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.
In the current era, organizations demand high-quality working data, and management systems that can scale, deploy quickly, robustly, are highly available, and highly secure for any unfortunate incidents. Traditionally, applications used relational databases as the primary data stores but in today’s need for data-driven applications, developers lean towards alternative databases like NoSQL(Not Only Structured Query Language).
NoSQL databases enable speed, flexibility, and scalability in this era of growing development in the cloud. Moreover, NoSQL databases also support JSON-like documents which are commonly used formats to share data in modern web applications.
Nginx is one of the most popular and widely used web servers mostly because of its speed and reliability. Nevertheless, it is paramount to keep track of the performance and availability that would help you to proactively prepare yourself for the worst scenarios like sudden/unexpected hikes in traffic. It will also keep you updated about the current state and health of your application.
This article will guide you on how to get Nginx Web Server metrics and visualize them. The main goal is a quick deployment and configuration using well-known open-source projects like Grafana, Prometheus, and Telegraf.
Prometheus: An open-source, time-series database for event monitoring and alerting managed by the Cloud Native Computing Foundation (CNCF).
Grafana: An Open-source project for analytics software and visualization of the metrics from any database.
Telegraf: An Open-source project, plugin-driven agent to collect and send metrics.
Elasticsearch is a scalable, full-text search and analytics engine based on Apache Lucene. It is Java-based and allows you to store, search, and analyze big volumes of data quickly in near real-time. It can search and index the document files in diverse formats. Lucene is the underlying technology that Elasticsearch uses for extremely fast data retrieval.
As flexible, scalable, and useful as Elasticsearch is, monitoring your cluster can help you ensure that the cluster is appropriately sized and handles all operations efficiently.