Collecting and processing logs, metrics, and application data from endpoints have caused many ITOps and SecOps engineers to go gray sooner than they would have liked. Delivering observability data to its proper destination from Linux and Windows machines, apps, or microservices is way more difficult than it needs to be. We created Cribl Edge to save the rest of that beautiful head of hair of yours.

One of the first considerations for FinOps teams trying to lower their public cloud spend is investing in long-term savings vehicles available from their Cloud Service Provider. These programs can provide customers with upwards of 72% savings off on-demand prices, in return for a 1-to-3-year usage commitment, so it’s pretty common that we see them in use by our customers.

In part I of this blog series, we understood that monitoring a Kubernetes cluster is a challenge that we can overcome if we use the right tools. We also understood that the default Kubernetes dashboard allows us to monitor the different resources running inside our cluster, but it is very basic. We suggested some tools and platforms like cAdvisor, Kube-state-metrics, Prometheus, Grafana, Kubewatch, Jaeger, and MetricFire.

In this post, we'll dive into what CrashLoopBackOff actually is and explore the quickest way to fix it. Fasten your seat belts and get ready to ride. Everyone working with Kubernetes will sooner or later see the infamous CrashLoopBackOff in their clusters. No matter how basic or advanced your deployments are and whether you have a tiny dev cluster or an enterprise multi-cloud cluster, it will happen anyway. So, let’s dive into what CrashLoopBackOff actually is and the quickest way to fix it.

I am happy to share that thanks to the power of the open-source community, and our friends over at Otterize, we have now enhanced our Kubernetes offering for developers with another visual aid to streamline operations and troubleshooting – Dependencies Map. The Otterize network mapper is a zero-config tool that aims to be lightweight and doesn’t require you to adapt anything in your cluster.

In our extensive guide of best ci/cd practices we included a dedicated section for database migrations and why they should be completely automated and given the same attention as application deployments. We explained the theory behind automatic database migrations, but never had the opportunity to talk about the actual tools and give some examples on how database migrations should be handled by a well disciplined software team.