Operations | Monitoring | ITSM | DevOps | Cloud

It’s not surprising that most failures are caused by a change somewhere in a system, such as a new code deployment, configuration change, auto-scaling activity or auto-healing event. As you investigate the root cause of an incident, the best place to start is to find what changed. To understand what change caused a problem and what effects propagated across your stack, you need to be able to see how the relationships between stack components have changed over time.

The concept of containerization helps you run applications as lightweight virtual machines. As a web developer, setting up local development environments can be tiresome. However, using tools like Docker and Kubernetes gives developers an upper hand to quickly set up and deploy applications. This guide uses Docker to deploy a React app to Kubernetes.

Alerting infrastructure is often complex, with many pieces of the pipeline that often live in different places. Scaling this across many teams and organizations is an especially challenging task. As organizations grow in size, the observability component tends to grow along with it. For example, you may have many components, each of which needs a different set of alerts. You may have several teams, each with a different channel where notifications should be delivered.

Over the last couple of years, Spike.sh has largely been a Simple Incident Management Platform helping engineering teams across the world. Our focus on simplicity has been well received by all of you and we couldn't be more happy about it. After speaking with users earlier this year, we quickly realised there is a lot we can do to help our responders and help them better than we currently are.

The why and what we learned from surveying 1,900 engineering teams around their best practices to build, scale, and maintain high availability.