Monitoring a Kubernetes Cluster is the need of the hour for any application following a microservices architecture. There are a bunch of solutions that one can implement to monitor their Kubernetes workload and one of them is Prometheus and Grafana. This article will help you to deploy Prometheus and Grafana in your kubernetes cluster with the help of prometheus-operator.
But before setting up these components let’s understand a bit about each of them.
Prometheus is a pull-based open-source monitoring and alerting tool originally built by SoundCloud. It works on a time-series database and scrapes metrics at a given interval from HTTP endpoints. After Kubernetes, Prometheus joined the Cloud Native Computing Foundation in 2016 as the second hosted project.
The Alertmanager takes care of alerts sent by alerting tools such as the Prometheus server. It handles grouping, silencing, and routing them to the correct receiver integration such as email, PagerDuty, Slack, etc. It also supports the inhibition of alerts.
Grafana is the visual representation of metrics collected by a data source which in our case happens to be Prometheus. We can create or import dashboards for grafana which will make use of promQL to visually represent metrics collected by Prometheus.
Most business managers get confused between CloudOps and DevOps easily. And it is a way too common problem so here we are drawing a line between CloudOps and DevOps that can help the business managers understand the basic difference between CloudOps and DevOps.
As the name proposes, DevOps is a mix of ”Development” and ”Operations”, and depicting it as “specialized deft” appears to be shockingly exact. A bunch of practices and processes assist associations with making a spry, cooperative climate that unites software development, IT tasks, and quality designing to fulfill the basic business operations such as:
Long since Prometheus took on the role of monitoring the systems, it has been the undisputed open-source leader for monitoring and alerting in Kubernetes systems, it has become a go-to solution. While Prometheus does some general instructions for achieving high availability but it has limitations when it comes to data retention, historical data retrieval, and multi-tenancy. This is where Thanos comes into play. In this blog post, we will discuss how to integrate Thanos with Prometheus in Kubernetes environments and why one should choose a particular approach. So let’s get started.
MongoDB is a popular NoSQL database that supports large as well as small size of datasets. Just like any other database standalone setup, MongoDB is straightforward but we have to make a replicated or shared cluster of MongoDB, and there we have certain complications. Especially if we are doing these kinds of setups in orchestration tools like Kubernetes.
There is a lot of complexity in setting up MongoDB on Kubernetes that people(including me) have faced for a long time which I would like to highlight:-
Standalone setup is pretty straightforward but for replicated and sharded clusters additional mongo configurations are required.
In the replicated scenario, separate configurations need to be managed for the leader and follower.
Monitoring and access management of MongoDB inside Kubernetes is a little tricky part to handle.
Let’s start with a scenario, whenever any application builds, we generally do have 3 environments on the basis of resources – dev for developers resources, test for testers resources, and prod for production resources. Likewise, we used to have a separate IT-Operational Team having strategies to maintain their environment resources. It was very time-consuming and many human resources were required.
We are in the microservices era where we follow the DevOps Methodology. The DevOps Team brings all the environment and strategies to maintain resources in one go. Resources are the ones who decide the behavior of your applications. We can apply the criteria to resources, so how can our application behave? To do this we can give the name to our resources, we can give the resources quota to the application, and can give resource ranges to the application.