---
title: "Tutorial: How to Use ChaosSearch with Grafana for Observability"
description: Building your observability stack? Uncover how Grafana and ChaosSearch pair up.
image: https://www.chaossearch.io/hubfs/C2020/Graphics/Blog/Grafana/Build%20Observability%20Stack.jpg
---

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6 MIN READ

# Tutorial: How to Use ChaosSearch with Grafana for Observability

By [Dave Armlin](https://www.chaossearch.io/blog/observability-stack-how-to-use-chaossearch-grafana#authorBlock) on Oct 6, 2022

Tutorial: How to Use ChaosSearch with Grafana for Observability

5:33

In my last blog post, [Building a Cost-Effective Full Observability Solution Around Open APIs and CNCF Projects](https://www.chaossearch.io/blog/building-cost-effective-observability-solution-w-open-apis-cncf), we introduced using ChaosSearch in combination with the most popular open source front- and back-ends in the application observability space. In case you missed it, the TL;DR version is that you can use a variety of open source projects and open API-based components to build the [best-of-breed observability stack](https://www.chaossearch.io/best-of-breed-observability) of your choice rather than relying on expensive, all-in-one solutions.

READ: [Beyond Observability: The Hidden Cost of Log Analytics](https://www.chaossearch.io/resources/beyond-observability)

An example of a best-of-breed observability architecture is below.

 

![Build Observability Stack](https://www.chaossearch.io/hs-fs/hubfs/C2020/Graphics/Blog/Grafana/Build%20Observability%20Stack.jpg?width=1576&name=Build%20Observability%20Stack.jpg)

 

![Observable Application](https://www.chaossearch.io/hs-fs/hubfs/C2020/Graphics/Blog/Observability%20Solution/Observable%20Application.png?width=850&name=Observable%20Application.png)

 

For DevOps and Ops teams that have bought into this best-of-breed and open approach, [Grafana](https://grafana.com/) has become the visualization tool of choice for metrics monitoring and understanding. As a result, ChaosSearch has a number of customers who would prefer to use Grafana to investigate and visualize their logs, rather than using the OpenSearch or [Kibana Dashboards](https://www.chaossearch.io/blog/how-to-create-kibana-dashboard) user interface that ChaosSearch provides out of the box.

Luckily, ChaosSearch was built to be compliant with the [Elasticsearch/OpenSearch](https://www.chaossearch.io/use-cases/elasticsearch-replacement) API, and Grafana comes with an out-of-the-box Elasticsearch Data Source connector.

To use ChaosSearch as a data source in Grafana, follow these simple steps.

 

## Configuring Your ChaosSearch Data Source

1. Login to Grafana under an account with administration and configuration access.
2. Go to Configuration → Data Sources and click the “Add data source” button
3. Select [ElasticSearch](https://grafana.com/grafana/plugins/elasticsearch/) from the list of options
4. In the ElasticSearch Settings enter the following values.
5. After the above changes are made, click on “Save & Test” at the bottom.

 

## Highlights: Exploring Your Log Data in Grafana

You are now ready to [gather information](https://grafana.com/docs/grafana-cloud/fundamentals/intro-to-observability/) using the ChaosSearch data source, just as you would any other Grafana data source.

The biggest difference between exploring ChaosSearch in Grafana vs. other data source types in Grafana is that the `Query` string is written in the Lucene query syntax rather than the Kibana Query Language (KQL) syntax more commonly used in Kibana and ChaosSearch.

To try out the correct Lucene Query in ChaosSearch’s embedded Kibana interface:

1. Go to ChaosSearch → Search Analytic → Discover
2. Select the “KQL” button to the right of the Search bar
3. Turn the Kibana Query Language toggle to “Off”

 

![Kibana Query Language](https://www.chaossearch.io/hs-fs/hubfs/C2020/Graphics/Blog/Grafana/Kibana%20Query%20Language.png?width=1004&name=Kibana%20Query%20Language.png)

 

## Creating Dashboards

In Grafana, you create Dashboards against ChaosSearch as a data source, the same as you would with other data sources. But, against this data source, Grafana has added in a visualization type named `Logs` to make Grafana work more like Kibana Discover.

In order for this Logs visualization to work you needed to correctly configure both the `Time` field name and `Message` field name when setting up the data source (see “Configuring Your Data Source” section above).

When configuring the Logs visualization, choose your option in the Logs section of the configuration panel. You will most likely want to at least turn “Time” and “Enable log details” on. The latter will allow you to expand out an individual log to see all of its fields, like in Kibana Discover.

 

![Enable Log Details](https://www.chaossearch.io/hs-fs/hubfs/C2020/Graphics/Blog/Grafana/Enable%20Log%20Details.png?width=1085&name=Enable%20Log%20Details.png)

 

Once you have followed the steps to getting set up, your completed dashboard will look something like this

 

![Dashboard Queries Over Time](https://www.chaossearch.io/hs-fs/hubfs/C2020/Graphics/Blog/Grafana/Dashboard%20Queries%20Over%20Time.png?width=1510&name=Dashboard%20Queries%20Over%20Time.png)

 

READ: [Managing Cloud Service Logs: Why It’s Difficult and How to Simplify It](https://www.chaossearch.io/blog/how-to-simplify-cloud-logging-observability-platform)

 

## Conclusion

Following the steps above, it’s easy to set up your Grafana instance to work with ChaosSearch, just as you would with Kibana or OpenSearch dashboards. In a best-of-breed architecture, you should be able to use the tools you like best and are strongest for the task at hand. That’s why ChaosSearch was built with an API-first approach, in hopes that more companies would tap into the benefits of best-of-breed observability architectures – including lower costs, increased agility, and more flexibility for DevOps teams and SREs. Happy log hunting!

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## Additional Resources

Read the Blog: [How to Create a Dashboard in Kibana](https://www.chaossearch.io/blog/how-to-create-kibana-dashboard)

Listen to the Podcast: [Trends and Emerging Technologies in Data Analytics](https://datalegendspodcast.com/trends-and-emerging-technologies-in-data-analytics)

Check out the eBook: [BEYOND OBSERVABILITY: The Hidden Value of Log Analytics](https://www.chaossearch.io/resources/beyond-observability)

   [DevOps](https://www.chaossearch.io/blog/tag/devops), [Log Analysis](https://www.chaossearch.io/blog/tag/log-analysis), [SecOps](https://www.chaossearch.io/blog/tag/secops), [Kibana](https://www.chaossearch.io/blog/tag/kibana), [Tutorials](https://www.chaossearch.io/blog/tag/tutorials), [What is Observability](https://www.chaossearch.io/blog/tag/what-is-observability)

### About the Author, Dave Armlin

![Dave Armlin](https://www.chaossearch.io/hubfs/ChaosSearch_September2019/Images/armlin_headshot-150x150.jpeg)

FOLLOW ME ON:

[Dave Armlin's LinkedIn ](https://www.linkedin.com/in/darmlin/)

 Dave Armlin is the VP Customer Success of ChaosSearch. In this role, he works closely with new customers to ensure successful deployments, as well as with established customers to help streamline integrating new workloads into the ChaosSearch platform. Dave has extensive experience in big data and customer success from prior roles at Hubspot, Deep Information Sciences, Verizon, and more. Dave loves technology and balances his addiction to coffee with quality time with his wife, daughter, and son as they attack whatever sport is in season. He holds a Bachelor of Science in Computer Science from Northeastern University. [More posts by Dave Armlin](https://www.chaossearch.io/blog/author/dave-armlin)

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