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As modern applications become more complex, monitoring and performance analysis are becoming increasingly important. In today's big data environment, developers need to be able to effectively monitor their applications and identify issues quickly. To address these issues, an advanced monitoring and performance analysis tool has become essential. In this article, we'll cover how to implement application monitoring and performance analysis using Prometheus and Grafana.
What is Prometheus?
Prometheus is an open source monitoring system and time series database developed by SoundCloud. Prometheus can record any observable data and provides a powerful query language and image or graphical interface. It is part of the Cloud Native Computing Foundation and provides seamless integration with modern container platforms and tool sets such as Kubernetes, Docker, and more.
Prometheus Advantages
What is Grafana?
Grafana is an open source data analysis and visualization tool that aggregates results from data sources into a single dashboard. Grafana supports a variety of data sources, including Prometheus and other time series databases, relational databases, log files, and IoT devices. Grafana is suitable for analyzing and monitoring data in large enterprises, as well as for use by small teams in development projects.
Grafana Advantages
Monitoring applications using Prometheus and Grafana
Prometheus and Grafana can help developers monitor various metrics of applications, including machine resource usage, request latency, and response time. In this section, we'll cover how to integrate application metrics into dashboards using Prometheus and Grafana.
Step 1: Install and configure Prometheus
The easiest way to install Prometheus is to use a container platform (such as Docker or Kubernetes). If you want to build Prometheus binaries from source, you need to install Go and Git. The configuration file config.yml contains all targets to be monitored and the persistence location for storing and retrieving files for exported samples, and can be configured in the following way:
global:
scrape_interval: 10s # Periodic detection Frequency
scrape_timeout: 5s # Detection timeout time
scrape_configs:
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