Operations | Monitoring | ITSM | DevOps | Cloud

Fully taking advantage of cloud infrastructure includes the ability to scale up and down dynamically, taking the need and load off your services. The compute services like Amazon Web Services (AWS) EC2, Azure Virtual Machines (VM), and Google Cloud Platform (GCP) Compute Engine allow Auto Scaling of the instances of the service. This helps manage the responsiveness and costs of your cloud services by ensuring that the instance counts go up and down depending on demand.

Monitoring Kubernetes, both the infrastructure platform and the running workloads, is on everyone’s checklist as we evolve beyond day zero and into production. Traditional monitoring tools and processes aren’t adequate, as they do not provide visibility into dynamic container environments. Given this, what tools can you use to monitor Kubernetes and your applications?

A step by step cookbook on best practices for alerting on Kubernetes platform and orchestration, including PromQL alerts examples. If you are new to Kubernetes and monitoring, we recommend that you first read Monitoring Kubernetes in production, in which we cover monitoring fundamentals and open-source tools. Interested in Kubernetes monitoring?

With the growing popularity of containerized applications, organizations and startups at all levels need to manage their Kubernetes deployments more safely at scale. Today, there is an expanding list of tools and services that can help do this. One of these services is the package manager known as Helm.

Netflix, Amazon, Google, Facebook, and a host of other companies have adopted chaos engineering, which encourages designing systems to proactively ward off potential issues through testing and the anticipation of failure. When it comes to container orchestration tools like Kubernetes, chaos engineering is a vital tactic for enhancing security.