---
title: FAQ
sort_rank: 5
toc: full-width
---

# Frequently Asked Questions

## General

### What is Prometheus?

Prometheus is an open-source systems monitoring and alerting toolkit
with an active ecosystem. See the [overview](/docs/introduction/overview/).

### How does Prometheus compare against other monitoring systems?

See the [comparison](/docs/introduction/comparison/) page.

### What dependencies does Prometheus have?

The main Prometheus server runs standalone and has no external dependencies.

### Can Prometheus be made highly available?

Yes, run identical Prometheus servers on two or more separate machines.
Identical alerts will be deduplicated by the [Alertmanager](https://github.com/prometheus/alertmanager).

For [high availability of the Alertmanager](https://github.com/prometheus/alertmanager#high-availability),
you can run multiple instances in a
[Mesh cluster](https://github.com/weaveworks/mesh) and configure the Prometheus
servers to send notifications to each of them.

### I was told Prometheus “doesn't scale”.

There are in fact various ways to scale and federate
Prometheus. Read [Scaling and Federating Prometheus](https://www.robustperception.io/scaling-and-federating-prometheus/)
on the Robust Perception blog to get started.

### What language is Prometheus written in?

Most Prometheus components are written in Go. Some are also written in Java,
Python, and Ruby.

### How stable are Prometheus features, storage formats, and APIs?

All repositories in the Prometheus GitHub organization that have reached
version 1.0.0 broadly follow
[semantic versioning](http://semver.org/). Breaking changes are indicated by
increments of the major version. Exceptions are possible for experimental
components, which are clearly marked as such in announcements.

Even repositories that have not yet reached version 1.0.0 are, in general, quite
stable. We aim for a proper release process and an eventual 1.0.0 release for
each repository. In any case, breaking changes will be pointed out in release
notes (marked by `[CHANGE]`) or communicated clearly for components that do not
have formal releases yet.

### Why do you pull rather than push?

Pulling over HTTP offers a number of advantages:

* You can run your monitoring on your laptop when developing changes.
* You can more easily tell if a target is down.
* You can manually go to a target and inspect its health with a web browser.

Overall, we believe that pulling is slightly better than pushing, but it should
not be considered a major point when considering a monitoring system.

For cases where you must push, we offer the [Pushgateway](/docs/instrumenting/pushing/).

### How to feed logs into Prometheus?

Short answer: Don't! Use something like the [ELK stack](https://www.elastic.co/products) instead.

Longer answer: Prometheus is a system to collect and process metrics, not an
event logging system. The Raintank blog post
[Logs and Metrics and Graphs, Oh My!](https://blog.raintank.io/logs-and-metrics-and-graphs-oh-my/)
provides more details about the differences between logs and metrics.

If you want to extract Prometheus metrics from application logs, Google's
[mtail](https://github.com/google/mtail) might be helpful.

### Who wrote Prometheus?

Prometheus was initially started privately by
[Matt T. Proud](http://www.matttproud.com) and
[Julius Volz](http://juliusv.com). The majority of its
initial development was sponsored by [SoundCloud](https://soundcloud.com).

It's now maintained and extended by a wide range of companies and individuals.

### What license is Prometheus released under?

Prometheus is released under the
[Apache 2.0](https://github.com/prometheus/prometheus/blob/master/LICENSE) license.

### What is the plural of Prometheus?

After [extensive research](https://youtu.be/B_CDeYrqxjQ), it has been determined
that the correct plural of 'Prometheus' is 'Prometheis'.

### Can I reload Prometheus's configuration?

Yes, sending `SIGHUP` to the Prometheus process or an HTTP POST request to the
`/-/reload` endpoint will reload and apply the configuration file. The
various components attempt to handle failing changes gracefully.

### Can I send alerts?

Yes, with the [Alertmanager](https://github.com/prometheus/alertmanager).

Currently, the following external systems are supported:

* Email
* Generic Webhooks
* [HipChat](https://www.hipchat.com/)
* [OpsGenie](https://www.opsgenie.com/)
* [PagerDuty](http://www.pagerduty.com/)
* [Pushover](https://pushover.net/)
* [Slack](https://slack.com/)

### Can I create dashboards?

Yes, we recommend [Grafana](/docs/visualization/grafana/) for production
usage. There are also [Console templates](/docs/visualization/consoles/).

### Can I change the timezone? Why is everything in UTC?

To avoid any kind of timezone confusion, especially when the so-called
daylight saving time is involved, we decided to exclusively use Unix
time internally and UTC for display purposes in all components of
Prometheus. A carefully done timezone selection could be introduced
into the UI. Contributions are welcome. See
[issue #500](https://github.com/prometheus/prometheus/issues/500)
for the current state of this effort.

## Instrumentation

### Which languages have instrumentation libraries?

There are a number of client libraries for instrumenting your services with
Prometheus metrics. See the [client libraries](/docs/instrumenting/clientlibs/)
documentation for details.

If you are interested in contributing a client library for a new language, see
the [exposition formats](/docs/instrumenting/exposition_formats/).

### Can I monitor machines?

Yes, the [Node Exporter](https://github.com/prometheus/node_exporter) exposes
an extensive set of machine-level metrics on Linux and other Unix systems such
as CPU usage, memory, disk utilization, filesystem fullness, and network
bandwidth.

### Can I monitor network devices?

Yes, the [SNMP Exporter](https://github.com/prometheus/snmp_exporter) allows
monitoring of devices that support SNMP.

### Can I monitor batch jobs?

Yes, using the [Pushgateway](/docs/instrumenting/pushing/). See also the
[best practices](/docs/practices/instrumentation/#batch-jobs) for monitoring batch
jobs.

### What applications can Prometheus monitor out of the box?

See [the list of exporters and integrations](/docs/instrumenting/exporters/).

### Can I monitor JVM applications via JMX?

Yes, for applications that you cannot instrument directly with the Java client, you can use the [JMX Exporter](https://github.com/prometheus/jmx_exporter)
either standalone or as a Java Agent.

### What is the performance impact of instrumentation?

Performance across client libraries and languages may vary. For Java,
[benchmarks](https://github.com/prometheus/client_java/blob/master/benchmark/README.md)
indicate that incrementing a counter/gauge with the Java client will take
12-17ns, depending on contention. This is negligible for all but the most
latency-critical code.

## Troubleshooting

### My Prometheus server takes a long time to start up and spams the log with copious information about crash recovery.

You are suffering from an unclean shutdown. Prometheus has to shut down cleanly
after a `SIGTERM`, which might take a while for heavily used servers. If the
server crashes or is killed hard (e.g. OOM kill by the kernel or your runlevel
system got impatient while waiting for Prometheus to shutdown), a crash
recovery has to be performed, which should take less than a minute under normal
circumstances, but can take quite long under certain circumstances. See
[crash recovery](/docs/operating/storage/#crash-recovery) for details.

### My Prometheus server runs out of memory.

See [the section about memory usage](/docs/operating/storage/#memory-usage)
to configure Prometheus for the amount of memory you have available.

### My Prometheus server reports to be in “rushed mode” or that “storage needs throttling”.

Your storage is under heavy load. Read
[the section about configuring the local storage](/docs/operating/storage/)
to find out how you can tweak settings for better performance.

## Implementation

### Why are all sample values 64-bit floats? I want integers.

We restrained ourselves to 64-bit floats to simplify the design. The
[IEEE 754 double-precision binary floating-point
format](http://en.wikipedia.org/wiki/Double-precision_floating-point_format)
supports integer precision for values up to 2<sup>53</sup>. Supporting
native 64 bit integers would (only) help if you need integer precision
above 2<sup>53</sup> but below 2<sup>63</sup>. In principle, support
for different sample value types (including some kind of big integer,
supporting even more than 64 bit) could be implemented, but it is not
a priority right now. A counter, even if incremented one million times per
second, will only run into precision issues after over 285 years.

### Why does Prometheus use a custom storage backend rather than [some other storage method]? Isn't the "one file per time series" approach killing performance?

Initially, Prometheus ran completely on LevelDB, but to achieve better
performance, we had to change the storage for bulk sample data. We evaluated
many storage backends that were available at the time, without getting
satisfactory results. So we implemented exactly the parts we needed, while
keeping LevelDB for indexes and making heavy use of file system
capabilities. Obviously, we could not evaluate every single storage backend out
there, and storage backends have evolved meanwhile. However, the performance of
the solution implemented now is satisfactory for most use-cases. Our most
important requirements are an acceptable query speed for common queries and a
sustainable ingestion rate of hundreds of thousands of samples per second. The
latter depends on many parameters, like the compressibility of the sample data,
the number of time series the samples belong to, the retention policy, and even
more subtle aspects like how full your SSD is. If you want to know all the
details, read
[this document with detailed benchmark results](https://docs.google.com/document/d/1lRKBaz9oXI5nwFZfvSbPhpwzUbUr3-9qryQGG1C6ULk/edit?usp=sharing). The highlights:

* On a typical bare-metal server with 64GiB RAM, 32 CPU cores, and SSD,
  Prometheus sustained an ingestion rate of 900k samples per second, belonging
  to 1M time series, scraped from 720 targets.

* On a server with HDD and 128GiB RAM, Prometheus sustained an ingestion rate
  of 250k samples per second, belonging to 1M time series, scraped from 720
  targets.

Running out of inodes is unlikely in a usual set-up. However, if you have a lot
of short-lived time series, or you have configured your file system with an
unusual low amount of inodes, you might run into inode depletion. Also, if you
want to delete Prometheus's storage directory, you will notice that some file
systems are very slow when deleting a large number of files.

### Why don't the Prometheus server components support TLS or authentication? Can I add those?

While TLS and authentication are frequently requested features, we have
intentionally not implemented them in any of Prometheus's server-side
components. There are so many different options and parameters for both (10+
options for TLS alone) that we have decided to focus on building the best
monitoring system possible rather than supporting fully generic TLS and
authentication solutions in every server component.

If you need TLS or authentication, we recommend putting a reverse proxy in
front of Prometheus. See, for example [Adding Basic Auth to Prometheus with
Nginx](https://www.robustperception.io/adding-basic-auth-to-prometheus-with-nginx/).

This applies only to inbound connections. Prometheus does support
[scraping TLS- and auth-enabled targets](/docs/operating/configuration/#%3Cscrape_config%3E), and other
Prometheus components that create outbound connections have similar support.
