Akamas can optimize any applications, any workload and any infrastructure – whether on-premise or in the cloud. Akamas optimal configurations work on any application, runtime, container, middleware, database and cloud parameters.
Akamas patented reinforcement learning techniques, combined with user-control features and safety policies, support both live optimization in production environments as well as planned or what-if scenarios.
Akamas optimization is driven by user-defined goals and constraints to ensure that recommended configurations and insights achieve the best performance, resilience and cost efficiency tradeoffs, while also matching SLOs.
Akamas configurations can be approved and reviewed by humans, applied in CI/CD pipelines or autonomously by Akamas, thanks to its Infrastructure-as-Code approach and smooth integration with any change/delivery process.
The Akamas enterprise-grade optimization platform supports performance engineers, SRE teams, and developers in optimizing complex applications, both in real-time and against planned or what-if scenarios.
Akamas uniquely features full-stack, smart exploration based on experiments and trials, custom workflows incorporating any load script, automatic stability windowing detection, and UI-based insights to evaluate tradeoffs among (sub)optimal configurations.
Akamas uniquely features full-stack, dynamic, context-aware optimization based on live observations, safe recommendations with respect to defined SLOs, and custom safety policies that ensure incremental changes are gradually applied to reach the optimal configuration.
The Akamas optimization platform manages any system and integrates with any ecosystem, thanks to its Infrastructure-as-Code (IaC) approach and comprehensive set of APIs and integration mechanisms.
Akamas can optimize any system and any set of parameters chosen from the application, middleware, database, cloud, and any other underlying layers.
Akamas provides dozens of out-of-the-box Optimization Packs for key technologies such as JVM, Go, Kubernetes, Docker, Oracle, MongoDB, ElasticSearch, PostgreSQL, Spark, AWS EC2 and Lambda, and more. Custom Optimization Packs do not require any coding.
Akamas can integrate with any ecosystem thanks to out-of-the-box integrations with major telemetry and monitoring tools to collect KPIs and cost data, configuration management tools and repositories to apply configurations, and value stream delivery tools to support a continuous optimization process.
Integrations to load testing tools are also available to generate simulated workloads in test/pre-production to support what-if scenarios.
“Tools like Akamas allow us to help our organizations deliver exceptional performance while keeping an eye on resource consumption and costs.”
“We believe Akamas is taking the right approach with its gradual recommendations to allow users to leverage AI-powered live optimization before eventually adopting a fully autonomous mode.”
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