How to Run Elasticsearch from Zero to Petabyte Scale

LogDNA’s solution leverages Kubernetes to automate the deployment, scaling, and maintenance of Elasticsearch nodes across a number of cloud and platforms.

Elasticsearch owes much of its success to its scalability. However, even the most well-optimized clusters can only scale to a certain point, after which performance will rapidly degrade. With enterprises generating and consuming ever-increasing amounts of data, these limits can quickly become barriers to growth.


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About The White Paper

At LogDNA, we developed a solution for scaling Elasticsearch to petabyte scale. Our solution leverages Kubernetes to automate the deployment, scaling, and maintenance of Elasticsearch nodes across a number of cloud and platforms. In this whitepaper, we will outline this approach and provide detailed information about the configurations, techniques, and optimizations we used to achieve our level of scale.

The information in this whitepaper is based on this webinar presented by our Head of DevOps, Ryan Staatz. To learn more about how we manage Elasticsearch across multiple clusters, read our Elasticsearch Index Manager whitepaper.