Prometheus is an open-source monitoring and alerting toolkit. Its architecture is made up of several components that work together to collect, store, and process monitoring data, and to notify users about important system events.
a. Prometheus Server
The Prometheus Server is the core component of the Prometheus architecture. It is responsible for the following main functionalities:
1. Retrieval (Scraping): The Prometheus Server periodically retrieves or "scrapes" metrics data from various target systems over HTTP. These targets expose their metrics through a dedicated HTTP endpoint, typically /metrics.
2. Storage (Time Series Database): After scraping, the collected metrics are stored locally on the Prometheus server in a time-series database. This database is optimized for storing data where each value is associated with a timestamp.
3. HTTP Server (API Access): Prometheus makes the collected data available through a built-in HTTP server. Users and other systems can query the data using the Prometheus Query Language (PromQL) via HTTP APIs.
b. Targets: Targets are the systems or applications that Prometheus monitors. These can include servers, applications, services, containers, or any other component that exposes metrics in the expected format. Prometheus scrapes data from these targets at configured intervals. Targets can be defined statically in the configuration or discovered dynamically using service discovery.
c. PushGateway: Prometheus primarily operates on a pull-based model, where it scrapes metrics from targets. However, in cases where jobs are short-lived such as batch scripts or cron jobs, they may terminate before Prometheus has a chance to scrape them.
To handle this, Prometheus provides a component called PushGateway. This component allows short-lived jobs to push their metrics to the PushGateway. Prometheus then scrapes the metrics from the PushGateway at regular intervals.
PushGateway is recommended only for short-lived jobs and not for long-running services. It should be used sparingly, as it does not follow Prometheus’s standard pull model.
d. Service Discovery: In environments where infrastructure is dynamic (such as container orchestration systems like Kubernetes or cloud platforms like AWS), the list of targets can frequently change due to scaling, failures, or deployment changes.
Service Discovery allows Prometheus to automatically detect and keep track of available targets. Instead of manually updating the configuration each time a new service or instance is added, Prometheus can automatically discover these changes based on metadata, tags, or labels provided by the infrastructure platform.
This ensures that Prometheus always has an up-to-date list of targets to monitor, making it suitable for modern, dynamic systems.
e. Alertmanager: Alertmanager is a critical component in the Prometheus monitoring ecosystem, responsible for handling and managing the alerts that Prometheus generates. Once Prometheus detects a condition that triggers an alert, it forwards that alert to Alertmanager, which then takes care of organizing and delivering it effectively.
Alertmanager performs several key functions to reduce alert fatigue and ensure relevant notifications reach the appropriate recipients. Alert fatigue occurs when system administrators, developers, or on-call engineers are bombarded with excessive alerts from monitoring systems. This often leads to stress, burnout, or even ignoring alerts altogether. Over time, critical alerts can be overlooked or delayed in response, increasing the risk of downtime or unresolved issues.
Alertmanager perform following activites.
· Grouping: It intelligently groups related alerts together to avoid overwhelming users with a flood of individual notifications.
· Deduplication: It eliminates duplicate alerts that may be triggered by the same underlying issue.
· Silencing: It allows users to temporarily mute alerts for known issues that are already being addressed, preventing unnecessary noise.
· Throttling: It controls the frequency of notifications to avoid sending too many alerts in a short period.
· Notification Routing: It sends alerts to various configured destinations such as email, Slack, PagerDuty, or XMatters, based on rules and receiver preferences.
Overall, Alertmanager plays a vital role in ensuring that alerts are actionable, relevant, and delivered in a timely and manageable way.
f. Clients: Prometheus provides various interfaces and clients to interact with the collected data:
· Prometheus Web UI: A built-in web interface that allows users to run PromQL queries, visualize metrics, and inspect targets and alerting rules.
· Grafana: A popular open-source visualization tool that integrates with Prometheus. Grafana can be used to create dashboards and graphs for better visualization of metrics.
· API Clients: Prometheus exposes a RESTful API that can be used by external applications or scripts to query and interact with the stored metrics programmatically.
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