<p>Prometheus stores time series in memory and on local disk in an efficient custom format. Scaling is achieved by functional sharding and federation.</p>
<p>Prometheus stores time series in memory and on local disk in an efficient custom format. Scaling is achieved by functional sharding and federation.</p>
<p>Each server is independent for reliability, relying only on local storage. Written in Go, all binaries are statically linked and easy to deploy.</p>
<p>Alerts are defined based on Prometheus's flexible query language and maintain dimensional information. An alertmanager handles notifications and silencing.</p>
</a>
</div>
<divclass="col-md-3 feature-item">
<ahref="/docs/instrumenting/clientlibs/">
<h2><iclass="fa fa-code"></i> Many client libraries</h2>
<p>Client libraries allow easy instrumentation of services. Currently, Go, Java, and Ruby are supported. Custom libraries are easy to implement.</p>
</a>
</div>
<divclass="col-md-3 feature-item">
<ahref="/docs/instrumenting/exporters/">
<h2><iclass="fa fa-cloud-upload"></i> Many integrations</h2>
<p>Existing exporters allow bridging of third-party data into Prometheus. Examples: system statistics, as well as Docker, HAProxy, StatsD, and JMX metrics. </p>
<p>Each server is independent for reliability, relying only on local storage. Written in Go, all binaries are statically linked and easy to deploy.</p>
<p>Alerts are defined based on Prometheus's flexible query language and maintain dimensional information. An alertmanager handles notifications and silencing.</p>
<h2><iclass="fa fa-cloud-upload"></i> Many integrations</h2>
<p>Existing exporters allow bridging of third-party data into Prometheus. Examples: system statistics, as well as Docker, HAProxy, StatsD, and JMX metrics. </p>