Automated Optimization of Containers through Machine Learning

Toronto, Ontario – April 3, 2019 – Densify, the leader in cloud resource management software market, today announced that it is launching machine learning capabilities that will automatically optimize use of containers. This technology will enable companies to be more efficient, limit wasted cloud spend, improve application uptime and scalability, and reduce performance risk. With Densify, organizations can ensure their containers are being deployed to their full potential.

Using machine learning, Densify can predict the utilization patterns of containerized applications and provide recommendations for the optimal resource requests and limits. This allows cloud operations teams to understand if their containerized applications are running in an optimal manner: If they are starved for resources, are they subject to performance risks? If they have over-allocated resources, could they be made more efficient?

Densify’s machine learning capabilities will provide visibility into what’s running, what resources are being allocated, and the true utilization of an organization’s Kubernetes environment at a cluster, namespace, and container level. The product will also provide individual container details, including historical utilization patterns. This ensures the cloud operations team has a grip on their environment and can communicate what’s going on to their business partners and executive team.

“Use of containers is growing rapidly, with 80% of organizations actively deploying containers or planning to in the near future,” said Gerry Smith, CEO, Densify. “And yet, far too many companies are blindly tackling containers without fully understanding the impact on application health. With our new advanced machine learning capabilities, Densify customers can optimize their containers to maintain application performance, reduce risk, with the lowest possible spend.”

Densify’s fully-automatable recommendations will be accessible via API and have available integrations with infrastructure as code frameworks, such as HashiCorp Terraform, AWS CloudFormation, and Red Hat Ansible. Automation Engineers can easily deliver optimally-sized containerized applications for their business, avoiding application performance risks by proactively ensuring that resources are being appropriately allocated. In addition, Densify helps optimize cluster resources by ensuring that containers are not causing waste due to over-allocation of unnecessary resources. This allows companies to do more with their currently purchased infrastructure or reduce costs by reducing their cloud infrastructure footprint.

Finally, customers can easily integrate with existing DevOps processes by using Densify’s optimization as code framework to deliver continuous integration, continuous delivery, and continuous optimization (CI/CD/CO) to the DevOps toolchain.