Analytics Driven Approach to Resource Control
Relieve developers from the burden of setting correct
CPU and Memory Requests and Limits
Don’t have developers waste time looking at utilization curves and raw numbers to figure out how much resources to give containers – just let purpose-built software figure it out based on actual behavior. Ensure requests and limits are high enough to keep you out of trouble, but not so high that FinOps comes knocking.
Densify is an AI-driven approach to Kubernetes Resource Control that can be embedded in the DevOps lifecycle:
- Deep and constant analysis of containers, pods, replica sets & deployments
- Automatic setting of container resource requests & limits
- Tunable polices to account for app-specific requirements, replication, availability, redundancy
- Automated Node Group Optimization at the cloud scale group level
Densify impacts key resource decisions throughout the cycle:
- Analyze detailed utilization patterns against cloud instance and container configurations, using sophisticated policies, to recommend optimal resource settings.
- Provide recommended instances for every workload via an intuitive Catalog Map. Go further via Guardrails to show a limited set of optimal choices from a cost and performance perspective.
- Integrate with tools like Terraform using the Densify API to enable seamless execution of resource optimization recommendations, fully honoring approval processes.
- Detect and eliminate operational risks and waste by automatically identifying sub optimal cloud instances, poorly performing scale groups, and misconfigured container requests and limits.
1. Analyze detailed utilization patterns against cloud instance and container configurations, using sophisticated policies, to recommend optimal resource settings.
2. Provide recommended instances for every workload via an intuitive catalog map. Go further via Guardrails to show a limited set of optimal choices from a cost and performance perspective.
3. Integrate with tools like Terraform using the Densify API to enable seamless execution of resource optimization recommendations, fully honoring approval processes.
4. Detect and eliminate operational risks and waste by automatically identifying sub optimal cloud instances, poorly performing scale groups, and misconfigured container requests and limits.
