3.resource('s3') - s3.meta.client.download_file(bucket, FILE_NAME, './{}'.format(FILE_NAME)) - -def get_number_of_frames(path): - """Reads the header of the blend file and calculates - the number of frames it has. - - Keyword arguments: - path -- path where the blend file is located - """ - - try: - frame_start, frame_end, scene = read_blend_rend_chunk(path)[0] - except FileNotFoundError as e: - print(e.args[1]) - sys.exit(2) - else: - return int(frame_end - frame_start + 1) - -def calculate_array_job_size(): - """Calculates the size of the job array - based on the number of frames of the blender file - and the number of frames that each job has to render - """ - - # Get the scene's number of frames by reading the header of the blend file - n_frames = get_number_of_frames('./{}'.format(FILE_NAME)) - - # Adjust the number of frames per job, if that value is greater than the number of frames in the scene - global F_PER_JOB - F_PER_JOB = min(F_PER_JOB, n_frames) - - # Calculate how many jobs need to be submitted - return n_frames, math.ceil(n_frames / F_PER_JOB) - -def build_job_kwargs(job_name, command): - """Returns a dictionary with properties for launching a job. - - Keyword arguments: - job_name -- name of the job - command -- command to be executed by the job - """ - - return { - 'jobName': job_name, - 'jobQueue': JOB_QUEUE, - 'jobDefinition': JOB_DEFINITION, - 'containerOverrides': { - 'command': command - }, - 'retryStrategy': { - 'attempts': 1 - } - } - -def submit_rendering_job(n_frames, array_size): - """Submits a Batch job that renders the frames. - Depending on the value of , it will submit either - a single job or an array job - - Keyword arguments: - n_frames -- total number of frames - array_size -- size of the array job - """ - - # Append the name of the job to the URI so that a folder is created in S3 - full_output_uri = '{}/{}'.format(OUTPUT_URI, JOB_NAME) - client = boto3.client('batch') - command = 'render -i {} -o {} -f {} -t {}'.format(INPUT_URI, full_output_uri, F_PER_JOB, n_frames) - kwargs = build_job_kwargs('{}_Rendering'.format(JOB_NAME), command.split()) - - # If this is not a single job, submit it as an array job - if array_size > 1: - kwargs['arrayProperties'] = { - 'size': array_size - } - - try: - return client.submit_job(**kwargs) - except Exception as e: - print(e.args[0]) - sys.exit(2) - -def submit_stitching_job(depends_on_job_id): - """Submits a Batch job that creates a mp4 video using the rendered frames. - - Keyword arguments: - depends_on_job_id -- identifier of the job that the stitching job depends on - """ - - # Append the name of the job to the URI so that a folder is created in S3 - full_output_uri = '{}/{}'.format(OUTPUT_URI, JOB_NAME) - client = boto3.client('batch') - command = 'stitch -i {} -o {}'.format(full_output_uri, full_output_uri) - kwargs = build_job_kwargs('{}_Stitching'.format(JOB_NAME), command.split()) - - # Add the job dependency - kwargs['dependsOn'] = [ - { - 'jobId': depends_on_job_id, - 'type': 'SEQUENTIAL' - } - ] - - try: - return client.submit_job(**kwargs) - except Exception as e: - print(e.args[0]) - sys.exit(2) - -if __name__ == "__main__": - job_results = [] - - # Gather command line arguments - parse_arguments() - - # Download the blend file from s3 and save it locally to work with it - download_blender_file_from_s3() - - # Calculate the size of the array job - n_frames, array_size = calculate_array_job_size() - - # Submit the rendering job - job_results.append(submit_rendering_job(n_frames, array_size)) - - # Submit the stitching job - job_results.append(submit_stitching_job(job_results[0]['jobId'])) - - print(json.dumps(job_results)) diff --git a/content/rendering-with-batch/batch/job_definition.md b/content/rendering-with-batch/batch/job_definition.md index 8606d1a3..167a05c3 100644 --- a/content/rendering-with-batch/batch/job_definition.md +++ b/content/rendering-with-batch/batch/job_definition.md @@ -18,7 +18,8 @@ cat < job-definition-config.json "containerProperties": { "image": "${IMAGE}", "vcpus": 1, - "memory": 8000 + "memory": 8000, + "command": ["Ref::action", "-i", "Ref::inputUri", "-o", "Ref::outputUri", "-f", "Ref::framesPerJob"] }, "retryStrategy": { "attempts": 3 @@ -36,6 +37,7 @@ Let's explore the configuration parameters in the structure: - **image**: the image used to start a container, this value is passed directly to the Docker daemon. - **vcpus**: The number of vCPUs reserved for the job. Each vCPU is equivalent to 1,024 CPU shares. - **memory**: hard limit (in MiB) for a container. If your container attempts to exceed the specified number, it's terminated. +- **command**: this is the command that will be executed in the container when the job is started. It has placeholders for some parameters that will be substituted when submitting the job using AWS Batch. - **platformCapabilities**: the platform capabilities required by the job definition. Either `EC2` or `FARGATE`. {{% notice info %}} diff --git a/content/rendering-with-batch/batch/job_queue.md b/content/rendering-with-batch/batch/job_queue.md index ddbe61b4..35c45c31 100644 --- a/content/rendering-with-batch/batch/job_queue.md +++ b/content/rendering-with-batch/batch/job_queue.md @@ -42,7 +42,8 @@ All the compute environments within a queue must be either (`SPOT` and/or `EC2`) Execute this command to create the job queue. To learn more about this API, see [create-job-queue CLI command reference](https://docs.aws.amazon.com/cli/latest/reference/batch/create-job-queue.html). ``` -aws batch create-job-queue --cli-input-json file://job-queue-config.json +export JOB_QUEUE_ARN=$(aws batch create-job-queue --cli-input-json file://job-queue-config.json | jq -r '.jobQueueArn') +echo "Job queue Arn: ${JOB_QUEUE_ARN}" ``` Next, you are going to create a **Job Definition** that will be used to submit jobs. diff --git a/content/rendering-with-batch/batch/submit_job.md b/content/rendering-with-batch/batch/submit_job.md index e237b538..96550229 100644 --- a/content/rendering-with-batch/batch/submit_job.md +++ b/content/rendering-with-batch/batch/submit_job.md @@ -1,92 +1,143 @@ --- -title: "Submitting the job" +title: "Workflow orchestration" date: 2021-09-06T08:51:33Z weight: 120 --- -You have now all the AWS Batch components in place, and are ready to start submitting jobs that will be placed in a queue and processed by a compute environment when AWS Batch's scheduler starts running them. The last step is to download a Python script that will take the bucket name, the rendering queue and the job definition as input parameters and will launch the two jobs of the rendering pipeline using the [AWS SDK for Python, Boto3](https://aws.amazon.com/sdk-for-python/). +You have now all the AWS Batch components in place, and are ready to start submitting jobs that will be placed in a queue and processed by a compute environment when AWS Batch's scheduler starts running them. We are going to use [AWS Step Functions](https://aws.amazon.com/step-functions/?nc1=h_ls&step-functions.sort-by=item.additionalFields.postDateTime&step-functions.sort-order=desc) to orchestrate the execution of our rendering pipeline, from the pre-processing of the Blender file to the stitching of the frames. -## Downloading the python script +AWS Step Functions helps you orchestrate your AWS Batch jobs using serverless workflows, called state machines. You can use Step Functions to orchestrate preprocessing of data and Batch to handle the large compute executions, providing an automated, scalable, and managed batch computing workflow. The CloudFormation template has created the following state machine: -To submit the jobs that will implement the rendering and stitching you are going to use a python script that has already been coded. Execute the following command to download it from GitHub. +![State machine](/images/rendering-with-batch/state_machine.png) -``` -wget https://raw.githubusercontent.com/awslabs/ec2-spot-workshops/master/content/rendering-with-batch/batch/batch.files/job_submission.py -``` - -## Reviewing the command line arguments - -This script needs a couple of command line arguments as input, execute the following to read the help documentation: +You can notice that each step in the rendering pipeline has been mapped to a state. In AWS Step Functions, you can create state machines using the [Amazon States Language](https://docs.aws.amazon.com/step-functions/latest/dg/concepts-amazon-states-language.html) or the [AWS Step Functions Workflow Studio](https://docs.aws.amazon.com/step-functions/latest/dg/tutorial-workflow-studio-using.html). -``` -python3 job_submission.py -h -``` -The script needs: (a) the location of the blender file, (b) the location where results will be uploaded, \(c\) the Job Definition that will be used to submit the job, (d) the Job Queue where it will be placed and (e) the name that will be used to submit it. +## Starting the state machine -Additionally, there's an extra argument `-f` that needs to be passed. The `-f` argument can be used to specify how many frames each job should render. This will have a direct impact on the size of the array job that is submitted. E.g.: if you want to render a file that has 250 frames and you specify a value of 1 for that argument, the size of the array job will be 250. If you specify a value of 5, the size will be 50 and so on. As you can imagine, the less the frames each job has to render, the less the time it will take for the job to complete. +The state machine will: -## Submitting the job +1. Download the Blender file from S3 to determine how many frames it has. +2. Submit a Batch array job that will run Blender to render the frames in parallel. +3. Submit a Batch job that will run FFmpeg to produce the final video. -To submit the rendering job, run the following block of code optionally replacing the value of the argument -f. It will launch the python script and export the identifiers of the two jobs to environment variables to be able to monitor them. +To start the process, perform the following api call to pass a payload to the state machine with the job name, input path, output path, ARNs of the Job Definition and Job queue for AWS Batch to use and the number of frames each job has to render: ``` -export JOB_NAME="RenderingWithBatch" -export JOB_IDS=$(python3 job_submission.py -i "s3://${BucketName}/${BlendFileName}" -o "s3://${BucketName}" -f 1 -n "${JOB_NAME}" -q "${RENDERING_QUEUE_NAME}" -d "${JOB_DEFINITION_NAME}") -export RENDERING_JOB_ID=$((echo $JOB_IDS) | jq -r '.[0].jobId') -export STITCHING_JOB_ID=$((echo $JOB_IDS) | jq -r '.[1].jobId') -echo "Job successfully submitted. Rendering job Id: ${RENDERING_JOB_ID}. Stitching job Id: ${STITCHING_JOB_ID}" +export JOB_NAME="Pottery" +export EXECUTION_ARN=$(aws stepfunctions start-execution --state-machine-arn "${StateMachineArn}" --input "{\"jobName\": ${JOB_NAME}, \"inputUri\": \"s3://${BucketName}/${BlendFileName}\", \"outputUri\": \"s3://${BucketName}/${JOB_NAME}\", \"jobDefinitionArn\": \"${JOB_DEFINITION_ARN}\", \"jobQueueArn\": \"${JOB_QUEUE_ARN}\", \"framesPerJob\": \"1\"}" | jq -r '.executionArn') +echo "State machine started. Execution Arn: ${EXECUTION_ARN}." ``` -At this point the jobs have been submitted and you are ready to monitor them. +To learn more about this API, see [start-execution CLI Command Reference](https://docs.aws.amazon.com/cli/latest/reference/stepfunctions/start-execution.html). At this point the state machine is started and you are ready to monitor the progress of the pipeline. -## Optional: understanding the script +## Optional: understanding the state machine -We have used a python program to submit the jobs to AWS Batch. Feel free to move to the next section and monitor the execution of your AWS Batch job. If at some point you are interested in knowing the details of how the `job_submission.py` python job submits the job, you can read the sections below. +We have orchestrated the workflow of the rendering pipeline using an AWS Step Functions state machine. Feel free to move to the next section and monitor its execution, but if at some point you are interested in knowing the details of its states, you can read the sections below. -### Method submit_rendering_job +### State *Number of frames extraction* -Two important things to highlight from this method: +This is the entry point of our state machine. In this state, a Lambda function is invoked to determine the number of frames of the Blender file. To do that, we are using a script included in Blender's script library that extracts information related to the scenes of the composition. In broad strokes, the Lambda function implements the following logic: -1. The command that is passed to the container is defined in the line 200. The arguments are preceded by the keyword `render`. These arguments will be received by the bash script that we have talked about in the section *Download image files* inside *Creating your Docker image*. - - {{< highlight go "linenos=table, hl_lines=3, linenostart=198" >}} -full_output_uri = '{}/{}'.format(OUTPUT_URI, JOB_NAME) -client = boto3.client('batch') -command = 'render -i {} -o {} -f {} -t {}'.format(INPUT_URI, full_output_uri, F_PER_JOB, n_frames) -kwargs = build_job_kwargs('{}_Rendering'.format(JOB_NAME), command.split()) -{{< / highlight >}} +1. Receives the payload that we passed on to the state machine when we started it. +2. Downloads the Blender file from S3. +3. Reads the number of frames of the file. +4. Calculates the dimension of the Batch array job taking into account the number of frames and how many frames each job has to render. -2. The array job is created by specifying the `arrayProperties` value. An array job is a job that shares common parameters, such as the job definition, vCPUs, and memory. It runs as a collection of related, yet separate, basic jobs that may be distributed across multiple hosts and may run concurrently. At runtime, the `AWS_BATCH_JOB_ARRAY_INDEX` environment variable is set to the container's corresponding job array index number. This is how the bash script is able to calculate the slice of frames that needs to render. +An array job is a job that shares common parameters, such as the job definition, vCPUs, and memory. It runs as a collection of related, yet separate, basic jobs that may be distributed across multiple hosts and may run concurrently. At runtime, the `AWS_BATCH_JOB_ARRAY_INDEX` environment variable is set to the container's corresponding job array index number. This is how the bash script is able to calculate the slice of frames that needs to render. To learn more about it, visit [Array jobs](https://docs.aws.amazon.com/batch/latest/userguide/array_jobs.html) and [Tutorial: Using the Array Job Index to Control Job Differentiation](https://docs.aws.amazon.com/batch/latest/userguide/array_index_example.html). - {{< highlight go "linenos=table, linenostart=204" >}} -if array_size > 1: - kwargs['arrayProperties'] = { - 'size': array_size - } -{{< / highlight >}} +You can view the Lambda function in the following URL: -### Method submit_stitching_job +``` +echo "https://console.aws.amazon.com/lambda/home?region=${AWS_DEFAULT_REGION}#/functions/${PreprocessingLambda}?tab=code" +``` -Two important things to highlight from this method: +### State *Rendering* + +Submits an AWS Batch array job of dimension *n*, where *n* is the number returned by the Lambda function of the previous state. Three important configurations are implemented in the definition of this state: + +1. **Extraction of the ARNs of the Job Definition and Job Queue** from the payload received by the state machine using a [JSONPath](https://docs.aws.amazon.com/kinesisanalytics/latest/dev/about-json-path.html) expression. Those are passed on to AWS Batch when submitting the job: + + {{< highlight go "linenos=table, linenostart=1, hl_lines=15-16" >}} +"Rendering": { + "Type": "Task", + "Resource": "arn:aws:states:::batch:submitJob.sync", + "Parameters": { + "JobName": "Rendering", + "ArrayProperties": { + "Size.$": "$.output.Payload.body.arrayJobSize" + }, + "Parameters": { + "action": "render", + "inputUri.$": "$.inputUri", + "outputUri.$": "$.outputUri", + "framesPerJob.$": "$.framesPerJob" + }, + "JobDefinition.$": "$.jobDefinitionArn", + "JobQueue.$": "$.jobQueueArn" + }, + "Next": "Stitching", + "ResultPath": "$.output" +} +{{< / highlight >}} -1. The command that is passed to the container is defined in the line 225. The arguments are preceded by the keyword `stitch`. + Read [this blog post](https://aws.amazon.com/es/blogs/compute/using-jsonpath-effectively-in-aws-step-functions/) to learn how to effectively use JSONPath expressions in AWS Step Functions. + +2. **Setting the dimension of the array job** by specifying a value for the attribute `Size` inside the `ArrayProperties` structure. Now, we are taking that value from the output of the previous state: + + {{< highlight go "linenos=table, linenostart=1, hl_lines=6-8" >}} +"Rendering": { + "Type": "Task", + "Resource": "arn:aws:states:::batch:submitJob.sync", + "Parameters": { + "JobName": "Rendering", + "ArrayProperties": { + "Size.$": "$.output.Payload.body.arrayJobSize" + }, + "Parameters": { + "action": "render", + "inputUri.$": "$.inputUri", + "outputUri.$": "$.outputUri", + "framesPerJob.$": "$.framesPerJob" + }, + "JobDefinition.$": "$.jobDefinitionArn", + "JobQueue.$": "$.jobQueueArn" + }, + "Next": "Stitching", + "ResultPath": "$.output" +} +{{< / highlight >}} - {{< highlight go "linenos=table, hl_lines=3, linenostart=225" >}} -full_output_uri = '{}/{}'.format(OUTPUT_URI, JOB_NAME) -client = boto3.client('batch') -command = 'stitch -i {} -o {}'.format(full_output_uri, full_output_uri) -kwargs = build_job_kwargs('{}_Stitching'.format(JOB_NAME), command.split()) +3. **Setting a value for the parameters defined in the Job Definition**. If you remember, we did specify a `command` attribute with the value `["Ref::action", "-i", "Ref::inputUri", "-o", "Ref::outputUri", "-f", "Ref::framesPerJob"]` when we created the Job Definition. Now it's time to give a value to the placeholders in that expression: + + {{< highlight go "linenos=table, linenostart=1, hl_lines=9-14" >}} +"Rendering": { + "Type": "Task", + "Resource": "arn:aws:states:::batch:submitJob.sync", + "Parameters": { + "JobName": "Rendering", + "ArrayProperties": { + "Size.$": "$.output.Payload.body.arrayJobSize" + }, + "Parameters": { + "action": "render", + "inputUri.$": "$.inputUri", + "outputUri.$": "$.outputUri", + "framesPerJob.$": "$.framesPerJob" + }, + "JobDefinition.$": "$.jobDefinitionArn", + "JobQueue.$": "$.jobQueueArn" + }, + "Next": "Stitching", + "ResultPath": "$.output" +} {{< / highlight >}} -2. The job dependency is created by specifying the `dependsOn` value, which is a dictionary that contains the identifier of the job towards which create the dependency, and the type of dependency. In this case, the dependency is `SEQUENTIAL` because the stitching job must be launched **after** all the frames have been rendered. To learn more about job dependencies visit [Job Dependencies](https://docs.aws.amazon.com/batch/latest/userguide/job_dependencies.html). +As you can see, the action is set to `render`, since this state implements the rendering part of the pipeline. - {{< highlight go "linenos=table, linenostart=229" >}} -kwargs['dependsOn'] = [ - { - 'jobId': depends_on_job_id, - 'type': 'SEQUENTIAL' - } -] -{{< / highlight >}} +### State *Stitching* + +Similarly to the previous state, the *Stitching* state launches an AWS Batch job but, in this case, it is a single job. By the way we have defined the execution flow of the state machine, this state will be executed **after** the previous state has completed its execution. Optionally, in AWS Batch you can define job dependencies to manage the relationship of jobs and start them when others finish their execution. To learn more about job dependencies visit [Job Dependencies](https://docs.aws.amazon.com/batch/latest/userguide/job_dependencies.html) and to learn more about AWS Step Functions transitions visit [Transitions](https://docs.aws.amazon.com/step-functions/latest/dg/concepts-transitions.html). + +The only configuration of this state that differs from the previous is the value of the parameter `action`, that in this case is set to `stitch` so that our Docker container runs FFmpeg to produce the video when all the frames have been rendered. diff --git a/content/rendering-with-batch/ecr-repository.md b/content/rendering-with-batch/ecr-repository.md index 81c80ca9..b183e868 100644 --- a/content/rendering-with-batch/ecr-repository.md +++ b/content/rendering-with-batch/ecr-repository.md @@ -61,7 +61,7 @@ You are now done with the container part. Next, you will configure some environm ## Optional: understanding the render.sh script When we send a batch job, the container that we just created will be executed. The entry point of the container is the bash script `render.sh`. The script just takes -a few arguments that AWS Batch will pass to each task and does run either blender when an environment variable named `ACTION` is set to `render` or or ffmpeg when is set to `stitch`. +a few arguments that AWS Batch will pass to each task and does run either blender when an environment variable named `ACTION` is set to `render` or ffmpeg when is set to `stitch`. The following section describes the `render.sh` script in more detail. You don't need to go through this to run this workshop, but if you are interested in fully understanding how Blender and FFmpeg are called it will give you a clear description. diff --git a/content/rendering-with-batch/final_thoughts.md b/content/rendering-with-batch/final_thoughts.md index c1b58055..42f6f769 100644 --- a/content/rendering-with-batch/final_thoughts.md +++ b/content/rendering-with-batch/final_thoughts.md @@ -10,7 +10,8 @@ weight: 160 2. Seen how easy it is to adopt Spot best practices when using AWS Batch, by defining several compute environments with the appropriate allocation strategies. 3. Learned the different types of jobs you find in AWS Batch (array and single). Also, you have learned how to define dependencies between them and how to work with the AWS_BATCH_JOB_ARRAY_INDEX environment variable. 4. Learned the concepts required to create a rendering pipeline using Blender and FFmpeg. -5. Built and published in ECR a Docker image that runs Blender and FFmpeg. +5. Used AWS Step Functions to orchestrate the workflow of the pipeline. +6. Built and published in ECR a Docker image that runs Blender and FFmpeg. ## Savings diff --git a/content/rendering-with-batch/monitor_job.md b/content/rendering-with-batch/monitor_job.md index dcbd9bd3..9d141176 100644 --- a/content/rendering-with-batch/monitor_job.md +++ b/content/rendering-with-batch/monitor_job.md @@ -11,6 +11,18 @@ You can check the rendering progress by running these commands in the Cloud9 ter ``` while [ true ] do + while [ true ] + do + export RENDERING_JOB_ID=$(aws batch list-jobs --job-queue "${RENDERING_QUEUE_NAME}" --filters name=JOB_NAME,values="${JOB_NAME}" --query 'jobSummaryList[*].jobId' | jq -r '.[0]') + + if [ ! -z "$RENDERING_JOB_ID" ] ; then + break + fi + + echo "Rendering not started yet" + sleep 5 + done + export RENDERING_PROGRESS=$(aws batch describe-jobs --jobs "${RENDERING_JOB_ID}") export RENDER_COUNT=$(echo $RENDERING_PROGRESS | jq -r '.jobs[0].arrayProperties.statusSummary.SUCCEEDED') export FRAMES_TO_RENDER=$(echo $RENDERING_PROGRESS | jq -r '.jobs[0].arrayProperties.size') @@ -21,12 +33,16 @@ do break fi - sleep 7 + sleep 5 done ``` +{{% notice info %}} +It is normal if the progress is stuck at 0% at the beginning and after it increases rapidly. The reason for this is that AWS Batch is provisioning capacity for the Compute environments as defined earlier, and jobs will remain in the `RUNNABLE` state until sufficient resources are available. You can read more about job states here: [Job States](https://docs.aws.amazon.com/batch/latest/userguide/job_states.html). +{{% /notice %}} + {{% notice tip %}} -This operation will take about 5 minutes. While it progresses, go to the AWS Batch Console, and explore the state of: (a) Compute Environments, (b) Jobs. You can also check in the EC2 Console the: \(c\) EC2 Instances and (d) Auto Scaling groups defined. +This operation will take about 10 minutes. While it progresses, go to the AWS Batch Console, and explore the state of: (a) Compute Environments, (b) Jobs. You can also check in the EC2 Console the: \(c\) EC2 Instances and (d) Auto Scaling groups defined. {{% /notice %}} When the progress reaches 100%, the output video will be available in the following URL: @@ -46,9 +62,20 @@ Explore also the rest of the S3 folders and check the frames that were created. {{% /notice %}} - ## Monitoring +### Viewing the execution of the state machine + +You can follow the progress of the rendering pipeline by navigating to the executions tab of the state machine. To do it: + +1. Navigate to the AWS Step Functions service page. +2. Select the state machine whose name begins with **RenderingPipeline**. +3. In the executions tab, select the first entry. +4. In the graph inspector, you can select a state to see the input it receives and the output it produces. + +![AWS Step Functions console](/images/rendering-with-batch/step-functions.png) + + ### Viewing the logs of a job To view the logs of a job using the console: @@ -65,7 +92,7 @@ To view the logs of a job using the console: You can monitor the status of a job using the following command: ``` -aws batch describe-jobs --jobs "${RENDERING_JOB_ID}" "${STITCHING_JOB_ID}" +aws batch describe-jobs --jobs "${RENDERING_JOB_ID}" ``` To learn more about this command, you can review the [describe-jobs CLI command reference](https://docs.aws.amazon.com/cli/latest/reference/batch/describe-jobs.html). diff --git a/content/rendering-with-batch/rendering-with-batch.files/diagrams.drawio b/content/rendering-with-batch/rendering-with-batch.files/diagrams.drawio index f8bc43ca..9430e57d 100644 --- a/content/rendering-with-batch/rendering-with-batch.files/diagrams.drawio +++ b/content/rendering-with-batch/rendering-with-batch.files/diagrams.drawio @@ -1 +1 @@ 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 \ No newline at end of file diff --git a/content/rendering-with-batch/rendering-with-batch.files/verifying_resilience.py b/content/rendering-with-batch/rendering-with-batch.files/verifying_resilience.py deleted file mode 100644 index 2fd6c708..00000000 --- a/content/rendering-with-batch/rendering-with-batch.files/verifying_resilience.py +++ /dev/null @@ -1,58 +0,0 @@ -import boto3 -import sys - - -def get_jobs_in_array(array_id): - """Returns the identifiers of the jobs inside an array job - - Keyword arguments: - array_id -- identifier of the array job - """ - - client = boto3.client('batch') - kwargs = {'arrayJobId': array_id, 'jobStatus': 'SUCCEEDED'} - job_ids = [] - - while True: - response = client.list_jobs(**kwargs) - job_ids += [job['jobId'] for job in response['jobSummaryList']] - - if 'nextToken' in response: - kwargs['nextToken'] = response['nextToken'] - else: - return job_ids - -def show_execution_attempts(job_ids): - """Shows the number of atemmps of the specified jobs, - if the attempt number is bigger than 1. - - Keyword arguments: - job_ids -- Identifiers of the target jobs - """ - - client = boto3.client('batch') - page = 0 - items_per_page = 100 - - while page * items_per_page < len(job_ids): - start_index = page * items_per_page - end_index = start_index + items_per_page - page += 1 - - response = client.describe_jobs( - jobs=job_ids[start_index:end_index] - ) - - for job in response['jobs']: - if len(job['attempts']) > 1: - print('Frame\t{}\twas attempted to render {} times'.format(job['arrayProperties']['index'], len(job['attempts']))) - - -if __name__ == "__main__": - array_id = sys.argv[1] - - # Get the identifiers of the jobs in the array job - job_ids = get_jobs_in_array(array_id) - - # Show the number of attempts per job - show_execution_attempts(job_ids) diff --git a/content/rendering-with-batch/rendering_pipeline.md b/content/rendering-with-batch/rendering_pipeline.md index b6b76992..4a7bf7c1 100644 --- a/content/rendering-with-batch/rendering_pipeline.md +++ b/content/rendering-with-batch/rendering_pipeline.md @@ -20,9 +20,7 @@ In this workshop we will use its [rendering capabilities](https://www.blender.or You can launch Blender's rendering capabilities from the command line. This allows to access Blender remotely and reduce compute resource consumption since it does not need to load a graphical interface. The Docker image that you will create will do exactly this; run a bash script that will execute Blender and pass to it some arguments needed to render a specific slice of frames. The command that will be executed is the following: -```bash -blender -b -E CYCLES -o -s -e -a -``` +``blender -b -E CYCLES -o -s -e -a`` The arguments mean the following: @@ -41,6 +39,7 @@ We will use a Blender file from [BlendSwap](https://blendswap.com/categories). * - The file must be configured to render the frames as .png files. - The file must be named **blendfile.blend**. +- The file size cannot exceed 512MB. - The more frames it has, the more compute resources you will need to render it thus impacting the costs of running the workshop. Run the following command to download the file and upload it to S3: @@ -58,6 +57,4 @@ FFmpeg is a free and open-source multimedia framework able to decode, encode, tr To concatenate multiple images and make a video out of them, you will use what in FFmpeg's wiki is referred to as [*SlideShow*](https://trac.ffmpeg.org/wiki/Slideshow). When you launch the stitching job, the Docker image that you create will execute ffmpeg from the command line and pass it some arguments needed to create the video. The command that will be executed is the following: -```bash -ffmpeg -i -``` +``ffmpeg -i `` diff --git a/content/rendering-with-batch/start/at-an-event.md b/content/rendering-with-batch/start/at-an-event.md index 08261cae..3c834e3c 100644 --- a/content/rendering-with-batch/start/at-an-event.md +++ b/content/rendering-with-batch/start/at-an-event.md @@ -17,9 +17,10 @@ You are now logged in to the AWS console in an account that was created for you, - An S3 bucket - An ECR repository - A Launch Template +- An AWS Step Functions state machine - An instance profile for AWS Batch compute environment - The Cloud9 environment where you will run all the commands - +You can check the CloudFormation stack by downloading the following file: [CloudFormation stack](https://raw.githubusercontent.com/awslabs/ec2-spot-workshops/master/content/rendering-with-batch/rendering-with-batch.files/stack.yaml) {{% insert-md-from-file file="rendering-with-batch/start/review-outputs.md" %}} diff --git a/content/rendering-with-batch/start/on-your-own.md b/content/rendering-with-batch/start/on-your-own.md index e9b15d11..bc5a8be2 100644 --- a/content/rendering-with-batch/start/on-your-own.md +++ b/content/rendering-with-batch/start/on-your-own.md @@ -12,6 +12,7 @@ As a first step, **download** a [CloudFormation stack](https://raw.githubusercon - An S3 bucket - An ECR repository - A Launch Template +- An AWS Step Functions state machine - An instance profile for AWS Batch compute environment - The Cloud9 environment where you will run all the commands @@ -22,6 +23,10 @@ After downloading the template, open the [CloudFormation console](https://consol 3. In the **Configure stack options** page, leave all the configuration as it is. Navigate to the bottom of the page and click on **Next**. 4. In the **Review** page, leave all the configuration as it is. Navigate to the bottom of the page, and click on **I acknowledge that AWS CloudFormation might create IAM resources** and finally on **Create stack**. +{{% notice warning %}} +It is important that you use **RenderingWithBatch** as the stack name, as later we will use that value to retrieve some outputs programmatically. +{{% /notice %}} + The stack creation process will begin. All the resources will be ready to use when the status of the stack is `CREATE_COMPLETE`. {{% insert-md-from-file file="rendering-with-batch/start/review-outputs.md" %}} diff --git a/content/rendering-with-batch/start/review-outputs.md b/content/rendering-with-batch/start/review-outputs.md index b4f277ba..ab868f87 100644 --- a/content/rendering-with-batch/start/review-outputs.md +++ b/content/rendering-with-batch/start/review-outputs.md @@ -5,8 +5,6 @@ hidden: true ## Reviewing the Launch Template -You can check the CloudFormation stack by downloading the following file: [CloudFormation stack](https://raw.githubusercontent.com/awslabs/ec2-spot-workshops/master/content/rendering-with-batch/rendering-with-batch.files/stack.yaml) - Note that the `UserData` of the created Launch Template contains the following script: ```bash diff --git a/static/images/rendering-with-batch/architecture.png b/static/images/rendering-with-batch/architecture.png index 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HcmV?d00001 From 2b1efa5c04a9c9fd29f60129d36675dfd086a5c8 Mon Sep 17 00:00:00 2001 From: Borja Perez I Guasch Date: Fri, 31 Dec 2021 15:03:17 +0100 Subject: [PATCH 4/7] Updated the CloudFormation stack --- content/rendering-with-batch/_index.md | 2 +- .../batch/batch.files/pottery.blend | Bin 1579273 -> 0 bytes .../rendering-with-batch/batch/submit_job.md | 2 +- .../rendering-with-batch.files/stack.yaml | 786 +++++++++++++----- .../rendering-with-batch/step-functions.png | Bin 85167 -> 111604 bytes 5 files changed, 585 insertions(+), 205 deletions(-) delete mode 100644 content/rendering-with-batch/batch/batch.files/pottery.blend diff --git a/content/rendering-with-batch/_index.md b/content/rendering-with-batch/_index.md index 7834b54a..21dfcd3e 100644 --- a/content/rendering-with-batch/_index.md +++ b/content/rendering-with-batch/_index.md @@ -7,7 +7,7 @@ pre: "8. " --- {{% notice info %}} -The estimated completion time of this lab is **60 minutes**. Please note that rendering the animation presented below can incur in costs up to **$15**. +The estimated completion time of this lab is **90 minutes**. Please note that rendering the animation presented below can incur in costs up to **$15**. {{% /notice %}} ## Overview diff --git a/content/rendering-with-batch/batch/batch.files/pottery.blend b/content/rendering-with-batch/batch/batch.files/pottery.blend deleted file mode 100644 index 9629522d57dc87d88881668baa069f6d89e70c6a..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1579273 zcmeEv31Ak*+5Zbc+1ktAXzkb7+LpFn;DrZ}kN^=m0^t-eyd*Cq5R#aKOMw6a0Tcm6 z?n4noZEdZ#Y7fPuHa%=@{i?RLY7hUVwTJz_eqXI$>-?W*=K1ZrJK24&yg8eN&Ft*X zGduHpe)G&Tv$Ok-7&~%&;mAqnEWY6U^C!_^QG~Wf9y@azhqU#P{W}zvl*OuJd@{pr z^2n0O4&~T9dEr-w_BEMs{!OxP*tkjc?!6fFa-f$3y&UM}KraV+Inc|2UJmqfpqB%^ z9O&ghF9&)#(93~d4)k)Mmjk^V=;c5!2YNZs%Yj}F^m3qQaG;r<|6%XdY0uDUI(j^E z^e%NL??;ZR!+JlW4&Ql1-NF0eJJs#j?>MXu-EoK6Z@)twy#01{@X+n*z@bCxz(KR` zKX_2>KX6d(<9+`DwHN!o{b~>Pz5CQ|?0fdAU3>PJefJ)b9L` z-$CJy+jgp3efw?dmL1-Ghq~p~9csI8zg2C!C1Brvi`p8tZ`-bJcK2;`9I$WQrna=& zx6-);`^|KX_M1}LZ>Dqs`xZKv#XS^*Fl_kzHnZPMp?Ammo}1PlIuRCjR)vE z(S6$ET6t`~s$8&8)m~e#8Wt~6%dcCZZdkuT`;3RkN8L+4r}i6n?o_+Tw`3ob&+R6^ zbH~oz+E3)Z_eS!kHf_F1HE-Ii);Dj|d91l%ooZUWR;^goq?RtfPAyrsT-7%;s_NQn z)q;hKR7K@NRUV_Z)9H4soa|`kd$|4s^ls_AJ#-qDXKY@Dy0)%CUAJO|TDxwY_JP^2 zXJ4N~_R%-rv_All*Uaob+dfd2qvmR^lxM|akH>##JYt?nvuhcrNq4rp{s9Ns}tEyG& zeG#2AJL@QTucGr+WJ`kfh1$k&dk@;H7S*Wgnrl@}ZJjRfqUu^TZ+@k^=9)Qb+O!#J z>a^+Vn$kJh=fhlT^I6!9{w}`XH5+yH)w2l8 zYt`ztYsntdd<@xRZpYkijcya`ko6d>OQT2bFM{-F&MimClJ~MQ54lJxW{&+FSYXZPYvTyt2MV-L$w` zt*=|47R{fhHc+^ve71^B9F^|jV*n(G+5W|mslSfjRI*Pw1B4y;%-Uv0atPOYn{P^+tADmrm2ak0$T z7D`K_YD9ja8aHl&TD)|rZliwvnKsC}n;+B$^*N(IzYgcC*|V-u(@IKI$+)Z3#G+AZ z+{k=2CU2-Jxbz~Gcku=4@(Ty4;X^J``Ild+Mvur-6NsPFrc71QXqjhh6y(RpZLnWA zWx9SWKZo|xIdfG>$yCkF>e^bJr$4=Eo3Xib)%@94tJzbh7

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zP|){mm+F3lm-sylUWT;vorj~tEAT2|22v+Rgtb0-l{FIgQ7{_&*TU_Qz}yqRC3h?g zhL?F4ABQCSCkMR(Pi zS;U!<{?}~GI4duGEOY<9iENDvzlAvm-iEm_4}bHKu>cmrBJ^F1PD{caX>VvxLHl!* zH}@#n`}BL467M^Ni|5Pm?}j_FQq;DVQO?VeSKr^!J1j*hImefgWH8S$uxm%vD4~fJB|JT; z|EzVR4qZd;<-;uo!CJe#Tz?%_r|`rYp=8@|4tL9#v?xG-rE^o z!l@!lkg|la6_Zz*)8B$ddG5{-mx3Aqe8Zanr#+#H!--K&6s!@$d H{`L2NzNAwA diff --git a/content/rendering-with-batch/batch/submit_job.md b/content/rendering-with-batch/batch/submit_job.md index 96550229..50c25bcc 100644 --- a/content/rendering-with-batch/batch/submit_job.md +++ b/content/rendering-with-batch/batch/submit_job.md @@ -25,7 +25,7 @@ To start the process, perform the following api call to pass a payload to the st ``` export JOB_NAME="Pottery" -export EXECUTION_ARN=$(aws stepfunctions start-execution --state-machine-arn "${StateMachineArn}" --input "{\"jobName\": ${JOB_NAME}, \"inputUri\": \"s3://${BucketName}/${BlendFileName}\", \"outputUri\": \"s3://${BucketName}/${JOB_NAME}\", \"jobDefinitionArn\": \"${JOB_DEFINITION_ARN}\", \"jobQueueArn\": \"${JOB_QUEUE_ARN}\", \"framesPerJob\": \"1\"}" | jq -r '.executionArn') +export EXECUTION_ARN=$(aws stepfunctions start-execution --state-machine-arn "${StateMachineArn}" --input "{\"jobName\": \"${JOB_NAME}\", \"inputUri\": \"s3://${BucketName}/${BlendFileName}\", \"outputUri\": \"s3://${BucketName}/${JOB_NAME}\", \"jobDefinitionArn\": \"${JOB_DEFINITION_ARN}\", \"jobQueueArn\": \"${JOB_QUEUE_ARN}\", \"framesPerJob\": \"1\"}" | jq -r '.executionArn') echo "State machine started. Execution Arn: ${EXECUTION_ARN}." ``` diff --git a/content/rendering-with-batch/rendering-with-batch.files/stack.yaml b/content/rendering-with-batch/rendering-with-batch.files/stack.yaml index c57b305b..328d2ebb 100644 --- a/content/rendering-with-batch/rendering-with-batch.files/stack.yaml +++ b/content/rendering-with-batch/rendering-with-batch.files/stack.yaml @@ -1,4 +1,303 @@ Resources: + CustomCloud9SsmCloud9Ec2EnvironmentF47DD48C: + Type: AWS::Cloud9::EnvironmentEC2 + Properties: + InstanceType: t3.large + Tags: + - Key: stack-id + Value: + Ref: AWS::StackId + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/Cloud9Ec2Environment + CustomCloud9SsmEc2RoleCE9ACBCB: + Type: AWS::IAM::Role + Properties: + AssumeRolePolicyDocument: + Statement: + - Action: sts:AssumeRole + Effect: Allow + Principal: + Service: + Fn::Join: + - "" + - - ec2. + - Ref: AWS::URLSuffix + Version: "2012-10-17" + ManagedPolicyArns: + - arn:aws:iam::aws:policy/AmazonSSMManagedInstanceCore + RoleName: CustomCloud9Ssm-CustomCloud9SsmEc2Role + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/Ec2Role/Resource + CustomCloud9SsmEc2RoleDefaultPolicy92A07C4C: + Type: AWS::IAM::Policy + Properties: + PolicyDocument: + Statement: + - Action: + - ec2:DescribeInstances + - ec2:ModifyVolume + - ec2:DescribeVolumesModifications + - batch:DescribeJobQueues + - batch:CreateComputeEnvironment + - batch:DeleteComputeEnvironment + - batch:SubmitJob + - batch:UpdateComputeEnvironment + - batch:ListJobs + - batch:ListJobs + - ecr:BatchDeleteImage + - ecr:GetAuthorizationToken + - batch:DescribeComputeEnvironments + - cloudformation:DescribeStacks + - batch:DeregisterJobDefinition + - s3:PutObject + - s3:ListBucket + - s3:DeleteObject + - batch:CreateJobQueue + - batch:DescribeJobs + - batch:RegisterJobDefinition + - states:StartExecution + - batch:DescribeJobDefinitions + - batch:DeleteJobQueue + - ecr:DescribeRepositories + - batch:UpdateJobQueue + - iam:PassRole + Effect: Allow + Resource: "*" + Version: "2012-10-17" + PolicyName: CustomCloud9SsmEc2RoleDefaultPolicy92A07C4C + Roles: + - Ref: CustomCloud9SsmEc2RoleCE9ACBCB + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/Ec2Role/DefaultPolicy/Resource + CustomCloud9SsmEc2InstanceProfile167B6BF8: + Type: AWS::IAM::InstanceProfile + Properties: + Roles: + - Ref: CustomCloud9SsmEc2RoleCE9ACBCB + DependsOn: + - CustomCloud9SsmEc2RoleDefaultPolicy92A07C4C + - CustomCloud9SsmEc2RoleCE9ACBCB + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/Ec2InstanceProfile + CustomCloud9SsmSsmDocumentD052D5F9: + Type: AWS::SSM::Document + Properties: + Content: + schemaVersion: "2.2" + description: Bootstrap Cloud9 EC2 instance + mainSteps: + - name: ResizeEBS + action: aws:runShellScript + inputs: + runCommand: + - "#!/bin/bash" + - echo '=== Installing packages ===' + - sudo yum -y install jq + - sudo pip install boto3 + - echo '=== Exporting current region ===' + - export AWS_DEFAULT_REGION=$(curl -s 169.254.169.254/latest/dynamic/instance-identity/document | jq -r '.region') + - echo 'Region is ${AWS_DEFAULT_REGION}' + - echo '=== Gathering instance Id ===' + - instanceId=$(curl -s 169.254.169.254/latest/dynamic/instance-identity/document | jq -r '.instanceId') + - echo 'Instance Id is ${instanceId}' + - echo '=== Resizing EBS volume ===' + - volumeId=$(aws ec2 describe-instances --instance-ids $instanceId | jq -r '.Reservations[0].Instances[0].BlockDeviceMappings[0].Ebs.VolumeId') + - echo 'Volume Id is ${volumeId}' + - aws ec2 modify-volume --volume-id $volumeId --size 100 + - echo '=== Waiting for the volume to enter the optimizing state ===' + - while [ true ] + - do + - modificationState=$(aws ec2 describe-volumes-modifications --volume-ids $volumeId | jq -r '.VolumesModifications[0].ModificationState') + - if [ $modificationState == "optimizing" ] ; then + - break + - fi + - sleep 5 + - done + - echo '=== Resizing file system ===' + - sudo growpart /dev/xvda 1 + - sudo resize2fs $(df -h |awk '/^\/dev/{print $1}') + DocumentType: Command + Name: CustomCloud9Ssm-CustomCloudSsm-SsmDocument + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/SsmDocument + CustomCloud9SsmSsmAssociationABF443F9: + Type: AWS::SSM::Association + Properties: + Name: CustomCloud9Ssm-CustomCloudSsm-SsmDocument + Targets: + - Key: tag:stack-id + Values: + - Ref: AWS::StackId + DependsOn: + - CustomCloud9SsmCloud9Ec2EnvironmentF47DD48C + - CustomCloud9SsmSsmDocumentD052D5F9 + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/SsmAssociation + CustomCloud9SsmProfileAttachLambdaFunctionServiceRoleF610D074: + Type: AWS::IAM::Role + Properties: + AssumeRolePolicyDocument: + Statement: + - Action: sts:AssumeRole + Effect: Allow + Principal: + Service: lambda.amazonaws.com + Version: "2012-10-17" + ManagedPolicyArns: + - Fn::Join: + - "" + - - "arn:" + - Ref: AWS::Partition + - :iam::aws:policy/service-role/AWSLambdaBasicExecutionRole + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/ProfileAttachLambdaFunction/ServiceRole/Resource + CustomCloud9SsmProfileAttachLambdaFunctionServiceRoleDefaultPolicy9CC20561: + Type: AWS::IAM::Policy + Properties: + PolicyDocument: + Statement: + - Action: + - ec2:DescribeInstances + - ec2:AssociateIamInstanceProfile + - ec2:ReplaceIamInstanceProfileAssociation + - ec2:RebootInstances + - iam:ListInstanceProfiles + - iam:PassRole + - ssm:DescribeAssociationExecutions + - ssm:DescribeAssociationExecutionTargets + Effect: Allow + Resource: "*" + Version: "2012-10-17" + PolicyName: CustomCloud9SsmProfileAttachLambdaFunctionServiceRoleDefaultPolicy9CC20561 + Roles: + - Ref: CustomCloud9SsmProfileAttachLambdaFunctionServiceRoleF610D074 + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/ProfileAttachLambdaFunction/ServiceRole/DefaultPolicy/Resource + CustomCloud9SsmProfileAttachLambdaFunction01DB4FFC: + Type: AWS::Lambda::Function + Properties: + Code: + ZipFile: | + import boto3 + import cfnresponse + import time + + + def is_association_applied(association_id): + client = boto3.client('ssm') + + # Retrieve the execution history of the association + response = client.describe_association_executions( + AssociationId=association_id, + Filters=[ + { + 'Key': 'Status', + 'Value': 'Success', + 'Type': 'EQUAL' + } + ] + ) + + # There are no executions yet + if 'AssociationExecutions' not in response or not response['AssociationExecutions']: + return False + + # Retrieve the targets of the execution to see if the SSM agent has picked up the EC2 instance yet + response = client.describe_association_execution_targets( + AssociationId=association_id, + ExecutionId=response['AssociationExecutions'][0]['ExecutionId'], + Filters=[ + { + 'Key': 'Status', + 'Value': 'Success' + } + ] + ) + + return 'AssociationExecutionTargets' in response and response['AssociationExecutionTargets'] + + + def handler(event, context): + if event['RequestType'] == 'Create': + # Extract context variables + stack_id = event['ResourceProperties']['stack_id'] + profile_arn = event['ResourceProperties']['profile_arn'] + association_id = event['ResourceProperties']['association_id'] + + try: + client = boto3.client('ec2') + + # Retrieve EC2 instance's identifier + print('Retrieving EC2 instance Id') + + instance_id = client.describe_instances( + Filters=[{'Name': 'tag:stack-id', 'Values': [stack_id]}] + )['Reservations'][0]['Instances'][0]['InstanceId'] + + # Associate the SSM instance profile + print('Associating the SSM instance profile to the instance') + + client.associate_iam_instance_profile( + IamInstanceProfile={'Arn': profile_arn}, + InstanceId=instance_id + ) + + # Reboot the instance to restart the SSM agent + print('Rebooting the instance so that the SSM agent picks up the association') + + client.reboot_instances( + InstanceIds=[instance_id] + ) + + # Wait for the SSM association to be applied + while True: + print('Waiting for the association to be applied') + + if is_association_applied(association_id): + break + else: + time.sleep(5) + except Exception as e: + cfnresponse.send(event, context, cfnresponse.FAILED, {'Error': e.args[0]}) + return + + cfnresponse.send(event, context, cfnresponse.SUCCESS, {}) + Role: + Fn::GetAtt: + - CustomCloud9SsmProfileAttachLambdaFunctionServiceRoleF610D074 + - Arn + Handler: index.handler + Runtime: python3.6 + Timeout: 800 + DependsOn: + - CustomCloud9SsmProfileAttachLambdaFunctionServiceRoleDefaultPolicy9CC20561 + - CustomCloud9SsmProfileAttachLambdaFunctionServiceRoleF610D074 + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/ProfileAttachLambdaFunction/Resource + CustomCloud9SsmCustomResourceCD940758: + Type: AWS::CloudFormation::CustomResource + Properties: + ServiceToken: + Fn::GetAtt: + - CustomCloud9SsmProfileAttachLambdaFunction01DB4FFC + - Arn + stack_id: + Ref: AWS::StackId + profile_arn: + Fn::GetAtt: + - CustomCloud9SsmEc2InstanceProfile167B6BF8 + - Arn + association_id: + Fn::GetAtt: + - CustomCloud9SsmSsmAssociationABF443F9 + - AssociationId + DependsOn: + - CustomCloud9SsmEc2InstanceProfile167B6BF8 + - CustomCloud9SsmSsmAssociationABF443F9 + UpdateReplacePolicy: Delete + DeletionPolicy: Delete + Metadata: + aws:cdk:path: RenderingStack/CustomCloud9Ssm/CustomResource/Default Vpc8378EB38: Type: AWS::EC2::VPC Properties: @@ -8,9 +307,9 @@ Resources: InstanceTenancy: default Tags: - Key: Name - Value: RenderingWithBatchStack/Vpc + Value: RenderingStack/Vpc Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/Resource + aws:cdk:path: RenderingStack/Vpc/Resource VpcRenderingWithBatchSubnet1SubnetADE6DAA0: Type: AWS::EC2::Subnet Properties: @@ -28,9 +327,9 @@ Resources: - Key: aws-cdk:subnet-type Value: Public - Key: Name - Value: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet1 + Value: RenderingStack/Vpc/RenderingWithBatchSubnet1 Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet1/Subnet + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet1/Subnet VpcRenderingWithBatchSubnet1RouteTable1BCC3903: Type: AWS::EC2::RouteTable Properties: @@ -38,9 +337,9 @@ Resources: Ref: Vpc8378EB38 Tags: - Key: Name - Value: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet1 + Value: RenderingStack/Vpc/RenderingWithBatchSubnet1 Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet1/RouteTable + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet1/RouteTable VpcRenderingWithBatchSubnet1RouteTableAssociation9592115F: Type: AWS::EC2::SubnetRouteTableAssociation Properties: @@ -49,7 +348,7 @@ Resources: SubnetId: Ref: VpcRenderingWithBatchSubnet1SubnetADE6DAA0 Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet1/RouteTableAssociation + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet1/RouteTableAssociation VpcRenderingWithBatchSubnet1DefaultRoute58E16100: Type: AWS::EC2::Route Properties: @@ -61,7 +360,7 @@ Resources: DependsOn: - VpcVPCGWBF912B6E Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet1/DefaultRoute + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet1/DefaultRoute VpcRenderingWithBatchSubnet2SubnetDC61207B: Type: AWS::EC2::Subnet Properties: @@ -79,9 +378,9 @@ Resources: - Key: aws-cdk:subnet-type Value: Public - Key: Name - Value: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet2 + Value: RenderingStack/Vpc/RenderingWithBatchSubnet2 Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet2/Subnet + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet2/Subnet VpcRenderingWithBatchSubnet2RouteTable5DF00176: Type: AWS::EC2::RouteTable Properties: @@ -89,9 +388,9 @@ Resources: Ref: Vpc8378EB38 Tags: - Key: Name - Value: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet2 + Value: RenderingStack/Vpc/RenderingWithBatchSubnet2 Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet2/RouteTable + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet2/RouteTable VpcRenderingWithBatchSubnet2RouteTableAssociationE3297937: Type: AWS::EC2::SubnetRouteTableAssociation Properties: @@ -100,7 +399,7 @@ Resources: SubnetId: Ref: VpcRenderingWithBatchSubnet2SubnetDC61207B Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet2/RouteTableAssociation + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet2/RouteTableAssociation VpcRenderingWithBatchSubnet2DefaultRoute42CB5476: Type: AWS::EC2::Route Properties: @@ -112,15 +411,15 @@ Resources: DependsOn: - VpcVPCGWBF912B6E Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/RenderingWithBatchSubnet2/DefaultRoute + aws:cdk:path: RenderingStack/Vpc/RenderingWithBatchSubnet2/DefaultRoute VpcIGWD7BA715C: Type: AWS::EC2::InternetGateway Properties: Tags: - Key: Name - Value: RenderingWithBatchStack/Vpc + Value: RenderingStack/Vpc Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/IGW + aws:cdk:path: RenderingStack/Vpc/IGW VpcVPCGWBF912B6E: Type: AWS::EC2::VPCGatewayAttachment Properties: @@ -129,11 +428,11 @@ Resources: InternetGatewayId: Ref: VpcIGWD7BA715C Metadata: - aws:cdk:path: RenderingWithBatchStack/Vpc/VPCGW + aws:cdk:path: RenderingStack/Vpc/VPCGW securityGroup32C48086: Type: AWS::EC2::SecurityGroup Properties: - GroupDescription: RenderingWithBatchStack/securityGroup + GroupDescription: RenderingStack/securityGroup GroupName: RenderingWithBatch SecurityGroupEgress: - CidrIp: 0.0.0.0/0 @@ -141,8 +440,20 @@ Resources: IpProtocol: "-1" VpcId: Ref: Vpc8378EB38 + DependsOn: + - VpcIGWD7BA715C + - VpcRenderingWithBatchSubnet1DefaultRoute58E16100 + - VpcRenderingWithBatchSubnet1RouteTable1BCC3903 + - VpcRenderingWithBatchSubnet1RouteTableAssociation9592115F + - VpcRenderingWithBatchSubnet1SubnetADE6DAA0 + - VpcRenderingWithBatchSubnet2DefaultRoute42CB5476 + - VpcRenderingWithBatchSubnet2RouteTable5DF00176 + - VpcRenderingWithBatchSubnet2RouteTableAssociationE3297937 + - VpcRenderingWithBatchSubnet2SubnetDC61207B + - Vpc8378EB38 + - VpcVPCGWBF912B6E Metadata: - aws:cdk:path: RenderingWithBatchStack/securityGroup/Resource + aws:cdk:path: RenderingStack/securityGroup/Resource launchTemplateDEE5742D: Type: AWS::EC2::LaunchTemplate Properties: @@ -155,11 +466,11 @@ Resources: - ResourceType: instance Tags: - Key: Name - Value: RenderingWithBatchStack/launchTemplate + Value: RenderingStack/launchTemplate - ResourceType: volume Tags: - Key: Name - Value: RenderingWithBatchStack/launchTemplate + Value: RenderingStack/launchTemplate UserData: Fn::Base64: |- MIME-Version: 1.0 @@ -176,14 +487,10 @@ Resources: --==MYBOUNDARY==-- LaunchTemplateName: RenderingWithBatch + DependsOn: + - securityGroup32C48086 Metadata: - aws:cdk:path: RenderingWithBatchStack/launchTemplate/Resource - bucket43879C71: - Type: AWS::S3::Bucket - UpdateReplacePolicy: Delete - DeletionPolicy: Delete - Metadata: - aws:cdk:path: RenderingWithBatchStack/bucket/Resource + aws:cdk:path: RenderingStack/launchTemplate/Resource repository9F1A3F0B: Type: AWS::ECR::Repository Properties: @@ -191,55 +498,8 @@ Resources: UpdateReplacePolicy: Delete DeletionPolicy: Delete Metadata: - aws:cdk:path: RenderingWithBatchStack/repository/Resource - cloud9envec2env8356485F: - Type: AWS::Cloud9::EnvironmentEC2 - Properties: - InstanceType: t2.micro - Name: RenderingWithBatch - SubnetId: - Ref: VpcRenderingWithBatchSubnet1SubnetADE6DAA0 - Tags: - - Key: SSMBootstrap - Value: RenderingWithBatch - Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/ec2env/Resource - cloud9envSSMDocument9E89DF0C: - Type: AWS::SSM::Document - Properties: - Content: - schemaVersion: '2.2' - description: Bootstrap Cloud9 Instance - mainSteps: - - action: aws:runShellScript - name: C9bootstrap - inputs: - runCommand: - - "#!/bin/bash" - - echo '=== Installing packages ===' - - sudo yum -y install jq - - sudo pip install boto3 - - echo '=== Resizing file system ===' - - sudo growpart /dev/xvda 1 - - sudo resize2fs /dev/xvda1 - DocumentType: Command - Name: BootstrapDocument - Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/SSMDocument - cloud9envSSMAssociation4FBBFEE5: - Type: AWS::SSM::Association - Properties: - Name: BootstrapDocument - Targets: - - Key: tag:SSMBootstrap - Values: - - RenderingWithBatch - DependsOn: - - cloud9envbootstrapLambdaCustomResourceD5142DA7 - - cloud9envSSMDocument9E89DF0C - Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/SSMAssociation - cloud9envFISRoleAD8CCA4E: + aws:cdk:path: RenderingStack/repository/Resource + ecsRole157644C0: Type: AWS::IAM::Role Properties: AssumeRolePolicyDocument: @@ -254,18 +514,26 @@ Resources: - Ref: AWS::URLSuffix Version: "2012-10-17" ManagedPolicyArns: - - arn:aws:iam::aws:policy/AmazonSSMManagedInstanceCore - RoleName: SSMInstanceProfile + - arn:aws:iam::aws:policy/AmazonS3FullAccess + - arn:aws:iam::aws:policy/service-role/AmazonEC2ContainerServiceforEC2Role Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/FISRole/Resource - cloud9envfisinstanceprofile96D194A9: + aws:cdk:path: RenderingStack/ecsRole/Resource + ecsinstanceprofile: Type: AWS::IAM::InstanceProfile Properties: Roles: - - Ref: cloud9envFISRoleAD8CCA4E + - Ref: ecsRole157644C0 + DependsOn: + - ecsRole157644C0 Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/fisinstanceprofile - cloud9envbootstrapLambdaServiceRole520F9D06: + aws:cdk:path: RenderingStack/ecsinstanceprofile + bucket43879C71: + Type: AWS::S3::Bucket + UpdateReplacePolicy: Delete + DeletionPolicy: Delete + Metadata: + aws:cdk:path: RenderingStack/bucket/Resource + PreprocessingServiceRole532E6474: Type: AWS::IAM::Role Properties: AssumeRolePolicyDocument: @@ -281,150 +549,190 @@ Resources: - - "arn:" - Ref: AWS::Partition - :iam::aws:policy/service-role/AWSLambdaBasicExecutionRole + DependsOn: + - bucket43879C71 Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/bootstrapLambda/ServiceRole/Resource - cloud9envbootstrapLambdaServiceRoleDefaultPolicy474DC27A: + aws:cdk:path: RenderingStack/Preprocessing/ServiceRole/Resource + PreprocessingServiceRoleDefaultPolicyF8800D5C: Type: AWS::IAM::Policy Properties: PolicyDocument: Statement: - - Action: - - ec2:DescribeInstances - - ec2:ModifyVolume - - ec2:AssociateIamInstanceProfile - - ec2:ReplaceIamInstanceProfileAssociation - - ec2:RebootInstances - - iam:ListInstanceProfiles - - iam:PassRole - - ssm:SendCommand + - Action: "*" Effect: Allow - Resource: "*" + Resource: + - Fn::GetAtt: + - bucket43879C71 + - Arn + - Fn::Join: + - "" + - - Fn::GetAtt: + - bucket43879C71 + - Arn + - /* Version: "2012-10-17" - PolicyName: cloud9envbootstrapLambdaServiceRoleDefaultPolicy474DC27A + PolicyName: PreprocessingServiceRoleDefaultPolicyF8800D5C Roles: - - Ref: cloud9envbootstrapLambdaServiceRole520F9D06 + - Ref: PreprocessingServiceRole532E6474 + DependsOn: + - bucket43879C71 Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/bootstrapLambda/ServiceRole/DefaultPolicy/Resource - cloud9envbootstrapLambda02FC7F40: + aws:cdk:path: RenderingStack/Preprocessing/ServiceRole/DefaultPolicy/Resource + Preprocessing329E01E4: Type: AWS::Lambda::Function Properties: Code: ZipFile: | - import time - import boto3 - import cfnresponse + import json, gzip, struct, boto3, math, sys - def retrieve_cloud9_instance(env_id): - print("Retrieving environment's instance...") + # ##### BEGIN GPL LICENSE BLOCK ##### + # + # Extract from Blender's script library included in scripts/modules. + # + # This program is free software; you can redistribute it and/or + # modify it under the terms of the GNU General Public License + # as published by the Free Software Foundation; either version 2 + # of the License, or (at your option) any later version. + # + # This program is distributed in the hope that it will be useful, + # but WITHOUT ANY WARRANTY; without even the implied warranty of + # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + # GNU General Public License for more details. + # + # ##### END GPL LICENSE BLOCK ##### + def read_blend_rend_chunk(file): + blendfile = open(file, "rb") - client = boto3.client('ec2') + head = blendfile.read(7) - return client.describe_instances( - Filters=[ - { - 'Name': 'tag:aws:cloud9:environment', - 'Values': [ - env_id, - ] - }, - ] - )['Reservations'][0]['Instances'][0] + if head[0:2] == b'\x1f\x8b': # gzip magic + blendfile.seek(0) + blendfile = gzip.open(blendfile, "rb") + head = blendfile.read(7) + if head != b'BLENDER': + print("not a blend file:", file) + blendfile.close() + return [] - def resize_volume(volume_id, new_size): - print('Resizing EBS volume...') + is_64_bit = (blendfile.read(1) == b'-') - client = boto3.client('ec2') + # true for PPC, false for X86 + is_big_endian = (blendfile.read(1) == b'V') - client.modify_volume( - VolumeId=volume_id, - Size=new_size - ) + # Now read the bhead chunk!!! + blendfile.read(3) # skip the version - print('EBS volume resized') + scenes = [] + sizeof_bhead = 24 if is_64_bit else 20 - def associate_ssm_instance_profile(c9_env_id, profile_arn): - instance_data = retrieve_cloud9_instance(c9_env_id) - client = boto3.client('ec2') + while blendfile.read(4) == b'REND': + sizeof_bhead_left = sizeof_bhead - 4 - while instance_data['State']['Name'] != 'running': - print('Waiting for the instance to be running to attach the instance profile...') - time.sleep(5) - instance_data = retrieve_cloud9_instance(c9_env_id) + struct.unpack('>i' if is_big_endian else '2i' if is_big_endian else '<2i', blendfile.read(8)) - print('Instance profile associated. Restarting SSM agent...') + scene_name = blendfile.read(64) - client.reboot_instances( - InstanceIds=[ - instance_data['InstanceId'] - ] - ) + scene_name = scene_name[:scene_name.index(b'\0')] - print('Instance rebooted') + try: + scene_name = str(scene_name, "utf8") + except TypeError: + pass + scenes.append((start_frame, end_frame, scene_name)) - def handler(event, context): - if event['RequestType'] == 'Create': - # Extract context variables - c9_env_id = event['ResourceProperties']['cloud9EnvId'] - ebs_size = int(event['ResourceProperties']['ebsSize']) - profile_arn = event['ResourceProperties']['profile_arn'] + blendfile.close() - try: - # Retrieve EC2 instance's identifier and its EBS volume's identifier - instance_data = retrieve_cloud9_instance(c9_env_id) - volume_id = instance_data['BlockDeviceMappings'][0]['Ebs']['VolumeId'] + return scenes - # Resize the EBS volume - resize_volume(volume_id, ebs_size) - # Associate the SSM instance profile - associate_ssm_instance_profile(c9_env_id, profile_arn) - except Exception as e: - cfnresponse.send(event, context, cfnresponse.FAILED, {'Error': e.args[0]}) - return + def get_number_of_frames(file): + """Reads the header of the blend file and calculates + the number of frames it has. - cfnresponse.send(event, context, cfnresponse.SUCCESS, {}) + Keyword arguments: + file -- Blender file to analyse + """ + + try: + frame_start, frame_end, scene = read_blend_rend_chunk(file)[0] + except FileNotFoundError as e: + print(e.args[1]) + sys.exit(2) + else: + return int(frame_end - frame_start + 1) + + + def download_blender_file_from_s3(uri): + """Downloads the blend file from S3 and stores it locally. + + Keyword arguments: + uri -- S3 URI of the file to download + """ + + uri_components = uri.split('s3://')[1].split('/') + bucket = uri_components[0] + file = uri_components[1] + + s3 = boto3.resource('s3') + s3.meta.client.download_file(bucket, file, '/tmp/{}'.format(file)) + + return '/tmp/{}'.format(file) + + + def calculate_array_job_size(file, frames_per_job): + """Calculates the size of the job array + + Keyword arguments: + file -- Blender file to analyse + frames_per_job -- Number of frames each Batch job has to render + """ + + # Get the scene's number of frames by reading the header of the blender file + n_frames = get_number_of_frames(file) + + # Adjust the number of frames per job if needed + frames_per_job = min(frames_per_job, n_frames) + + # Calculate how many jobs need to be submitted + return n_frames, math.ceil(n_frames / frames_per_job) + + + def lambda_handler(event, context): + # Download the blend file from s3 and save it locally to work with it + file = download_blender_file_from_s3(event['inputUri']) + + # Calculate the size of the array job and extract the number of frames + n_frames, array_job_size = calculate_array_job_size(file, int(event['framesPerJob'])) + + return { + 'statusCode': 200, + 'body': {'arrayJobSize': array_job_size} + } Role: Fn::GetAtt: - - cloud9envbootstrapLambdaServiceRole520F9D06 + - PreprocessingServiceRole532E6474 - Arn - Handler: index.handler - Runtime: python3.7 + Handler: index.lambda_handler + Runtime: python3.9 Timeout: 300 DependsOn: - - cloud9envbootstrapLambdaServiceRoleDefaultPolicy474DC27A - - cloud9envbootstrapLambdaServiceRole520F9D06 + - bucket43879C71 + - PreprocessingServiceRoleDefaultPolicyF8800D5C + - PreprocessingServiceRole532E6474 Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/bootstrapLambda/Resource - cloud9envbootstrapLambdaCustomResourceD5142DA7: - Type: AWS::CloudFormation::CustomResource - Properties: - ServiceToken: - Fn::GetAtt: - - cloud9envbootstrapLambda02FC7F40 - - Arn - cloud9EnvId: - Ref: cloud9envec2env8356485F - ebsSize: 40 - profile_arn: - Fn::GetAtt: - - cloud9envfisinstanceprofile96D194A9 - - Arn - UpdateReplacePolicy: Delete - DeletionPolicy: Delete - Metadata: - aws:cdk:path: RenderingWithBatchStack/cloud9env/bootstrapLambdaCustomResource/Default - ecsRole157644C0: + aws:cdk:path: RenderingStack/Preprocessing/Resource + RenderingPipelineRole4AAB9C07: Type: AWS::IAM::Role Properties: AssumeRolePolicyDocument: @@ -435,27 +743,93 @@ Resources: Service: Fn::Join: - "" - - - ec2. - - Ref: AWS::URLSuffix + - - states. + - Ref: AWS::Region + - .amazonaws.com Version: "2012-10-17" - ManagedPolicyArns: - - arn:aws:iam::aws:policy/AmazonS3FullAccess - - arn:aws:iam::aws:policy/service-role/AmazonEC2ContainerServiceforEC2Role Metadata: - aws:cdk:path: RenderingWithBatchStack/ecsRole/Resource - ecsinstanceprofile: - Type: AWS::IAM::InstanceProfile + aws:cdk:path: RenderingStack/RenderingPipeline/Role/Resource + RenderingPipelineRoleDefaultPolicy951F3306: + Type: AWS::IAM::Policy Properties: + PolicyDocument: + Statement: + - Action: lambda:InvokeFunction + Effect: Allow + Resource: + Fn::GetAtt: + - Preprocessing329E01E4 + - Arn + - Action: batch:SubmitJob + Effect: Allow + Resource: + - Fn::Join: + - "" + - - "arn:" + - Ref: AWS::Partition + - ":batch:" + - Ref: AWS::Region + - ":" + - Ref: AWS::AccountId + - :job-definition/* + - Fn::Join: + - "" + - - "arn:" + - Ref: AWS::Partition + - ":batch:" + - Ref: AWS::Region + - ":" + - Ref: AWS::AccountId + - :job-queue/* + - Action: + - events:PutTargets + - events:PutRule + - events:DescribeRule + Effect: Allow + Resource: + Fn::Join: + - "" + - - "arn:" + - Ref: AWS::Partition + - ":events:" + - Ref: AWS::Region + - ":" + - Ref: AWS::AccountId + - :rule/StepFunctionsGetEventsForBatchJobsRule + Version: "2012-10-17" + PolicyName: RenderingPipelineRoleDefaultPolicy951F3306 Roles: - - Ref: ecsRole157644C0 + - Ref: RenderingPipelineRole4AAB9C07 Metadata: - aws:cdk:path: RenderingWithBatchStack/ecsinstanceprofile + aws:cdk:path: RenderingStack/RenderingPipeline/Role/DefaultPolicy/Resource + RenderingPipeline477A29E4: + Type: AWS::StepFunctions::StateMachine + Properties: + RoleArn: + Fn::GetAtt: + - RenderingPipelineRole4AAB9C07 + - Arn + DefinitionString: + Fn::Join: + - "" + - - '{"Comment": "Workflow orchestration for a rendering pipeline using AWS Batch","StartAt":"Number of frames extraction","States":{"Number of frames extraction":{"Next":"Rendering","Retry":[{"ErrorEquals":["Lambda.ServiceException","Lambda.AWSLambdaException","Lambda.SdkClientException"],"IntervalSeconds":2,"MaxAttempts":6,"BackoffRate":2}],"Type":"Task","Resource":"arn:' + - Ref: AWS::Partition + - :states:::lambda:invoke","Parameters":{"FunctionName":" + - Fn::GetAtt: + - Preprocessing329E01E4 + - Arn + - '","Payload.$":"$"}, "ResultPath":"$.output"},"Rendering":{"Type":"Task","Resource":"arn:aws:states:::batch:submitJob.sync","Parameters":{"JobName.$":"$.jobName","ArrayProperties":{"Size.$":"$.output.Payload.body.arrayJobSize"},"Parameters":{"action":"render","inputUri.$":"$.inputUri","outputUri.$":"$.outputUri","framesPerJob.$":"$.framesPerJob"},"JobDefinition.$":"$.jobDefinitionArn","JobQueue.$":"$.jobQueueArn"},"Next":"Stitching","ResultPath":"$.output"},"Stitching":{"Type":"Task","Resource":"arn:aws:states:::batch:submitJob.sync","Parameters":{"JobName":"Stitching","Parameters":{"action":"stitch","inputUri.$":"$.outputUri","outputUri.$":"$.outputUri","framesPerJob.$":"$.framesPerJob"},"JobDefinition.$":"$.jobDefinitionArn","JobQueue.$":"$.jobQueueArn"},"End":true}}}' + DependsOn: + - RenderingPipelineRoleDefaultPolicy951F3306 + - RenderingPipelineRole4AAB9C07 + Metadata: + aws:cdk:path: RenderingStack/RenderingPipeline/Resource CDKMetadata: Type: AWS::CDK::Metadata Properties: - Analytics: 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RenderingWithBatchStack/CDKMetadata/Default + aws:cdk:path: RenderingStack/CDKMetadata/Default Condition: CDKMetadataAvailable Outputs: Subnet1: @@ -466,11 +840,6 @@ Outputs: Ref: VpcRenderingWithBatchSubnet2SubnetDC61207B LaunchTemplateName: Value: RenderingWithBatch - BucketName: - Value: - Ref: bucket43879C71 - BlendFileName: - Value: blendfile.blend RepositoryName: Value: Ref: repository9F1A3F0B @@ -479,6 +848,17 @@ Outputs: Fn::GetAtt: - ecsinstanceprofile - Arn + BucketName: + Value: + Ref: bucket43879C71 + BlendFileName: + Value: blendfile.blend + PreprocessingLambda: + Value: + Ref: Preprocessing329E01E4 + StateMachineArn: + Value: + Ref: RenderingPipeline477A29E4 Conditions: CDKMetadataAvailable: Fn::Or: diff --git a/static/images/rendering-with-batch/step-functions.png b/static/images/rendering-with-batch/step-functions.png index db7ec076523af23bc5c742ec7d85ed7d7629b6f0..c6905f1157a789eeee323f94e6498dc37c896e59 100644 GIT binary patch literal 111604 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z!+-^D3-*>&I`w5+D6WI+TY)0o0q`|qps7GR%DNr@wudc1Inrc|-*~N#xnYB~|9mI} zQgn^rj-Rx|0Z;%HYFQti*N7i)0My*B0W}2&X{YZqjo+RQJ;~RVP!8)B98cU5DJ(yk zxJ1tUAt(x>Yn6M40#~2#Ex?yysI!8u90uVFw1n_|GU(JW#`4<1+l@8gK-2>_U&}H&;t)F_BxqU`9a;;b9 zzmCX14+HCIZY}lb+dI+_(>D@mA<*SNcK;8-BfdvcG=4tCF|=MUQ3*>-QAtSZ7uUr9 z^oXiX0G&G2_dlp({|(IIMWA;DGHIu=fWFbUZ*t=Q zB?8d6+!Pumxv&t1ylH$8eU#^(?rm8(pS=FqO>Qt=1(9#+`|adC-gA1J+G z>JZNSeW|HkcD)Mv2dka0w})m=W{WDiT{AN`pYnTfxudP=X_N#wq~O?-Ya3 D=h_G+ From 686d53b12bcc3838e5ec14aaa519ad64578b3894 Mon Sep 17 00:00:00 2001 From: Borja Perez Guasch Date: Thu, 13 Jan 2022 11:42:18 +0100 Subject: [PATCH 5/7] Updated ECR permissions to be able to push the Docker image --- .../rendering-with-batch.files/stack.yaml | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/content/rendering-with-batch/rendering-with-batch.files/stack.yaml b/content/rendering-with-batch/rendering-with-batch.files/stack.yaml index 328d2ebb..b6613ca2 100644 --- a/content/rendering-with-batch/rendering-with-batch.files/stack.yaml +++ b/content/rendering-with-batch/rendering-with-batch.files/stack.yaml @@ -44,8 +44,7 @@ Resources: - batch:UpdateComputeEnvironment - batch:ListJobs - batch:ListJobs - - ecr:BatchDeleteImage - - ecr:GetAuthorizationToken + - ecr:* - batch:DescribeComputeEnvironments - cloudformation:DescribeStacks - batch:DeregisterJobDefinition @@ -58,7 +57,6 @@ Resources: - states:StartExecution - batch:DescribeJobDefinitions - batch:DeleteJobQueue - - ecr:DescribeRepositories - batch:UpdateJobQueue - iam:PassRole Effect: Allow From 4f537fed77a05907243e2e64db95a3050e3abd10 Mon Sep 17 00:00:00 2001 From: Borja Perez Guasch Date: Thu, 13 Jan 2022 16:03:30 +0100 Subject: [PATCH 6/7] Final version of the template tested in EE --- .../rendering-with-batch.files/stack.yaml | 22 ++++++++++++++++++- content/rendering-with-batch/start/_index.md | 2 +- 2 files changed, 22 insertions(+), 2 deletions(-) diff --git a/content/rendering-with-batch/rendering-with-batch.files/stack.yaml b/content/rendering-with-batch/rendering-with-batch.files/stack.yaml index b6613ca2..642f7d1c 100644 --- a/content/rendering-with-batch/rendering-with-batch.files/stack.yaml +++ b/content/rendering-with-batch/rendering-with-batch.files/stack.yaml @@ -1,12 +1,31 @@ +Parameters: + C9InstanceType: + Description: Cloud9 instance type + Type: String + Default: m5.large + AllowedValues: + - t3.small + - t3.medium + - m4.large + - m5.large + ConstraintDescription: Must be a valid Cloud9 instance type + # Used only by Event Engine, if you are self-deploying the stack leave the default value to NONE + EETeamRoleArn: + Description: "ARN of the Team Role" + Default: NONE + Type: String + ConstraintDescription: This is ONLY used Event Engine, don't change this if you are self-deploying the stack Resources: CustomCloud9SsmCloud9Ec2EnvironmentF47DD48C: Type: AWS::Cloud9::EnvironmentEC2 Properties: - InstanceType: t3.large + InstanceType: + Ref: C9InstanceType Tags: - Key: stack-id Value: Ref: AWS::StackId + OwnerArn: !If [NotEventEngine , !Ref AWS::NoValue , !Sub 'arn:aws:sts::${AWS::AccountId}:assumed-role/TeamRole/MasterKey'] Metadata: aws:cdk:path: RenderingStack/CustomCloud9Ssm/Cloud9Ec2Environment CustomCloud9SsmEc2RoleCE9ACBCB: @@ -858,6 +877,7 @@ Outputs: Value: Ref: RenderingPipeline477A29E4 Conditions: + NotEventEngine: !Equals [!Ref EETeamRoleArn, NONE] CDKMetadataAvailable: Fn::Or: - Fn::Or: diff --git a/content/rendering-with-batch/start/_index.md b/content/rendering-with-batch/start/_index.md index 6e2d7a9d..5cc28279 100644 --- a/content/rendering-with-batch/start/_index.md +++ b/content/rendering-with-batch/start/_index.md @@ -11,5 +11,5 @@ To start the workshop head to one of the following pages, depending whether you When you finish the workshop, don't forget to execute the commands described in [**Clean up**](/rendering-with-batch/cleanup.html) to prevent incurring in additional charges. {{% notice info %}} -The estimated completion time of this lab is **60 minutes**. Rendering the animation presented in the initial page of this workshop, you will incur in an estimated cost of up to **$15**. +The estimated completion time of this lab is **90 minutes**. Rendering the animation presented in the initial page of this workshop, you will incur in an estimated cost of up to **$15**. {{% /notice %}} From 34a6c54f3f3e2be8e76bc1ddaa73cf34a2337a7a Mon Sep 17 00:00:00 2001 From: Borja Perez Guasch Date: Mon, 1 Aug 2022 17:44:04 +0200 Subject: [PATCH 7/7] Modified theme files --- themes/learn | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/themes/learn b/themes/learn index e817f53d..ed760baf 160000 --- a/themes/learn +++ b/themes/learn @@ -1 +1 @@ -Subproject commit e817f53d690d35f181c896e0e320cb40f797e88c +Subproject commit ed760baf3f083bc774f49eed688973a97de28904