Prometheus
prometheus.io › docs › tutorials › understanding_metric_types
Understanding metric types | Prometheus
They are used when the buckets of a metric are not known beforehand, but it is highly recommended to use histograms over summaries whenever possible. In this tutorial, we covered the types of metrics in detail and a few PromQL operations like rate, histogram_quantile, etc.
Prometheus
prometheus.io › docs › concepts › metric_types
Metric types | Prometheus
The Prometheus instrumentation libraries offer four core metric types. With the exception of native histograms, these are currently only differentiated in the API of instrumentation libraries and in the exposition protocols. The Prometheus server does not yet make use of the type information and flattens all types except native histograms into untyped time series of floating point values.
DataDog Custom Metrics
What an absolute mess DD's custom metrics are. Have they guilded the dumpster fire over and over? New Relic's costs are such a breath of fresh air. All data charged at the same rate is simply much more understandable. More on reddit.com
How does prometheus monitoring work?
Save yourself some money, visualize it in grafana. The way the Prometheus works, you have a server ( which actually is the client) which is configured to call all the endpoints it can discover. The real power in Prometheus is its Dynamic Discovery Framework that allow you to have a configuration that talks to other things that actually get the list of instances. It can be kubernetes, it can be AWS API, whatever. Once you have a configuration of targets that's dynamically populated, the client( server, the main thing ) reaches out to all the clients( actually the servers, also known as exporters) which just sit there listening for connections to expose data to. the main process collects the data under its data dir, and also has a rudimentary interface to allow query and expose config and state information. More on reddit.com
How do you define a new metric type in Prometheus?
You cannot define new metric types beyond the standard four. You can define custom metrics using the existing types through client libraries, setting up counters, gauges, histograms (with configurable buckets), or summaries for your needs.
last9.io
last9.io › blog › prometheus-metrics-types-a-deep-dive
Prometheus Metrics Types - A Deep Dive | Last9
What are the types of metrics in Prometheus?
Prometheus supports four metric types: Counter, Gauge, Histogram, and Summary. Each type offers distinct capabilities for tracking different system behaviors.
last9.io
last9.io › blog › prometheus-metrics-types-a-deep-dive
Prometheus Metrics Types - A Deep Dive | Last9
How does the Prometheus counter metric type work?
A counter increases monotonically. It tracks events like API hits, background job runs, or errors. When the process restarts, the counter resets, but functions like rate() account for the reset.
last9.io
last9.io › blog › prometheus-metrics-types-a-deep-dive
Prometheus Metrics Types - A Deep Dive | Last9
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4 Essential Metric Types in Data Monitoring Explained Simply - YouTube
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Understanding Prometheus Metrics Types-Counter, Gauge, Histogram, ...
Understanding Prometheus Metric Types | Meaning and ...
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Prometheus Metrics Types with Real Life Examples | Counter, Gauge, ...
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How Prometheus Works - How to Collect Metrics - YouTube
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Prometheus Custom Metrics - YouTube
Better Stack
betterstack.com › community › guides › monitoring › prometheus-metrics-explained
A Practical Guide to Prometheus Metric Types | Better Stack Community
The table below summarizes the differences between the two metric types: ... You need to aggregate quantiles across multiple instances. You want the flexibility to calculate different quantiles or use different time windows later on. You are monitoring system-wide Service Level Objectives (SLOs). ... You are monitoring a single instance or service. You need high precision for specific quantiles with low server-side overhead. Aggregation is not required or practical. ... Prometheus is a powerful monitoring tool, but it can struggle to keep up as your systems grow.
Chronosphere
chronosphere.io › home › an introduction to the 4 primary prometheus metrics types
An introduction to the 4 primary Prometheus metrics types
April 2, 2025 - These metric types fulfill the needs or requirements for most use cases, and are found in Prometheus’ official client libraries: Go, Java, Ruby, and Python. Note: each client library has its own documentation on how to use each metric type with the corresponding client library API. This blog explains Prometheus’ four primary metric types, covers when and how to use them, and gives resources for implementation.
Dash0
dash0.com › home › knowledge base › understanding the prometheus metric types
Understanding the Prometheus Metric Types · Dash0
July 21, 2025 - We’ll move beyond the trivial examples and dive deep into what each metric type is, when to use it, and, most importantly, the common pitfalls that turn promising monitoring setups into dumpster fires. Forget the hand-waving; let’s get our hands dirty. Before you can use a tool, you must understand its model of the world. In Prometheus, everything is a time series: a stream of timestamped values belonging to the same metric and the same set of labeled dimensions.
client_java
prometheus.github.io › client_java › getting-started › metric-types
Metric Types | client_java
The Prometheus Java metrics library ... standard: Counter Gauge Histogram Custom Bucket Boundaries Native Histograms with Custom Buckets (NHCB) Summary Info StateSet GaugeHistogram and Unknown Counter Counter is the most common and useful metric type....
DZone
dzone.com › coding › tools › understanding prometheus metric types: a guide for beginners
Understanding Prometheus Metric Types: A Guide for Beginners
December 9, 2024 - It's perfect for tracking things that only increase, like total API requests, error counts, or tasks completed. When a counter resets to zero (like during a system restart), Prometheus can detect this reset and handle calculations correctly. Counters are the simplest metric type and should be used whenever you're counting the total occurrences of something.
Promlabs
promlabs.com › blog › 2020 › 09 › 25 › metric-types-in-prometheus-and-promql
PromLabs | Blog - Metric Types in Prometheus and PromQL
September 25, 2020 - Metric types are most visible when you are instrumenting a service using one of the Prometheus client libraries, as each metric type's API object offers you methods specific to that type. Using the Prometheus Go client library as an example, let's take a look at how these types differ in usage.