Prometheus
What is Prometheus
Prometheus is a server-based monitoring system where typically, you run one instance per environment.
- Cross-platform, works with Linux and Windows
- Gather metrics exposed in your systems
- Provides metrics on CPU, memory, disk use, etc.
- Stores this data in a time-series database on the same server.
Time-series data
- This means that all metrics recorded have a timestamp.
- This makes it easier to see trends and spikes over a period of time.
- Timestamps are added when the data is fetched.
- This makes them easy to query using time ranges.
PromQL
- Prometheus also has its own query language called PromQL.
- This is because time-series data doesn’t work well with standard SQL.
- Queries can be ran using the HTTP API running in the server.
Server Configurations
- Server configurations can be viewed through the web UI on the server.
- The Web UI can be used for administrative tasks, like verifying reachability of the monitored systems.
- The web UI is limited and not a comprehensive dashboard.
- For a complete system health view, connect Grafana to Prometheus to visualize data.
- In-built alerting system to set rules for sending emails or creating tickets when triggered.
Exporters
To monitor systems with Prometheus, you need to run an exporter on each system.
- The exporter creates an HTTP endpoint that provides metrics.
- Metrics are then collected and stored by the Prometheus server a regular schedule.
- Prometheus doesn’t interpret what the system or metrics represent.
- It simply collects them in a standardized format.
- It can monitor various systems, including:
- Websites running on Windows
- Batch processes on Linux
- Servers on both Windows and Linux
For example, to monitor a Linux server, you would run a node exporter on it. This exporter provides an HTTP endpoint that returns all current metric values in the Prometheus format.
<metric name>{<label name>=<label value>, ...}
An example of a time series could be an entry with the metric name api_http_requests_total and the labels method="POST" and handler="/messages".
api_http_requests_total{method="POST", handler="/messages"}
The entire monitoring stack runs on a single, lightweight server. Additionally, many exporters, developed by the community or the Prometheus project, are available for various use cases, including:
- Databases
- Message queues
- Cloud services
- Hardware, etc.
For application-level metrics, Prometheus also supports several client libraries, including:
- Python
- Node.js
- Go
- Java
- Microsoft .NET