Metis Blog

Ensuring database reliability is challenging. We aim to accelerate development while reducing rollbacks, enabling developers to work efficiently and take full ownership of their databases. This process becomes significantly easier with strong database observability in place. Let’s dive into how it works.

Ensuring database consistency is a complex and often overwhelming challenge, especially as systems scale and evolve. Without a well-structured approach, managing schema migrations and updates can become chaotic, leading to unexpected failures, performance bottlenecks, and downtime. These issues not only impact system reliability but also disrupt business operations and user experience.

Platform engineers oversee every phase of the SDLC related to databases, but they often lack the necessary tools, processes, and mindset to fully empower their teams. Let’s explore what’s missing and how we can transform our organizations to accelerate progress.

Ensuring database consistency can quickly become a complex and daunting challenge. To tackle these difficulties, it's essential to adopt effective strategies for streamlining schema migrations and updates. These approaches facilitate smooth database modifications while reducing downtime and performance issues. Without them, the risk of misconfigurations increases - something Razorpay experienced firsthand. Learn how to avoid making the same mistakes.

No matter how careful we are, issues can still arise in production. We might deploy buggy code, execute a slow schema migration, or experience a surge in traffic that overwhelms our systems. When database-related problems occur, developers often feel powerless. They may lack a deep understanding of database internals, the necessary permissions, or visibility into active queries. Despite having robust CI/CD pipelines and highly optimized IDEs, databases remain beyond their direct control. It’s time to change that. Here are three key strategies to help regain control over our databases.

Managing database configurations can quickly become a daunting and intricate task, often posing significant challenges. To tackle these difficulties, it’s essential to adopt efficient strategies for streamlining schema migrations and updates. These practices facilitate smooth database transitions while reducing downtime and minimizing performance issues. Without such measures, the risk of data loss increases - much like the situation KeepTheScore faced. Learn how you can steer clear of similar pitfalls.

Imagine a world where your database practically takes care of itself, made possible by advanced observability. Intrigued? Keep reading to learn how this can become your reality.

Our teams dedicate a considerable amount of time to managing the databases, which is understandable - keeping things running smoothly is essential for maintaining business operations. But what if database maintenance could be eliminated? Picture a situation where constant database oversight wasn’t necessary. Intrigued? Keep reading to learn how this can become a reality.

Maintaining database consistency can quickly spiral into chaos, presenting considerable challenges. To overcome these, it’s crucial to employ effective strategies for managing data modifications and adjustments. These methods ensure the smooth implementation of database changes, minimizing both downtime and performance issues. Without such strategies, the risk of outages rises - as evidenced by AppNexus. Discover how to avoid making similar mistakes.

Traditional monitoring falls short. We need developer-focused solutions that only Observability 2.0 can provide. Read on to discover why.

Ensuring database consistency can quickly become chaotic, posing significant challenges. To tackle these hurdles, it's essential to adopt effective strategies for streamlining schema migrations and adjustments. These approaches help implement database changes smoothly, with minimal downtime and impact on performance. Without them, the risk of misconfigured databases increases - just as Heroku experienced. Learn how to steer clear of similar mistakes.

Testing databases alone isn’t sufficient; observability is essential for ensuring database reliability. Here’s why and how it matters.

Schema changes and migrations can quickly spiral into chaos, leading to significant challenges. Overcoming these obstacles requires effective strategies for streamlining schema migrations and adaptations, enabling seamless database changes with minimal downtime and performance impact. Without these practices, the risk of flawed schema migrations grows - just as GitHub experienced. Discover how to avoid similar pitfalls.

Platform engineers oversee all phases of the software development lifecycle (SDLC) related to databases. Yet, they often lack the necessary tools, processes, and mindset to fully empower their teams. Let’s explore what’s missing and how we can transform our organizations to accelerate progress.

Managing databases in today’s landscape can be a daunting task. With hundreds of clusters and applications to handle, combined with a lack of clear ownership, the complexity can feel overwhelming. This challenge is compounded when there is no clear guidance for addressing specific problems, and when processes rely heavily on manual work and communication instead of automation.

Shift-left involves moving tasks, particularly testing, to earlier stages in the development pipeline instead of leaving them for the end. Traditionally, late-stage testing has proven problematic, as time and resource constraints often lead to skipping comprehensive tests or overlooking edge cases. Even when issues are identified late, they become costly to fix, as the implementation is already complete and has passed through most of the pipeline.

Data loss is the worst that can happen to a company. It immediately destroys customers’ trust and leads to many technical issues. There is a way to avoid that with database guardrails. Let’s see how and why database guardrails could have saved Atlassian from their data loss.

We need a fresh perspective on how databases are managed: database guardrails. Let’s explore the harsh reality of current practices and how we can truly improve our databases.

We’re all familiar with the core principles of DevOps: building small, well-tested increments, deploying frequently, and automating pipelines to eliminate manual processes. We closely monitor applications, set up alerts, roll back problematic changes, and ensure we’re notified when issues occur. Yet, when it comes to databases, this level of control and visibility is often lacking. Debugging performance issues can be daunting, and understanding why databases slow down isn’t always straightforward. Schema migrations and modifications can quickly become chaotic, creating significant challenges. Addressing these issues requires strategies to streamline schema migration and adaptation, allowing for seamless database changes with minimal downtime or performance degradation. Without these measures, the risk of data loss becomes very real - just as Linear experienced. Learn how to avoid such pitfalls.

You don’t need to test your databases to keep them in shape. There is a better way to achieve database reliability. Let’s see how.

Keeping pace with database advancements becomes even more challenging when machine learning and AI enter the equation. Companies that fail to adopt AI risk falling behind, wasting resources on outdated solutions, and missing out on the automation and efficiency AI can offer. If you're a C-level executive looking to elevate your business, read on to discover how AI can revolutionize observability.

Overcoming database issues requires strategies that streamline schema migration and adaptation, enabling efficient database structure changes with minimal downtime or performance impact. It’s essential to test all changes cohesively throughout the pipeline. Let’s explore how this can be achieved.

As DevOps engineers, our goal is to create systems that perform seamlessly in production - and this extends beyond application code to include our databases! Imagine the peace of mind that comes with implementing changes confidently, deploying without stress, and relying on automated safeguards to ensure that updates to your database or business logic don’t impact your production environment. Interested in learning how to achieve this? Read on!

Many monitoring tools prioritize quantity over quality, overwhelming users with an abundance of data points and metrics rather than providing clear insights into what’s happening and how to resolve issues. In this blog post, we’ll explore what’s truly needed and how to create more effective solutions.

As developers, we all aim to craft code that performs exceptionally well in production. This principle applies not only to application code but also to our databases! Imagine the confidence of making changes without worry, deploying stress-free, and receiving automated assurance that your updates to the database or business logic won’t disrupt your production environment. Curious about achieving this? Keep reading to find out how.

An Object-Relational Mapper (ORM) is a library that handles the conversion between domain models and database entities, and vice versa. While ORMs are designed to simplify this process, they aren't always efficient in every scenario. This can sometimes lead to performance bottlenecks and a subpar user experience. In this blog post, we’ll explore common challenges associated with ORMs and discuss strategies to overcome them.

Dealing with database issues is something most of us have experienced. Databases can become slow, unreliable, or even crash soon after deployments, impacting business operations and diminishing customer satisfaction. It's no wonder we strive to resolve these issues as quickly as possible. But what if we could sidestep these problems altogether? Imagine having databases that can self-heal and automatically resolve issues - or better yet, prevent them before they happen. Keep reading to discover how Metis can help your databases remain resilient and automatically address any problems.

The database domain is constantly evolving, with innovations emerging rapidly and today’s cutting-edge systems becoming tomorrow’s legacy. Despite our best efforts, issues can still arise in production. Faulty code may be deployed, slow schema migrations may occur, or unexpected surges in traffic may overwhelm our systems. Here, we explore three key trends in the database landscape that can help us maintain optimal database reliability.

DevOps Engineers often aim to take ownership of the tools and systems they manage, which brings significant advantages: they can streamline communication, set their priorities, and implement improvements through optimized tools and processes. However, it becomes challenging for them to work effectively without full ownership. This issue frequently arises with databases - DevOps Engineers typically don't control the database engines, which hinders their ability to move quickly amid their many responsibilities. But what if they did own their databases? What if they could operate independently without relying on other teams? Read on to explore how this can become a reality.

Our teams invest a significant amount of time managing the database, which makes sense - we need to ensure everything runs smoothly to keep the business on track. But what if there was a way to avoid database maintenance altogether? Imagine a scenario where you didn’t have to oversee the database constantly. Sound interesting? Read on to discover how this is possible

As DevOps Engineers, we work hard to keep our systems running smoothly. We monitor, analyze metrics and logs, and respond to alerts - doing everything we can to prevent disruptions, especially in databases that are vital to our applications. But imagine if maintenance wasn’t necessary at all. What if there were tools to manage your databases for you, allowing you to forget they’re even there? Read on to discover how this can be a reality.

The tools, processes, and procedures needed to efficiently manage hundreds of clusters are often lacking. How can we improve? Read on to discover how Metis transforms database fleet management.

If you've ever had to troubleshoot problems in a production database, you're likely aware of how difficult it can be. Numerous factors influence performance - such as execution plans, indexes, caching, I/O activity, extensions, and more. Understanding all of these aspects can be overwhelming and time-consuming. But what if this process could be automated? Imagine a tool that guides you through what went wrong and how to resolve it. Keep reading to learn how Metis provides exactly that and how it assists DevOps Engineers in their work.

No matter how careful we are, issues can still arise in production. We might deploy faulty code, execute a slow schema migration, or experience a spike in traffic that overwhelms our systems. Let's see how to deal with that.

Creating a product is often a long and evolving journey. As we gain more insight into the market, plans can shift. To experiment with new ideas, we need to iterate quickly. However, this can lead to technical challenges - developers might make errors, systems can become unreliable, and sometimes we need to revert changes. But what if we could prevent all of that? What if we could map out a reliable roadmap, build swiftly, and never worry about rollbacks? What if the database was always dependable? Read on to discover how Metis delivers just that.

We need a new approach to database management. Load tests are just a waste of time. Let’s understand why.

As DevOps engineers, our goal is to write efficient, high-performing code that excels in production environments. This applies not only to our application code but also to our databases. Imagine having the confidence to make code changes without worry - deploying without stress. Wouldn't it be reassuring to have automated verification that your updates, whether to the database or business logic, won't cause issues in production? Keep reading to discover how you can achieve all of this.

To achieve continuous database reliability, it's essential to implement database guardrails, which include the right tools, processes, and mindset. However, it goes beyond just technical aspects - a cultural change that needs to happen. Once embraced, developers will take pride in owning their databases and delivering top-tier reliability. Let's explore why and how this shift makes a difference.

Creating a product can be a lengthy process, with numerous changes occurring as we gain insights into the market. Rapid development is essential for testing new ideas.

Let’s see what is VACUUM in PostgreSQL, how it’s useful, and how to improve your database performance.

Being a product manager is challenging when developers struggle with delivering tasks end-to-end. No matter if it’s domain complexity or technological obstacles, we always need to look for better solutions and improvements. Fortunately, we can solve all the issues around databases easily. Read on to see how.

PostgreSQL 17 came out in September. Let’s see what’s new.

Product managers may face many challenges along the way. They would like to focus on their products and never be limited by technology. However, it’s not as straightforward as possible. If you’d like to learn how not to get slowed down by your database - read on.

Platform engineers thrive on automation. Our goal is to have everything scripted and operating seamlessly, without the need for manual intervention. Unfortunately, databases can be slow, unreliable, or prone to failure after deployments, impacting both business operations and customer experience. It's no wonder we're eager to resolve these issues quickly. But what if we could avoid these problems entirely? Imagine if our databases could self-heal and resolve issues automatically - or even better, prevent them from occurring in the first place. Read on to discover how Metis can help ensure your databases never fail and handle issues automatically.

Traditional monitoring is not enough. We need developer-centric solutions that only Observability 2.0 can give us. Read on to see why.

Developers play a crucial role in modern companies. If we want our product to be successful, we need to have a developer-first approach and include observability from day one. Read on to understand why.

Platform engineers face significant challenges when organizing development teams. Developers typically prefer to have ownership over the components they work with, which brings various advantages. They can prioritize their tasks, optimize workflows by implementing improved tools and processes, and work independently without needing to collaborate with other teams. However, when they lack ownership, particularly with databases, it becomes difficult to perform efficiently. Developers often don’t control the database engines they use, which slows them down amid their heavy workloads. But what if they could manage their databases without needing to rely on other teams? Read on to discover how this can be achieved.

Ensuring database reliability can be difficult. Our goal is to speed up development and minimize rollbacks. We want developers to be able to work efficiently while taking ownership of their databases. Achieving this becomes much simpler when robust database observability is in place. Let’s explore how.

As software testers, we always want to know about issues in the production databases. We handle maintenance, monitor metrics and logs, and respond to alerts. We do whatever it takes to ensure our systems, particularly the databases critical to our applications, remain stable. But wouldn’t it be ideal if maintenance wasn’t required at all? Imagine having tools that manage your databases automatically, allowing you to forget about them entirely. Keep reading to learn how.

Developers might not be familiar with the inner workings of databases. They could lack the necessary permissions, technical know-how, or even awareness of the queries running within the database. Regardless of how well-established their CI/CD pipelines are or how fine-tuned their IDEs may be, they do not have direct control over databases. Let’s see what scares developers.

PostgreSQL is widely regarded as one of the most popular SQL databases and is often the preferred choice for projects involving Online Transaction Processing systems. However, its versatility extends far beyond that, enabling it to effectively manage less common SQL use cases as well as workflows that don’t rely on SQL. In this blog post, we’ll explore various scenarios where PostgreSQL excels and provide insights into how to leverage it in these situations.

The demands of modern software development are high. We're expected to deliver quickly while maintaining uninterrupted system availability. As a platform engineer, you're likely aware of the challenges in balancing speed with accuracy. Developers often find themselves overwhelmed by the complexity of the systems they work on. They may not have a deep understanding of all the details, lack confidence in deploying changes, or be unsure how to address issues that arise in production. But what if there was a way to support them? Imagine if your developers could make code changes, deploy with confidence, and easily troubleshoot problems. This would empower you, as a platform engineer, to increase team velocity and accelerate progress. It would enable rapid product changes and faster feature development. Continue reading to discover how Metis can help you achieve all of this.

It may happen that we created an index and yet PostgreSQL doesn’t use it. What could be the reason and how to fix it? Read on to find out.

All big players in the market use PostgreSQL nowadays. Postgres is just the best and the most popular solution these days, no matter if it’s for startups or enterprise companies. But why is that? What makes PostgreSQL so great and why did companies abandon their enterprise-ready databases like Oracle, MS SQL, or DB2? Read on to find the answers.

Platform engineers focus on all phases of SDLC around databases. However, they lack the tools, processes, and mindset to unleash the power of their teams. Let’s see what they miss and how to change our organizations to move faster.

DevOps engineers tend to automate everything. We automate deployments, infrastructure, cloud formation, and other artifacts. We try to keep everything as code and automate with CI/CD. This includes infrastructure, configurations, or even documentation. What about databases? Let’s see what we need and how Metis helps us put database performance in CI/CD.

Project managers may struggle with many things related to database reliability. They would like the things to be developed fast and avoid rollbacks. They want their developers to work faster and own their databases. All these things are easy to achieve when we have proper database observability in place. Let’s see how.

Many companies dropped load tests. Even though for many years we relied on load tests as the only way to prevent scalability issues, we now have other ways. Let’s see what happened and why you should drop load tests too.

PostgreSQL is one of the most popular SQL databases. It’s a go-to database for many projects dealing with Online Transaction Processing systems. However, PostgreSQL is much more versatile and can successfully handle less popular SQL scenarios and workflows that don’t use SQL at all. In this blog post, we’ll see other scenarios where PostgreSQL shines and will explain how to use it in these cases.

Testing is important to keep our applications running and reliable. We need to make sure we avoid all the issues around our applications and databases. However, what if we could go with no testing at all? What if we could save time on testing databases and still have them reliable? Read on to understand how.

Database administrators play a crucial role in our organizations. They manage databases, monitor performance, and address issues as they arise. However, consider the possibility that their current role may be problematic and that we need to rethink how they operate and integrate within our organizations. Successful companies do not have DBAs. Continue reading to find out why.

Many things can improve database performance. One of the most obvious solutions is to use indexes. This blog post will examine them in detail to understand how they work in PostgreSQL and what makes them useful.

There is a discrepancy between what developers want and what evangelists or architects think the right way is. It’s clearly seen in the world of monitoring and observability. Architects and C-level executives promote monitoring solutions that developers just can’t stand. Monitoring solutions are just wrong. Let’s see why.

What if your team didn’t need to speak with other teams? What if your team could own their database end-to-end? Read on to understand how to achieve that.

Database administrators are often important parts of our organizations. They take care of databases, keep an eye on performance, and step in when we need to fix issues. However, what if I told you that they are harmful and we should change how they work and how they fit our organizations? Read on to understand why.

Product management may be challenging. Managers need to deal with many problems when developing new features and products. It’s hard to plan the roadmap reliably when developers need to improve database performance as it may be a neverending story. Developers need to work faster but it’s hard to estimate the work, making the management even less predictable. However, what if we could avoid all of that? What if we could have tools that optimize databases and handle the hard part with query tuning? Read on to understand how Metis achieves that.

Most monitoring solutions go for quantity instead of quality. They swamp users with lots of data points and metrics instead of showing them what happens and how to fix the issues. In this blog post, we will see what we need instead and how to build better solutions.

Managing projects is hard. We need to deal with the complexity of the domain, the intricacies of the business requirements, and difficulties of the software development. Wouldn’t it be great if we could feel that our team is confident when changing the code? Would you like to have database issues fixed automatically or avoid them entirely? Read on to learn how to have all of that.

Executing transactions is not atomic and takes time. For example, a single UPDATE statement might modify multiple rows, and the database system needs time to update each row. During this update process, another transaction might start and attempt to read the modified rows. This raises the question: should the other transaction read the new values of the rows (even if not all rows are updated yet), the old values of the rows (even if some rows have been updated), or should it wait? What happens if the first transaction must be canceled later for any reason? How should this affect the other transaction? Read on to understand!

Load tests are just a waste of time. Let’s read on to understand why.

We spent years improving our monitoring solutions. We can now capture metrics nearly automatically thanks to solutions like OpenTelemetry. We can visualize data points easily with open-source solutions. Finally, we can easily measure our applications' performance. And yet, there are still more things to incorporate to make observability even better. Let's see 4 hot trends in database observability that modern companies are chasing now.

DevOps engineers want to automate everything. This gives them many benefits - they don’t need to do any manual steps, they don’t need to speak to other teams and can prioritize their important tasks better. However, many organizations make automating things harder. They require synchronous communication between the teams, they limit access permissions, and they scatter ownership throughout various squads. In turn, DevOps engineers don’t own their databases and struggle to move fast with automation since they need to maintain the databases manually. What if they could own their database? What if they didn’t need to speak to other teams? Read on to understand how to achieve that.

Developers often want to own the stuff they work with. This gives them many benefits - they don’t need to speak to other teams, they can prioritize their work, and they can optimize the things they work on by introducing better tools and processes. It’s hard for them to do their work when they aren’t the owners. Unfortunately, this is common with databases. Developers don’t own their database engines and struggle with moving fast with all the work on their plates. What if they could own their database? What if they didn’t need to speak to other teams? Read on to understand how to achieve that.

Let’s see 3 hot trends in database reliability that every team should incorporate into their organization.

There are two important tasks that each developer faces when using databases - how to make queries faster and how to improve the schemas. There are many ways to tackle these problems and we need to find the balance between how much time we spend and how much we improve the performance. Let’s see what we need and how Metis helps us achieve these improvements.

Memory usage is one of the most important aspects of the database system. Having not enough memory directly affects every performance metric and negatively impacts the performance. This in turn affects our users and the business. In this blog post, we are going to understand how databases (and PostgreSQL specifically) manage memory and how to troubleshoot low free-memory scenarios.

Logging is one of the most important parts of the distributed systems. Many things can break, but when the logging breaks, then we are completely lost. In this blog post, we will understand log levels and how to log efficiently in distributed systems.

A connection pooler is a software component that manages database connections. This can help in multiple ways to improve resource utilization, help with load balancing or failover, and can greatly reduce transaction times. In this blog post, we’re going to see what a connection pooler is and how to configure it.

Every read from a physical drive is a tremendous performance hit and should be avoided. In this blog post, we are going to see how to debug scenarios where we can’t utilize cached data and need to read from the physical drive. We’re going to see why it’s important, what to look for, and what tools and extensions to use.

DevOps changed the way how we think about software development. We moved from isolated groups to teams working together hand in hand or even self-sufficient teams capable of building and deploying the software. However, DevOps misses databases. We don’t verify database performance, we don’t check indexes or execution plans, and we don’t achieve database reliability. Let’s see what DevOps needs around databases and 3 things that developers want to have today.

Wrapping your head around databases is challenging and takes time. What if you could have all of that automated? What if you had a tool that could walk you through what happened and how to fix the issues? Read on to understand how Metis gives you all of that.

No matter how diligent we are, things may break in production. We may deploy faulty code, run a slow schema migration, or simply face an increase in traffic that can bring our systems down. When things break around databases, developers often feel like they are at a loss. Let’s see 3 things that can bring us control of our databases.

Building a product may be a long journey. Many things may change along the way as we learn more about the market. To test new ideas, we need to develop fast. However, many things may break on the technical level. Developers may make mistakes, products may not be reliable, and we may need to roll things back. What if we could avoid all of that? What if we could plan the roadmap reliably, develop things fast, and never need to roll things back? Read on to see how Metis gives you all of that.

The complexity of the world increases every day. We tend to build more, deploy more, and handle more and more data. We split our applications into smaller microservices and deploy them many times a day. This makes more and more moving parts and makes us automate everything. Let's see how to replace monitoring and change it into understanding.

As a project manager, you probably know how hard it is to move fast and not make mistakes. Developers may be overwhelmed by the complexity of the systems they work on. They may lack working knowledge, not understand all the details of their systems, and may lack confidence when deploying their changes. This may lead to failures in production that they may not know how to tackle. What if we could help them? What if you could have your developers change the code and deploy with confidence, and troubleshoot issues easily?

We must understand how to move fast and increase velocity with databases and what new tools and processes we need to build around. This comes down to incorporating database guardrails and moving towards DBOps. Starting and scaling DevOps in the enterprise is only the beginning. DevOps automation tools helped us achieve improvements in many areas of software development, but now we need to see how to move forward with DBOps. In this article, we’re going to explore how to build DevOps for databases called DBOps and how it can scale efficiency and drive business growth

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.

Are you sure that your CI/CD covers everything? While it may sound obvious, there are so many things that we miss. We don’t check our queries properly, we don’t control configurations, and we don’t cover non-functional requirements in general. Let’s see what 5 things we lack in our CI/CD pipeline and why they are crucial in today’s world.

Reliability is not something we can just build in one place. We need to make sure all parts of the ecosystem work together to guarantee reliability everywhere. One unstable component can take down the whole system. And there is no more important component than the database. The domain model and the storage affect the whole system heavily as it affects every single operation in your application. A good product starts with a good database.

We wanted to calculate a unique identifier for each SQL query in the database. See how we solved this challenge.

This agility in managing database schema changes is key to maintaining speed and flexibility in our database strategies. But how can we move fast around databases? How can we be agile in the database world? Read on to see.

Testing may be hard and we as testers know that. We may face many edge cases, things hard to reproduce, and problems with performance, or network connectivity. Depending on the type of our application, we may need to use dedicated tools for testing or sometimes even build our own.

Many misconceptions arise around database reliability. We typically think in terms of availability (which more or less comes down to minimizing downtime), durability (so we don’t lose data), integrity (meaning that we don’t break the data), fault tolerance (we distribute databases), recoverability (we can still recover the data after issues), safety (who can access what), or performance (it must be fast). However, these categories do not capture what is truly important in databases. Let’s see 3 things that we overfocus on instead of seeing the big picture.

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.

Do you rely on your monitoring solutions to let you know when things are wrong? That is so brave of you! On a more serious note, please think twice. Monitoring is not enough! It can’t explain why things happen the way they do (because it doesn’t see the past beyond metrics) and it doesn’t tell you what is going to happen (so it can’t predict the future). This is a serious problem and we need a solution (spoiler alert: we need database guardrails). Let’s read on to understand why.

Imagine a world where you don’t have to worry about your database, no bugs are deployed to production, all the performance checks happen early during the development phase, you don’t need DBAs nor the maintenance team, and still, everything works great. No matter how fantastic that sounds, you can get it today. Read on to learn how.

We want to test early and more often. This is what shift-left refers to. Instead of testing applications just before the release, we want to test our applications early to identify issues when it’s still easy to fix them. However, shifting to the left carries much bigger consequences. Let’s see what.