What is the difference between push-based and pull-based metrics collection?

In a pull-based system, the monitoring server (like Prometheus) periodically initiates HTTP requests to each target's metrics endpoint and fetches the current metric values. The monitoring server controls the scrape interval and decides which targets to scrape.

In a push-based system, applications and agents send metrics to a central aggregation point as they are generated. StatsD, the InfluxDB line protocol, and AWS CloudWatch all use push models. Applications call a client library that buffers metrics and periodically flushes them to the aggregation server.

Pull advantages: The monitoring server always knows if a target is down (a scrape failure is itself a signal). No need to configure agents with the server's address. Easier to scale by adding new scrapers. Health of monitoring is transparent — you can check the scrape job.

Push advantages: Works naturally for short-lived jobs (batch, serverless functions, CI pipelines) that may finish before a pull can happen. Works when the monitored target is behind a firewall and cannot be reached by the monitoring server. Lower latency — metrics appear at the server as soon as they are generated, not on the next scrape cycle.

Hybrid approaches exist: Prometheus uses the Pushgateway for short-lived jobs, and the OpenTelemetry Collector accepts both push (OTLP) and pull (scraping Prometheus endpoints) depending on configuration. Many organizations use push for application telemetry and pull for infrastructure metrics.

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