> ## Documentation Index
> Fetch the complete documentation index at: https://metoro.io/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Metrics Overview
Metrics are a great way to understand the performance and internal characteristics of your services and infrastructure.
## Metoro Produced Metrics
Metoro automatically generates a large number of metrics from your services and infrastructure. These metrics are collected by the in-cluster agents and provide detailed information about the performance of your services and infrastructure. This includes things like
These are collected by the in-cluster agents and provide detailed information about the performance of your services and infrastructure. This includes things like:
* Network metrics at the container level
* Disk metrics at the container level
* CPU metrics at the container level
* Memory metrics at the container level
* Node level metrics
* And many many more...
You can check out all of the available metrics in the [metric explorer](https://demo.us-east.metoro.io/metric-explorer?chart=%7B%22startTime%22%3A1731371066%2C%22endTime%22%3A1731371966%2C%22metricName%22%3A%22container_net_tcp_active_connections%22%2C%22filters%22%3A%7B%22dataType%22%3A%22Map%22%2C%22value%22%3A%5B%5D%7D%2C%22excludeFilters%22%3A%7B%22dataType%22%3A%22Map%22%2C%22value%22%3A%5B%5D%7D%2C%22splits%22%3A%5B%5D%2C%22metricType%22%3A%22metric%22%2C%22type%22%3A%22line%22%2C%22functions%22%3A%5B%5D%2C%22aggregation%22%3A%22avg%22%7D\&tab=catalog\&startEnd=)
For a complete list of metrics that Metoro automatically generates, see [Default Metrics](/metrics/generated-metrics) or look at the [metric explorer](https://demo.us-east.metoro.io/metric-explorer) in platform.
## Custom Metrics
In addition to the automatically generated metrics, you can also send your own custom metrics to Metoro using OpenTelemetry. See [Custom Metrics](/metrics/custom-metrics) for details on how to send custom metrics to Metoro.
Learn how to send your own metrics to Metoro
## MetoroQL
Metoro provides a powerful query language called MetoroQL for working with metrics and other observability data. MetoroQL is designed to be familiar to users of PromQL but with enhanced capabilities:
* Query not just metrics, but also logs, traces, and Kubernetes resources with a unified syntax
* Simplified counter handling that doesn't require `rate()` or `increase()` functions
* Advanced filtering and correlation capabilities across different data types
MetoroQL is used throughout Metoro's UI, including in dashboards, charts, and alerts.
Learn how to query observability data with MetoroQL
## PromQL
Metoro also supports PromQL as an alpha query mode for metric dashboard widgets. This is useful when you want to reuse existing Prometheus or Grafana queries, but native MetoroQL remains the recommended path for best correctness, performance, and broader observability queries.
Learn how to use PromQL queries in Metoro dashboards
## Searching and Filtering Metrics
Metoro provides powerful search capabilities for your metrics. You can filter metrics using:
* Metric names
* Label values
* Time ranges
* Regular expressions
For any metric label, you can use regex search with the syntax `label = regex: `. For example:
* `service.name = regex: .*metoro.*` will match metrics from any service containing "metoro"
* `container.name = regex: ^api-.*` will match containers starting with "api-"
* `kubernetes.namespace = regex: prod|staging` will match namespaces "prod" or "staging"
## Units
Metoro uses the UCUM (Unified Code for Units of Measure) standard for metric units, providing consistent unit representation across all metrics. Units can be configured at multiple levels with a flexible precedence system.
Learn how to work with units in Metoro
## Dashboarding
Metoro supports custom [dashboarding](/dashboards/overview) to help you gain insights into your services and infrastructure. See [Dashboards](/dashboards/overview) for more details.