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HQ: Texas, USA
Securonix delivers a next generation security analytics and operations management platform for the modern era of big data and advanced cyber threats. The platform unlocks security analytics at scale, achieving unmatched detection in a unified, modern SIEM that lets customers deploy everywhere.
Infrastructure: Apache Spark on AWS EMR
As Securonix collects, analyzes and responds to massive volumes of data in real time, most of their operating expenses are attributed to cloud spend. At the point of first contact with Granulate, 50% of their overall infrastructure cost was allocated to Spark Streaming on AWS EMR.
Securonix had already started their cloud optimization journey by prioritizing observability with dashboarding and metrics, which confirmed that data processing costs represent the largest portion of cloud spend. As a result, Securonix turned their focus towards optimizing the underlying AWS EMR infrastructure used for Spark Streaming.
Securonix had several requirements for optimization solutions given the dynamic nature of their cloud environment. Any added solution had to be able to optimize the entire EMR fleet, require minimal engineering efforts for implementation, and assure over 15% in cost savings. They also needed the solution to work in parallel with other optimization and cost saving initiatives already in place.
Additionally, the security and resiliency of any new solution remained highly critical given the company's responsibility to maintain sensitive customer data.
Initially, Securonix chose five EMR clusters on which to deploy Granulate for optimization. During the benchmark period, Securonix processed higher amounts of traffic while using fewer cores and met the 15% infrastructure reduction goal with up to 33.57% fewer cores in one environment.
Securonix was able to achieve these results by leveraging Granulate’s ability to automatically and dynamically allocate Spark executor resources based on job patterns and predictive idle heuristics. Granulate’s solution also applied continuous YARN optimizations by more efficiently allocating resources based on CPU and Memory utilization. Following these initial results, the cost saving potential was clearly identified and Securonix quickly decided to expand Granulate fleet-wide.
In a matter of weeks, Securonix successfully optimized all 45 EMR clusters with Granulate, which enabled them to achieve their cost savings goal through a capacity reduction in excess of 15%.