Update: 2026 GigaOm Radar available
The 2026 GigaOm Radar is now available → Read the latest version
Recognized once again for delivering innovation and impact in autonomous cloud optimization
We are pleased to share that Akamas has been recognized once again as both a Leader and an Outperformer in the newly released GigaOm Radar for Cloud Resource Optimization.
This recognition highlights the continued strength of Akamas in enabling organizations to effectively balance performance and cost. This is achieved across their cloud-native environments through AI-driven optimization.
According to GigaOm, Akamas stands out for its ability to autonomously optimize applications and infrastructure. It helps teams achieve superior efficiency and reliability with minimal manual intervention.
Akamas offers a highly effective approach to cost-performance optimization through ML-based tuning and support for a wide range of use cases, including Kubernetes, JVM, and autoscaling policies. — GigaOm Radar for Cloud Resource Optimization
Positioned as a Leader and Outperformer
The 2025 GigaOm Radar places Akamas in the Leader circle and identifies it as an Outperformer due to its fast pace of innovation and execution.
GigaOm highlights several areas where Akamas excels:
- AI-powered optimization engine for configurations and resources: Akamas leverages advanced AI/ML capabilities to deliver high-quality optimization recommendations. These rival top-tier platforms.
- Simultaneous cost and performance optimization, enabling intelligent trade-offs: Through objective-based tuning, Akamas enables teams to define custom goals. It then automatically finds the best configurations to meet them.
- Strong support for Kubernetes, including pod resources and autoscaling: Akamas natively supports pod-level tuning, runtime allocation, and autoscaling policies. This applies in both staging and live production environments.
- Broad platform coverage, from JVM tuning to cloud-native workloads: Akamas optimizes across the full stack. It supports major cloud platforms (AWS, Azure, GCP) as well as language runtimes and application-level configurations.
- Advanced workload simulation and scenario-based planning: Using an AI-driven experimental approach, Akamas helps validate system behavior under real-world conditions. It supports data-driven capacity planning.
These strengths make Akamas a trusted solution for teams. They can go beyond traditional rightsizing and gain continuous control over performance and cost.
Supporting modern FinOps and platform engineering initiatives
As organizations adopt FinOps practices and platform engineering models, the need for intelligent and automated optimization has never been greater.
Akamas enables engineering teams to move from reactive cost control to proactive, data-driven optimization. This integrates into their CI/CD pipelines and operating environments.
By minimizing cloud waste and ensuring application SLOs, Akamas empowers DevOps, SRE, and FinOps teams. They can deliver better business outcomes through smarter infrastructure decisions.
