The True Cost of the Elastic Stack

Elastic Stack can be a great option for teams that are just beginning their journey to better log management practices.However, as they quickly scale, teams realize that the Elastic Stack’s free price tag comes with many hidden costs.

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As log management becomes a crucial piece of the software development lifecycle, DevOps teams need fast and cost effective ways to scale their efforts to manage log data at scale. One option for teams is to build their own solution from scratch, more commonly known as the Elastic Stack.

This white paper explores the costs associated with building, scaling and maintaining the Elastic Stack. Our total cost of ownership analysis provides insight into key budgetary considerations, and compares them with commercial solutions, like LogDNA.

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Choosing a log management solution is crucial in allowing developers to deliver products faster. It also has big implications on an organization’s bottom line. This infographic demonstrates the expected costs to build, scale, and maintain the Elastic Stack over a three year period. This total cost of ownership analysis assumes a midsize Elastic Stack deployment on AWS, and accounts for moderate growth year-over-year.

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The best features are being able to drill down to pod level, server level metrics (in k8s), searching against time frame, their ease of using words to search, saving searches, and the alerting through slack. The benefit of being able to debug a problem going through the logs helps us fix bugs and issues faster than we could imagine.

Ravi D., DevOps Engineer - Enterprise

Maybe what is LogDNA video here?

Lorem Ipsum here limits on the volume of logs stored. A hard quota lets you set a specific threshold to stop retaining and a soft quota triggers pre-defined exclusion rules to throttle the volume of logs being retained.

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