Essential Strategies for Upgrading Microservices Without Downtime

In the fast-paced world of software development, it’s not uncommon for systems to be quickly built, deployed, and left unsupported. Often, a “rockstar developer” writes code to meet immediate business needs, deploys it to production, and moves on without adding tests or planning for long-term maintenance. The business is thrilled with the results, and the developer earns accolades, but maintaining that code becomes a significant challenge.

Fast forward a few years, and you’re faced with a critical update. Let’s say your cloud provider announces they’ll soon deprecate a key feature, like MySQL support for a specific version. All of a sudden, an essential service to your business — let’s call it Flibblenator 3000 — risks catastrophic failure if no action is taken. At this point, options seem limited:

1. Panic.
2. Leave the problem for someone else.
3. Rewrite the service from scratch.
4. Incrementally improve and update the existing code.

If you’ve been in software long enough, you know rewriting from scratch is tempting. But let’s be honest — it rarely ends well. So how do we tackle these upgrades without creating a bigger mess?

The Yak Shaving Dilemma

Legacy code upgrades often involve a bunch of dependencies. For example, upgrading a Java-based microservice might require:

1. Updating the database library to support a newer version of MySQL.
2. Discovering that the library needs a newer version of Java.
3. Learning that the newer Java version requires an updated Spring Boot version
4. Fixing compilation errors, test failures, and runtime issues caused by the Spring Boot upgrade.
5. Dealing with Docker and OS compatibility issues when deploying.

And just like that, you’re off on a classic yak-shaving adventure — one upgrade leading to another until you wonder how you ended up debugging Docker when all you wanted was a MySQL update. However, with the right preparation and tools, these challenges can be manageable. 

The Value of Preparation

The aforementioned example is a real-life situation of this all-too-common challenge. The previous developers managing the service left my team with a well-tested and monitored codebase. This included:

• A comprehensive test suite following the test pyramid (unit tests, integration tests, and acceptance tests). 
• Production monitoring and alerts to detect issues early.

Thanks to these safeguards, even this outdated system was stable enough to upgrade incrementally — without introducing major risks.

Our Approach: Incremental Updates 

Rather than attempting a complete rewrite, the team focused on small, manageable changes. Here’s how:

1. Upgrade step-by-step: We started by upgrading Spring Boot one minor version at a time, ensuring compatibility before moving to the next step.
2. Run tests frequently: After each change, we ran unit, integration, and acceptance tests to catch issues early.
3. Frequent commits and deployments: Changes were committed to version control and deployed as soon as they passed testing. Smaller deployments reduced the risk of large scale issues.
4. Leverage CI/CD pipelines: Automated pipelines allowed us to quickly roll back deployments if issues arose.

Even with these safeguards, some issues only appeared in production. However, monitoring and rollback capabilities allowed us to resolve these quickly with minimal disruption.

The Importance of Keeping Software Up to Date

Ignoring updates might seem harmless — until it isn’t. One day, your stack is "working fine." Next, you’re facing a breaking change that derails everything. Here’s what happens when you let things slide:

• Time-consuming upgrades: Upgrading legacy systems is never just an upgrade. It’s a scavenger hunt where every clue leads to another broken dependency, until suddenly you’re knee-deep in error logs wondering how you got here.
• Unplanned work: What starts as a "we’ll get to it eventually" task quickly turns into a full-blown emergency. One day, everything’s fine. The next, a critical security patch or a decommissioned service pulls the rug out from under your roadmap, and suddenly your team is scrambling to fix something they didn’t plan for — while your feature deadlines stare at you in disappointment. 
• Security vulnerabilities: Outdated dependencies are like leaving your front door unlocked in a neighborhood full of hackers. You might be fine for a while — until you’re not. High-profile incidents like Log4Shell prove that vulnerabilities don’t just impact the obvious parts of your stack; they can be lurking in the most mundane places, waiting for an attacker to find them first.

Tips for Managing Software Modernization

Now that it’s clear why it’s important to keep our software up to date, how do you do it?

1. Automate dependency management: Tools like Renovate Bot, Dependabot, and Snyk can identify and automate dependency updates, streamlining maintenance. 
2. Use specialized tools: Tools like OpenRewrite provide migration recipes for updating frameworks like Java or Spring Boot. While not foolproof, they can save significant effort. 
3. Dedicate time for maintenance: Adopt policies like the 80/20 rule, where 20% of development time is reserved for addressing technical debt. Initiatives like “Fix-it Friday” can make regular maintenance part of the culture.
4. Leverage IDE features: Use tools like IntelliJ’s dependency analyzer to identify version conflicts and transitive dependencies that may cause subtle bugs. 
5. Adopt compatibility modes: Many frameworks offer fallback modes for legacy components. For example, JUnit 5 includes a “vintage” mode to support JUnit 4 tests, easing transitions.
6. Invest in tests and monitoring: A solid suite of tests (unit, integration, and acceptance) means confidence during updates. Monitoring tools provide critical insights post-deployment. 
7. Perform incremental updates: Keep changes small and frequent, deploying updates regularly to minimize risk and simplify troubleshooting.
8. Make reliability visible: Use service-level objectives (SLOs) to highlight reliability issues caused by outdated components. This visibility can help prioritize fixes. 

Conclusion

Although rewriting legacy systems can be tempting, incremental updates often provide greater value by delivering continuous improvements with less risk. By maintaining a culture of regular updates and embracing small, manageable changes, teams can avoid the pitfalls of outdated software and keep systems reliable, secure, and scalable.

Keeping software up to date isn’t glamorous, but it’s better than being forced into an all-hands-on-deck scramble. A little maintenance now beats yak shaving later — so grab those clippers and stay ahead of the mess.