diff --git a/.gitbook.yaml b/.gitbook.yaml index bdd2977aa..1d974eca0 100644 --- a/.gitbook.yaml +++ b/.gitbook.yaml @@ -10,4 +10,5 @@ redirects: usage/contour-progressive-delivery: tutorials/contour-progressive-delivery.md usage/gloo-progressive-delivery: tutorials/gloo-progressive-delivery.md usage/nginx-progressive-delivery: tutorials/nginx-progressive-delivery.md + usage/skipper-progressive-delivery: tutorials/skipper-progressive-delivery.md usage/crossover-progressive-delivery: tutorials/crossover-progressive-delivery.md diff --git a/README.md b/README.md index 4c1a237e3..7686360b7 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ by gradually shifting traffic to the new version while measuring metrics and run ![flagger-overview](https://raw.githubusercontent.com/weaveworks/flagger/master/docs/diagrams/flagger-canary-overview.png) Flagger implements several deployment strategies (Canary releases, A/B testing, Blue/Green mirroring) -using a service mesh (App Mesh, Istio, Linkerd) or an ingress controller (Contour, Gloo, NGINX) for traffic routing. +using a service mesh (App Mesh, Istio, Linkerd) or an ingress controller (Contour, Gloo, NGINX, Skipper) for traffic routing. For release analysis, Flagger can query Prometheus, Datadog or CloudWatch and for alerting it uses Slack, MS Teams, Discord and Rocket. @@ -37,6 +37,7 @@ Flagger documentation can be found at [docs.flagger.app](https://docs.flagger.ap * [Contour](https://docs.flagger.app/tutorials/contour-progressive-delivery) * [Gloo](https://docs.flagger.app/tutorials/gloo-progressive-delivery) * [NGINX Ingress](https://docs.flagger.app/tutorials/nginx-progressive-delivery) + * [Skipper](https://docs.flagger.app/tutorials/skipper-progressive-delivery) * [Kubernetes Blue/Green](https://docs.flagger.app/tutorials/kubernetes-blue-green) ### Who is using Flagger @@ -71,7 +72,7 @@ metadata: namespace: test spec: # service mesh provider (optional) - # can be: kubernetes, istio, linkerd, appmesh, nginx, contour, gloo, supergloo + # can be: kubernetes, istio, linkerd, appmesh, nginx, skipper, contour, gloo, supergloo provider: istio # deployment reference targetRef: @@ -180,17 +181,17 @@ For more details on how the canary analysis and promotion works please [read the ### Features -| Feature | Istio | Linkerd | App Mesh | NGINX | Gloo | Contour | CNI | -| -------------------------------------------- | ------------------ | ------------------ |------------------ |------------------ |------------------ |------------------ |------------------ | -| Canary deployments (weighted traffic) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | -| A/B testing (headers and cookies routing) | :heavy_check_mark: | :heavy_minus_sign: | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | :heavy_check_mark: | :heavy_minus_sign: | -| Blue/Green deployments (traffic switch) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | -| Webhooks (acceptance/load testing) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | -| Manual gating (approve/pause/resume) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | -| Request success rate check (L7 metric) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | -| Request duration check (L7 metric) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | -| Custom metric checks | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | -| Traffic policy, CORS, retries and timeouts | :heavy_check_mark: | :heavy_minus_sign: | :heavy_minus_sign: | :heavy_minus_sign: | :heavy_minus_sign: | :heavy_check_mark: | :heavy_minus_sign: | +| Feature | Istio | Linkerd | App Mesh | NGINX | Skipper | Gloo | Contour | CNI | +| -------------------------------------------- | ------------------ | ------------------ |------------------ |------------------ |------------------ |------------------ |------------------ |------------------ | +| Canary deployments (weighted traffic) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark:| :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | +| A/B testing (headers and cookies routing) | :heavy_check_mark: | :heavy_minus_sign: | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign:| :heavy_minus_sign: | :heavy_check_mark: | :heavy_minus_sign: | +| Blue/Green deployments (traffic switch) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark:| :heavy_minus_sign: | :heavy_check_mark: | :heavy_check_mark: | +| Webhooks (acceptance/load testing) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark:| :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | +| Manual gating (approve/pause/resume) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark:| :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | +| Request success rate check (L7 metric) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark:| :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | +| Request duration check (L7 metric) | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark:| :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | +| Custom metric checks | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark:| :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | +| Traffic policy, CORS, retries and timeouts | :heavy_check_mark: | :heavy_minus_sign: | :heavy_minus_sign: | :heavy_minus_sign: | :heavy_minus_sign:| :heavy_minus_sign: | :heavy_check_mark: | :heavy_minus_sign: | ### Roadmap diff --git a/charts/flagger/README.md b/charts/flagger/README.md index c2476ecae..fa5589aeb 100644 --- a/charts/flagger/README.md +++ b/charts/flagger/README.md @@ -7,7 +7,7 @@ Flagger can run automated application analysis, testing, promotion and rollback * A/B Testing (HTTP headers and cookies traffic routing) * Blue/Green (traffic switching and mirroring) -Flagger works with service mesh solutions (Istio, Linkerd, AWS App Mesh) and with Kubernetes ingress controllers (NGINX, Gloo, Contour). +Flagger works with service mesh solutions (Istio, Linkerd, AWS App Mesh) and with Kubernetes ingress controllers (NGINX, Skipper, Gloo, Contour). Flagger can be configured to send alerts to various chat platforms such as Slack, Microsoft Teams, Discord and Rocket. ## Prerequisites diff --git a/cmd/flagger/main.go b/cmd/flagger/main.go index 540179a80..0ce5c76ce 100644 --- a/cmd/flagger/main.go +++ b/cmd/flagger/main.go @@ -78,7 +78,7 @@ func init() { flag.BoolVar(&zapReplaceGlobals, "zap-replace-globals", false, "Whether to change the logging level of the global zap logger.") flag.StringVar(&zapEncoding, "zap-encoding", "json", "Zap logger encoding.") flag.StringVar(&namespace, "namespace", "", "Namespace that flagger would watch canary object.") - flag.StringVar(&meshProvider, "mesh-provider", "istio", "Service mesh provider, can be istio, linkerd, appmesh, contour, gloo or nginx.") + flag.StringVar(&meshProvider, "mesh-provider", "istio", "Service mesh provider, can be istio, linkerd, appmesh, contour, gloo, nginx or skipper.") flag.StringVar(&selectorLabels, "selector-labels", "app,name,app.kubernetes.io/name", "List of pod labels that Flagger uses to create pod selectors.") flag.StringVar(&ingressAnnotationsPrefix, "ingress-annotations-prefix", "nginx.ingress.kubernetes.io", "Annotations prefix for NGINX ingresses.") flag.StringVar(&ingressClass, "ingress-class", "", "Ingress class used for annotating HTTPProxy objects.") diff --git a/docs/diagrams/flagger-skipper-overview.png b/docs/diagrams/flagger-skipper-overview.png new file mode 100644 index 000000000..e2f18aec4 Binary files /dev/null and b/docs/diagrams/flagger-skipper-overview.png differ diff --git a/docs/gitbook/README.md b/docs/gitbook/README.md index e0361dd04..fae6f42f1 100644 --- a/docs/gitbook/README.md +++ b/docs/gitbook/README.md @@ -5,7 +5,7 @@ description: Flagger is a progressive delivery Kubernetes operator # Introduction [Flagger](https://github.com/weaveworks/flagger) is a **Kubernetes** operator that automates the promotion of -canary deployments using **Istio**, **Linkerd**, **App Mesh**, **NGINX**, **Contour** or **Gloo** routing for +canary deployments using **Istio**, **Linkerd**, **App Mesh**, **NGINX**, **Skipper**, **Contour** or **Gloo** routing for traffic shifting and **Prometheus** metrics for canary analysis. The canary analysis can be extended with webhooks for running system integration/acceptance tests, load tests, or any other custom validation. @@ -39,6 +39,7 @@ After install Flagger, you can follow one of the tutorials: * [Contour](tutorials/contour-progressive-delivery.md) * [Gloo](tutorials/gloo-progressive-delivery.md) * [NGINX Ingress](tutorials/nginx-progressive-delivery.md) +* [Skipper Ingress](tutorials/skipper-progressive-delivery.md) **Hands-on GitOps workshops** diff --git a/docs/gitbook/SUMMARY.md b/docs/gitbook/SUMMARY.md index 9f565064f..d39be4b2f 100644 --- a/docs/gitbook/SUMMARY.md +++ b/docs/gitbook/SUMMARY.md @@ -25,6 +25,7 @@ * [Linkerd Canary Deployments](tutorials/linkerd-progressive-delivery.md) * [App Mesh Canary Deployments](tutorials/appmesh-progressive-delivery.md) * [NGINX Canary Deployments](tutorials/nginx-progressive-delivery.md) +* [Skipper Canary Deployments](tutorials/skipper-progressive-delivery.md) * [Gloo Canary Deployments](tutorials/gloo-progressive-delivery.md) * [Contour Canary Deployments](tutorials/contour-progressive-delivery.md) * [Blue/Green Deployments](tutorials/kubernetes-blue-green.md) diff --git a/docs/gitbook/install/flagger-install-on-kubernetes.md b/docs/gitbook/install/flagger-install-on-kubernetes.md index 3f45eba6f..07b040d11 100644 --- a/docs/gitbook/install/flagger-install-on-kubernetes.md +++ b/docs/gitbook/install/flagger-install-on-kubernetes.md @@ -77,6 +77,7 @@ For ingress controllers, the install instructions are: * [Contour](https://docs.flagger.app/tutorials/contour-progressive-delivery) * [Gloo](https://docs.flagger.app/tutorials/gloo-progressive-delivery) * [NGINX](https://docs.flagger.app/tutorials/nginx-progressive-delivery) +* [Skipper](https://docs.flagger.app/tutorials/skipper-progressive-delivery) Enable **Slack** notifications: @@ -198,7 +199,7 @@ kustomize build https://github.com/weaveworks/flagger/kustomize/linkerd?ref=v1.0 **Generic installer** -Install Flagger and Prometheus for Contour, Gloo or NGINX ingress: +Install Flagger and Prometheus for Contour, Gloo, NGINX or Skipper ingress: ```bash kustomize build https://github.com/weaveworks/flagger/kustomize/kubernetes | kubectl apply -f - @@ -219,7 +220,7 @@ metadata: name: app namespace: test spec: - # can be: kubernetes, istio, linkerd, appmesh, nginx, gloo + # can be: kubernetes, istio, linkerd, appmesh, nginx, skipper, gloo # use the kubernetes provider for Blue/Green style deployments provider: nginx ``` diff --git a/docs/gitbook/tutorials/skipper-progressive-delivery.md b/docs/gitbook/tutorials/skipper-progressive-delivery.md new file mode 100644 index 000000000..813f77df7 --- /dev/null +++ b/docs/gitbook/tutorials/skipper-progressive-delivery.md @@ -0,0 +1,382 @@ +# Skipper Canary Deployments + +This guide shows you how to use the [Skipper ingress controller](https://opensource.zalando.com/skipper/kubernetes/ingress-controller/) and Flagger to automate canary deployments. + +![Flagger Skipper Ingress Controller](https://raw.githubusercontent.com/weaveworks/flagger/master/docs/diagrams/flagger-skipper-overview.png) + +## Prerequisites + +Flagger requires a Kubernetes cluster **v1.14** or newer and Skipper ingress **0.11.40** or newer. + +Install Skipper ingress-controller using [upstream definition](https://opensource.zalando.com/skipper/kubernetes/ingress-controller/#install-skipper-as-ingress-controller). + +## Bootstrap + +Flagger takes a Kubernetes deployment and optionally a horizontal pod autoscaler (HPA), +then creates a series of objects (Kubernetes deployments, ClusterIP services and canary ingress). +These objects expose the application outside the cluster and drive the canary analysis and promotion. + +Create a test namespace: + +```bash +kubectl create ns test +``` + +Create a deployment and a horizontal pod autoscaler: + +```bash +kubectl apply -k github.com/weaveworks/flagger//kustomize/podinfo +``` + +Deploy the load testing service to generate traffic during the canary analysis: + +```bash +helm upgrade -i flagger-loadtester flagger/loadtester \ +--namespace=test +``` + +Create an ingress definition \(replace `app.example.com` with your own domain\): + +```yaml +apiVersion: networking.k8s.io/v1beta1 +kind: Ingress +metadata: + name: podinfo + namespace: test + labels: + app: podinfo + annotations: + kubernetes.io/ingress.class: "skipper" +spec: + rules: + - host: app.example.com + http: + paths: + - backend: + serviceName: podinfo + servicePort: 80 +``` + +Save the above resource as podinfo-ingress.yaml and then apply it: + +```bash +kubectl apply -f ./podinfo-ingress.yaml +``` + +Create a canary custom resource \(replace `app.example.com` with your own domain\): + +```yaml +apiVersion: flagger.app/v1beta1 +kind: Canary +metadata: + name: podinfo + namespace: test +spec: + provider: skipper + # deployment reference + targetRef: + apiVersion: apps/v1 + kind: Deployment + name: podinfo + # ingress reference + ingressRef: + apiVersion: networking.k8s.io/v1beta1 + kind: Ingress + name: podinfo + # HPA reference (optional) + autoscalerRef: + apiVersion: autoscaling/v2beta1 + kind: HorizontalPodAutoscaler + name: podinfo + # the maximum time in seconds for the canary deployment + # to make progress before it is rollback (default 600s) + progressDeadlineSeconds: 60 + service: + # ClusterIP port number + port: 80 + # container port number or name + targetPort: 9898 + analysis: + # schedule interval (default 60s) + interval: 10s + # max number of failed metric checks before rollback + threshold: 10 + # max traffic percentage routed to canary + # percentage (0-100) + maxWeight: 50 + # canary increment step + # percentage (0-100) + stepWeight: 5 + # Skipper Prometheus checks + metrics: + - name: request-success-rate + interval: 1m + # minimum req success rate (non 5xx responses) + # percentage (0-100) + thresholdRange: + min: 99 + - name: request-duration + interval: 1m + # maximum req duration P99 + # milliseconds + thresholdRange: + max: 500 + webhooks: + - name: gate + type: confirm-rollout + url: http://flagger-loadtester.test/gate/approve + - name: acceptance-test + type: pre-rollout + url: http://flagger-loadtester.test/ + timeout: 10s + metadata: + type: bash + cmd: "curl -sd 'test' http://podinfo-canary/token | grep token" + - name: load-test + type: rollout + url: http://flagger-loadtester.test/ + timeout: 5s + metadata: + type: cmd + cmd: "hey -z 10m -q 10 -c 2 -host app.example.com http://skipper-ingress.kube-system" + logCmdOutput: "true" +``` + +Save the above resource as podinfo-canary.yaml and then apply it: + +```bash +kubectl apply -f ./podinfo-canary.yaml +``` + +After a couple of seconds Flagger will create the canary objects: + +```bash +# applied +deployment.apps/podinfo +horizontalpodautoscaler.autoscaling/podinfo +ingress.networking.k8s.io/podinfo-ingress +canary.flagger.app/podinfo + +# generated +deployment.apps/podinfo-primary +horizontalpodautoscaler.autoscaling/podinfo-primary +service/podinfo +service/podinfo-canary +service/podinfo-primary +ingress.networking.k8s.io/podinfo-canary +``` + +## Automated canary promotion + +Flagger implements a control loop that gradually shifts traffic to the canary while measuring +key performance indicators like HTTP requests success rate, requests average duration and pod health. +Based on analysis of the KPIs a canary is promoted or aborted, and the analysis result is published to Slack or MS Teams. + +![Flagger Canary Stages](https://raw.githubusercontent.com/weaveworks/flagger/master/docs/diagrams/flagger-canary-steps.png) + +Trigger a canary deployment by updating the container image: + +```bash +kubectl -n test set image deployment/podinfo \ +podinfod=stefanprodan/podinfo:4.0.6 +``` + +Flagger detects that the deployment revision changed and starts a new rollout: + +```text +kubectl -n test describe canary/podinfo + +Status: + Canary Weight: 0 + Failed Checks: 0 + Phase: Succeeded +Events: + New revision detected! Scaling up podinfo.test + Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available + Pre-rollout check acceptance-test passed + Advance podinfo.test canary weight 5 + Advance podinfo.test canary weight 10 + Advance podinfo.test canary weight 15 + Advance podinfo.test canary weight 20 + Advance podinfo.test canary weight 25 + Advance podinfo.test canary weight 30 + Advance podinfo.test canary weight 35 + Advance podinfo.test canary weight 40 + Advance podinfo.test canary weight 45 + Advance podinfo.test canary weight 50 + Copying podinfo.test template spec to podinfo-primary.test + Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available + Routing all traffic to primary + Promotion completed! Scaling down podinfo.test +``` + +**Note** that if you apply new changes to the deployment during the canary analysis, Flagger will restart the analysis. + +You can monitor all canaries with: + +```bash +watch kubectl get canaries --all-namespaces + +NAMESPACE NAME STATUS WEIGHT LASTTRANSITIONTIME +test podinfo-2 Progressing 30 2020-08-14T12:32:12Z +test podinfo Succeeded 0 2020-08-14T11:23:88Z +``` + +## Automated rollback + +During the canary analysis you can generate HTTP 500 errors to test if Flagger pauses and rolls back the faulted version. + +Trigger another canary deployment: + +```bash +kubectl -n test set image deployment/podinfo \ +podinfod=stefanprodan/podinfo:4.0.6 +``` + +Exec into the load tester pod with: + +```bash +kubectl -n test exec -it deploy/flagger-loadtester bash +``` + +Generate HTTP 500 errors: + +```bash +hey -z 1m -c 5 -q 5 http://app.example.com/status/500 +``` + +Generate latency: + +```bash +watch -n 1 curl http://app.example.com/delay/1 +``` + +When the number of failed checks reaches the canary analysis threshold, the traffic is routed back to the primary, +the canary is scaled to zero and the rollout is marked as failed. + +```text +kubectl -n flagger-system logs deploy/flagger -f | jq .msg + +"New revision detected! Scaling up podinfo.test" +"GetRoutes primaryWeight: 100, canaryWeight: 0" +"canary deployment podinfo.test not ready: waiting for rollout to finish: 0 of 1 updated replicas are available" +"GetRoutes primaryWeight: 100, canaryWeight: 0" +"Starting canary analysis for podinfo.test" +"Pre-rollout check acceptance-test passed" +"primaryWeight: 95, canaryWeight: 5" +"Advance podinfo.test canary weight 5" +"GetRoutes primaryWeight: 95, canaryWeight: 5" +"primaryWeight: 90, canaryWeight: 10" +"Advance podinfo.test canary weight 10" +"GetRoutes primaryWeight: 90, canaryWeight: 10" +"primaryWeight: 85, canaryWeight: 15" +"Advance podinfo.test canary weight 15" +"GetRoutes primaryWeight: 85, canaryWeight: 15" +"primaryWeight: 80, canaryWeight: 20" +"Advance podinfo.test canary weight 20" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 53.42% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 53.19% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 48.05% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 47.62% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 51.90% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 48.84% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 49.32% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 58.33% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 42.53% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Halt podinfo.test advancement success rate 51.72% < 99%" +"GetRoutes primaryWeight: 80, canaryWeight: 20" +"Rolling back podinfo.test failed checks threshold reached 10" +"primaryWeight: 100, canaryWeight: 0" +"Canary failed! Scaling down podinfo.test" +``` + +## Custom metrics + +The canary analysis can be extended with Prometheus queries. + +The demo app is instrumented with Prometheus so you can create a custom check that will use the +HTTP request duration histogram to validate the canary. + +Create a metric template and apply it on the cluster: + +```yaml +apiVersion: flagger.app/v1beta1 +kind: MetricTemplate +metadata: + name: latency + namespace: test +spec: + provider: + type: prometheus + address: http://flagger-prometheus.skipper:9090 + query: | + histogram_quantile(0.99, + sum( + rate( + skipper_serve_route_duration_seconds_bucket{ + route=~"{{ $route }}",, + le="+Inf" + }[1m] + ) + ) by (le) + ) +``` + +Edit the canary analysis and add the latency check: + +```yaml + analysis: + metrics: + - name: "latency" + templateRef: + name: latency + thresholdRange: + max: 0.5 + interval: 1m +``` + +The threshold is set to 500ms so if the average request duration in the last minute goes over half a second +then the analysis will fail and the canary will not be promoted. + +Trigger a canary deployment by updating the container image: + +```bash +kubectl -n test set image deployment/podinfo \ +podinfod=stefanprodan/podinfo:4.0.6 +``` + +Generate high response latency: + +```bash +watch curl http://app.exmaple.com/delay/2 +``` + +Watch Flagger logs: + +```text +kubectl -n flagger-system logs deployment/flagger -f | jq .msg + +Starting canary deployment for podinfo.test +Advance podinfo.test canary weight 5 +Advance podinfo.test canary weight 10 +Advance podinfo.test canary weight 15 +Halt podinfo.test advancement latency 1.20 > 0.5 +Halt podinfo.test advancement latency 1.45 > 0.5 +Halt podinfo.test advancement latency 1.60 > 0.5 +Halt podinfo.test advancement latency 1.69 > 0.5 +Halt podinfo.test advancement latency 1.70 > 0.5 +Rolling back podinfo.test failed checks threshold reached 5 +Canary failed! Scaling down podinfo.test +``` + +If you have alerting configured, Flagger will send a notification with the reason why the canary failed. diff --git a/docs/gitbook/usage/deployment-strategies.md b/docs/gitbook/usage/deployment-strategies.md index 4033d3cdb..80af73486 100644 --- a/docs/gitbook/usage/deployment-strategies.md +++ b/docs/gitbook/usage/deployment-strategies.md @@ -2,7 +2,7 @@ Flagger can run automated application analysis, promotion and rollback for the following deployment strategies: * **Canary Release** (progressive traffic shifting) - * Istio, Linkerd, App Mesh, NGINX, Contour, Gloo + * Istio, Linkerd, App Mesh, NGINX, Skipper, Contour, Gloo * **A/B Testing** (HTTP headers and cookies traffic routing) * Istio, App Mesh, NGINX, Contour * **Blue/Green** (traffic switching) diff --git a/kustomize/README.md b/kustomize/README.md index a1298dffe..b50b9007b 100644 --- a/kustomize/README.md +++ b/kustomize/README.md @@ -67,12 +67,12 @@ metadata: name: app namespace: test spec: - # can be: kubernetes, istio, linkerd, appmesh, nginx, gloo + # can be: kubernetes, istio, linkerd, appmesh, nginx, skipper, gloo # use the kubernetes provider for Blue/Green style deployments provider: nginx ``` -You'll need Prometheus when using Flagger with AWS App Mesh, Gloo or NGINX ingress controller. +You'll need Prometheus when using Flagger with AWS App Mesh, Gloo, NGINX or Skipper ingress controller. The Prometheus instance has a two hours data retention and is configured to scrape all pods in your cluster that have the `prometheus.io/scrape: "true"` annotation.