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Tutorial: How to Use ChaosSearch with Grafana for Observability

In my last blog post, Building a Cost-Effective Full Observability Solution Around Open APIs and CNCF Projects, 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 of your choice rather than relying on expensive, all-in-one solutions.

READ: Beyond Observability: The Hidden Cost of Log Analytics

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


Build Observability Stack


Observable Application


For DevOps and Ops teams that have bought into this best-of-breed and open approach, Grafana 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 user interface that ChaosSearch provides out of the box.

Luckily, ChaosSearch was built to be compliant with the Elasticsearch/OpenSearch 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
    • Add Data Source
  3. Select ElasticSearch from the list of options
  4. In the ElasticSearch Settings enter the following value.
    • URL - The ChaosSearch url to access your data + /elastic
      • for example
    • Access - Server (default)
    • Auth - Turn on SigV4 auth. If you don’t see SigV4 as an option, then you need to enable it in your config file or docker-compose file. sigv4_auth_enabled = true
      • To enable via the Docker command line, add this to the command
        • -e GF_AUTH_SIGV4_AUTH_ENABLED=true
        • For example:
          • docker run -d -p 3000:3000 -v "$(pwd)"/grafana-plugins:/var/lib/grafana/plugins -e GF_AUTH_SIGV4_AUTH_ENABLED=true --name=grafana grafana/grafana-oss
    • SigV4 Auth Details
      • Authentication Provider - select Access and Secret Key
      • Access Key ID & Secret Access Key - These are the API keys from Settings → API Keys in ChaosSearch Kibana.
        • Settings API Keys Kibana
      • Default Region - Select the region where your cluster is deployed
    • Elasticsearch Details
      • Index name - The name of the view from the ChaosSearch Refinery tab
      • Time field name - the name of the time field. Make sure this matches the exact same field name as in the index type.
        • For example - @timestamp
      • Version - Select the version of Elasticsearch that is deployed. 7.10+ is selected in this example
    • Logs
      • Message field name - The name of the field that contains the full test of the message. This is required to use Grafana’s Logs Visualization described below.
        • For example _source or message
      • Grafana Data Sources
  5. After the above changes are made, click on “Save & Test” at the bottom.
    • If you get a red error message, please check the settings again. Some common mistakes may include region, index-name and version.
    • Once you get a green check, you are good to query and make graphs and dashboards.


Highlights: Exploring Your Log Data in Grafana

You are now ready to gather information 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


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


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


Dashboard Queries Over Time


READ: Managing Cloud Service Logs: Why It’s Difficult and How to Simplify It



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!

See ChaosSearch in Action: Schedule Personalized Demo


Additional Resources

Read the Blog: How to Create a Dashboard in Kibana

Listen to the Podcast: Trends and Emerging Technologies in Data Analytics

Check out the eBook: BEYOND OBSERVABILITY: The Hidden Value of Log Analytics

About the Author, Dave Armlin

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