"-No, look into microservices. It’s the future. It’s how we do everything now. You take your monolithic app and you split it into like 12 services. One for each job you do.
That seems excessive"
A 100 times yes. We tried to split our monolithic Rails app into micro-services built in Go. 2 years and many fires later, we decided to abandon the project. It was mostly because the monitoring and alerting were now split into many different pieces. Also, the team spent too much time debating standards etc. I think micro-services can be valuable, but we definitely didn't do it right, and I think a lot of companies get it wrong. Any positive experiences with micro-services here?
I think that splitting into micro services is valuable if and only if you reach a scale where it makes sense to split into micro services. By scale, I mean the number of people on the team (if you have a lot of people, it can make sense to split into micro-services to limit communication bottlenecks between developers) or in term of traffic, in which case microservices can be very useful to better optimize the system piece by piece.
A small team starting a new project should not waste a single second considering microservices unless there's something that is so completely obviously decoupled in a way that not splitting it into a microservice will lead to extra work. It's also way easier to split into microservices after the fact than when you're developing a new app and you don't have a clue how it will look like or what the overall structure of the app will be in a year (most common case for startups).
In practice micro services mean that you turn a function or method call into a network request. This doesn't really limit communication bottlenecks. It is often more difficult to argee on a network interface than on a simple function or object interface. It's also more difficult to change. You introduce a whole new set of failure modes due to going over the network. Debugging is more difficult since you now can no longer step through your program in a debugger but rather have an opaque network request that you can't step into. You can no longer use editor/IDE features like go to definition. It becomes harder to do integration tests. Version control becomes harder if the different services are in different repositories. A network request is much slower than a function call. You no longer have the advantage of a garbage collector for logical values that now cross network boundaries, and rather need to manually free them. Deployment is more difficult. The list is much longer than this, but I'd be interested in the counter-list: what are the advantages of micro-services?
> You introduce a whole new set of failure modes due to going over the network.
A thousand times yes. Distributed systems are hard.
> Debugging is more difficult since you now can no longer step through your program in a debugger but rather have an opaque network request that you can't step into.
Yes. Folks underestimate how difficult this can be.
In theory it should be possible to have tooling to fix this, but I've not seen it in practice.
> You can no longer use editor/IDE features like go to definition.
Not a problem with a good editor.
> Version control becomes harder if the different services are in different repositories.
No organisation should have more than one regular-use repo (special-use repos, of course, are special). Multiple repos are a smell.
> No organisation should have more than one regular-use repo (special-use repos, of course, are special). Multiple repos are a smell.
I would modify this slightly. Larger organizations with independent teams may want to run on per-team repos. Conway's law is an observation about code structure but it sometimes also makes good practice for code organization. And of course, sometimes the smell is "this company is organized pathologically".
Another problem is that large monolithic repositories can be difficult to manage with currently available software. Git is no panacea and Perforce isn't either.
I guess Facebook, Twitter, and Google are doing things "flat out wrong", then. Yes, that's a weak argument (argument from authority) but it is true that monolithic repositories have major advantages even for organizations with multiple products. Common libraries and infrastructure are much easier to work with in monolithic repositories.
My personal take on it, at this point, is that much of our knowledge of how to manage projects (things like individual project repos, semantic versioning, et cetera) is centered on the open-source world of a million mostly-independent programmers. Things change when you work in larger organizations with multiple projects. You even start to revisit basic ideas like semantic versioning in favor of other techniques like using CI across your entire codebase.
Those are huge organizations with commensurately large developer resources, and they simply work at a different scale than most people on HN. "It works for Google" is not an argument for anything.
Monorepos come with their own challenges. For example, if any of your code is open source (which means it must be hosted separately, e.g. on Github), you have to sync the open-source version with your private monorepo version.
Monorepo are large. Having to pull and rebase against unrelated changes on every sync puts an onerous burden on devs. When you're remote and on the road, bandwidth can block your ability to even pull.
And if you're going to do it like Google, you'll vendor everything -- absolutely everything (Go packages, Java libraries, NPM modules, C++ libraries) -- which requires a whole tool chain to be built to handle syncing with upstream, as well as a rigid workflow to prevent your private, vendored fork from drifting away from upstream.
There are benefits to both approaches. There is no "one right way".
It seems we agree, we are both claiming that "there is no one right way".
I love Git, and I used submodules for years in personal projects. It started with a few support libraries shared between projects, or common scripts for deployment, but it quickly ballooned into a mess. I'm in the process of moving related personal projects to a monolithic repository, and in the process I'm giving up the ability to tag versions of individual projects or provide simple GitHub links to share my code.
Based on these experiences, I honestly think that the only major problem with monolithic repositories is that the software isn't good at handling it, and this problem could be solved with better software. If the problem is solved at some point in the future, I don't think the answer will look much like any of the existing VCSs.
Based on experiences in industry, my observation is that the choice of monolithic repository versus separate repository is highly specific to the organization.
> No organisation should have more than one regular-use repo (special-use repos, of course, are special). Multiple repos are a smell.
Totally agree with everything else, but gotta completely disagree on this last point. Monorepos are a huge smell. If there's multiple parts of a repo that are deployed independently, they should be isolated from each other.
Why? Because you're fighting human nature, otherwise. It's totally reasonable to think that once you excise some code from a repo that it's no longer there, but when you have multiple projects all in one repo, different services will be on different versions of that repo, and your change may have changed semantics enough that interaction bugs across systems may occur.
You may think that you caught all of the services using the code you refactored in that shared library, but perhaps an intermediate dependency switched from using that shared library to not using it, and the service using that intermediate library hasn't been upgraded, yet?
When separately-deployable components are in separate repositories, and libraries are actual versioned libraries in separate repositories these relationships are explicit instead of implicit. Explicit can be `grep`ed, implicit cannot, so with the multi-repo approach you can write tools to verify that all services currently in production are no longer using an older, insecure shared library, or find out exactly which services are talking to which services by the IDLs they list as dependencies.
While with the monorepo approach you can get "fun" things like service A inspecting the source code of service B to determine if cache should be rebuilt (because who would forget to deploy service A and service B at the same time, anyways...), as an example I have personally experienced.
My personal belief is that the monorepo approach was a solution back when DVCSs were all terrible and most people were still on centralized VCSs like Subversion that couldn't deal with branches and cross-repo dependencies well, and that's just what you had to do, while Git and Mercurial, along with the nice language-level package managers, make this a non-issue.
Finally, there's an institutional bias to not rock the boat (which I totally agree with) and change things that are already working fine, along with a "nobody got fired buying IBM" kind of thing with Google and Facebook being two prominent companies using monorepos (which they can get away with by having over a thousand engineers each to manage the infrastructure and build/rebuild their own VCSs to deal with the problems inherent to monorepos that most companies don't have the resources and/or skills to replicate).
EDIT: Oh, I forgot, I'm not advocating a service-oriented architecture as the only way to do things, I'm just advocating that whatever your architecture, you should isolate the deployables from each other and make all dependencies between them explicit, so you can more easily write tooling to automatically catch bad deploy states, and more easily train new hires on what talks to/uses what, since it's explicitly (and required to be) documented.
If that still means a monorepo for your company's single service and a couple of tiny repos for small libraries you open source, that's fine. If it means 1000 repos for each microservice you deploy multiple times a day, that's also fine (good luck!).
> It's totally reasonable to think that once you excise some code from a repo that it's no longer there, but when you have multiple projects all in one repo, different services will be on different versions of that repo, and your change may have changed semantics enough that interaction bugs across systems may occur.
But having multiple repos doesn't prevent the equivalent situation from happening (and, I think, actually makes it much likelier): no matter what, you have to have the right processes in place to catch that sort of issue.
> You may think that you caught all of the services using the code you refactored in that shared library, but perhaps an intermediate dependency switched from using that shared library to not using it, and the service using that intermediate library hasn't been upgraded, yet?
That's the sort of problem which happens with multiple repos, but not (as often) with a single repo.
> Explicit can be `grep`ed, implicit cannot, so with the multi-repo approach you can write tools to verify that all services currently in production are no longer using an older, insecure shared library, or find out exactly which services are talking to which services by the IDLs they list as dependencies.
A monorepo is explicit, too, even more explicit than multiple repos: WYSIWYG. And you can always see if your services are using the same API by compiling them (with a statically-typed language, anyway).
The beautiful thing about a monorepo is it forces one to confront incompatibilities when they happen, not at some unknown point down the road, when no-one know what changed and why.
I think that your comment is actually a pretty good test for when not to spin out a micro service.
If you expect to need to step into a function call when debugging, then it's too tightly coupled to spin out. You should be able to look at the arguments to the call and the response and determine if it's correct (and if not, now you have isolated a test case to take to the other service and continue debugging there).
If the interface will change so often that you expect it will be a problem that it's in a separate repository, if you expect that you will always need to deploy in tandem, then it's too tightly coupled to spin out.
The advantage of micro services is the separation in fact of things that are separate in logic. The complexity of systems grows super-linearly, so it's easier to reason about and test several smaller systems with clear (narrow) interfaces between them than one big. It's easier to isolate faults. It's harder to accidentally introduce bugs in a different part of the system when the system doesn't have a different part. If done right, scaling can be made easier. But these are hard architectural questions, there's no clear-cut rule for when you should spin off a new service and when you should keep things together.
Someone else mentioned separating the shopping app from the payment system for an ecommerce business, which even has security benefits. I think that's an excellent example.
Edit: Another clear benefit is that you can choose different languages, libraries, frameworks and paradigms for different parts of the code. You can write your boring CRUD backend admin app in Ruby on Rails, your high-performance calculation engine in Rust and your user-facing app in Node.js (so the front- and backend an share Javascript validation code).
I just want to add one disadvantage before I give some advantages. There's a lot of operational complexity involved in routing, monitoring, and keeping every instance of every microservice running. That complexity also makes debugging in production much more difficult, as one must track a relay of network requests through many separate layers to find the point where it actually got stuck.
As for advantages, microservices tend to keep code relatively simple and free from complex inheritance schemes. There's rarely a massive tangled-up engine full of special cases in the mix, as there often is in monolithic apps. This substantially decreases technical debt and learning curve, and can make it simple to understand the function an isolated microservice performs.
There is the obvious advantage that if you have disparate applications executing nearly-identical logic to read or write data to the same location, and the application platforms can't execute the same library code, you can centralize that logic into an HTTP API, which reduces maintenance burden and prevents potentially major bugs.
My opinion is that adopting microservices as a paradigm leads to a slow, difficult-to-debug application, primarily because people take the "micro" in microservices too seriously. One shouldn't be afraid to split functionality out into an ordinary service after it's been shown to be reasonable to do so.
Yes, but there's another dimension here. If another team breaks your build in a monolithic repo, you may or may not be able to resolve this quickly. You're in a contract with them about the state of the repo and thus your service.
With microservices, the production version of their service would conceivably be stable. It moves the contract from the repo to the state of production services.
> If another team breaks your build in a monolithic repo, you may or may not be able to resolve this quickly.
With a monolithic repo done right, the other teams broke their build of their branch, and it's up to them to resolve it. You, meanwhile, are perfectly happy working on your branch. When their changes are mergeable into trunk, then they may merge them, not before — and likewise for you.
With multiple repos, they break your build, but don't know it. You don't know it either, until you update your copies of their repos — and now you have to figure out what they did, and why, and how to update your logic to handle their new control flow, and then you update again and get to do it again, until finally you ragequit and go live in a log cabin with neither electricity nor running water.
> With multiple repos, they break your build, but don't know it. You don't know it either, until you update your copies of their repos — and now you have to figure out what they did, and why, and how to update your logic to handle their new control flow, and then you update again and get to do it again, until finally you ragequit and go live in a log cabin with neither electricity nor running water.
I don't see how this is a problem if you are pushing frequently and have a CI system. You know within minutes if the build is broken. If it broke, don't pull the project with the breaking changes.
My point is, I don't think one approach is inherently better than the other. Both require effort on the part of the teams to manage changes (or a CM team), and both require defined processes.
> If it broke, don't pull the project with the breaking changes.
I agree with the overall sentiment of your comment, but the quoted part is where I've seen trouble brew. The tendency is to be conservative about pulling updates to dependencies, which can easily get you into a very awkward state when a critical update eventually sits on top of a bunch of updates you didn't take because they broke you. It is usually better to be forced to handle the breakage immediately, one way or another.
You don't debug distributed systems by tracing into remote calls and jumping into remote code. You debug it by comparing requests and responses (you use discrete operations, right) with the specified requests and responses, and then opening the code that has a problem¹.
It calls for completely different tooling, not for a "better debugger".
1 - Or the specs, because yes, now that your system is distributed you also have to debug the specs. Why somebody would decide on doing that for no reason at all? Yet lots of people do.
I think it's more to do with a need rather than going straight just because you have enough people on a team. For instance, if you find that some of your processing/specific request handling can outperform better by using a different framework, programming language than the ones it's currently developed on, then you should definitely consider a microservice approach by decoupling that specific service/functionality from your current stack.
Careful with this one too. Usually adding new features to adapt to a changing marketplace can have new requirements across many of your services that need to be finished quickly. If those services are each in a different language, it can slow everything down by weeks or months.
Multiple platforms is not a problem and generally a good thing as long as it's not excessive. You don't want to be in a case where you have the same number of different platforms as developers or anything like that. I'm guessing there is a rule of thumb here, but I'm not sure what it would be. Max 1 different platform per 5 developers? Something like that.
OSGi makes it easy to end up with a cornucopia of tightly coupled nanoservices all running in the same JVM.
Unless you can coax dOSGi into working (which is tons of fun), then you can have services tightly coupled to other services running on entirely different machines causing frequent (and hilarious) cascades of bundle failures whenever the network hiccups.
OSGi is a trigger word for me now. I've worked on two large OSGi projects (previous job and current job) and it's always the same. Sh*t is always broken (and my lead still insists that OSGi is the one true way to modular bliss). And the OSGi fanboys always say "Your team is using it wrong!" Which very well might be true, but I no longer care. Apparently it's just too damn hard to get a team of code monkeys to respect service boundaries when OSGi makes it so damn easy to ignore them.
If I'm ever in a position of getting to design a new software architecture (hasn't happened in 10 years, but hey I can dream), I'll punch anyone who suggests "OSGi" to me right in the face.
Wholeheartedly agree on OSGi. Disastrous implementations. I worked with servicemix and still have nightmares around class path issues and crazy bundle scoping rules.
A plain old maven built jar with shading works much better in practice, but shading itself is shady :)
Well, I consider that by definition tightly coupled microservices should never be done. If it's not possible to decouple that function then it should not be in a micro service.
> A small team starting a new project should not waste a single second considering microservices unless there's something that is so completely obviously decoupled in a way that not splitting it into a microservice will lead to extra work.
That's a good point. I think this thought extrapolates to other parts of software engineering as well. Sometimes writing very modular and decoupled software from the beginning is very hard for a small team, and we can't see well if this is the best approach since it's also hard to grasp the big picture.
I'm currently facing this issue. I'm trying to write very modular and reusable applications, but now I'm paralyzed trying to picture the best patterns to use, where should I use a facade, a decorator, etc. I think I'll adopt this strategy for myself--only focus on modularizing from the beginning if it'd lead to extra work otherwise.
I'd also add that microservices have increased value if you begin with such an architecture in the first place. It's much more difficult to "gracefully" rip an existing monolith into modular pieces than to build modularly from the start.
I don't like correcting with "well, actually", however, I have to say that the author of the book "Building Microservices" in his first few chapters (in particular: Chapter 3: Premature Decomposition) warns against using microservices with new apps, especially if you are new to the domain. He claims that they are actually easier to use when you have to refactor a large monolith, and that normally you shouldn't start with microservices unless you know what you are doing - therefore my criticism towards the article which starts with a pre optimization (split one service in 12), which seems to be a common, yet arguable practice.
This has not been my experience. I've seen a few projects where microservices had been added from the start because it's the thing to do and, in all cases, it didn't work well. It's extremely difficult to split in microservices if you do not have a clear big picture of your projects functions and coupling. And, in most cases, in new projects, you don't have that big picture.
Microservices also make it much harder to refactor the code which you often need to do in the early stage of a project.
Yeah, we do micro services, the "real" kind. Not the "SOA with a new name kind", but the "some services are literally a few douzan lines of code and we have 100x the amount of services as we do devs" kind.
The thing is, you need a massive investment in infrastructure to make it happen. But once you do, its great. You can create and deploy a new service in a few seconds. You can rewrite any individual service to be latest and greatest in an afternoon. Different teams don't have to agree on coding standards (so you don't argue about it).
But, the infrastructure cost is really high, a big chunk of what you save in development you pay in devops, and its harder to be "eventually consistant" (eg: an upgrade of your stack across the board can take 10x longer, because there's no big push that HAS to happen for a tiny piece to get the benefits).
Monolithic apps have their advantages too, and many forget it: less devops cost, easier to refactor (especially in statically typed languages: a right click -> rename will propagate through the entire app) and while its harder to upgrade the stack, once its done, your entire stack is up to date, not just parts of it being all over. Code reuse is significantly easier, too.
Yeah, add in things like MORE THAN ONE PRODUCTION ENVIRONMENT and LETTING YOUR CUSTOMER HOST AN INSTANCE OF YOUR MICROSERVICES and you have guaranteed your own suffering.
It is a matter of tooling. One data center or ten, it does not matter much with proper tooling. We deploy to seven data centers with a click of a button, with rollback, staggered deployment etc. Centralized logging using ELK gives us great visibility in to each DC, without worrying about individual microservice instances.
beyond just the docker environment, you only need to be able to run the service you're working on locally. Anything you don't run local should hit some shared dev/QA infrastructure (which share a db with local). Whatever you use to develop should be able to detect what you have running locally and prefer those when available.
Anything you're not running locally just hits the shared infra.
Dockerized apps make it simple to run on dev environment, which is what we do. Of course , one cannot run everything on a laptop, we have a dev cluster
Seems like a terrible idea if "different teams" actually means "random assortment of developers for this specific project." If it actually means "different teams," e.g. you rarely if ever would move from one team to another, I don't see the issue if one team uses tabs and one uses spaces, or you have different naming conventions or whatever.
Well, you use the standard you like, and the other team can use the standard they like. Then you write a micro service to convert from one standard to the other.
So that sounds pretty much like a function call in a monolithic app. How do you store state? I assume you need to between all those microservices.
>The thing is, you need a massive investment in infrastructure to make it happen.
I thought that one of the selling points of microservice architectures was the minimal infrastructure. I am really struggling to see an advantage in this way of doing things. You are just pushing the complexity to a dev ops layer rather than the application layer - even further form the data.
I wonder what language I would pick for that. I usually use Scala, but it seems a bit silly when the footprint of the platform would massively outweigh the actual service. I don't like Go. I like Python, but I prefer static typing. Rust seems a bit too low level (although I'd like to try it for embedded). I don't see any point in learning Ruby when i already know Python well.
Maybe Swift? Scala Native in a year or two? I've done a little Erlang before, so maybe Elixir?
Building Microservices needs discipline, an eye to find reusable components and extracting them and as you said, investment in infrastructure.
Monoliths invariably tend to become spaghetti over time, and completely impossible to any non trivial refactoring. With microservices, interfaces between modules are stable and spaghetti is localized.
Deployment has to be easy. Create a new service from scratch, including monitoring, logging, instrumentation, authentication/security, etc, and deploying it to QA/Production with tests has to take minutes from the moment you decide "Hey, I need a service to do this" until it's in prod.
Because individuals may be jumping through dozens of services a day, moving, refactoring, deploying, reverting (when something goes wrong), etc. It has to be friction-free, else you're just wasting your time.
eg: a CLI to create the initial boilerplate, a system that automatically builds a deployable on commit, and something to deploy said deployable nearly instantly (if tests passed). The services are small, so build/tests should be very quick (if you push above 1-5 minutes for an average service, it's too slow to be productive).
Anyone should be able to run your service locally by just cloning the repo and running a command standard across all services. Else having to learn something every time you need to change something will slow you down.
That infrastructure is expensive to build and have it all working together.
I do have a positive micro-service experience, and although we are still in that process of breaking down our monolith SOA based app, we have seen the benefits already.
The more dramatic effect was on a particular set of endpoints that have a relative high traffic (it peaks at 1000 req/s) that was killing the app, making upset our relational database (with frequent deadlocks) and driving our Elasticsearch cluster crazy.
We did more than just split the endpoints into microservices. We also designed the new system to be more resilient. We changed our persistence strategy to make it more sensible to our traffic using a distributed key-value database and designed documents accordingly.
The result was very dramatic, like entering into a loud club and suddenly everything goes silent. No more outages, very consistent response times, the instances scaled with traffic increase very smoothly and in overall a more robust system.
The moral of this experience (at least for me) is that breaking a monolith app into pieces has to have a purpose and implies more than just move the code to several services keeping the same strategy (that's actually slower, time consuming and harder to monitor)
Do you think the result could also be a dramatic improvement if you kept old system and do those other things except splitting into microservices?
I can't get my head around how people introduce changes to their system if they have to update 12 different microservices at once? It must be horrible.
Often you hear stories how people are converting monolithic app to microservices - but this is easy. Rewriting code is easy and it's fair to say it always yields better code (with or without splitting into microservices - it doesn't matter).
What I'd like to hear is something about companies doing active development in microservice world. How do they handle things like schema changes in postgres where 7 microservices are backed by the same db? What are the benefits compared to monolithic app in those cases?
It seems to me that microservices can easily violate DRY because they "materialise" communication interfaces and changes need to be propagated at every api "barrier", no?
Multiple microservices are supposed to have different data backends, so that they are completely independent. Splitting your data up this way isn't all roses, but ideally the services are isolated so an update to one doesn't affect the others.
>Do you think the result could also be a dramatic improvement if you kept old system and do those other things except splitting into microservices?
As I said in another thread, the separation in different components was key for resiliency. That allowed independence between the higher volume update and the business critical user facing component.
>I can't get my head around how people introduce changes to their system if they have to update 12 different microservices at once? It must be horrible.
The thing is, if you design the microservices properly it is very rare to introduce a change in so many deployments at once. Most of the time is just 1 or 2 services at a time.
>What I'd like to hear is something about companies doing active development in microservice world. How do they handle things like schema changes in postgres where 7 microservices are backed by the same db? What are the benefits compared to monolithic app in those cases?
We don't introduce new features in our monolith service anymore. So, from that perspective we do all active development in microservices.
>"How do they handle things like schema changes in postgres where 7 microservices are backed by the same db?
The trick is, you want to avoid sharing relational data between microservices. I don't know if it is just us, but we have been able to split our data model so far and in most cases we don't even need a relational database anymore, so having a schemaless key/value store makes seems easy too.
> What are the benefits compared to monolithic app in those cases?"
There are several advantages, but the critical one for me is being able to have a resilient platform that can still operates even if a subsystem is down. With our monolithic app is an all or nothing thing. Another advantage is splitting the risk of new releases.
>It seems to me that microservices can easily violate DRY because they "materialise" communication interfaces and changes need to be propagated at every api "barrier", no?
Not necessarily. YMMV but you can have separation of concerns and avoid sharing data models. When you do have shared dependencies (like logging strategy or data connections) you can always have modules/libraries.
Which one of the four major improvements do you attribute the success to though? Could you have done the work on making it more resilient, persistence, sensible, redesign the docs without breaking into micro-services and still have seen the positive results?
I don't think the level success comes from one dimension, but I don't think either that we could have achieved the resiliency without breaking it in micro-services (or just services that happened to be small if you will).
One key factor was decoupling the high volume updates from the users requests so one didn't affect the other one.
> Any positive experiences with micro-services here?
In my experience, any monolith that can be broken up into a queue based system will benefit enormously. This cleans up the pipelines, and adds monitoring and scaling points (the queues). Queues removes run-time dependencies to the other services. It requires that these services are _actually_ independent, of course.
I do, however, avoid RPC based micro-services like the plague. RPC adds run-time dependencies to services. If possible, I limit RPC to other (micro) services to launch/startup/initialization/bootstrap, not run-time. In many cases, though, the RPC can be avoided entirely.
> Any positive experiences with micro-services here?
Yep. We already had a feature flag system, a minimal monitoring system, and a robust alerting system in place. Microservices make our deployments much more granular. No longer do we have to roll back perfectly good changes because of bugs in unrelated parts of the codebase. Before, we had to have involved conversations about deployments, and there were many things we just didn't do because the change was too big.
We can now incrementally upgrade library versions, upgrade language versions, and even change languages now, which is a huge win from the cleaning up technical debt perspective.
How granular are your services? I've heard a lot of talk about microservices without much talk about how micro they are. As someone who's happy with the approach, would you mind giving a little context in terms of what sort of degree you've split the system down?
They are of varying sizes. We have maybe 3-4 per developer. And they vary in size. The smallest are maybe 5-6 python classes.
To be honest, we still have a monolithic application at the heart of our system that we've been slow to decompose, though we're working on it. We deploy it on a regular cadence and use feature flags heavily to make it play nice with everything else.
"We rolled out this update with 220 changes. There's a breaking bug. Where is it? We need to find out in the next 5 minutes, revert, and deploy. Otherwise we have to revert the whole thing- we're losing money."
Git doesn't really help with that. More granular deployments do, and if microservices help with more granular deployments, go for it.
Only if you have a test that catches the bug and it still needs time to run. You'll also need time to write a fix, validate it and deploy. Plus any extra time your organization needs between code and deployment
It helps with the find part. The revert and deploy not so much, especially say if it's the middle commit if 200 and you'd still like to deploy all the commits before and after.
My experience is that most devs don't even know how to use SVN correctly. I just had a conversation with someone waiting for me to finish something before they could branch. The idea that I could merge my change into their branch afterwards didn't occur to them.
>Any positive experiences with micro-services here?
It makes sense for some thing. We run a webshop, but have a separate service that handles everything regarding payments. It has worked out really well, because it allows us to fiddle around with pretty much everything else and not worry about breaking the payment part.
It helps that it's system where we can have just one test deployment and everyone just uses that during testing of other systems.
I've also work at a company where we had to run 12 different systems in their own VMs to have a full development environment. That sucked beyond belief.
The idea of micro-service are is enticing, but if you need to spin up and configure more than a couple to do your work, it starts hurting productivity.
> have a separate service that handles everything regarding payments. It has worked out really well, because it allows us to fiddle around with pretty much everything else and not worry about breaking the payment part.
Is the payments service a single service that manages the whole transaction, or have you go for multiple services handling each part and, if so, how did you manage failure with a distributed transaction?
Not sure if it's the case here. But what works really well for us is queues with at-least-once guarantee. (For payment services you might need an additional check to guarantee exactly one execution.) I think you can find this queue offered by most providers.
We had almost the same story with payments. Except for we've jumped to a payment-processing SaaS but got dissatisfied (all those SaaSes I saw don't work with PayPal EC without so-called "reference transactions" enabled) and decided that wasn't a good idea and we have to jump back to in-house implementation.
I didn't want to re-integrate the payments code back to the monolith - thought it would take me more time and make code messier. So I wrote a service (it's small but to heck with "micro" prefix) that resembled that SaaS' API (the parts we've used). It had surely evolved and isn't compatible anymore, but it doesn't matter as we're not going back anyway.
Works nicely and now I'm feel more relaxed - touching the monolith won't break payments.
On the other hand, I see how too many services may easily lead to fatigue. Automated management tooling (stuff like docker-compose) may remedy this, but also may bring their own headaches.
I don't think having a handful of services handling a specific, atomic section of the app really classifies as this 'micro-services' claim, it's just smart separation of concerns.
We have specific services that process different types of documents, or communicate and package data from different third parties, or process certain types of business rules, that multiple apps hook into, but it's literally like 20 services total for our department, some that are used in some apps and not others.
When I hear 'micro-services' I'm picturing something more akin to like node modules, where everything is broken up to the point where they do only one tiny thing and that's it. Like your payment service would be broken into 20 or 30 services.
But maybe I'm mistaken in my terms. I haven't done too much with containers professionally, so I'm not too hip with "the future".
I'm building a podcast discovery app and I find myself being de-facto pulled towards modularity. It's because my feed checker is in Elixir, my site is WordPress-based, and I communicate between them using the WP API, and I'm using Google Cloud SQL, and Elasticsearch on its own virtual machine...
The thing is though, the Elixir feed checker has its own database table that tracks whether it's seen an episode in a feed. And when there's a new episode it sends an API call to WP to insert the new post. The problem is that sometimes the API calls fail! Now what? I'll need to build logging, re-try etc. So I'm thinking of making the feed checker 'stateless' and only using WP with a lot of query caching as the holder of 'state' information about whether an episode has been seen before.
To sum up my experience so far, there's something nice about being able to use the right tech for each task, and separating resources for each service, but the complexity--keeping track of whether a task completed properly--definitely increases.
I think your problem might be not expanding wordpress. PHP will gladly do the above through wordpress plugins and cron jobs. I built something similar and ended up going that way. The system is still running to this day. Sure, its not hip but gets the job done with miniml fuss and makes money.
You are right that PHP can do the feed checking part but I wanted to use something with easy async/concurrency out of the box (and wanted to learn Elixir instead of using Node.)
One hard tech limit is that with 50k podcasts, 4million+ episodes, search definitely doesn't work well. Not just WP, but SQL itself. Hence Elasticsearch. I also plan to work on recommendations, etc. so will need probably to be exporting SQL data into other systems anyway for making the "people who liked this also liked this" kinda things.
Also I kinda lied about using the WP API--that's how I built the system initially (and will switch to it moving forward), but to import the first few million posts from the content of the feeds, I just used wp_insert_post against the DB of new entries that Elixir fetched (I posted the code I used here: http://wordpress.stackexchange.com/a/233786/30906).
I also plan to write the whole front-end in React (including server side rendering) so will have to figure out how to get that done. Would probably use the WP-API with a Node.js app in front of it, will look into hypernova from AirBNB. So probably more usage of WP API accessed by another service...
I hope you are not doing all of this alone. I'd try and keep things as simple as possible within a monolith and then improve as needs increase. Good luck :)
I generally write what I consider monolithic Django apps. I would add in Haystack (a search module for Django) and configure it to use Elasticsearch to overcome the problems you describe.
It doesn't sound like microservices are needed, just adding in the appropriate tech for the job.
That's an incisive question. My impression, which may be mistaken, is that a cronjob would be used to move data (pages compiled from templates, chart images, etc.) into the PHP host on a "batch" basis. To me, that implied the existence of other systems that handle the data in their own way, but I guess in this thread the salient difference between micro and mono is that the former connects components via a web stack. Are there more agile interfaces available for cronjobs? If instead we're only considering transformations of data already resident on the host (as what, flat files?), I don't imagine that cronjobs are the best solution available.
Care sharing your progress with the podcast discovery app? I'm a cofounder of Podigee which is a podcast hosting service. Maybe we can exchange know-how, find some synergies or even join forces on certain topics. Feel free to drop me a line at mati@podigee.com
The problem with microservices is that your state is spread over multiple systems. You completely lose the concept of transactional integrity, so you will have to work around that from the start.
The advantage though is that APIs (system boundaries) are usually better defined.
Perhaps one should use the best of both worlds, and run microservices on a common database, and somehow allow to pass transactions between services (so multiple services can act within the same transaction).
One of the big advantages of microservices is scaling/migrating the databases behind each service independently. If you need transactions across multiple services then one could argue that either your API endpoint is doing too much, or your services are doing too little. It's not perfect, and certainly not always convenient, but it's a balance. Microservices with a common DB is asking for trouble. The monolith is a better option in that case IMO.
Say you sell a widget. You want to update both your cash account and your inventory, and never one without the other. Which is easier to understand and more reliable: doing them atomically, or making sure you have designed in 2^n intermediate states and all the code required to complete work that should happen but hasn't yet?
The problem with microservices is that your state is spread over multiple systems.
Then again, sometimes it's advantageous to identify parts of your system where aspects of state can be safely decoupled. And in which having them reside in disparate systems (and yes, sometimes be inconsistent or differently available) might actually be a better overall fit.
You completely lose the concept of transactional integrity, so you will have to work around that from the start.
Then again, sometimes your state changes not only don't need to be transactional; it can be disadvantageous to think of them that way.
> Then again, sometimes your state changes not only don't need to be transactional; it can be disadvantageous to think of them that way.
I'm curious; in what kinds of situation would this apply?
> Depends, depends, depends.
Flexibility is usually an important requirement. Often you cannot freeze your architecture and be done with it. I think a transactional approach could better fit with this.
I'm curious; in what kinds of situation would this apply?
Any situation where the business value of having your state be 100% consistent does not outweigh the performance or implementation cost of making it so.
Probably more. I'd say, like, at least 30-40 years.
I mean, the infamous "UNIX way" of "do one thing, do it well" (something we nearly lost with popularity of "do everything in a manner incompatible with how others do it" approach in too many modern systems), when complex behavior was frequently achieved through the modularity of smaller programs communicating through well-defined interfaces.
Heck, microkernels are all about this, and their ideas haven't grew out of nowhere. And HURD (even though it was never finished) is quarter a century old already.
Oh yeah, there's certainly other ways of doing it. My own experience is just that message queuing seems to be the default loosely-coupled RPC mechanism for larger orgs (from before the term 'micro services' was popular).
Yes. A lot of success. And with only one person on the backend full time.
That said, in places where it doesn't make sense we didn't try to force it. Our main game API is somewhat monolithic, but behind it we have almost 10 other services. Here's a quick breakdown:
- Turn based API service (largest, "monolithic")
- Real-time API service (about 50% the size of turn-based)
- config service (serves configuration settings to clients for game balancing)
- ad waterfall service (dynamic waterfall, no actual ads)
- push notification service
- analytics collection service (mostly a fast collector that dumps into Big Query)
- Open graph service (for rich sharing)
- push maintenance service (executes token management based on GCM/APNS feedback)
- help desk form service (simple front-end to help desk)
- service update service (monitors CI for new binaries, updates services on the fly - made easy by Go binary deployment from CI to S3)
- service ping service (monitors all service health, responds to ELB pings)
- Facebook web front-end service (just serves WebGL version of our game binary for play on Facebook)
- NATS.io for all IPC between services
...and a few more in the works. Some of these might push the line of "micro" in that they almost all do more than a single function's worth of work, but that level of granularity isn't practical.
But don't get too caught up on the "micro" part. Split services where domain lines naturally form, and don't constrain service size by arbitrary definitions. You know, right tool for the job and whatnot.
I only use a microservice if its something that can operate by itself. Things like a file data store, reports generation, etc. But all business logic goes in the monolith.
Oh yes. We're splitting up a large monolith into a bunch of different services. Completely amazing, though there's a ton of tools (like Netflix's Hysterix, etc) that make it much, much easier to do.
I wouldn't, however, just "do microservices" from day one on a young app. But usually that young app has no idea what the true business value is, i.e., you have no idea what down time of certain parts of your services really means to the business. That's the #1 pain point we're solving: having mission critical things up 100%, and then rapidly iterating on new, less stable feature designs in separate services.
You should, however, keep an eye on how "splittable" everything is, i.e., does everything need to be in the same DB schema? Most languages have package concepts, which typically align (somehow) with "service" concepts. Do you know their dependencies? That sort of thing. Then, the later process of "refactor -> split out service" is pretty straightforward and easy to plan.
saw done properly once, with good separation of services etc, but it still required a truckload of commitment to make it work, because one thing is interface changes when the code just don't work when you merge, another is figuring out the publish and restart order of each service when you have to add an operation so you don't have to knock out the whole system at every upgrade.
I don't really like that model applied to everything, but eh now you are kind of forced in a hybrid approach - say, your macro vertical plus whatever payment gateway service, intercom or equivalent customer interaction services, metrics services, retargeting services, there are a lot of heterogeneous pieces going into your average startup.
but back on topic, what Docker really needs now is a whack on the head of whoever thought swarms/overlays and a proper, sane way to handle discovery and fail-over - instead we got a key-value service deployment to handle, which cannot be in docker and highly available unless you like infinite recursion.
I don't know if the community will consider this example to be microservices as currently defined, but many years ago I wrote client-server systems using a PC-based fat client application, and transactions running on a CICS server. I think this was pretty similar to what people currently think of as a microservices architecture, although we didn't have to worry about running/monitoring multiple servers (all the transactions/services ran on a single mainframe server), and the transaction monitor managed things like start-up and shutdown pretty simply. This approach worked really well for us, and we built several robust, scalable applications using this approach. To be clear, we numbered our users in hundreds, not thousands or millions. I can well understand how scaling this approach across many servers could be very challenging.
> Any positive experiences with micro-services here?
I'm currently working on a large refactoring effort along these lines. The end goal is to create a modular, potentially distributed system that can be deployed in a variety of configurations, updated piecemeal for different customers, and integrated by our customers with the third-party or in-house code of their choice using defined APIs. We aren't typical of the other examples, though, in that we do literally ship our software to our customers and they run it on their own clusters.
positive experience with microservices: identify discrete functions that can considered "stateless" (i.e. no side effects, deterministic output for given input) and factor those out into stand-alone microservices.
a good example of this that I've used in production at my current $dayjob: dynamic PDF generation. user makes request from our website, request data is used to fill out a pdf template context which is then sent over to our PDFgen microservice which does its thing and streams a response back to the user.
Does it connect to the database to fill in some values in the template? Does it keep connection pool of let's say 5 connection always open (as libraries like to do)? Does it have authentication? Is it public or private API? Who is managing security? Is it running behind it's own nginx or other proxy? Does it have DoS protection (PDF generation can be CPU intense)? What about the schema for request? How do you manage changes to the schema? They need to be deployed together with changes in other services, right? What about changes to database schema - you need to remember to update that service as well and redeploy it at the right time as well - just after successful db migrations - which live in another project.
All of that and much more needs to be replicated for each microservice, right?
Why not just have a module in your monolithic app that does it. The logic will still be separate. In most languages/frameworks you can spawn pdf generation task. Any changes are easier to introduce as well. There's no artificially materialised interface. Updates are naturally introduced. All auth logic is there already, you don't need to worry about deploying yet another service, same with logging etc.
> Does it connect to the database to fill in some values in the template?
the template has values that are related to database models. the main app (still mostly monolithic) fills out the template context. the context itself is what's passed to the microservice. the microservice does not connect to a database at all.
> Does it keep connection pool of let's say 5 connection always open (as libraries like to do)?
no. the service probably handles a few hundred requests per day, it is not in constant use. communication is over HTTPS. it opens a new connection on each request. this does impact throughput, but its a low throughput use case, and pdf rendering itself is much slower and that time totally dominates the overhead of opening and closing connections anyway.
> Does it have authentication?
yes, it auths with a bearer token that is borne only by our own internal server. this is backend technology so we don't have to auth an arbitrary user. we know in advance which users are authorized.
> Is it public or private API?
private
> Who is managing security?
we are, with a lot of assistance from the built-in security model of AWS.
> Is it running behind it's own nginx or other proxy?
the main app is behind nginx. the microservice is running in a docker container that exposes itself over a dedicated port. there's no proxy for the microservice, again, because of the low throughput/low load on the service. no need to have a load balancer for this so the most obvious benefit of a proxy wasn't applicable.
> Does it have DoS protection (PDF generation can be CPU intense)?
yes, it's an internal service and our entire infrastructure is deployed behind a gatekeeper server and firewall. the service is inaccessible by outside requests. the internal requests are queue'd up and processed 1 at a time.
> What about the schema for request?
request payload validation handled on both ends. the user input is validated by the main app to form a valid template context. the pdf generator validates the template context before attempting to generate one also. its possible to have a valid schema that has data that can't be handled correctly though. errors are just returned as a 500 response though. happens infrequently.
> They need to be deployed together with changes in other services, right?
nope. the microservice is fully stand alone.
> What about changes to database schema - you need to remember to update that service as well and redeploy it at the right time as well - just after successful db migrations - which live in another project.
the microservice doesn't interact with a database at all. schema changes in the main app database could potentially influence the pdf template context generation, but there are unit tests for that, so if it does happen we'll get visibility in a test failure and update the template context generation code as needed. none of this impacts the microservice itself though. it is fully stand alone. that's the point.
> All of that and much more needs to be replicated for each microservice, right?
in principle yes, and these are good guidelines for determining what is or is not suitable to be a microservice. if it would need to auth an arbitrary user, or have direct database access, or be exposed to public requests, it might not be a good candidate for a microservice. things that can stand alone and have limited functional dependencies are much better candidates.
> Why not just have a module in your monolithic app that does it.
because the monolithic app is Python/django and the PDF generation tool is Java. one of the main advantages of microservices architecture is much greater flexibility in technology selection. A previous solution used Python subprocesses to call out to PDF generation software. It's actually easier and cleaner for us to use a microservice instead.
> Also, the team spent too much time debating standards etc.
Ah yes, the 'let's have decentralised microservices with centralised standards!' anti-pattern. It results in lots of full-fledged, heavyweight, slow-to-update services, which also have all the problems of a distributed system. It's the worst of both worlds.
was it a complete rewrite? I don't think thats the right way to transition. Why didn't you try to separate the features one-by-one from the monolith? That would give more immediate feedback and real problems to work on instead of the possibility to get stuck on the holy architecture debate.
No it wasn't a complete rewrite. We started by separating out the most mission critical components. Maybe that's where we went wrong; the most mission critical components were quite large and unwieldy to split out all at once. There was also the overhead of keeping the newly separated out component and the monolithic app in sync.
Microservices is a technology. IMO, like any other tech, it should be used when there are clear benefits expected in the near future, not as a blanket "always microservices" policies.
Although I personally had to deal with some monolithic monsters that I wished were split into smaller services.
We were looking to break up our monolithic rails app into micro-services so devs could iterate and develop faster. We also thought that the application as a whole would become more failure resistant. Unfortunately, inter-dependancies among the services themselves meant that the failure-resistance didn't pan out as we thought.
You split off specific parts of your app into microservices because you want to scale those parts independently from the rest. It's not just a blind decomposition of a monolith for the sake of decomposition.
We did have a lead with a vision, and part of the vision was standards for each service (for example, file structure in Go). I can see the rationale behind it; a new dev can onboard very quickly on to a new service. But in hindsight, maybe it wasn't thought out enough.
> It was mostly because the monitoring and alerting were now split into many different pieces
Well, there's your problem - you need a monitoring microservice and an alerting microservice! Well, those may be too coarse by themselves, but once you break them down into 5 or 6 microservices each, you'll be ready for production.
That seems excessive"
A 100 times yes. We tried to split our monolithic Rails app into micro-services built in Go. 2 years and many fires later, we decided to abandon the project. It was mostly because the monitoring and alerting were now split into many different pieces. Also, the team spent too much time debating standards etc. I think micro-services can be valuable, but we definitely didn't do it right, and I think a lot of companies get it wrong. Any positive experiences with micro-services here?