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This is a short summary of my recent experiences with customers implementing architectures similar to microservices but with different characteristics in the post-microservices world.
The microservices architectural style has been around close to five years now, and much has been said and written about it. Today, I see teams deciding not to follow strictly certain principles of the "pure" microservices architecture and breaking some of the "rules". Teams are now more informed about pros and cons of microservices and take context driven decisions respecting team experience, organizational boundaries and accepting the fact that not every company is Netflix. Below are some examples I see in my recent microservices gigs.
No premium in advance
Teams (composed of devs, ops, testers, business analysts, architects, etc) are becoming more and more aware of on the premium they have to pay for the privilege of going into pure microservices based architecture. A typical Java based microservice running on Kubernetes (the most popular microservices platform) will require: a git repository, maven module, a collection of tests (unit, integration, acceptance), APIs, maven artifacts, container images, configurations, secure configurations, build pipelines, design, documentation, etc. At runtime, it will require CPU, memory, disk, networking, metrics aggregation, log aggregation, database, endpoints, service mesh proxy side car, etc. Also a collection of Kubernetes objects: container, volume, configmap, secret, pod, service, replica set, deployment, etc. Navigating and managing tens or hundreds of these artifacts puts a serious burden on everybody in a team. No surprise that recently Thoughtworks announced they are not intending to put microservices architecture into adopting phase of their technology radar in a foreseeable future.Raison d'être
Considering there is a price per service (not envisaging all the hidden premium), rather than the original "start small, start with few hundred lines of code", systems start as one service, as a mono repository as long as it belongs to one team. Then for every service, there is a clearly identified reason with benefits justifying its existence as an independent microservice. That is a mandatory existence check before carving a service as a standalone. Talking about reasons, below are a few very valid reasons.Breaking the bounded context
While the most talked method for decomposition into microservices is decomposition by bounded context, in practice there are many more reasons for creating microservices: decomposing by maturity, decomposing by data-access pattern (read vs write), decomposition by data source (rather than partitioning a data source per microservice, create a microservice per data source), aggregation for a derived functionality (create an orchestrating service for a few other services), aggregation for client convenience (such as backend for frontend pattern), aggregation to aid system performance, etc.Shared data sources
One of the fundamental principles of microservices is that every service has a separate data store. While in theory, this principles makes perfect sense, in practice, for brownfield projects, it is the hardest part about microservices, and not always worth the effort. That is especially true for integration projects where the data source is typically owned by a different team or company and cannot be partitioned to start with. It is still possible to benefit from having independent services sharing the same data store, by acknowledging its future constraints caused by the data source level coupling.Less inflated expectations
The good news is that teams are now making more informed decisions rather than blindly trusting microservices conference slides. In regards to Gartner's Hype cycle, that means, after a couple of years of "Inflated Expectations", the microservices architecture is heading (down) towards "Trough of Disillusionment" stage where expectations are more aligned with the real benefits.Hype cycle |
Mutated microservices
Microservices favor event-driven interactions and choreography over orchestration to decrease service coupling. But at the same time we have seen projects like Cadence by Uber, Conductor by Netflix created specifically to orchestrate distributed long-running services as an alternative of the choreography approach.Bernd Ruecker has done a very good review of using events, orchestration and workflow engines in distributed system and analysing their real against perceived benefits.
In a different post titled Microservices in a Post-Kubernetes Era, I also described what are the changes in the microservices architectural style driven purely by Kubernetes and the cloud native primitives.
There are also others who also wrote about non-microservices architectures such as self-contained systems, miniservices, goodbye-microservices that are better alternatives to pure microservices in certain contexts. These are all good reasons for breaking away from pure microservices principles whenever the context requires it.
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