Many cloud infrastructure providers make deploying services as easy as a few clicks. However, making those services high availability (HA) is a different story. What happens to your service if your cloud provider has an Availability Zone (AZ) outage? Will your application still work, and more importantly, can you prove it will still work? In this blog, we'll discuss AZ redundancy with a focus on Kubernetes clusters.
Getting your applications running on Kubernetes is one thing: keeping them up and running is another thing entirely. While the goal is to deploy applications that never fail, the reality is that applications often crash, terminate, or restart with little warning. Even before that point, applications can have less visible problems like memory leaks, network latency, and disconnections. To prevent applications from behaving unexpectedly, we need a way of continually monitoring them.
For many software engineering teams, most testing is done in their CI/CD pipeline. New deployments run through a gauntlet of unit tests, integration tests, and even performance tests to ensure quality. However, there's one key test type that's excluded from this list, and it's one that can have a critical impact on your application and your organization: reliability tests. As software changes, reliability risks get introduced.
Gremlin's Detected Risks feature immediately detects any high-priority reliability concerns in your environment. These can include misconfigurations, bad default values, or reliability anti-patterns. A common risk is deploying Pods without setting a CPU request. While it may seem like a low-impact, low-severity issue, not using CPU requests can have a big impact, including preventing your Pod from running.
We're excited to introduce a new enhancement to help teams build more reliable software: Detected Risks. Available today, Detected Risks helps you find and fix the most common causes of infrastructure outages and incidents in minutes—without running Chaos Engineering experiments or reliability tests.
Reliability impacts every organization, whether you plan for it or not. Leading companies take matters into their own hands and get ahead of incidents by building reliability programs. But since many of these programs are still nascent, how do you know what good looks like? Of course, the right tools and technology that can enable your team to uncover reliability risks before they impact users play an important role. But improving reliability goes beyond technology.
We knew Chaos Engineering was in high demand when we first launched the Gremlin certifications in 2021. But we had no idea our Chaos Engineering certification programs would be such a success. There’s a reason: the market is looking for professionals who know how to wield Chaos Engineering well, and Gremlin's certification has become the gold-standard to learn the principles of Chaos Engineering and demonstrate proficiency.
Ensuring software availability is essential for any SaaS company—including Gremlin. To do that, our teams need to identify the reliability risks hiding in our systems. That’s why our development, platform, and SRE teams use Gremlin regularly to perform Chaos Engineering experiments, run reliability tests, and track the reliability of our systems against our standards. Along the way they’ve picked up a thing or two about how to find and fix reliability risks with Gremlin.
Building momentum for a reliability program can be tough. Improving reliability takes time, effort, and resources. But when everything from launching new features to improving security demands those same resources, it can be a struggle to get the buy-in you need to address reliability risks. And it makes sense! If a team spends time patching a known security bug or creating a new feature, they have a clear demonstration of the value created.
Incident response has been the cornerstone of reliability for decades. From digging in the server logs to navigating modern observability dashboards, responding quickly to incidents and outages is a big part of minimizing downtime. And it should be! When something breaks, your team should move as quickly as possible to address and repair the problem.
