Feature spotlights

Container Resource Optimization

Resource inefficiency results from developers specifying the CPU and memory requests and limits for each container. But determining these values is often very difficult, causing resources to go unused. Densify solves this by learning the activity patterns of the containers and pods, and scientifically determining request and limit values that give each container what it needs, while at the same time optimizing the overall density of the container environment, providing precise recommendations.

Node Resource Automation

Once the container resource allocations are aligned with actual consumption, Densify will also optimize the nodes the containers are running on in order to make sure the underlying resources are consistent with workload demands. This process is supported for both on-prem nodes as well as cloud-based deployments


Because of the precision of the Densify optimization recommendations, it is possible to close the loop on execution and achieve a high degree of automation. A highly differentiated feature of Densify is the ability to integrate with automation frameworks such as HashiCorp Terraform, AWS CloudFormation, and Red Hat Ansible, creating optimization as code. By embedding the machine learning recommendations directly in the application definitions, they will optimize themselves based on lea

DevOps Integration

Optimization as code becomes a key strategy in DevOps environments. Any changes made outside the DevOps toolchain will be quickly undone next time a release occurs. Densify becomes part of the toolchain, providing closed-loop optimization by embedding hooks in the upstream process. Densify generates human-readable (approvals) and machine-readable outputs (automation) that populate a repository of machine learning artifacts, and this repo is made available to the entire DevOps toolchain.

Software License Control

As organizations deploy containers into production, a set of new challenges often arise. One such challenge is optimizing the use of licensed software, and specifically, controlling container placement and resource consumption in a way that ensures licensing policies are met and costs are minimized. Densify has a proven track record of advanced software license control, where licensing is often enforced at the node level and workload placement and resource allocation are critical.

Workload routing and reservation

Any organization that spans multiple physical locations or hosting providers needs to have clear policies governing where workloads run, includes security and compliance policies, data residency, jurisdictional requirements, technical hosting capabilities, service proximity, resiliency, and other policies. Any organization with more than one Kubernetes cluster needs to adopt an automated mechanism to route workloads. Densify provides detailed automated workload routing analytics.

Customer case studies

Continuous Optimization for Public Cloud

Fortune 2000 clients

How to Optimize Your Cloud in the Era of Infrastructure as Code

Fortune 1000 clients

How Verisk Achieves Cloud Migration & Continuous Optimization

Verisk Analytics

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