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Well, the problem is that master is a bottleneck. Trying to build CI on every branch before merging to master just won't work with the scale they are dealing wi

Well, the problem is that master is a bottleneck. Trying to build CI on every branch before merging to master just won't work with the scale they are dealing with. At 1000 developers, the rate of PRs coming in makes it impossible to determine what current master will be when the PR is ready to merge (i.e. when the branch has a green build). It's also wasteful to build each branch against current master because what is "current" will not be when the branch is ready to merge. Perhaps this problem is what microservices are meant to solve. When you can't coherently integrate code fast enough, attack the bottleneck (master) by splitting it (multiple services).

scrollaway 7y ago
> Perhaps this problem is what microservices are meant to solve. Kinda. Microservices have always been an organizational solution; they're a way to shard your company's work output. Usually that's API contracts, but whatever mechanisms are bottlenecked on the work output is affected, including how many concurrent builds are running due to how many people are touching the code at the same time.
tudelo 7y ago
Yet it seems like large companies mostly prefer monorepos, so while it takes investment to have such a monorepo, it seems the benefits are worth the investment.
- peterwwillis 7y ago
  This is appeal to accomplishment fallacy. Because large companies have a lot of money, whatever they do must be great. But this is false - they do what they do because they are large companies, not because it is a good idea. At scale, managing complexity can require either a lot of coordination, or a lot of careful planning. Large companies (especially tech companies) don't do either well, so they pick architectures that remove choices, and iterate on them until they are workable. And they have the money and workforce to do it.
- anon73044 7y ago
  Google, Microsoft, Facebook and Twitter prefer monorepos but this is not indicative of most large orgs. You'll notice that those listed have had to customize or creat new vcs's to meet their needs. https://news.ycombinator.com/item?id=17605371 https://news.ycombinator.com/item?id=17605371 https://news.ycombinator.com/item?id=11789182 https://news.ycombinator.com/item?id=11789182 https://medium.com/@maoberlehner/monorepos-in-the-wild-33c6eb246cb9 https://medium.com/@maoberlehner/monorepos-in-the-wild-33c6e...
carlisle_ 7y ago
This paper might be of interest to you on this very subject: https://eng.uber.com/research/keeping-master-green-at-scale/ https://eng.uber.com/research/keeping-master-green-at-scale/
adrianN 7y ago
Microservices don't really help with this. They just force you to think about your interfaces, but you should do that in a monolith too. If you interfaces are reasonably stable, merging is unlikely to break master if the branch was green before, if your interfaces change rapidly you get problems with microservices too, just one level higher up, where you try to integrate them into a usable product.
- gav 7y ago
  One of the things I think microservices does help with is thinking about systems being composed of components that are being developed at different velocities and different tolerances of risk. Imagine an e-commerce site broken into a bunch of services including search and checkout. The search team is making updates daily, trying to improve ranking and drive conversion. The checkout team (assuming that the site is mature and has hit some design equilibrium) may only be releasing changes every couple of months, and if a bug is introduced, the financial impact is a lot higher. By not bundling the outputs of very different teams together, you can help those that want to "move fast and break things" with their "moving fast" goal, and de-risk breaking everything by reducing the surface area of changes. Microservices-based architectures are a way to reduce friction caused by the structure of your organization and is one outcome of an Inverse Conway Maneuver.
- isaacaggrey 7y ago
  They do help if a single team of 5-7 developers own a set of microservices; it's unlikely you will have tons of PRs to merge all at once in a single repository with a smaller team. Granted, the ownership is is a bit more clear when talking about a self-contained system that a team owns: https://scs-architecture.org/vs-ms.html https://scs-architecture.org/vs-ms.html In the SCS literature, you would integrate via async mechanisms across SCSes, provide versioned interfaces, and enforce via consumer-driven contract testing like Pact: https://pact.io https://pact.io
jrockway 7y ago
We didn't have a merge queue at Google. You rebased if there was a merge conflict, ran through CI again, and hoped there wasn't another merge conflict. I think I ran into merge conflicts maybe once a year, if that. I think the success of this system breaks down into several parts: 1) Yup, microservices. You could submit your proto change, which would affect all clients, before actually implementing the code that used the new feature. (Or after, in the case of renaming some field from foo to deprecated_foo and refactoring the clients to stop using that field.) That means you could wrangle that change without having to worry about it affecting your actual feature. (Typically proto changes did not cause any breakages since people were very conservative about what changes they would make. Nobody renames all the fields, invalidating dependent code, or renumbers the fields, invalidating all existing messages. You COULD do those things, but nobody ever did.) 2) Clear dependencies in the build system. The CI system only had to run a small set of tests for most changes, because it knew exactly what tests the change would affect. You had to go way out of your way to depend on code without informing the build system. This is very different from every CI system that I've seen outside of Google, which seem to default to running everything and hoping your programming language or build system magically tracks dependencies. It doesn't; Docker for example will happily use random images that it thinks haven't changed, without actually checking if it has changed. (Consider building your app on top of golang:latest. Go is updated, and docker may or may not pull that new base image. Meanwhile, docker will happily clear its build cache if you edit README.md and no code. The result is that 50% of the time you waste 10 minutes rebuilding stuff that didn't change, and 50% of the time you get an outdated build. And nobody seems to care at all!) 3) Being careful about keeping changes small. I don't know what the average CL size is, but I would aim for 100 lines changed rather than 1000 lines changed. This is something that surprised me post-Google, people go away and work for a week and you have a 2000 line PR to review. These are tough to merge and were relatively rare in my experience at Google. It is not always possible to make every change small, but that should be the norm. Figure out how much work you can do in a day, and try to make a CL/PR that is that size. A lot can churn in a week. A lot less churns in a day. If you respected steps 1 and 2, that means your tests will run fast and it's unlikely that your merge will fail between CI and actually merging. If you have 2000 lines of code across 8 services... you'll probably never get it merged. But I am sure that I have successfully merged ginormous changes before, it's just more work. All in all, my takeaway from this article is that Shopify is huge but I'm surprised that specialized merge tooling was necessary. I wonder what the underlying problem is; do they really have a 1000 developer monolith? Do they not use a proper build system like Bazel?
username90 7y ago
> Trying to build CI on every branch before merging to master just won't work with the scale they are dealing with. Google does it with 50 times the developer count. > At 1000 developers, the rate of PRs coming in makes it impossible to determine what current master will be when the PR is ready to merge (i.e. when the branch has a green build). True, it is impossible to catch all errors like this, but you can catch almost every error by building and testing it against current master and then merge it with the master 20 minutes later when the build is done. I have seen maybe one build breakage a year being introduced due to this in projects I've worked on, so it isn't a big deal.
- greiskul 7y ago
  > building and testing it against current master and then merge it with the master 20 minutes later when the build is done. And I'm pretty sure that is the way Google does it too. Test a commit against current master, if tests are green commit. Then run tests against master again (and I think this stage might not run for every single commit) to see if anything broke on the rare times there was an actual conflict. If that run was red, which should be rare, then you can have the system do a bisect to find the offending commit, or just run all the ones that haven't been individually tested.
- iamweswilson 7y ago
  For even better accuracy you can use a tool that will run tests against speculative merge states. Zuul[1] is an open source project that supports it out of the box. [1] https://zuul-ci.org/docs/zuul/user/gating.html https://zuul-ci.org/docs/zuul/user/gating.html
- randomidiot666 7y ago
  You have no idea how Google solved it. Basically everyone with a Monorepo (except Google) implements it as a cargo cult best practice. Mindlessly copying Google without understanding how Google actually does it.
  - deleted 7y ago
    [deleted]
marcosdumay 7y ago
This is the problem external libraries were created to solve, in a time when it was a much harder problem. Microservices are the same kind of solution, with the same gains and costs for this specific problem.
bob1029 7y ago
By virtue of having a queue of PRs that need to test & merge, you could pipeline this thing out pretty substantially. The implication here being that a queue must be processed in-order, so you will ultimately have a perfect sequence of future commits to speculate against, and can incrementally build up each hypothetical future master state for a test build on one of any number of parallel build agents. As the queue depth grows, you would see higher and higher throughput.

scrollaway 7y ago

> Perhaps this problem is what microservices are meant to solve. Kinda. Microservices have always been an organizational solution; they're a way to shard your company's work output. Usually that's API contracts, but whatever mechanisms are bottlenecked on the work output is affected, including how many concurrent builds are running due to how many people are touching the code at the same time.

tudelo 7y ago

Yet it seems like large companies mostly prefer monorepos, so while it takes investment to have such a monorepo, it seems the benefits are worth the investment.

peterwwillis 7y ago
This is appeal to accomplishment fallacy. Because large companies have a lot of money, whatever they do must be great. But this is false - they do what they do because they are large companies, not because it is a good idea. At scale, managing complexity can require either a lot of coordination, or a lot of careful planning. Large companies (especially tech companies) don't do either well, so they pick architectures that remove choices, and iterate on them until they are workable. And they have the money and workforce to do it.
anon73044 7y ago
Google, Microsoft, Facebook and Twitter prefer monorepos but this is not indicative of most large orgs. You'll notice that those listed have had to customize or creat new vcs's to meet their needs. https://news.ycombinator.com/item?id=17605371 https://news.ycombinator.com/item?id=17605371 https://news.ycombinator.com/item?id=11789182 https://news.ycombinator.com/item?id=11789182 https://medium.com/@maoberlehner/monorepos-in-the-wild-33c6eb246cb9 https://medium.com/@maoberlehner/monorepos-in-the-wild-33c6e...

carlisle_ 7y ago

This paper might be of interest to you on this very subject: https://eng.uber.com/research/keeping-master-green-at-scale/ https://eng.uber.com/research/keeping-master-green-at-scale/

adrianN 7y ago

Microservices don't really help with this. They just force you to think about your interfaces, but you should do that in a monolith too. If you interfaces are reasonably stable, merging is unlikely to break master if the branch was green before, if your interfaces change rapidly you get problems with microservices too, just one level higher up, where you try to integrate them into a usable product.

gav 7y ago
One of the things I think microservices does help with is thinking about systems being composed of components that are being developed at different velocities and different tolerances of risk. Imagine an e-commerce site broken into a bunch of services including search and checkout. The search team is making updates daily, trying to improve ranking and drive conversion. The checkout team (assuming that the site is mature and has hit some design equilibrium) may only be releasing changes every couple of months, and if a bug is introduced, the financial impact is a lot higher. By not bundling the outputs of very different teams together, you can help those that want to "move fast and break things" with their "moving fast" goal, and de-risk breaking everything by reducing the surface area of changes. Microservices-based architectures are a way to reduce friction caused by the structure of your organization and is one outcome of an Inverse Conway Maneuver.
isaacaggrey 7y ago
They do help if a single team of 5-7 developers own a set of microservices; it's unlikely you will have tons of PRs to merge all at once in a single repository with a smaller team. Granted, the ownership is is a bit more clear when talking about a self-contained system that a team owns: https://scs-architecture.org/vs-ms.html https://scs-architecture.org/vs-ms.html In the SCS literature, you would integrate via async mechanisms across SCSes, provide versioned interfaces, and enforce via consumer-driven contract testing like Pact: https://pact.io https://pact.io

jrockway 7y ago

We didn't have a merge queue at Google. You rebased if there was a merge conflict, ran through CI again, and hoped there wasn't another merge conflict. I think I ran into merge conflicts maybe once a year, if that. I think the success of this system breaks down into several parts: 1) Yup, microservices. You could submit your proto change, which would affect all clients, before actually implementing the code that used the new feature. (Or after, in the case of renaming some field from foo to deprecated_foo and refactoring the clients to stop using that field.) That means you could wrangle that change without having to worry about it affecting your actual feature. (Typically proto changes did not cause any breakages since people were very conservative about what changes they would make. Nobody renames all the fields, invalidating dependent code, or renumbers the fields, invalidating all existing messages. You COULD do those things, but nobody ever did.) 2) Clear dependencies in the build system. The CI system only had to run a small set of tests for most changes, because it knew exactly what tests the change would affect. You had to go way out of your way to depend on code without informing the build system. This is very different from every CI system that I've seen outside of Google, which seem to default to running everything and hoping your programming language or build system magically tracks dependencies. It doesn't; Docker for example will happily use random images that it thinks haven't changed, without actually checking if it has changed. (Consider building your app on top of golang:latest. Go is updated, and docker may or may not pull that new base image. Meanwhile, docker will happily clear its build cache if you edit README.md and no code. The result is that 50% of the time you waste 10 minutes rebuilding stuff that didn't change, and 50% of the time you get an outdated build. And nobody seems to care at all!) 3) Being careful about keeping changes small. I don't know what the average CL size is, but I would aim for 100 lines changed rather than 1000 lines changed. This is something that surprised me post-Google, people go away and work for a week and you have a 2000 line PR to review. These are tough to merge and were relatively rare in my experience at Google. It is not always possible to make every change small, but that should be the norm. Figure out how much work you can do in a day, and try to make a CL/PR that is that size. A lot can churn in a week. A lot less churns in a day. If you respected steps 1 and 2, that means your tests will run fast and it's unlikely that your merge will fail between CI and actually merging. If you have 2000 lines of code across 8 services... you'll probably never get it merged. But I am sure that I have successfully merged ginormous changes before, it's just more work. All in all, my takeaway from this article is that Shopify is huge but I'm surprised that specialized merge tooling was necessary. I wonder what the underlying problem is; do they really have a 1000 developer monolith? Do they not use a proper build system like Bazel?

username90 7y ago

> Trying to build CI on every branch before merging to master just won't work with the scale they are dealing with. Google does it with 50 times the developer count. > At 1000 developers, the rate of PRs coming in makes it impossible to determine what current master will be when the PR is ready to merge (i.e. when the branch has a green build). True, it is impossible to catch all errors like this, but you can catch almost every error by building and testing it against current master and then merge it with the master 20 minutes later when the build is done. I have seen maybe one build breakage a year being introduced due to this in projects I've worked on, so it isn't a big deal.

greiskul 7y ago
> building and testing it against current master and then merge it with the master 20 minutes later when the build is done. And I'm pretty sure that is the way Google does it too. Test a commit against current master, if tests are green commit. Then run tests against master again (and I think this stage might not run for every single commit) to see if anything broke on the rare times there was an actual conflict. If that run was red, which should be rare, then you can have the system do a bisect to find the offending commit, or just run all the ones that haven't been individually tested.
iamweswilson 7y ago
For even better accuracy you can use a tool that will run tests against speculative merge states. Zuul[1] is an open source project that supports it out of the box. [1] https://zuul-ci.org/docs/zuul/user/gating.html https://zuul-ci.org/docs/zuul/user/gating.html
randomidiot666 7y ago
You have no idea how Google solved it. Basically everyone with a Monorepo (except Google) implements it as a cargo cult best practice. Mindlessly copying Google without understanding how Google actually does it.
- deleted 7y ago
  [deleted]

marcosdumay 7y ago

This is the problem external libraries were created to solve, in a time when it was a much harder problem. Microservices are the same kind of solution, with the same gains and costs for this specific problem.

bob1029 7y ago

By virtue of having a queue of PRs that need to test & merge, you could pipeline this thing out pretty substantially. The implication here being that a queue must be processed in-order, so you will ultimately have a perfect sequence of future commits to speculate against, and can incrementally build up each hypothetical future master state for a test build on one of any number of parallel build agents. As the queue depth grows, you would see higher and higher throughput.