Dear Learner's In Previous article we learn the Monitoring with Grafana Cloud. In today's article we will explain the Prometheus.
Now, the next step is to learn about the Prometheus. It's an open-source system for monitoring services and alerts based on a time series data model. Prometheus collects data and metrics form different services data model. Prometheus collects data and metrics from different services and stores them according to a unique identifier -the metric name-and a time stamp.
What is the Architecture of Prometheus Monitoring?
Prometheus is an open-source monitoring and alerting system that was originally developed at SoundCloud . It is designed for monitoring systems and applications in a distributed environment. The architecture of Prometheus consists of serveral key components that work together to collect store and process metrics data. here is an overview of the Prometheus architecture.
1 Prometheus Server: The core component that collects and stores metrics data.
2 Data Collection: Metrics are obtained by Scraping HTTP endpoints or using exporters.
3 Service Discovery: Mechanisms to automatically find and monitor new targets.
4 Alerting and Alertmanager: Define and handle alerts based on collected metrics.
5 Data Storage: Metrics are stored in a local on-disk-series database.
6 Visualization and UI: Web-based interface for exploring metrics,querying and visualization.
2 What are the features of Prometheus?
Prometheus offers multiple graphing and dashboards options,allowing users to visualize metircs data in various ways.
Metrics collection in Prometheus follows a pull model over HTTP where the server pulls data form the targets.
Prometheus utilizes a multidimensional data model,where time series data is associated with metric names and key-value pairs (KVP).
The PromQL query language in Prometheus supports the multidimensional nature of the data model,enabling powerful querying and analysis.
Prometheus operates as autonomous single server nodes,eliminating the need for distributed storage.
Target discovery in Prometheus can be achieved through static configuration or dynamic service discovery mechanisms.
Prometheus also provides the capability to push time series data through an intermediary gateway,allowing flexibility in data ingestion.
3 What are the Components of Prometheus?
Prometheus server: The Prometheus server acts as the central hub for collecting,storing,processing,querying and alerting on metrics data. It is a highly flexible and scalable component that forms the backbone of the Prometheus.
Prometheus UI: The Prometheus UI Servers as a user-friendly interface for interacting with Prometheus allowing users to explore,analyse and visualise metrics data, create custom dashboards,manage alerting rules and monitor the status of targets and jobs.
Prometheus Alertmanager: Prometheus Alert manager is a component of the Prometheus monitoring system that handles the management and routing of alerts triggered by Prometheus. It acts as a central hub for processing,duplicating, grouping and sending alerts to different notification channels.
Prometheus Pushgateway: The Prometheus Pushgateway serves as a bridge between Prometheus and short-lived or batch jobs into the Prometheus monitoring system. It provides a convenient mechanism for pushing metrics to Prometheus allowing for a more comprehensive monitoring solution.
4 What database is used by Prometheus?
Prometheus uses its own built-in time-series database called the Prometheus Time Series Database(TSDB). It is optimised for storing and querying time-series data and is designed to efficiently handle the metrics collected by Prometheus. The TSDB provides compression, indexing and effectively. While Prometheus does not support external databases as its primary storage back end. it offers mechanisms for exporting or pushing data to other systems if long-term storage or additional analysis is required.
5 What is the default data retention period in Prometheus?
The default data retention period is 15 days in Prometheus. Data would be automatically deleted after the data storage default retention duration has passed.
Thank you for reading!! Hope you find this helpful.
#day73challenge#90daysofdevops
Always open to suggestions..!!
~ Manoj Bhamidipati 🙂