Explore documentation
  1. Welcome to Telemetry 👋
  2. Quick start guide
  3. Wide events vs. metrics
  4. Ingesting data
    1. Better Stack collector
    2. OpenTelemetry
    3. Vector
    4. Ingesting via HTTP API
    5. Ingesting metrics
    6. Ingesting logs
    7. Migrating to Better Stack
  5. Using the product
    1. AI SRE ↗
    2. MCP server ↗
    3. Transforming ingested data
    4. Querying data
      1. Live tail
      2. Events
      3. Dashboards
        1. Get started
        2. Writing SQL queries
        3. Query variables
        4. Querying histograms
        5. GeoIP map visualization
        6. Simplified PromQL
        7. Pipelined Query Language
        8. Transforming query results with JavaScript
        9. Dashboard JSON
        10. Schema migration Feb '26
      4. SQL API
      5. Query boost
      6. Faster queries
      7. Host data in own bucket
    5. Tracing
    6. Grafana
    7. Alerts
  6. Telemetry API
    1. Getting an API token
    2. Sources & collectors
    3. Dashboards
    4. Explorations
    5. Alerts API
    6. Connections API
    7. Query API ↗
  7. Alternative to
    1. Lightstep

Simplified PromQL

Getting started

Create your first chart using a PromQL query. Start by creating a dashboard in Dashboards → Create dashboard.

Create a new chart on your dashboard and use a query like the one below:

Average rate of http requests
avg(rate(http_requests_total))

Want to query logs instead of metrics?

Simplified PromQL can only query metrics. To query logs, use SQL queries instead.

PromQL is designed for querying time series data. In Better Stack, we've adapted a subset of PromQL to work with log data, allowing you to leverage some of your existing PromQL knowledge. Note that our implementation currently has some limitations:

  1. The only supported function is rate().
  2. Some of the more advanced queries may not be supported yet.

Supported operations

Better Stack supports the following PromQL operations:

  • Basic metric selection
  • Label matching (e.g., {label="value"})
  • Aggregation operators with by and without clauses
  • The rate() function
  • Mathematical operations between series with the same tags

Aggregation operators include:

  • sum: Calculate the sum of elements in the vector
  • avg: Calculate the average of elements in the vector
  • min: Select the minimum element of the vector
  • max: Select the maximum element of the vector
  • count: Count the number of elements in the vector
  • topk: Select the k largest elements of the vector
  • bottomk: Select the k smallest elements of the vector

Examples

See the examples below for full queries using PromQL in Better Stack.

HTTP request rate by method

Query the rate of HTTP requests
sum by (method) (rate(http_requests_total))

This query returns the rate of HTTP requests, grouped by HTTP method.

CPU usage rate by pod

Query CPU usage
rate(container_cpu_usage_seconds_total{container!=""}) without (id)

This query returns the per-second rate of CPU usage over the last 15 minutes for each pod, excluding the "id" label.

Average memory usage rate

Query memory usage by instance
avg by (instance) (rate(process_resident_memory_bytes))

This query calculates the average per-second rate of memory usage for each instance.

Top 5 most frequently accessed API endpoints

Query the top 5 most used api endpoints
topk(5, sum by (endpoint) (rate(api_requests_total)))

This query returns the top 5 API endpoints with the highest per-second request rate.

Network I/O rate by interface

Query the network transmission of each interface
sum by (interface) (rate(network_transmit_bytes_total))

This query returns the per-second rate of network transmission (in bytes), grouped by network interface.

Need help?

Please let us know at hello@betterstack.com.
We're happy to help! 🙏

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Writing queries using Pipelined Query Language