In the cloud computing era, application development moves far faster, and microservices is a big factor in this increased speed. Yet it is only with a clear plan for microservices best practices that companies attain the greatest efficiency boost.
Microservices are, simply put, large applications broken down into smaller, individual functions for more rapid revision and scalability. Microservices are used primarily in the cloud-based online world. A banking app, for instance, can be broken down into the various features: login, balance checking, and bill pay. These various features can then be revised at different times, instead of needing to rewrite the entire app all at once.
Microservices and containers are a natural combination. Microservices lend themselves well to a containerized environment, since all of the software components—code, runtime, system tools, system libraries, and settings—can be confined to a container. However, containers are not necessary to run microservices.
List of Microservices Best Practices
So what are some of the best practices to maximize your microservices architecture? Here they are:
• Team autonomy: Rather than a large team divvying up the work of a large app, assign small teams to work in parallel to focus on just their microservice and not be dependent on the work of others.
• Scalability: Smaller components require fewer resources and can be scaled to meet increasing demand for just that microservice. Plan accordingly.
• Revise your schedule: Because the overall scope for the team is much smaller, with focus on one feature or function, work can be completed much faster than in a monolithic environment.
• Automation: Because they work well with orchestration containers like Kubernetes and Docker, the deployment and updating of microservices can be easily automated and handled by the orchestrator. So a developer won’t always be needed.
• Flexibility: Microservices offer greater flexibility by allowing groups to work independent of each other, and therefore, they can innovate at their own pace rather than wait for other changes to take place. But make sure the teams are communicating with one another.
• Resilience: If a microservice crashes, it doesn’t take down all the other components like one bug would do to a monolithic app. Just spin up a new instance of the microservice and start debugging.
• Maintenance: Devote fewer resources here. It’s a lot easier for a team to maintain 10,000 lines of code than one million lines of code.
• Properly scoped functionality: In the process of breaking up a monolithic app into microservices, you must clearly define the scope and function of each service so as not to make it too big or too small.
• Presenting an API: APIs are a portion of a microservice – a login API for a login service, for example – so the service can be the wrapper for an API.
• Traffic management: Microservices are distributed by nature, so traffic management is a must to avoid overloading and bottlenecks.
• Data offloading: The converse of traffic management, data needs to be balanced among the services to avoid server or network overload
• Monitoring: You must be in a constant state of monitoring, because microservices are meant to be used as scale out apps to handle usage spikes. Monitoring helps determine if more or less resources are needed, spot errors in new code, and watch the status of your network.
• Development and deployment: Microservices work well in the continuous iteration/continuous delivery methodology of DevOps, much more so than giant applications. Also, your chances to break things increase with complexity. The small size of a microservice reduces the chance for something to go wrong, and the smaller code bases make it much easier to isolate and detect problems.
• Private Data Ownership: Each microservice can have its own database, and they can either communicate with each other or be isolated. This allows for greater security by isolating the most sensitive of data from less secure apps.
Related Key Issues with Using Microservices
1) Ask yourself why you are doing it.
This seems to happen with every new tech paradigm. People rush to embrace it because everyone else is doing it without asking why do they even need it. If you have a modest Web-facing presence and your enterprise apps are primarily inward-facing, you don’t need much for microservices and are better off with SOA.
If, however, you want faster response time to make changes, and to take advantage of the cloud, public or private, then microservices might be a better fit.
2) Understand what they are.
There are several reports out that delve deep into the differences between SOA and microservices. Know what a microservice actually is and the changes it will introduce to your network and your data.
3) Learn to distribute your code.
This is a big change that comes with microservices. Before, with a monolithic app, you had one process. Now you have many. That means adopting some form of distributed computing to distribute the load, which is hard to do right. You may want to containerize the services and other forms of load balancing, and if this is new to you, that’s part of the learning curve.
4) Insure coexistence and documentation.
The lure of microservices is that they can all be done independent of each other. That’s also a potential pitfall. Part of the testing should also insure that the services all work together and don’t crash each other, and make sure everything is well-documented. A small team is a familiar team but change is constant and new people need to be able to come up to speed quickly.
5) Adopt AI.
To err is human. And humans need a rest. Artificial Intelligence needs no time off. Utilizing AI to monitor and respond can bring much faster responses to problems that will inevitably crop up. Done right, AI can maximize efficiency of microservices in a way humans cannot.
No technology is bulletproof, microservices included. This technology has pitfalls, shortcomings, and other issues you must be aware of to avoid wasted time and resources.
• Watch the scale. Just because they are small doesn’t mean they can’t add up as you add more microservices. This is a distributed network so you must make sure to balance the load carefully and make sure all of the services you are adding can scale.
• New logging needed: Traditional logging is ineffective because microservices are stateless, distributed and independent, so each service would produce its own log and not know of problems in another service. A new form of coordination is needed.
• It’s all so new: Microservices platforms are still a work in progress. Shop around.
• Where’s the problem? Tracing performance problems across distributed tiers for a single transaction can be difficult with the nature of the app and your network.
• Infrastructure concerns: The structure of your network will play a much more significant role, since the work is distributed. This means making sure your network is well-balanced, and that your development teams work with operations to make sure one team doesn’t surprise the other.
• Keeping the languages straight: You can use a wide variety of languages in a microservices environment, so you must make sure you are all on the same page with coding languages and don’t end up in a situation where 20 services are written in eight different languages.
• Security is critical: Likewise, you must settle on a security model for all services because many services present more targets for hackers.
• Failover: A distributed network must have solid failover, so when something inevitably crashes, another portion of the network can pick up the slack.