Prometheus - A widely used monitoring and alerting toolkit for real-time metrics tracking and incident detection. https://github.com/prometheus/prometheus

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Prometheus is an open-source monitoring and alerting toolkit originally built at SoundCloud. It has become a popular choice for monitoring containerized applications and microservices, particularly within the Kubernetes ecosystem. Prometheus excels in collecting, storing, and querying time-series data, providing insights into system performance, resource utilization, and application health.

• **Time-Series Data Model:** Prometheus stores metrics as time series data, where each metric is identified by a name and a set of key-value pairs called labels. This allows for flexible and powerful querying and aggregation of data.
• **Pull-Based Metrics Collection:** Prometheus pulls metrics from instrumented applications or exporters at regular intervals, simplifying deployment and scaling.
• **PromQL:** Prometheus provides a powerful query language (PromQL) for querying and aggregating time-series data, enabling you to create custom dashboards, alerts, and visualizations.
• **Alerting:** Prometheus includes an alerting manager that can send notifications based on user-defined alert rules.
• **Service Discovery:** Prometheus supports various service discovery mechanisms, including Kubernetes, allowing it to automatically discover and monitor targets as they are deployed.

• **Scalability:** Prometheus's architecture is designed for scalability, handling large volumes of metrics data from distributed systems.
• **Flexibility:** The time-series data model and PromQL provide flexibility in querying and analyzing metrics data.
• **Extensibility:** Prometheus has a vast ecosystem of exporters and integrations, making it easy to collect metrics from various sources and integrate with other tools.
• **Kubernetes Integration:** Prometheus natively integrates with Kubernetes, making it a popular choice for monitoring containerized applications and microservices.

While Prometheus configuration primarily involves YAML files and PromQL queries, here's a simple example of a Prometheus alert rule:

```yaml groups: - name: example

 rules:
 - alert: HighCPUUsage
   expr: node_cpu_seconds_total{mode="idle"} / node_cpu_seconds_total * 100 < 10
   for: 5m
   labels:
     severity: warning
   annotations:
     summary: "High CPU usage on {{ $labels.instance }}"
     description: "{{ $labels.instance }} has had high CPU usage for the past 5 minutes."

This rule triggers an alert when the CPU usage of a node falls below 10% for 5 minutes.

• **Prometheus Official Website:** s://prometheus.io/(https://prometheus.io/)
• **Prometheus GitHub Repository:** s://github.com/prometheus/prometheus(https://github.com/prometheus/prometheus)
• **Prometheus Documentation:** s://prometheus.io/docs/introduction/overview/(https://prometheus.io/docs/introduction/overview/)

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