Sunday, 5th December 2021
Logo

Densify brings Machine Learning to automated optimisation of containers

Densify is launching machine learning capabilities that will automatically optimise 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, organisations can ensure their containers are being deployed to their full potential.

Using machine learning, Densify can predict the utilisation pattern of containerised applications and provide recommendations for the optimal resource requests and limits. This allows cloud operations teams to understand if their containerised 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 utilisation of an organisation’s Kubernetes environment at a cluster, namespace, and container level. The product will also provide individual container details, including historical utilisation 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 organisations 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 optimise 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 Terraform, CloudFormations, and Ansible. Automation Engineers can easily deliver optimally sized containerised applications for their business, avoiding application performance risks by proactively ensuring that resources are being appropriately allocated. In addition, Densify helps optimise 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 Optimisation as Code framework to deliver Continuous Integration, Continuous Delivery, and Continuous Optimisation (CI/CD/CO) to the DevOps toolchain.

Precise, AI-powered insights enable DevOps and SRE teams to proactively optimize cloud-native applic...
Sumo Logic has introduced new integrations with CircleCI and GitLab designed to help development tea...
High-speed application development platform underpins ‘MyWorkSpace’ App and safe return to the offic...
After Kubernetes Kosmos and S3-based Object Storage, Scaleway continues to deliver on its Multi Clou...
CloudBees has been selected by HSBC as its software delivery platform provider, supporting the bank...
Latest Akamai Security Research examines global API security landscape; reveals 2020-2021 attack tra...
DevOps and SRE practices are critical to high-quality, efficient releases, but teams still devote 27...
Canonical has released Ubuntu 21.10 - the most productive environment for cloud-native developers an...