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Overview
Collects metrics from your services on a schedule, stores them as time series, evaluates rules over them and raises alerts. For teams that run and watch systems. Written in Go.
prometheus is an open-source project on GitHub in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Install it from GitHub as its README says. Get Mindket’s setup notes on your Mindket account, as a zip.
At a glance
- Runs in
- A server you run yourself, with no distributed storage needed
- Graphs and dashboards, in several modes
- Several servers linked by hierarchical or horizontal federation
- Start with
git clone https://github.com/prometheus/prometheus.git cd prometheus
Platform
Server
About
What it is
Prometheus is a monitoring system and a time series database. It collects metrics from the targets you configure at set intervals, evaluates rule expressions, shows the results and can raise alerts when a condition is met. It belongs to the Cloud Native Computing Foundation.
Who it suits
Prometheus suits teams that run services and need to see how they behave, such as site reliability engineers, DevOps teams and developers.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Software operations | Site reliability and DevOps teams | Watch service metrics and set alerts | Raising an alert when a measured value crosses a limit they chose |
| Cloud platforms | Platform engineers | Let it find targets automatically | Picking up new targets without editing a list by hand |
| Batch processing | Owners of short jobs | Push metrics through an intermediary gateway | A short batch job sending its metrics through the gateway |
| Application development | Developers | Query metrics with PromQL | Slicing a metric by its key and value dimensions |
Anyone who does not run or measure services can skip it.
Where to use it
Prometheus runs as a server you host yourself, and its results show up in graphs and dashboards.
- A server you run yourself, with no distributed storage needed
- Graphs and dashboards, in several modes
- Several servers linked by hierarchical or horizontal federation
| Use case | Who | What they get back |
|---|---|---|
| Metrics collection | Operations teams | Time series stored by metric name and key and value dimensions |
| Alerting | On-call engineers | Alerts when the conditions your rules describe are observed |
| Querying | Developers | PromQL results, graphed or placed on dashboards |
How to set it up
Several ways to install Prometheus exist. One route is a precompiled binary of a released version.
- Download a precompiled binary for a released version from the download section of the project's website, or copy the source with git.
- List your targets, either as static configuration or by letting it find them automatically.
- Start the server and follow the project's documentation for the rest.
Run these in a terminal:
# Copy the project to your computer git clone https://github.com/prometheus/prometheus.git # Go into its folder cd prometheus
How to use it
You write PromQL queries over your metrics, set rule expressions for alerts and view the results in graphs and dashboards. These parts do the main work:
| Tool | What it does |
|---|---|
| PromQL | Query language that works over metrics and their key and value dimensions |
| Rule expressions | Evaluated on collected metrics to trigger alerts |
| Intermediary gateway | Takes pushed time series from batch jobs |
| Automatic target lookup | Finds targets without a fixed list, as an alternative to static configuration |
| Federation | Links servers in a hierarchy or side by side |
Example
A team wants to know when a service passes a limit they set. They write a rule expression over its metrics, and Prometheus triggers an alert when the condition is observed.
For newcomers and experts
Prometheus keeps a running record of numbers from your systems, such as how busy a service is, and warns you when something looks wrong. A first small step is to point it at one target and look at what it collects.
It pulls metrics over HTTP, so the server asks each target on a schedule. A series is a metric name plus key and value dimensions, which PromQL can slice. Single server nodes are autonomous with no distributed storage, and federation links servers when one is not enough.
- Targets expose metrics over HTTP
- Prometheus pulls them at set intervals
- It stores them as time series
- Rules and PromQL queries read the series
- Graphs, dashboards and alerts come out
Good to know
This kit holds notes and a pointer to the code, so nothing runs by itself.
- License: Apache-2.0
- Cost to run: none named
- Data it reaches: the metrics of the targets you configure, pulled over HTTP, and any time series pushed through the gateway
README and files
prometheus
Collects metrics from your services on a schedule, stores them as time series, evaluates rules over them and raises alerts. For teams that run and watch systems. Written in Go.
Made by prometheus on GitHub. These notes are Mindket's, written from its README; the project's own files and license are in its repository.
About
What it is: Prometheus is a monitoring system and a time series database. It collects metrics from the targets you configure at set intervals, evaluates rule expressions, shows the results and can raise alerts when a condition is met. It belongs to the Cloud Native Computing Foundation.
Who it suits: Prometheus suits teams that run services and need to see how they behave, such as site reliability engineers, DevOps teams and developers.
Industry | Who uses it | How they use it | Example
Software operations | Site reliability and DevOps teams | Watch service metrics and set alerts | Raising an alert when a measured value crosses a limit they chose
Cloud platforms | Platform engineers | Let it find targets automatically | Picking up new targets without editing a list by hand
Batch processing | Owners of short jobs | Push metrics through an intermediary gateway | A short batch job sending its metrics through the gateway
Application development | Developers | Query metrics with PromQL | Slicing a metric by its key and value dimensionsAnyone who does not run or measure services can skip it.
Where to use it: Prometheus runs as a server you host yourself, and its results show up in graphs and dashboards.
- A server you run yourself, with no distributed storage needed
- Graphs and dashboards, in several modes
- Several servers linked by hierarchical or horizontal federation
Use case | Who | What they get back
Metrics collection | Operations teams | Time series stored by metric name and key and value dimensions
Alerting | On-call engineers | Alerts when the conditions your rules describe are observed
Querying | Developers | PromQL results, graphed or placed on dashboardsHow to set it up: Several ways to install Prometheus exist. One route is a precompiled binary of a released version.
- Download a precompiled binary for a released version from the download section of the project's website, or copy the source with git.
- List your targets, either as static configuration or by letting it find them automatically.
- Start the server and follow the project's documentation for the rest.
How to use it: You write PromQL queries over your metrics, set rule expressions for alerts and view the results in graphs and dashboards. These parts do the main work:
Tool | What it does
PromQL | Query language that works over metrics and their key and value dimensions
Rule expressions | Evaluated on collected metrics to trigger alerts
Intermediary gateway | Takes pushed time series from batch jobs
Automatic target lookup | Finds targets without a fixed list, as an alternative to static configuration
Federation | Links servers in a hierarchy or side by sideExample: A team wants to know when a service passes a limit they set. They write a rule expression over its metrics, and Prometheus triggers an alert when the condition is observed.
For newcomers and experts: Prometheus keeps a running record of numbers from your systems, such as how busy a service is, and warns you when something looks wrong. A first small step is to point it at one target and look at what it collects.
It pulls metrics over HTTP, so the server asks each target on a schedule. A series is a metric name plus key and value dimensions, which PromQL can slice. Single server nodes are autonomous with no distributed storage, and federation links servers when one is not enough.
Targets expose metrics over HTTP
Prometheus pulls them at set intervals
It stores them as time series
Rules and PromQL queries read the series
Graphs, dashboards and alerts come outGood to know: This kit holds notes and a pointer to the code, so nothing runs by itself.
- License: Apache-2.0
- Cost to run: none named
- Data it reaches: the metrics of the targets you configure, pulled over HTTP, and any time series pushed through the gateway
On GitHub, 7 November 2026
- Stars: 67,195 (148 that day)
- Forks: 10,988
- Watching: 1,158
- Open issues and pull requests: 1,075
- Language: Go
- License: Apache-2.0
- Topics: alerting, graphing, hacktoberfest, metrics, monitoring, prometheus, time-series
- Trending: #9 repository of the day on GitHub trending (7 November 2026)
Links
- Code: https://github.com/prometheus/prometheus
- Website: https://prometheus.io/
- Releases: https://github.com/prometheus/prometheus/releases
- Issues: https://github.com/prometheus/prometheus/issues
- Star history: https://www.star-history.com/#prometheus/prometheus&Date
Get the code
git clone https://github.com/prometheus/prometheus.gitThen follow the setup in its README. Nothing in this kit runs by itself.
README.md 5 KB
What’s new
Reviews
What people say
Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search and on Trendshift. Mindket doesn’t write or check them. Open one to read it where it was posted.
valyalaAre Prometheus and Thanos developers against fair competition?Hi all. I'm the core developer of VictoriaMetrics - open source time series database, which can be used as remote storage for Prometheus monitoring system. It implements opinionated query language, which is backwards compatible with PromQL from Prometheus. Is it called Extended PromQL [1]. It…8 points · 17 repliesAmbrosia 🔞really annoying millennial giantess sees a crowd of tiny people running from her in a straight line and goes “*ding* prometheus school of running away from things” before crushing them all45 likes · 3 repliest-writescodeAsk HN: Prometheus vs. StatsD / TelegrafI see a lot of people talk about Prometheus on here and speak about it as though it's the only metrics gathering solution. In this way, it really does seem like it has become the poster child of Hacker News and metrics gathering. I've used both Prometheus and the Telegraf / StatsD solutions; and,…5 points · 2 repliessnowDetail of relief with Prometheus modeling the first man, accompanied by Athena bringing it to life, from a fragment of a Roman sarcophagus31 likes · 1 replyAvicebronWe're Living Through the AI Utopia and Can't See ItWe need a moratorium on prometheus and prometheus-related metaphors, references, and general self-aggrandizing hobgoblinery. It was worn to the bone by 2015.Lisandra bravePrometheus, 10 seconds before being chained to the rock26 likesbbrazilBosun – open-source monitoring and alerting system by Stack ExchangeWe'd like it to run on Windows, however none of the core developers use Windows. https://github.com/prometheus/prometheus/issues/505 We haven't head back recently, so it's possible it's all working now.Hannah Stronghello my book is out in a month. idk if it's going to get any coverage because i haven't heard anything from the publisher lol. but if you would like to review it or interview me about it let me know! it looks cool! www.abramsbooks.com/product/mode...23 likes · 2 repliesbbrazilSetting Go variables from the outsideWe've been doing this in our makefiles and exposing it to the user https://github.com/prometheus/prometheus/blob/0e383b0b9f4ff0... Cloudflare have been putting out quite a few high-quality posts recently.herta müller ultrawenn prometheus uns damals nicht das feuer gebracht hätte könnten wir heute nicht lecker zikrette rauchen denkt mal drüber nach18 likes · 2 repliesjrvThoughts on Time-series DatabasesIf you don't need to keep data forever, but only several weeks or months, and you only need numeric time series data and not raw event logs, Prometheus (http://prometheus.io/) is your friend. Since it's optimized towards purely numeric time series (with arbitrary labeled dimensions), it currently…Cake Bake Jake 🍰Such a great view up by Mount Prometheus!20 likes
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