Optimizer Runtime

Optimizer Runtime

Concertio Optimizer Runtime is a dynamic optimization framework for DevOps and IT professionals aimed at optimizing systems, servers and components automatically and in real-time.

Using AI techniques, Optimizer Runtime works to make applications and systems operate in concert for maximum performance, through the optimization of the myriad of configuration settings employed in these complex systems. It is an easy-to-integrate performance optimization software that monitors (and learns from) the interactions between applications and systems, to deliver optimal configuration settings for peak performance.

Deploying Optimizer Runtime

DevOps teams and IT professionals use Concertio Optimizer Runtime to automatically and dynamically optimize systems more quickly and effectively than with human operators in a variety of use-cases including:

  • As a background process in production systems. Use Optimizer Runtime to automatically discover and apply the most effective system settings for the currently running workload on production systems and achieve peak performance. Installation is a breeze and higher performance is realized within minutes from the installation.
  • As a service. Use Optimizer Runtime to continuously optimize system settings such as K8s resources, serverless function resources, or Hadoop jobs. By leaving resource management to Optimizer Runtime, DevOps teams can ensure that their infrastructure is always operating with the most efficient resources, even as their software evolves and needs change.

Companies that Deploy Optimizer Runtime Can Expect:

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Peak application performance

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Reduced cloud and datacenter infrastructure bill

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Completely automatic and hassle-free optimization process

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Industry best-practices for performance optimization

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Automatic support for new tunable settings as they are introduced by vendors

How Optimizer Runtime Works

Concertio Optimizer Runtime is an easy-to-use software tool that uses AI techniques to discover near-optimal configuration settings for peak performance, all in real-time. Optimizer Runtime software uses a workload classification engine to detect different phases of execution of a workload while system applications run. Optimizer Runtime then uses reinforcement learning to evaluate and optimize each detected program phase, testing various system configuration settings, and choosing settings that maximize performance. As applications’ needs change over time, Optimizer Runtime adapts and reconfigures systems dynamically. Being able to optimize each execution phase separately from the others, Optimizer Runtime can outperform any preset system configuration discovered by human operators.

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