Today’s modern architecture is complex. We may run multi-tenant applications that may span hundreds of clusters and databases. Keeping track is hard, and we may have a hard time understanding what’s deployed where, what’s yet in the pipelines, and what is going to happen soon. To tame the complexity, we may want to build processes that let us navigate around all the moving parts. This includes pipelines, on-call rotations, monitoring, observability, alerts, metrics, and dashboards.
Despite these efforts, database operations can still be a headache. Even though we have all these pieces in place, we may still struggle to run things smoothly. We may deploy faulty code to production, we may run schema migrations that take our databases down, and we may get surprised by changing data distributions. What if we could avoid all of that? What if developers could have confidence their changes won’t break production, and all the problems could be identified even before we commit the code to the repository? What if we didn’t need to set alarms and alerts, but we would have everything automated instead? Read on to see how to reduce MTTR, automate operations, and achieve continuous database reliability.
Software Development Aspects Leading to Database Headaches
Many things may break. First, developers need to implement intricate queries and often prioritize the accuracy of their business logic over other aspects. Developers’ focus remains primarily on verifying if queries produce correct results or appropriately store data, neglecting to assess query performance. This leads to numerous issues. Inefficient queries may emerge, lacking index utilization, reading excessive data, or inefficiently filtering using sargable arguments. Object-Relational Mapping (ORM) libraries may retrieve data lazily with N+1 queries. We may even accidentally break performance by refactoring the code to use more readable solutions like Common Table Expressions which are less efficient.
Recommended reading: Query Optimization Techniques For Top Database Performance
Next, our testing procedures miss many issues. Let’s take schema migrations. While adding columns or modifying indexes seems straightforward, migrations can be time-consuming, potentially leading to hours of downtime when executed on production databases. We won’t notice the problems in non-production environments because we use small databases and we don’t project how changes will work in production.
Then, we try to analyze the performance with stress testing our applications. Load tests are slow, expensive, and happen way too late in the pipeline. We need to anonymize the data from production, handle stateful changes, spin up new hardware on the side, and run the load tests for hours. Even worse, when we find issues during load tests, it’s already very late to fix them. We already wrote the code, reviewed it within the team, merged it, and pushed it through the pipelines. To fix it, we need to start from scratch which makes it very slow and expensive.
Moving forward, once we deploy to production, we need to keep the solutions reliable. We use metrics to identify problems, and we configure alarms to be notified whenever things break. However, we need to manually prepare alarms and tune them based on actual business conditions. We won’t get notified about issues if we don’t implement specific alerts for that manually. This is slow, tedious, and requires our constant attention.
We would like to change that. We need to increase the velocity and performance of our processes. We need to reduce MTTR and get actionable insights instead of raw alerts and metrics. Our DevOps teams need to move faster and deliver more in a shorter time. Our developers need to feel confident when implementing and deploying changes. We need to avoid rollbacks and decrease the number of issues. Let’s see how to achieve smooth operations and say goodbye to database headaches.
Let’s See How to Make Dreams Come True
Our goal should be to help our developers. We need to give developers tools that can review their database-related changes and give actionable insights right when developers are implementing the changes. These tools need to analyze queries and schema migrations and need to integrate with developers’ environments to work even before any code is committed. These tools need to work regardless of the programming language or the database we use. We want to do that to increase velocity, reduce the number of bugs we find, and make the development processes run faster.
We should help our DevOps Engineers. We need to have methods to identify issues during CI/CD deployments. We need to find slow queries, inefficient schema migrations, and wrong configuration changes. We need to make our pipelines run faster which means we need to have fewer issues and find these issues earlier. We need to avoid slow load tests but still have methods to assess the performance during CI/CD. This way, we can have CI/CD pipelines that are not blocked and deploy things faster.
We ought to help our operations. Once we deploy things to production, we need to have ways to identify issues as early as possible, pinpoint them to the root causes, and provide actionable solutions that we can apply immediately. Our goal is to cut the root-causing time and remove as much communication as possible. Finally, we aim to remove the need to manually configure and tune alarms. Our systems should finally be cloud-native, self-heal themselves, and adapt to changing conditions. This way, we can decrease MTTR and have our solutions run smoothly in production.
We need to help ourselves and make our lives easier. Metis gives us all of that. Metis covers the whole software development life cycle thanks to three angles: prevention, observability, and curation.
Prevention can integrate with your programming flow and your CI/CD pipelines to automatically check queries, schema migrations, and how you interact with databases. Prevention lets you increase velocity and move faster by streamlining your development process and making it reliable. Metis decreases your lead time for changes and increases your deployment frequency.
Observability provides database-oriented analysis and dashboards that show you what happens in your database. Not some generic metrics or ideas about the infrastructure, but curated insights showing how changes, deployments, extensions, and configurations affect each other. Observability reacts to changing conditions, automatically tunes alarms, and detects anomalies. Metis connects the dots for you and explains what happens instead of giving you raw signals. Metis reduces MTTR and Change Failure Ratio.
Curation focuses on troubleshooting and fixing the issues automatically. Metis automatically fixes issues, provides actionable insights that you can apply with a single click, and submits changes on your behalf which you just need to approve. Metis shortens your software development life cycle loop.
Let’s see the details.
Metis Guardrails That Give You Smooth Operations
Metis automatically checks all your queries during implementation. Metis can project your interactions on production databases to indicate whether your changes will be fast enough and will not take databases down. This way, you can make your developers feel confident and write the right solutions from the first go.
Metis analyzes schema changes and checks if the migrations will execute fast enough or if there are any risks. Metis tells you immediately if your modifications can lead to a database outage.
Metis integrates with your CI/CD pipelines. You can use it with your favorite tools like GitHub Actions and get all the checks automated. Developers can feel confident that nothing wrong will be deployed to production.
Metis truly understands how your database works. It can analyze database-oriented metrics around transactions, caches, index usage, extensions, buffers, and all other things that show the performance of the database. DevOps Engineers don’t need to pay attention to metrics anymore as Metis detects anomalies, looks for changes in patterns, and understands what is expected in databases and what needs intervention.
Metis analyzes queries and looks for anomalies. It can give you insights into how things behave over time, why they are slow, and how to improve performance. All of that is in real-time for the queries that come to your database.
Metis understands everything database-related! It can reason about your indexes, settings, configurations, extensions, and schemas. Metis replaces your DBAs and takes ownership of your whole operations.
Metis alerts you when things need your attention. Metis integrates with your systems to send you alerts and notifications when your actions are needed. If you don’t hear back from Metis, all is good!
Metis walks you end-to-end through the software development life cycle. It covers everything from when you implement your changes until they are up and running in production. Metis unblocks your teams, gives them the ability to self-serve their issues, and keeps an eye on all you do to have your databases covered.
Summary
Achieving continuous database reliability is hard when we don’t have the right tools. We must prevent the bad code from reaching production, make sure things will scale well and will not take our business down, and monitor our databases and understand how things affect each other. This is time-consuming and tedious. However, it’s automated with Metis. Once you integrate with Metis, you don’t need to worry about your database anymore. Metis covers your whole software development life cycle, fixes problems automatically, and alerts you when your attention is needed.
