New Feature: AWS ECS Cost Savings Insights
Cloudthread now uncovering savings opportunities by detecting underutilized ECS resources.
Cloudthread now uncovering savings opportunities by detecting underutilized ECS resources.
New feature alert! Cloudthread is launching AWS ECS Cost Savings Insights. This feature allows to uncover cloud cost efficiency enhancements by identifying underutilized ECS containers and recommending cost-saving configurations.
Cloudthread platform now can assist you in keeping your ECS costs in check by surfacing containers with low utilization (less than 40% max over 7 days) for both CPU and Memory dimensions, and intelligently suggesting more optimal configurations.
AWS Elastic Container Service (ECS) is a popular managed alternative to Kubernetes (K8s). It provides a fully managed experience for container orchestration and is used widely both in a serverless setting (on top of AWS Fargate), and in traditional server architecture (on top of EC2).
Major benefits of ECS over K8s include hassle-free setup experience and less heavy maintenance. However, this convenience comes at a cost – ECS workloads are considerably more expensive at scale, and require tight cloud cost management attention.
Cloudthread platform now can assist you in keeping your ECS costs in check by surfacing containers with low utilization (less than 40% max over 7 days) for both CPU and Memory dimensions, and intelligently suggesting more optimal configurations. Potential savings get calculated and highlighted as well, so that you know which resources should be adjusted in the first place.
ECS Cost Savings Insights together with powerful reporting and alerting unlock direct path to cloud cost savings for your Engineering team if they heavily use ECS workloads. The feature does not require any setup and comes out-of-the-box in all the versions of Cloudthread platform.
The feature is now available for all the users – contact us to start using it as well as other engineering-focused cloud cost management capabilities Cloudthread platform provides.