Any sufficiently complicated infrastructure that has uptime requirements and significant revenue associated with it is going to have a DevOps Team (or the equivalent) ultimately responsible for ensuring that things are working. I guess it's possible to turn your entire dev team into part-time DevOps engineers, while still calling them Software Engineers, but I've usually found that doesn't work long-term and causes employee retention issues. It's like saying your company does 'No-Support' because you don't hire Support Engineers, while in fact you've enlisted your Software Engineering team to handle all support requests.
Also, if you're working in a regulated field like Healthcare or Finance, or anything that touches PII, your developers often can't have access to deploy code directly to production. Again, you could maybe work around this in the short-term by turning all developers into developers+devops, but they're different skillsets.
As a software engineer, there is just no way I can stay up to date with my craft as well as everything there is to know about infrastructure AND the all important security. I don't know about all the latest kernel patches and firewall rules. I don't know about monitoring failed hard drives. Etc.
I mean, I do know a lot about deploying and maintaining my running software, but Ops has a ton of other concerns that themselves are a full time job and I already have my time fully consumed by development tasks. I'm also ok with being pushed enough of the work so that I don't accidentally make software that's a PITA to deploy or manage and that I don't needlessly wake somebody else. That doesn't mean that I can take on the entire job (well, I can, but I wouldn't be doing as good a job, especially when security and such is concerned, and I wouldn't be doing as good a development job either). What next - DevOpsSalesMarkettingAccounting?
Much better, IMO, is to have small tightly-knit cross-functional teams which include an ops engineer.
You do a better job communicating with yourself though?
For example, in my current work, I could try to figure all the ops stuff out, but I've already got a backlog of months of development tasks for a project that needs to be done asap.
If your DevOps people reside in a separate group outside of the development team, then you are not doing DevOps.
Architecture and Infrastructure go hand in hand, and DevOps is the glue that merges them together. I've worked with both DevOps and Architecutre groups in larger companies where Development, DevOps, and Infrastructure have been separated and siloed. This invariably leads to waste that undercuts any advantage provided by modern development practices.
The core of the issue is the designs will only consider trade offs within their skill set. Problems that are easily solved with a combination of dev/devOps/inf are instead solved using complex designs within a single skill set. The other end of the spectrum is that decisions get made in one group that will undercut the efforts of another group.
Real life examples:
The dev group wants to deploy backend service version 2 with fail back option in production. The API's are identical, the database is unchanged. Instead of using a load balancer and monitoring to automate role back the dev group builds another system with the job of routing traffic between the two systems, identifying failures, and then stop sending traffic to the new system.
The dev group designs a system with "micro-services" in mind. The developers have all containerized the services and run them on their laptop. The infrastructure and/or devops group doesn't want to deal with containers and instead deploys one service per VM. (In these scenarios the dev group will get a bill for the extra services).
The problem is that it's easier to grab the people sitting next to design something than scheduling a meeting with groups you rarely see. This is a key driver of Conway's law.
Devops and swdevs sitting and working together, understanding each other's problems and needs, and keeping them in mind when designing solutions, is indeed a beautiful thing to watch.
If you write code, you're a developer. If you run servers, your in ops. If you are doing both, it's devops. So when discussing the idea of having a total separate team for running the servers, OP says it's not devops and he's right, because the definition of devops is not having the teams be separate. And you say that it's often totally needed to have that separation and you're also right.
> I guess it's possible to turn your entire dev team into part-time DevOps engineers,
I think you mean, it's possible to turn your entire dev team into part-time ops engineers. Which is 1) the entire concept of "devops", and 2) often a horrible idea. :)
(Sorry, but people who use "devops" to mean "ops" is a pet peeve of mine. If you're not a developer, it's just ops.)
If a devops teams is actually managing all the servers, I agree that they aren't doing devops, but at a large enough company it makes sense to have a team working just on things that make it easier for the company to do devops.
The rebranding is cute and all, and the tooling's a fair bit better, but nothing I've seen suggests that
combining these two full-time roles in the same people is any more a good idea today than it was fifteen years ago.
All things being equal (i.e. I've got the money to have someone who's role is more ops than dev but still does both) having that person to "own" the production configuration is valuable, but developers still need to be in touch with what their code does in production. Otherwise you eventually end up with the equivalent of a cool interaction design that's damn near impossible to implement on the web (another pet peeve of mine...)
The inherent failing in this structure is when one of two things happens; one, the system administration team does not have the appropriate channels (and clout) to provide push back against the engineering team; two, the technical teams (both engineering and system administration) don't have the ability to get technical debt payed off properly due to an improperly structured project management process.
Anecdotally, I've been witness to the second issue a number of times. If there isn't an immediate understanding of ROI for a proposed change then it isn't prioritized to be worked on. The thought process is generally along the lines of, "Engineers are an expensive resource, having them working on something that won't make the company money is obviously not the priority."
While some of this is on the engineering leadership as their job is to provide insight into ROI for technical matters there also needs to be a balance where the non-technical leadership trusts the technical leadership to know when to prioritize projects with non-obvious ROI.
Some places just rebrand administration as devops. Shiny new title for you, stakeholders can be told we're not missing the trendy new hotness, carry on.
Some places will pull in a "devops person" and drop them on the IT team. This seems to usually result in something between "Jenkins? The devops guy sites over there" and incremental improvements.
Better than that is the model where the "devops person" is something of a liaison as well as an individual contributor - they sit in engineering standups, collaborate on how things are going to be built with an eye towards deployment and manageability, and generally play both sides of the fence. This, however, requires a "devops person" who is also a bit of a politician, and that's not usually contemplated when hiring. It also requires engineering to let the person meaningfully take part, which can become even more political some places.
Best, in theory, is more of less of a merger, but that does ignore that IT is a very different beast than engineering, and that the workplace has been dealing with the distinction for a very long time. Changing that is not a technical issue, it is a (big) management and perception issue. If you get it wrong, the power balance gets wonky and causes the usual problems when you have managers who are IT-clueless managing IT people.
All that said, and putting aside org-chart and political issues, I like to think two things are true:
- That someone who has done both engineering and administration is more likely to spot friction, second-order effects, and various traps and dead ends than someone who hasn't.
- That treating the various "devopsy" things - deployment, integration, monitoring, etc. as first-class requirements alongside product features leads to better results along multiple dimensions.
So it reduces to people-problems. There just aren't many folks who have lived on both sides of the fence who also want to do this sort of role. And if you adopt "devops" as a cost-savings measure, you're doomed up-front.
 You never see IT managers promoted over engineering, for obvious reasons. The reasons why the reverse happens are obvious to me in descriptive terms, but not in normative terms.
 Of course, keep in mind that I'm in this category. I don't write this as ego fluffing - I believe these things to be true - but here's my disclaimer.
me@homebox $ for host in foo bar baz; do cat random_stuff_who_knows_if_it_works.sh | ssh $host 'bash -'; done
That said, immutable configuration is static, so the need for grumpy admin style scripts did not go away. It just reduced.
But yeah, I agree that Ansible is the minimum that should be in place.
Oh, Python is quite old already :)
I had used very readable and documented scripts that would build images, boot VMs, deploy on physicals, configure network devices with hundreds of SLOC by simply calling the right CLI tools instead of (re)writing many thousands of lines in $language.
I was in a company around 2002 doing immutable deployments by updating images from git-tracked config files for whole datacenters.
E.g. calling to debootstrap takes few lines. Generating an ISO. Configuring PXE to serve it...
As a funny non-example: https://github.com/p8952/bocker
In my anecdotical experience, the ability to recover from such incidents degrades with age, so nowadays I regard "everybody [but management] does DevOps" as codeword for ageism.
I don't think these are mutually exclusive; I think you can both have a dedicated applicative operations (rebranded DevOps or SRE) team and still allow developers to rapidly provision and deploy. The point is a change in responsibilities and workflow on the part of operations: whereas their task was originally to deploy, verify success, rollback if necessary, monitoring, etc., their new task is to embed those tasks in code, so that developers can safely and reliably perform those tasks by themselves. You can have an organization where developers can automatically provision infrastructure which is behind your enterprise firewalls, hooked up to up-to-date enterprise artifact repositories, has enterprise PKI management already set up, etc., because expecting developers to know the ins and outs of setting that up manually is moronic and much of that should be scripted for ease of management anyway.
I think the intent here is a good one. You as a developer should be involved with how your software is deployed and managed. It's just that there is a pretty grey boundary between where developer involvement ends and ops involvement begins.
Another issue is that devops is extremely poorly defined. Some people insist this means only writing chef scripts. Some people it's diagnosing and fixing production issues. Some people it's just sysadmin work. Or other responsibilities and combinations.
Amazon does it this way because it's made of teams that are not just loosely coupled but somewhat firewalled from each other, along with a brutal internally competitive process.
> is going to have a DevOps Team
The parent is arguing that the concept of a "DevOps Team" that does Ops makes sense and is not an oxymoron. Yet "DevOps" literally means doing Dev and Ops together.
Otherwise have a "Developer Team" and an "Operations|Engineering|SRE|SysAdmin Team".
Even big guys who are using microservices started with monolith. Many people can't seem to catch this important detail - they started as monolith that was later refactored/modularised/split/microserviced. It doesn't mean, the moment they did it, that humanity found a better way of writing software called "microservices". It just means that, at that stage of life of the project, it made sense. Starting with monolith is still, in most cases, the best way to write projects, even if later they evolve into microservices.
Starting projects with maximum split into microservices is, in most cases, just a plain, stupid idea.
The most important part when starting project is avoiding friction at all levels - from dev setup, contribution, deployments, database evolution (migrations), interaction between different parts of the system (it's easier to just call a function from a module than to do rpc - which involves implementing rpc on the other side, managing it's deployment, keeping interfaces in sync etc)...
Microservices are for mature services with crystallized interfaces. They emerge naturally and the split is obvious at later stage - this information is not available at the beginning.
Even when doing incredibly small front-end projects, I have a hard time thinking about times where I didn't regret optimizing or modularizing things before it was obviously necessary. Would usually later uncover that it was either useless or that I had built the wrong abstractions, needing to start over again. Conversely, every time where I've spun something quickly using the most straightforward patterns and optimized or refactored only when it became abundantly clear that it was necessary, the right way to abstract the code always felt like a no-brainer and I would always end up with very useful abstractions which allowed me to build meaningfully on top of them.
the Dtos, the data, the WebAPI, and the tests; all for each entity.
Breaking down a monolithic platform into different microservices is not something I would call refactoring.
> Microservices are for mature services with crystallized interfaces.
You are not making any sense here. What exactly is a 'mature service'? Just throwing technical jargon around?
> The most important part when starting project is avoiding friction at all levels - from dev setup, contribution, deployments, database evolution (migrations), interaction between different parts of the system (it's easier to just call a function from a module than to do rpc - which involves implementing rpc on the other side, managing it's deployment, keeping interfaces in sync etc)...
Those things are pretty important for any kind of project.
> They emerge naturally and the split is obvious at later stage - this information is not available at the beginning.
Most microservices are plain boring and extremely predictable. Have an eCommerce site? Then you have a user service, a cart service, payment service, etc.
2. Mature service is your app after several cycles of release. At the beginning the project is just a dance with the client, going in circles, changing things all the time, until she's happy (with at least parts of the system). The thing is that at the beginning you don't know how the system will look like and more importantly - she doesn't know as well. The only tool that we have, that we know works well, is rapid prototyping with quick feedback loop. You want to minimize the friction of changes. She asks you to do something, you do it, then she changes her mind, rearranges things etc - often those changes require schema changes, shuffling hierarchy or adding some indirection layers etc. You can't do it fast if you have to coordinate several microservices to use new schema. You need to promote all of them to the new version and you need to orchestrate it on live, production system. With monolith you don't have this problem, everything is in one place, you run migrations on deployment to bring the system to the new state and presto, you're done. This kind of friction echoes through all environments - from your local dev, through staging to production. If you're working with more colleagues, your changes can easily block others' work.
3. So we agree that avoiding friction is important for any kind of project. I'm saying this implying that microservices are adding extra friction to the development. Instead of just calling function in your system you now have to maintain separate, coordinated, interface compatible service. All changes now need to go to two places. They need to be coordinated on migration/deployment, have their own devops setup etc.
4. ...and then you introduce discount codes, different countries, tax information, translations, connecting users with paypal and what not - all spanning across multiple microservices, you need to duplicate new communication schema across all of them, versioning apis, sometimes managing breaking changes which are pain in the ass in microservice world... all that for what? What exactly are you gaining? Are you really maxing out on thousands of requests per second on any one of those components? Is microservice going to save you because you can scale horizontally? Aren't they writing to the same store that's a bottleneck and scaling out the middleware won't improve anything at all? If they are separate then how are your joins doing when you need to match multiple, cross database collections? For example to update some kind of aggregate information for every user? Or any kind of reporting?
E-commerce site with user, cart, payment and all the rest is trivial in monolith webapp as described in full in beginners book Agile Web Development with Rails for example. There's no need to clutter basic app like that with microservices IMHO.
Microservices were not just concocted by a team at Netflix, and everyone then followed. Instead, microservices emerged across many different companies and teams concurrently. The architectural style was a natural reaction to many simultaneous forces that were being applied across the broader development ecosystem.
Of course, I'm biased because I built two similar architectures at the same time that micro service was becoming a buzz word, and I only knew that the type of architecture had a name much later. But, me and my team just did it that way because we were trying to find the architecture that worked best for us, our tools, and our environment. That is, the form followed the function. And, this was the type of design that naturally turned out.
In the distant past, "microservices" were called "loosely coupled architectures" and these have been around since the early 80's I believe, but probably earlier. There isn't anything new about microservices, and they are a great idea in theory. In practice, there are all kinds of challenges, and these will have to weigh in on the architectural decision to deploy this particular pattern.
I am genuinely curious as to why we in information technology have such an astounding capacity for re-inventing (and re-labeling) the wheel. I rarely see as much "Not Invented Here" and "Not In My Backyard" as I do in our field.
Conversely, the field is full of autodidacts. It's much easier to teach yourself by doing. Companies like it this way and fill themselves with smart kids who reinvent the wheel. Let's not forget that often it's easier to reinvent the wheel than look for existing solutions, especially with the risk of running across a software patent (never read these!).
As an example, we're talking about microservices, so one could start looking into things that people brought up, like the Unix Philosophy.
The thing developers really need to constantly be aware of is this - if you think of it today, another developer has already thought of it 30 years ago. Go find out what he knows.
Just reading Knuth can give you a fantastic window into what has been done before. Looking into the history of Bell labs and Xerox PARC can make you understand the reality of what you suggest.
I'm not in any way suggesting that there's nothing new to invent in CS, but the current mindframe in many devs is that the state of the art is akin to quantum mechanics following Newtonian physics by a couple of decades.
The current revolutions in CS are mostly capability based rather than concept based. The ideas are relatively old, but the technology has allowed them to come to fruition.
I think it would be beneficial for all new CS practitioners to have access to a history of CS, as they would not just realise that the current trends aren't particularly new, but that there are a huge number of equally old ideas that are probably ready for prime time, but weren't feasible when first suggested.
HPS for CS wouldn't be a whole graduate course, but would be a worthwhile module in a larger course.
It would be interesting to see some of the thinking behind current approaches to HPS being applied to development teams, both as teams and as part of the larger community of developers
Technically, it was the first 'wiki'.
I like to call it "ego-driven/fashion development" and I pretty much see some form of it nowadays every time I work with a team of devs with members under the age of 30.
First, the subject is very wide and diverse, such that one individual might take decades to come across a reasonable percentage of it all, and by that time 75% of the field would have churned to new stuff.
Second, relatively little is written about real life software, certainly until quite recently. Most books and papers are about academic subjects and issues, not closely related to rubber hitting road and war in the trenches.
The result is that techniques get reinvented without the new inventors ever having realize the thing they invented already existed. So now it has a new name and even the people who did know about the old thing don't realize the new thing is the same with a different name.
Good example : Sharding.
1. Incorrect or incomplete understanding of the differences between CS and software engineering
2. Ego and arrogance. There are plenty of very arrogant high achieving physics and engineering PhDs I know from my former life as an academic who would be ashamed at the arrogance of a lot of the folks in this field. In my view there is a very deep strain of "I know better than those who came before (and, incidentally, better than many now)." I've never seen anything quite like it in any other context.
I think people also simply like to D.I.Y
I too feel there were good points, but I'm not ready to throw the baby out with the bathwater because there have been failures in organizations because they chose to adopt the pattern without a great reason for why.
The biggest problem I have with microservice is that they lock you into a particular data flow up front. And the only times I've worked on a project where the data flow didn't change substantially from first implementation to having a rich set of features and many customers? Those were the projects that never got anywhere.
No battle plan survives contact with the enemy, and microservices are making decisions early on that are difficult to change later. Because you've picked one decomposition and then erected fences around the parts.
You say that as if that's an unalterable fact.
> No battle plan survives contact with the enemy, and microservices are making decisions early on that are difficult to change later. Because you've picked one decomposition and then erected fences around the parts.
If you know about that problem, then don't do that! :P
In my experience, if you slice your microservice boundaries with the philosophy that each of them should be able to be sold as a white label product (or more realistically be reused for a completely different product internally), microservices can survive pretty large pivots of the startup/project with little changes.
Once you're at the point of having multiple products you've already made it past the valley of death. In my experience you only understand the system well enough to be able to decompose it correctly if it's already working end-to-end.
The same applies to larger business. With microservices, ie. large banks can easily offer API services, enabling new revenue streams that were nearly impossible to offer before.
Microservices are an excellent way to deal with future changes. The unknown unknowns like some would put it.
The anecdote that comes with that:
I joined a startup as the second developer. The first developer built everything in a microservices architecture with the background that we were supposed to grow as a devteam significantly in the next 6 months. One of my first tasks was setting up CI/CD for the microservices so we can launch the product, which is a pretty routine setup for me since I've done the same thing ~5 times before. Then startup things happened and we stayed a 2 person team for a long long time.
In the beginning, I was skeptical if the microservice architecture was really the right choice there, but overall I think we came out ahead. There were a lot of instances where we needed to upgrade libraries to fix some bugs or get some newer features and only had to upgrade very little of the whole codebase, allowing us to iterate faster. This would not have been possible in a monolith. We also experienced some of the microservices downsides, like slower refactoring and network connections being less reliable than in-process function calls, but with the right approach and tools, they were not much of a problem.
Microservices are not a free lunch, but they can be a cheap and tasty one.
Where does this axiom stem from? A quick google search shows many instances of proclaiming the opposite.
Body cameras on police address a social problem.. If you're talking in absolute terms, such as something being the perfect solution that vanquishes an issue (i.e. a silver bullet) then I think it's a disingenuous stance to take. Social problems aren't solved overnight, and the greatest ones have always required incremental approaches.
This feels akin to saying, "I need code that's 100% bug-free", but in reality, writing bugless code isn't the goal.
For example: when a bank's retail locations are using different lending criteria than the corporate call center, there's no amount of code that will solve the turf war between corporate and retail.
However, there is that 5% that matters. In my opinion, one of the things that separates a good "architect" from "a really senior engineer with lots of responsibilities" is the ability to engage with the social and political implications of code design, and convert social concerns into lines of code. (This further reinforces the idea that architects must code, on the grounds that in general, this degree of understanding of a situation is not transferable. Especially to people who don't even believe these issues exist or are relevant to a design, which is quite a lot of even quite senior engineers.) The 5% is not equally distributed and a lot of it will concentrate on to the architects, so for instance I find myself thinking about this stuff a lot because of my position. But it's still the exception, it just happens that I get a lot of that exception.
Of that 5%, the vast majority of it relates to Conway's Law: "Organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations." I first encountered this in a list of funny jokes and such that had been knocking about since the old UNIX days, and at first I figured it was a joke too. Then as I grew more experienced, I thought it was a lament, in the style of "The first 90% takes 90% of the time. The remaining 10% takes 90% of the time." Now I understand it simply to be a law of software design. Like gravity, if you intend to defy it you'd better have a really solid story as to how you intend to avoid it. It is often much better to reorganize teams rather than fix this with code, but even optimal organizations of teams will still have a certain amount of Conway's Law issues, because the real world is messier than team structures should be. Plus engineers suggesting team reorganizations doesn't always go well; if nothing else you will confuse the heck out of your management even proposing it, like, "what are you doing thinking about that?". You may be forced as an architect to deal with suboptimal organizations anyhow.
And thus we wrap back around to microservices... once an organization hits a certain size, you are almost inevitably constrained to use microservices, because organizationally it is simply impossible to have 500 people working on "the same thing". You'll either use microservices, or a monolith that contains an ad-hoc, informally-specified, bug-ridden, slow implementation of microservices, even strictly de facto in the form of "this code belongs to this team, that code belongs to that team".
(The generic form of Greenspun's 10th rule is "Any sufficiently complicated program in a certain domain will inevitably be pushed towards certain solutions based on the domain, and if the designers attempt to resist that solution, that will simply result in an ad-hoc, informally-specified, bug-ridden, and slow implementation of those solutions." Or, in short, "use the right tool for the right job, even if you thing you don't like that tool.")
That metaphor isn't good here. You gain nothing by including network communication between those different pieces of code. The ad-hoc solution is often more formally specified, less bug-ridden, and faster than the microservices solution.
Microservices solve some technical problems, not social ones.
I consider the network aspect of the communication a bit of a side show here. What's important is the information flow. Even if you've got a monolith, you've got some components, and if you are taking such good "advantage" of your monolith that the communication flow between modules is not something that is clearly specifiable and understandable because of the global variables and shared state and shared everything else, what you've got there is a mess, not a beautiful shining example of architecture that obviates the need for microservices.
Or possibly, you've just got something too small for the microservices to be relevant. Which is totally a thing, and I totally agree with the various things that say "Don't write your startup as microservices".
But eventually as your size grows large enough, you will either end up with components so nicely separated that putting a network between them doesn't affect them all that much, or you will have a big ball of mud that nobody can move around anymore. If you don't have one of those, you just aren't large enough yet. Humans can not code the way biology tends to work; we need bite-sized chunks of a larger system to get our heads around.
When you add that network communication, you remove coherent type enforcement, timing restrictions, availability guarantees, causality guarantees, unicity guarantees, and likely more stuff that are just not on my mind right now. Those are all characteristics of the information flow.
It's tempting if you don't believe in Conway's Law to say "What's so hard about having everyone share authentication services? We'll just mandate that they have to use one service without having to create a separate structural team to do it." But it will not generally work.
One element that contributes to this is that the teams are not just technical, they are embedded in a company in a larger context. If you create product teams A, B, and C, the larger company will be grading the management of A, B, and C on the revenue they generate, or other appropriate metric. Thus, the management for those projects will tend to be very focused on that metric. If you tell each of them that they are responsible for authentication, they will each want to spend as little as possible on it because it is not a revenue generator. (Who has ever signed up for a service because its authentication was just so awesome?) They will each correctly come to the conclusion that the cheapest thing is just to bash something that vaguely resembles authentication into their own system, because the costs of coordinating between the three teams will be too large. So you really have to carve out this interest into a team that will be measured on the goals relevant to authentication, such as scalability and security rather than revenue.
Engineers are also constitutionally inclined to say "Well, the solution is just to stop measuring teams A, B, and C by revenue and instead measure them by..." but then it's somewhat hard to figure out what the next words are. "Code quality" is something engineers would love to say, but even engineers on some level tend to recognize that does not actually put food on the table, so to speak. (It is an important element of considerations of how to spend resources, and I would agree that it is often underestimated. But it makes no sense for it to be the prime measurement of a team's output, even before we get into the issues involved in objective measurement of code quality.) It's really hard to avoid having at least some of your development teams being measured directly in dollars in one form or another, and from there the rest of these forces tend to flow.
Why would merging two or more microservices be any more difficult than turning a monolith into several microservices?
I'm not implying one would be harder than the other. I'm really curious to understand the downsides of going each route.
It's time to stop hand-waving away the overhead of microservices. The two big reasons to introduce microservices are because you have different workload profiles that need to scale independently, or because you have separate teams with bounded areas of responsibility and you want them to operate independently and minimize communication overhead. I'll also give a pass for microservices where the interface is very obvious and stable, and there are low cross-cutting concerns.
But in a lot of cases devs are just complexifying things for their own resume and ego.
I wouldn't even go that far. The complexities of communications between network services simply escapes most devs who think in terms of features.
They see most of the issues as an ops problem that they can chuck over the wall. Many of them don't stay in one place too long, so they've not really hard to live with the consequences of their decisions.
The problem is, working with more buzzwords and moving about is the best way to further your career as a dev. Being a stable hand will likely result in you being underpaid and under valued, and at the end of the day most of us live in expensive cities and are quickly in our 30s where we want a family. Of course, we're going to chase the shiney that pays well.
Evolving enterprise systems is hard, being able to eliminate wait barriers between new dependencies being made available is a massive benefit to the wider release schedule.
You can release new functionality on your teams schedule and turn it on later when collaborating teams are ready. For various reasons enabling a feature is usually much easier than releasing a version bump.
1) never change data exchange formats between trivially connected parts of the application (e.g. splitting billing and delivery address in the payment system, no way you can do that easily with microservices)
2) effectively have 3 versions of every service running essentially constantly, and at the same time. This is more work than just running 3 versions : they must also be developed so they CAN run at the same time (e.g. they must tolerate the non-existence of a delivery address in the same example)
#2 i dont follow at all sorry
I've done a complex robotic system which had about ten processes running on QNX.
Most of them were running some microservice - GPS, INS, LIDAR, mapping, logging,
short-term vehicle control, etc. This worked fine. That's because QNX does interprocess communication well. MsgSend/MsgReceive is like making a subroutine call on the send side. The receive side is more like an event loop.
This sort of thing is common in robotics. ROS does something similar, although the interprocess communication is slower. Usually you have dummy services for simulation purposes, so you can run the operational code in a simulated environment. We could run the system for real, or run it entirely with simulated inputs and outputs, or could put the robot vehicle up on blocks and run the system with fake inputs while operating the real vehicle, engine running and wheels spinning but going nowhere.
Everything could be run on one desktop, or on the vehicle's own computers, or partially split. There were shell files to launch the various configurations. We could plug in shims between services and watch the data go by.
I don't see the fear of multiple intercommunicating processes. Even on Linux, there are decent ways to distribute. They're not as good at hard real time as QNX, but they work.
We're also talking about very, very large scale systems, like hundreds of API endpoints, not ten, with multiple on-call rotations, each assigned their own section of the microservices surface, running in front of customers at all times, without the engineering effort to make sure things are close to perfect before exposing to customers.
What happens here is a combinatorial explosion. 1 faulty service can end up affecting it and its transitive dependencies, but operationally, it's hard to distinguish symptom from cause. Worse, a problem on one team may be cause by an unmonitored problem two teams across the network, increasing time to resolution, as each on-call is woken up to discover the root cause is another layer up the network.
More efficient RPC doesn't solve any of this.
Out of interest: what would you consider to be some of those decent ways, and what are some of the less-than-decent ways?
Since scalability is probably a bigger concern in web architectures than robotics, expecting to be able to use IPC to communicate between two services is unlikely. I would imagine in many web architectures being able to scale systems independently and dynamically makes up for the overhead in communication protocols.
Erlang processes do this if I'm not mistaken.
Developers are forced to export public module functions to provide a smooth api for other services (processes, in the same runtime, or distributed).
Thankfully, Erlang provides the protocols and so on, instead of requiring some nasty hand-crafted json weirdness over http.
Forcing everything into the same abstraction can have issues. For instance, calling a different machine has orders of magnitude more overhead and different error scenarios than making a call to a local process. If you make them look identical, you obscure that.
This time around it's what ... 0MQ and Protobufs?
It is an old maxim in programming that correctly modeling the data is a huge percentage of the design. For example:
Pike's 5th Rule: Data dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming. - Rob Pike, Notes on C Programming (1989)
In that sense, in nontrivial problem spaces, if forced to generalize, then I am generally more for spending time carefully developing interfaces (ie. a paradigm potentially more closely aligned (in a network services context) with the microservices model = older coders with maintenance chops) than immediately writing actual code (ie. approach of the keyboard-happy iterative tweaker = young coder with fire-and-forget habit).
Any real world project lies somewhere between these extremes.
Because otherwise, how do you guarantee atomicity across module boundaries?
The more fundamental answer is: It depends upon questions such as whether the system seeks to exhibit parallel processing properties or not, and the application-specific data generation/processing/storage/retrieval/consistency goals.
The short answer is: Ideally you don't, because architecturally you are likely creating a monster.
The longer answer is that in the case that it is justified (and such cases do exist) you would generally either use a reference to a transaction (potentially knowing that it may be out of date and having a planned strategy for eventual consistency carefully limiting the effect of such to a non-critical scope), or eat the latency overheads and use an established algorithm - see https://en.wikipedia.org/wiki/Atomic_operation https://en.wikipedia.org/wiki/Consensus_(computer_science) and https://en.wikipedia.org/wiki/Consistency_model - which for most of us simply means 'choose your database/network replication layer carefully'.
What microservices actually work towards is a viable strategy towards the Two Pizza rule, where teams can be kings and queens of their kingdoms & drive their own agenda forward without needing to consult with everyone else working on the monolith. Containerizing your software allows containerizing your culture, keeps there from being ancient legacy top-down hierarchical culture and praxis set forth long ago and which will dwell ever on in the monolith your whole company must collectively lurchingly keep trying to push forward. Free yourself from the more brutal pieces of Conway's Law. Create an organization that can continue to try new ideas, that allows team's freedom to work without always bumping elbows with others.
At the end of a somewhat different thread amid these comments, gloverkcn happened upon a wonderful synopsis:
The problem is that it's easier to grab the people sitting next to design something than scheduling a meeting with groups you rarely see. This is a key driver of Conway's law.
Microservices & their platform infrastructure are the answer to make this not a problem, to free you from tight organizational grips of Conway's Law.
For small and new companies, technical and organizational structuring has not accrued. These are not major problems in early stages, because everything is small enough to be changed easily anyways. But as time goes on, as software or head count grows, maintaining the liberty to ongoingly innovate and pick up new ideas and new technologies is a liberty that has to be fought for. Making your way from a 1->many service organization comes with a lot of complexity and cost, but it is a key step to allowing diversity and innovation and technical growth, particularly for multi-department organizations.
I don't think the author disagrees with the goal of reducing dependencies or coupling between dev teams. What they disagree with is whether moving to microservices is necessary to achieve this. They think a "a monolith, composed of well-defined modules, with well-defined interfaces" can get you the upside without the downsides.
Trying to upgrade from Netty 3 -> Netty 4 (like Twitter Finagle had to do) in less than a big bang? Say hello to remarkable levels of pain and suffering one has to do, probably shading one's own Netty and pointing other dependent libraries at that shaded version. No matter how much decoupling you try to build into APIs within your monolith, trying to get the thing to build and ship together forces a co-interactivity of teams, coheres everyone to common technical underpinnings and which exposes all folk involved to any of the technical risk attempted by any one team. Decoupling may allow some modularity, some ability to replace X with Y, but it's will always have to be done within a common framing, a common framing that as the project grows will become immensely harder to un-stick and push forward, will be much more resistant to experimentation & great leaps forward.
Any software project has so much diversity and risk budget associated with it: a willingness to innovate technically that depletes with use. Even if you "decouple" you monolith, if everyone has to build and ship together you are going to forever be bound into deep interdependencies. Trying to update a logging framework or trying out a Reactive Functional Programming is going to encounter vastly more resistance when you're working on the same sandcastle as perhaps hundreds of other devs, dozens of other teams. And if it is low resistance? Well then you're in more trouble- your monolith grows boundlessly, with everyone being exposed to the rapidly growing risk and diversity that other teams experiment with.
Isolation, containerization, is a good defense. I think Conway would approve. Apologies, paragraphs above are a bit thought soupy- havent the time to edit.
When these kind of things are not defined, people may take good advice and apply it wrong way. You read articles how large companies are embracing micro services. However a "micro" for them might mean very much different thing than what is means for smaller company. Just like with "big data".
There are two kinds of scalability requirements. Some applications scale almost linearly with number of users, for example, Google Maps. That happens if users need interact with each other in limited ways. For such, horizontal scalability of a monolith is almost always a better answer than microservices, and splitting the data before processing is almost always better solution than Spark or Hadoop.
The second kind of scalability requirement is where the users interact, and so the processing required scales more than linearly (quadratically) with number of users. The examples are social networks, the more users you have, then you need to deliver quadratically more messages to all of them. In this case, microservices (and Spark and Hadoop) are probably better, since you can't solve the problem just by scaling the monolith horizontally.
This would be scaling vertically since your only option is to increase the resources dedicated to that single application instance (more CPU, RAM, Disk, etc). The definition of a monolith is a single application running on a single platform so scaling a true monolithic application horizontally (adding more instances of the application) is not usually possible.
What I mean is that you can e.g. run two monoliths on two machines, and process half of your users at the 1st machine, and the 2nd half of your users at the 2nd machine. If the users don't need to interact (or in a limited way, for instance, you need to recalculate something each day or so), it's a good enough solution just using horizontal scaling.
"Micro" is a meaningless prefix. This is all SOA - service oriented architecture. A "service" can be anything, it's a vague definition of whatever is a natural encapsulation of a bit of logic in your application (or company). This encapsulation can be easily done with separate classes, namespaces, or even packages, while still running together in the same process.
In the end, you're putting some binaries on a server. The machine doesn't care how often you do that or how many different binaries you choose to use, so the only real reasons are multiple languages that aren't compatible in the same process or massive apps/organizations that need to have completely separate projects to make forward progress.
For everything else, microservices are a silly solution to no actual problem.
It is not. Not even close.
You have to manage separate onboarding processes, ensure the standards are completely up to date, ensure that training is extremely relevant and covers every single critical component of the system.
You have to maintain up to date documentation of integration state, data flow, testing capabilities, etc.
> You can bring an extra hand into the team without them having to have to understand other parts of the code to do their job.
That sounds awful.
> won't allow you for example to place each service under its own repo which would also provide you with the ability to limit code access
Let me guess, you are not paying for engineering talent? The notion of having distributed teams for most of the companies is so ridiculous it's not even funny.
What happens if a lead person on team X and Y quits? Are you going to retain a full-time person to manage your deployment process now?
What happens if your budget is cut in half and you need to fire half of the team? Do you expect other engineers to pick up something they have not touched for the duration of their stay without slowing down business?
> That requires a lot more up-front investment, but it's worth it over the long run
None of that is true.
"One of the fundamental concepts to remember is that microservices architecture is a share-as-little-as-possible architecture pattern that places a heavy emphasis on the concept of a bounded context, whereas SOA is a share-as-much-as-possible architecture pattern that places heavy emphasis on abstraction and business functionality reuse."
I can't decide if the author actually has a problem with an appropriately deployed microservice architecture (and no, you do not need 100 engineers to support such a thing... I replaced a legacy back-end system for a $100M/yr revenue company with such an architecture using 4 devs) or if this is just a misapplied generic rant about cargo culting that has been applied to $THINGIREADABOUTTODAY.
I don't have any preference for or against microservices, as long as the benefits they bring outweigh the drawbacks which come along with such an approach.
The goal wasn't so much to rant against cargo culting, but to provide some counter points along with a more measured progression for moving towards microservices.
I agree that the points at the end should be what such a transition looks like, but it's amazing how often companies skip the first two steps and try to immediately break up their monolith as a form of technical bankruptcy, which is rarely warranted.
Thank you again for the comments!
In a traditional sense, we are implementing a system in Django that will be deployed to AWS lambda via Zappa or SAM. All, the traditional task-queue tasks will be separate microservices (lambda). So, We are implementing fusion and I personally see future in that.
One of our customers are developing a service, which in turn consist of four minor services. They are completely separate services, one provide the core functionality and the rest a supporting tools, but the core can run without them. To me that's a completely reasonable seperation, and it allows multiple teams to work in parallel.
One of the "services" above however consist of 10 to 15 smaller services, all of which are communicating via http. The idea as I understand it is that these are small components that can be reused in other projects, if needed. What I don't understand is why these aren't just made into library that can be reused, rather than having them as micro-services.
This project is an example of where microservices is done both right and wrong.
Also, there are cases where microservices would make sense even with one person on the tech team. For instance if you want to scale services independently of each other. For example, your web app isn't used that much, but you get heavy traffic on the mobile API. In that case, maybe having the mobile API as a separate service helps.
That's where the discussion should start. Better yet if that is a business problem, then dive into technical solutions. Many times technologists take a new (but not really) silver bullet and try to fit it in somewhere without understanding if it solves a problem or not.
It also seems like we like to reskin solutions with new names and the industry picks up on this, starts their marketing engines and the guys in suits come around trying to sell the new silver bullet.
Personally, the microservice-y project I'm currently working on makes me want to burn my face off every day.
edit: that even sounds like business opportunity.
See Erlang and theorems also proven for clique networks.
Erlang (OTP?) comes to mind (though I have very little experience with it so I could be off)
If you make a component that is the sole entrypoint to it's concerns, gets it's own database, and have an ORM or database context layer that is capable of dealing with that,
moving to a microservice is as simple as taking that same code, exposing an http layer to it, and making your original interface call to the service instead.
If other code is joining into the relevant tables, skipping said interface and doing it's own thing with the guts of it, you'll have issues.
This can of course be done in any language, really, though database tooling can definitely vary in ease of doing it
If you are thinking about migrating to microservices at some point, it's also beneficial to try to limit the areas of the database schema that each of these pieces accesses. There's no point having lots of microservices running over the top of a single monolithic database schema: extracting microservices should imply extracting the relevant part of the database schema and putting it into a private database with operational access only through the microservice. You can make this much easier while still working in a monolithic application by being more disciplined about how much of the schema a piece of the application needs to know about.
Ruby has its own kind of "modules":
Does anyone know of some good (modern) examples of monoliths that adhere to these, and other, principles?
"The Unix philosophy emphasizes building simple, short, clear, modular, and extensible code that can be easily maintained and repurposed by developers other than its creators. The Unix philosophy favors composability as opposed to monolithic design."
Which is a lot more akin to what's now called microservices. Unix philosophy has always been about software modularity and do we really need to use 'microservices' these days to describe such an approach? The meaning is not clearly defined anyway, what one company describes as a microservice architecture might not be described as such by another. I certainly don't need any buzzwords (e.g. re-invented terminology) to describe a modular software system, and whether your processes IPC mechanism is HTTP/JSON, pipes, or sockets, we are talking about exactly the same kind of system.
With microservices you have the ability to take one service and fix it, reimplement it or replace it if necessary. Also use whatever technology makes more sense for that project, as long as it speaks the same protocols and sticks to the same interfaces.
With monoliths, there's always the analysis paralysis related to the possible ramifications of a change, which slows down everything.
Developers could be tasked with working on these libraries that would have 0% overhead (since they are just a piece of code that can be used in another library), instead of creating REST/SOAP/RPC APIs that come with the HTTP/SOAP/RPC overhead.
This means you can start small, with a public REST/SOAP/RPC API. Less infrastructure, less server config, etc. And if at some point you need more scalability, you can always do an actual microservice (ie a separate REST/SOAP/RPC API) with the library code the day you absolutely need it for horizontal scalability or whatever.
I have seen this pattern used in the Rust world a lot. Projects expose both a library and a binary. And the binary is built on top of the library. This means you have 0 overhead if you want to use the binary's features, since you can simply include the library and get going.
Also, I think that having the tools to support deprecation is big advantage when working with a monolith. I think Rust has built-in support for compile-time deprecation notices. PHP, for instance, doesn't have that particular feature yet, as far as I know. Symfony tries its best by adding deprecation notices when you call a deprecated method/function. But you have to call it to realize it's deprecated.
I'm not here to promote Rust or hurt PHP, I actually love both. The statements above apply to a lot of other languages as well. I just took the examples of Rust and PHP because these are the ones I've worked with the most.
@xxs's comment is spot on as well.
Microservices are a way of achieving this, but as you describe it, is not the only way. Discipline is another way.
Now, as you have more people involved, or release deadlines get tighter, chances that tech debt gets introduced increase. Unless you go back and repay the tech debt, situation would worsen.
In that sense, microservices are some sort of cap on the impact of tech debt from rushed deadlines and lack of discipline.
I agree that microservices tend to make it harder to accrue tech debt past a certain point, though. Although they can also dramatically complexify the process of figuring out what is going on in an app if log files are spread around a ton of places (which is mainly a tooling problem).
I'm not saying that it's an unsolvable, or even unusually difficult problem, I'm just saying that it's very possible to do wrong. If an organization can fill a monolith with tech debt, they can probably find a way to do the same with microservices.
Any interpreted language will have this problem anyway.
Not to take away anything from your comment, just nitpicking.
The worst kind of technical debt is usually about having the service boundary in the wrong place and crappy APIs. With microservices this problem is amplified. It's harder to unpick a service than it is a module.
If you've ever tried debugging a problem across a series of microservices as well, you'll wish you hadn't...
You can do that inside a monolith too. Microservice as a solution points to architectural problems, we try to build systems that are too vertical, our architecture should be horizontal. Microservices enforce this horizontalness, but it's not the only way to achieve it.
I haven't seen a configuration of teams that doesn't screw up the monolith by creating "spaghetti" dependencies between the pieces. Hence making the transition to microservices a multi year journey.
And that, coincidentally, is also what you need to not write spaghetti service interactions.
So I am in your boat that every single screwed up, beyond repair project has been a monolith. And always because a small handful of developers decided at some point to cross a logical boundary and introduce spaghetti-like dependencies.
This is just false, there are pull requests, reviews and all. Morealso there are modules and just because you can deploy the 'monolith' as a single process and use shared memory doesn't mean you can't add/remove parts or have to compile all at once.
Analogy with microservices - your login service is borked. The rest of your site is kind of useless even if perfectly operational.
And in the Java world at least modules aren't real. They are purely logical constructs that developers can work around by importing from packages in other modules. And creating the spaghetti code problem again.
And in the Java world at least modules aren't real. The statement shows lack of understanding how modules should be utilized (it has very little to do with packages). Interfaces (can) do exactly the same what protocols in microservices do. Enforcing that might be harder but facades/proxies ensure there would be no (feasible) way to bypass. There is no substitute for good data models/responsibility.
Or, a bit dirtier solution - a commit was made with an explicit request for a closer review from the rest of the team.
The mental overhead of that is HUGE. Every new bit of functionality you have to figure out how this microservice was built? Opening a microservice and learning what developer X did with developer Y's "I don't understand functional, but I'm damn well going to use it, and wouldn't it be great to build this in the Zebeedeee framework that trended on HN two weeks ago and then mysteriously disappeared forever".
Bad programmers are going to muck up microservices even worse than they're going to muck up monoliths.
At least with monoliths they might actually reuse some code rather than cut and paste it from the last microservice they worked on.
And if you find scaling microservices harder than a giant stateful monolith well then clearly you've done something wrong.
Likewise local development should be far easier if you define your APIs and contract boundaries properly.
Monoliths don't have to be stateful anymore than a microservice does. Stop arguing against strawmen. This is why this topic is maddening.
I searched the article for "domain" and "bounded contexts", found nothing. Article is not without merit, however; Sam Newman in his book  cautions about going too aggressive, i.e. splitting down into too many microservices before the domain is fully understood. On the other hand, having systems cross obvious domains is a definite warning sign (of disaster).
So the motto might be, use them, but in moderation (as with a lot of things).