Prometheus
- Prometheus Server Configuration
This article details the configuration of a Prometheus server, a leading open-source systems monitoring and alerting toolkit. It is aimed at system administrators and engineers new to deploying Prometheus within our infrastructure. We will cover installation, configuration, and basic usage. This guide assumes a Debian/Ubuntu-based system, but principles apply to other distributions.
== Introduction to Prometheus
Prometheus collects metrics from configured target services by scraping HTTP endpoints. These metrics are stored as time-series data and can be queried using the Prometheus Query Language (PromQL). Prometheus excels at alerting based on these metrics and provides visualization capabilities through its built-in expression browser and integration with tools like Grafana. Understanding the core components is crucial for effective monitoring. See also our article on Time Series Databases for broader context.
== Installation
The following steps outline the installation process on a Debian/Ubuntu system.
1. Download the latest Prometheus release from the official Prometheus Download Page. 2. Extract the archive: `tar -xzf prometheus-*.tar.gz` 3. Create a dedicated user: `sudo useradd --system --no-create-home prometheus` 4. Move the extracted files: `sudo mv prometheus-* /opt/prometheus` 5. Change ownership: `sudo chown -R prometheus:prometheus /opt/prometheus`
== Core Configuration (prometheus.yml)
The `prometheus.yml` file is the heart of your Prometheus setup. It defines scraping configurations, global settings, and alert rules. A basic configuration looks like this:
| Section | Description |
|---|---|
| `global` | Defines global settings like scrape interval and evaluation interval. |
| `scrape_configs` | Lists the jobs Prometheus will scrape. Each job defines a target and how to scrape it. |
| `rule_files` | Specifies alert rule files. |
Here’s an example `prometheus.yml` file:
```yaml global:
scrape_interval: 15s evaluation_interval: 15s
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['localhost:9090']
- job_name: 'node_exporter'
static_configs:
- targets: ['node-exporter-server:9100']
```
This configuration scrapes Prometheus itself and a `node_exporter` instance. You'll need to adjust the `targets` to match your environment. Refer to the Prometheus Configuration Documentation for detailed options. Incorrect configuration can lead to data loss or inaccurate monitoring, so review carefully.
== Storage Configuration
Prometheus stores data locally on disk. The performance and capacity of this storage are important considerations.
| Parameter | Description | Recommended Value |
|---|---|---|
| `storage.tsdb.path` | Path to the time series database directory. | `/opt/prometheus/data` |
| `storage.tsdb.retention` | Data retention period. | `15d` (15 days) |
| `storage.tsdb.wal.fsync` | Whether to fsync the WAL (Write-Ahead Log). | `true` (for data safety) |
Adjust the retention period based on your storage capacity and monitoring requirements. Increasing the retention period requires more disk space. See the Prometheus Storage Documentation for more details on storage optimization. Consider the impact of `fsync` on performance.
== Alerting Configuration
Prometheus's alerting capabilities are configured through alert rules. These rules define conditions that, when met, trigger alerts. Alerts can be sent to various receivers like email, PagerDuty, or Slack.
| Component | Description | Example |
|---|---|---|
| `alerts` | Defines the alert rules. | `ALERT HighCPUUsage When CPU_USAGE > 90` |
| `receivers` | Defines the alert receivers. | `email: '[email protected]'` |
| `route` | Defines how alerts are routed to receivers. | `receiver: 'email'` |
Alert rules are written in PromQL. The example above triggers an alert named `HighCPUUsage` when the `CPU_USAGE` metric exceeds 90%. Refer to the Prometheus Alerting Documentation for more information on creating and managing alert rules. Properly configured alerts are essential for proactive issue resolution.
== Running Prometheus
To start Prometheus, run the following command:
`sudo -u prometheus /opt/prometheus/prometheus --config.file=/opt/prometheus/prometheus.yml`
You can then access the Prometheus web UI at `http://localhost:9090`. Consider using a process manager like systemd to ensure Prometheus restarts automatically on failure. See our article on Systemd Service Configuration for details. Remember to check the logs for any errors.
== Additional Resources
- PromQL Documentation
- Prometheus Node Exporter
- Grafana Integration
- Alertmanager Configuration
- Prometheus Best Practices
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️