Optimize Your Amazon ECS

Improve ECS Agility & Utilization Through Machine Learning

AWS ECS Pitfalls Can Negate Containerization Benefits

Amazon Elastic Container Service (ECS) is a container hosting service that automatically leverages EC2 instances and Auto Scaling groups to provide a flexible, elastic application hosting environment.

Even though container technologies are very efficient, ECS environments often have poor utilization. This is usually caused by a combination of node misconfiguration (the EC2 instances don’t match the workload demands) and container missizing. Container schedulers typically scale out the underlying nodes based on the container resource allocations, not actual utilization, and putting conservative values in container manifests will cause many more nodes to run than are actually needed.

Amazon Elastic Container Service Optimization

Machine Learning Keeps Your ECS Optimized Indefinitely

Densify’s Cloud-Learning Optimization Engine—Cloe—analyzes the node utilization and optimizes the Auto Scaling group configurations to eliminated wasted resources. And, Densify also analyzes container-level utilization patterns to automate the process of sizing containers. By integrating with popular templating technologies such as Terraform, Densify will close the loop and constantly optimize the container definitions based on learned behavior.

Densify’s Cloud-Learning Optimization Engine helps you leverage Amazon ECS more effectively

Increase ECS Infrastructure Agility & Utilization Through Optimization

Densify enables container schedulers to run more workloads on each node, decreasing infrastructure requirements and increasing responsiveness to new demands. Node utilization will drastically increase once the container manifests have been optimized.

Densify allows you to make better use of your containers by intelligently juxtaposing workloads and microservices