Data Persistent Prometheus-Grafana Intergration with Jenkins

Data Persistent Prometheus-Grafana Intergration with Jenkins

Prometheus is an open-source application monitoring and alerting software solution. It is a web application which can be deployed anywhere — in a PC, virtual machine, or even in a container. It scrapes data from the exporters (small programs convert system data to Prometheus metrics) periodically and records the real-time metrics in a time series database.

Prometheus is an open-source application monitoring and alerting software solution. It is a web application which can be deployed anywhere — in a PC, virtual machine, or even in a container. It scrapes data from the exporters (small programs convert system data to Prometheus metrics) periodically and records the real-time metrics in a time series database.

On the other hand: Grafana is an open-source metric analytics & visualization application. It is used for visualizing time series data for infrastructure and application analytics.

It is also a web application which can be deployed anywhere that users want. It can target a data source from Prometheus and use its customizable panels to give users powerful visualization of the data from any infrastructure under management.

Why Prometheus + Grafana?

The relationship between Prometheus and** Grafana** is like a backend and frontend for a data monitoring system. Prometheus acts as the data collection and storage backend and Grafana as the interface for analysis and visualization.

One of the significant advantages of Prometheus is the exporter feature. The official Prometheus website has already provided many useful exporters for users, and the Prometheus communities also have many customized exporters built by users themselves. By using different kinds of the exporters, Prometheus is able to monitor applications in all types of environments. This is especially efficient for docker & Kubernetes container environments.

One of the significant advantages of Grafana is its customization features. It’s effortless to customize the visualization for massive amounts of data. Users can choose a linear graph, a single number panel, a gauge, a table, or a heatmap to display their data. They can also sort all their data with various labels; data with different labels will go to different panels. The dashboard can be rearranged and resized simply by dragging panels around. These customization features make Grafana useful and powerful for many different types of users, such as DevOps, Security, Operations, and Networking.

Problem Statement:

Integrate Prometheus and Grafana and perform in following way:

1. Deploy them as pods on top of Kubernetes by creating resources Deployment, Replica Set, Pods or Services.

2. And make their data to be remain persistent.

3. And both of them should be exposed to outside world.

devops prometheus grafana jenkins automation github docker data

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