Microservices: Size Doesn't Matter, Reliability Does
Posted by bsstahl on 2023-02-20 and Filed Under: development
There are conflicting opinions among architects about how many microservices a distributed system should have, and the size of those services. Some may say that a particular design has too many microservices, and that it should be consolidated into fewer, larger services to reduce deployment and operational complexity. Others may say that the same design doesn't have enough microservices, and that it should be broken-down into smaller, more granular services to reduce code complexity and improve team agility. Aside from the always true and rarely helpful "it depends...", is there good guidance on the subject?
The truth is, the number and size of microservices is not a measure of quality or performance unto itself, it is a design decision based on one primary characteristic, Reliability. As such, there is a simple rule guiding the creation of services, but it isn't based on the size or quantity of services. The rule is based entirely on how much work a service does.
After security, reliability is the most important attribute of any system, because it affects the satisfaction of both the users and developers, as well as the productivity and agility of the development and support teams. A reliable system has the following characteristics:
- It performs its duties as expected
- It has minimal failures where it has to report to the user that it is unable to perform its duties
- It has minimal downtime when it cannot be reached and opportunities may be lost
- It recovers itself automatically when outages do occur, without data loss
Having reliable systems means that your support engineers won't be constantly woken-up in the middle of the night to deal with outages, and your customers will remain satisfied with the quality of the product.
How do we build reliable systems with microservices?
The key to building reliable systems using microservices is to follow one simple rule: avoid dual-writes. A dual-write is when a service makes more than one change to system state within an execution context. Dual-writes are the enemy of reliability, because they create the risk of inconsistency, data loss, and data corruption.
For example, a web API that updates a database and sends a message to a queue during the execution of a single web request is performing a dual-write since it is making two different changes to the state of the system, and both of the changes are expected to occur reliably. If one of the writes succeeds and the other fails, the system state becomes out of sync and system behavior becomes unpredictable. The errors created when these types of failures occur are often hard to find and remediate because they can present very differently depending on the part of the process being executed when the failure happened.
The best-practice is to allow microservices to perform idempotent operations like database reads as often as they need, but to only write data once. An atomic update to a database is an example of such a write, regardless of how many tables or collections are updated during that process. In this way, we can keep the state of each service consistent, and the system behavior deterministic. If the process fails even part-way through, we know how to recover, and can often do it automatically.
Building this type of system does require a change in how we design our services. In the past, it was very common for us to make multiple changes to a system's state, especially inside a monolithic application. To remain reliable, we need to leverage tools like Change Data Capture (CDC), which is available in most modern database systems, or the Transactional Outbox Pattern so that we can write our data once, and have that update trigger other activities downstream.
Since microservices are sized to avoid dual-writes, the number of microservices in a system is determined by what they do and how they interact. The number of microservices is not a fixed or arbitrary number, but a result of the system design and the business needs. By following the rule of avoiding dual-writes, you can size your microservices appropriately, and achieve a system that is scalable and adaptable, but most of all, reliable. Of course, this practice alone will not guarantee the reliability of your systems, but it will make reliability possible, and is the best guideline I've found for sizing microservices.
For more detail on how to avoid the Dual-Writes Anti-Pattern, please see my article from December 2022 on The Execution Context.
Barry S. Stahl (he/him/his) - Barry is a .NET Software Engineer who has been creating business solutions for enterprise customers since the mid 1980s. Barry is also an Election Integrity Activist, baseball and hockey fan, husband of one genius and father of another, and a 40 year resident of Phoenix Arizona USA. When Barry is not traveling around the world to speak at Conferences, Code Camps and User Groups or to participate in GiveCamp events, he spends his days as a Solution Architect for Carvana in Tempe AZ and his nights thinking about the next AZGiveCamp event where software creators come together to build websites and apps for some great non-profit organizations.