Part of the Gremlin Office Hours series: A monthly deep dive with Gremlin experts. Pop quiz - what are all of the dependencies your services rely on? If you’re like most engineers, you probably struggled to come up with the answer. Modern applications are complex and rely on dozens (if not hundreds) of dependencies. Many teams rely on spreadsheets, but manual processes like these break down over time. What if you had a tool that found and tracked dependencies for you?

Cloud-based distributed applications have changed how we need to approach reliability and resiliency. How do you make your applications reliable? Here’s Gremlin CEO Josh Leslie to tell you how. Today’s dynamic applications are too complex and constantly changing for humans to wrap their heads around. This means the reliability approaches that worked ten years ago simply won’t be enough. As a technology company (and these days, every company is a technology company), you need to take a different, programmatic approach to testing and improving the reliability of your applications.

80% of failures at the infrastructure layer come from the same core gaps in reliability. Jeff Nickoloff, Gremlin Principal Engineer, goes over how Reliability Management test suites help improve reliability across your organization. Are you waiting for the other reliability shoe to drop and hoping that you actually fixed core resilience issues? Or do you know for sure that you’re resilient to common reliability issues?

Part of the Gremlin Office Hours series: A monthly deep dive with Gremlin experts. To get the most value out of Chaos Engineering and reliability testing, you need a way to observe your service’s behavior. Observability tools offer insight into how your systems are performing, but observability on its own isn’t enough. You need a way to monitor your systems while testing their reliability so you can determine whether your service passed or failed a test.

Unreliable software can have a painful impact on your customers and your business—something we’ve all seen and felt during high-profile outages. And while building on the cloud with AWS unlocks improved scaling and reliability capabilities, the complexity of modern distributed systems can potentially introduce outage-causing reliability risks. How can you be sure your systems are resilient to failure when they’re based on complex architecture, built by hundreds of teams, and are being updated almost constantly?

Part of the Gremlin Office Hours series: A monthly deep dive with Gremlin experts. Serverless applications are ideal for deploying scalable applications without having to manage infrastructure. However, this also makes it difficult to test their reliability. It’s easy to simulate a network outage or latency when you have direct access to the host that your software’s running on. What do you do when you only have control over the code?

For global financial services companies, reliability must be built-in and validated before and after shipping to production. Resilience testing is crucial for verifying the reliability of your applications under real-world conditions. But ad-hoc testing and exploratory experiments aren't sufficient: you need to run automated, standardized tests at global scale.

Part of the Gremlin Office Hours series: A monthly deep dive with Gremlin experts. Cloud platforms make it easier than ever to deploy massively scalable, distributed workloads, but this is a double-edged sword. There are reliability challenges unique to the cloud that didn’t exist before. Failed migrations, recurring incidents, and reliability toil take their toll.

The four Golden Signals are an easy and effective way to measure the most important aspects of a system, and when paired with a reliability management platform like Gremlin, they help you proactively meet your SLOs so you can meet your legal obligations and deliver the perfect customer experience.

Part of the Gremlin Office Hours series: A monthly deep dive with Gremlin experts. Migrating to the cloud usually means faster deployments and easier scalability, but it also means latency. Cloud applications communicate over distributed networks, and while these networks are fast, little bits of latency can quickly add up.