Reliable systems are vital to meeting customer expectations. Downtime not only hurts a company’s bottom line but can be detrimental to reputation. Our goal at Gremlin is to help enterprises build more reliable systems using Chaos Engineering. Whether your infrastructure is deployed on bare metal in a corporate-owned data center or as Kubernetes-orchestrated microservices in a public cloud, chaos experiments can help you find system weaknesses early, before they affect customers.

From smart thermostats and grocery store checkouts to public utility infrastructures and industrial manufacturing lines, the Internet of Things (IoT) is all around us—and growing larger every day. But with this rapid growth comes a number of operational challenges: IoT devices collect a large amount of data, and are often distributed across harsh, ever-changing environments.

Out-of-memory (OOM) errors take place when the Linux kernel can’t provide enough memory to run all of its user-space processes, causing at least one process to exit without warning. Without a comprehensive monitoring solution, OOM errors can be tricky to diagnose. In this post, you will learn how to use Datadog to diagnose OOM errors on Linux systems.

Synthetic monitoring lets you improve end user experience by proactively verifying that they can complete important transactions and access key endpoints. But your applications serve many users, from customers to all the employees who run your business. This makes testing the performance of any internal-facing services within your private network just as critical as monitoring your external-facing applications.