Lambda lazy load #2278
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Lambda lazy load #2278
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This specific port per integration is pretty brittle to begin with, but it does work. Currently, the fact that it works is facilitated by the fact that most people don't use 5555 (Hapi) and 6666 (Express) for anything. That said, the ever-popular Gatsby uses 8888 by default, so let's use 9999!
Without this fix to `package-lock.json`, which it's not immediately clear to me what was wrong (possibly a transitive error) there were type errors manifesting on the `master` branch.
I've added these on Mac, and I believe that Mac will no longer _remove_ them after [email protected], so hopefully fix some `package-lock.json` flapping!
When debugging the fix in b84770c, I removed the `package-lock.json`, ran `npm install`, then individually reviewed the fixes to better understand what happened. I noted a few other differences in the `package-lock.json`, mostly due to changes in `fsevents` (which internally switched to `bundledDependencies`), and changes in `@apollographql/apollo-tools`. I've reviewed these as well, and they all look reasonable, but wanted to put them in a different commit for later bisecting purposes (hopefully a purpose I won't have!).
There was a breaking change to `core-js` in `3.0.0-beta.12` which seems to warrant this extra protection.
The purpose of this PR is to remove the `apollo-graphql` package from this repository, to be added to `apollo-tooling` instead. https://github.com/apollographql/apollo-tooling Ref: apollographql/apollo-tooling#1018
This will allow Lerna to release the first version as `[email protected]`.
- [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected]
Re-land: Fastify integration from #1971.
- [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected] - [email protected]
hacky lambda process.env fix" fix linting issues update changelog fix polyfill check use AWS_EXECUTION_ENV fix styling fix version check Update CHANGELOG.md
…nto lambda_lazy_load
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I screwed up a rebease and cant seem to unscrew it, so I am closing this and opening #2324 |
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TODO:
This is to address loading time issues raised in #2162
There are three changes of note.
lambda-server-coreI moved thesubscriptions-transport-wsandapollo-engine-reportinginto lazy-loadedrequiresand changed the top-level imports to just import the type. Since lambda's cannot take advantage of these packages, loading them is pure cost. I didn't see any other type-only imports to style after, so I followed the handbook convention of underscore-prefix-capitalized.util.promisifypolyfill check the node version before loading itself. NOTE: there are already tests in node 6 and node 8 that exercise this coderuntimeSupportsUploads()that looks forAWS_EXECUTION_ENV, which the lambda runtime sets. This checks stop the import ofapollo-uploadfrom occuring. The library is unfortunately a top-level import, so moving it anywhere thatapollo-server-lambdacould have controlled directly without changing the contract was impossible. A better solution probably exists that does not hack its way throughprocess.env. The best solution would be removingapollo-uploadfrom the core entirely, since it surely does not belong there.These changes combine to reduce the cold-start time of a 512mb AWS Lambda from ~450ms to ~250ms.
Before
After
(Yes, the flame graph has a rendering bug, but the numbers are accurate)
512 is a pretty beefy lambda for node, 256 is more common. These effect will be amplified the lower memory you go, because AWS matches the CPU to the allocated memory. If it is necessary, I can re-run these performance profiling on smaller lambdas.