We all may face issues with databases. They can be slow, unreliable, or can break shortly after deployments. This can directly affect our business and degrade customer experience. No surprise that we want to fix these issues as soon as possible.
What if we could avoid all of that? What if we could make our databases self-heal and fix the issues automatically? Or even better, what if we could prevent these issues altogether? Read on to see how Metis can help your databases never fail and fix the issues automatically.
Turn Monitoring Into Observability
Database monitoring is not enough to troubleshoot issues. Swamping developers with data points and unreadable charts doesn’t bring them closer to solving the problems. The issue with data is that we don’t see the solutions. We see that the CPU usage went up or there is less free memory available, but we don’t see what caused the issue and how to fix it.
What we need is observability. We need to turn metrics into facts and correlations. It’s not enough to see the CPU usage. We also need to see what has been deployed recently, what changes were introduced, which queries were affected, how was database configuration modified, and many more details about the process. We need to see these facts presented together to reason about the issues easily.
Recommended reading: Observability vs Monitoring - Key Differences & How They Pair
Metis gives you exactly that. Metis integrates with your CI/CD pipelines and analyzes performance. Metis can reason about your schema migrations, configuration changes, extensions, and deployments. This way you can see all things together. Metis shows you what is important across your ecosystem.
Get Solutions Instead of Data Points
Capturing data points and facts is just the first step. The next thing is turning data points into a comprehensive story explaining where the issues come from. Maybe the CPU usage is caused by an inefficient extension? Maybe it’s because of the recent code changes. Or maybe it’s due to different data distribution coming to our application. There may be many reasons why the system is now overloaded.
To do that, we need to understand how databases work. We need systems that can reason about the database internals and draw meaningful conclusions. This includes understanding query execution plans, statistics, internals of indexes, data structures, and routine database tasks. All of that should be analyzed automatically and presented to developers in a way that lets them take action.
Metis covers all these aspects. Thanks to its reasoning module, Metis builds a comprehensive picture of the ecosystem of the database and everything that happens around it. This includes:
- Understanding changes introduced by developers by analyzing them in their environments, in the CI/CD pipelines, and during deployments
- Capturing configurations, extensions, schemas, statistics, and schedules of routine tasks running in the database
- Detecting anomalies in infrastructure, OS, and database metrics
- Identifying changes in the execution and where they come from
All these areas let Metis reason about the changes and explain how to fix the issues. This way, Metis can explain that the CPU spiked because last week’s code change caused a query to not use the index anymore. The solution is to drop the old index and create a new one. This way Metis gives developers actionable solutions they can apply immediately.
Recommended reading: 3 Things Database Reliability Is Not About And How Metis Brings Observability
Connect The Dots And Fix Issues Automatically
Once we have all the solutions, there is no reason to do manual steps anymore. Just like with CI/CD, we want to automate as much as possible. We want to automate everything around databases to decrease the risk of breaking things. Since all the manual steps are error-prone, we want to avoid them entirely. Also, automation is the key to performance.
Metis gives developers all of that. Since Metis knows everything about the database activity and changes in the ecosystem, it can suggest improvements and apply them automatically or nearly automatically. Metis can suggest code improvements, and configuration changes, submit pull requests with fixes, or tune things automatically. This way, developers only need to approve the changes to have the issues fixed or prevented altogether. Effectively, all the troubleshooting around database issues is automated and databases can self-heal themselves.
Use Metis And Have Your Databases Self-Heal
Many things can break when we move fast in production. Monitoring solutions are not enough as they just swamp developers with data points. Metis takes it one step further and turns data points into comprehensive stories. This way, Metis can provide solutions and even automate fixes. Even if something breaks, Metis can fix the issues without waiting for the developers to step in. This turns databases into self-healing systems that can survive unexpected situations and react to changes around them.
