---
title: "Data processing and analytics tools | Grafana Cloud documentation"
description: "Machine learning platforms, data processing engines, and analytics tools that provide Prometheus metrics for monitoring data pipelines and model performance."
---

# Data processing and analytics tools

The following machine learning platforms, data processing engines, and analytics tools provide Prometheus metrics.

For integration methods, refer to the [integration guide](/docs/grafana-cloud/send-data/metrics/metrics-prometheus/prometheus-config-examples/integration-guide/).

## Cloud CV Eval AI

- [Cloud CV Eval AI](https://github.com/Cloud-CV/EvalAI/tree/master/monitoring/prometheus/prometheus.yml): Machine learning evaluation platform

## DataBiosphere Toil

- [DataBiosphere Toil](https://github.com/DataBiosphere/toil/tree/master/dashboard/prometheus/prometheus.yml): Workflow engine for large-scale data analysis

## DataStation

- [DataStation](https://github.com/multiprocessio/datastation/tree/main/testdata/prometheus/prometheus.yml): Data science workspace

## Feature Form

- [Feature Form](https://github.com/featureform/featureform/tree/main/metrics/prometheus/prometheus.yml): Feature store for machine learning

## Google Timesketch

- [Google Timesketch](https://github.com/google/timesketch/tree/master/docker/dev/prometheus/prometheus.yml): Collaborative forensic timeline analysis

## Jina AI

- [Jina AI](https://github.com/jina-ai/jina/tree/master/tests/k8s_otel/otel-test/prometheus.yml): Neural search framework

## Multiprocess Labs DataStation

- [Multiprocess Labs DataStation](https://github.com/multiprocessio/datastation/tree/main/testdata/prometheus/prometheus.yml): Data IDE for developers

## Ray Autoscaler

- [Ray Autoscaler](https://github.com/ray-project/ray/tree/master/python/ray/autoscaler/aws/cloudwatch/prometheus.yml): Distributed computing framework

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