by Tega AkuruliMonitoring Application Performance with Prometheus
Monitoring is essential. Whether you’re managing a monolith or a microservices architecture, understanding how your application behaves in production is critical. Prometheus is an open-source monitoring tool designed for real-time performance tracking, metric scraping, and alerting.
In this article, you’ll learn how Prometheus works, how to integrate it with your application, and how to set up custom alerts and dashboards.
Why Prometheus?
- Time-series database: It collects data as timestamped metrics.
- Powerful query language: PromQL allows for filtering and aggregation.
- Alerting system: It works with Alertmanager for threshold-based notifications.
- Ecosystem friendly: It supports Grafana, Kubernetes, Docker, Node.js, Python, and more.
Core Concepts in Prometheus
- Metrics: Key-value pairs that represent application data (e.g., http_requests_total).
- Jobs: Groups of endpoints to scrape, like a web app or database.
- Targets: Specific IPs and ports that Prometheus scrapes for data.
- Exporters: Tools that expose metrics from services, such as Node Exporter and Blackbox Exporter.
- PromQL: Prometheus Query Language used to extract and analyze data.
Installing Prometheus (Standalone)
For local development:
# Download and extract
wget https://github.com/prometheus/prometheushttps://
tar -xvzf prometheus-*.tar.gz
cd prometheus-*
# Start Prometheus
./prometheus –config.file=prometheus.yml
Basic prometheus.yml Configuration
global:
scrape_interval: 15s
scrape_configs:
– job_name: ‘my_app’
static_configs:
– targets: [‘localhost:3000’]
This config tells Prometheus to scrape localhost:3000 every 15 seconds.
Instrumenting Your Application
In Node.js using prom-client:
npm install prom-client
const client = require(‘prom-client’);
const counter = new client.Counter({
name: ‘http_requests_total’,
help: ‘Total number of HTTP requests’,
});
app.get(‘/’, (req, res) => {
counter.inc();
res.send(‘Hello World!’);
});
app.get(‘/metrics’, async (req, res) => {
res.set(‘Content-Type’, client.register.contentType);
res.send(await client.register.metrics());
});
Prometheus will now scrape your metrics from /metrics.
Creating Dashboards with Grafana
- Install Grafana.
- Add Prometheus as a data source.
- Import prebuilt dashboards from Grafana.com.
- Visualize request rates, error counts, response times, and CPU/memory usage.
Setting Up Alerts with Alertmanager
1. Define alert rules in prometheus.yml:
groups:
– name: example
rules:
– alert: HighErrorRate
expr: rate(http_requests_total{status=”500″}[5m]) > 0.05
for: 1m
labels:
severity: critical
annotations:
summary: “High error rate detected”
2. Connect Alertmanager to Slack, email, or SMS for real-time notifications.
Use Cases
- Track application uptime and API error rates.
- Observe memory, CPU, and disk usage.
- Alert on failed background jobs.
- Monitor Kubernetes pods and nodes.
Prometheus is more than just a monitoring tool. It builds the foundation of observability in modern cloud-native applications. Together with Grafana and Alertmanager, it gives you full control over your system’s behavior and how quickly you respond when issues arise.