Logging is a critical part of monitoring and there are a lot of tools for logs monitoring like Splunk, Sumologic, and Elasticsearch, etc. Since Kubernetes is becoming so much popular now, and running multiple applications and services on a Kubernetes cluster requires a centralized, cluster-level stack to analyze the logs created by pods. One of the well-liked centralized logging solutions is the combination of multiple opensource tools i.e. Elasticsearch, Fluentd, and Kibana. In this blog, we will talk about setting up the logging stack on the Kubernetes cluster with our newly developed operator named “Logging Operator”.
Redis is a popular and opensource in-memory database that supports multiple data structures like strings, hashes, lists, and sets. But similar to other tools, we can scale standalone redis to a particular extent and not beyond that. That’s why we have a cluster mode setup in which we can scale Redis nodes horizontally and then distribute data among those nodes.
Since Kubernetes is becoming buzz technology and people are using it to manage their applications, databases, and middlewares at a single place. So in this blog, we will see how we can deploy the Redis cluster in production mode in the Kubernetes cluster and test failover.
When I set forth with my journey of containerization with docker, I have gone through a misconception that Overlay networking in docker can’t be set up without any orchestrator like Docker swarm, Kubernetes. But after spending some time with containers I realized that I was wrong, Orchestrators leverage the functionality of overlay networking but it is not true that we cannot use overlay networks without any swarm or Kubernetes.
In the modern world, the container is a fascinating technology, as it has revolutionized software development and delivery. Everyone is using containers because of its dynamic, scalable, and isolated nature.
People do use some orchestration software such as Kubernetes, Openshift, Docker Swarm, and AWS ECS, etc to run their production workloads on containers.
While tools like Kubernetes is becoming an essential need for modern cloud-based infrastructure, there is a high potential for cloud-native CI/CD. To achieve that there is a philosophical approach has emerged i.e. GitOps. As we have discussed the important principles of GitOps in our previous blog, So in this blog, we will see how to implement GitOps in our current DevOps processes, and finally GitOps implementation in a light manner. If you haven’t gone through our previous blog, here you can take a look at it.