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CareersAmazon ECS management at scale
Advanced automation for Amazon ECS
Simple way to run Amazon ECS clusters while saving up to 90% on compute costs and achieving maximum resource utilization
The Challenge
Manage, operate and scale infrastructure to maximize cluster utilization without suffering from idle resources can be a big challenge, especially
at scale.
Traditional Approach:
- Manage multiple Auto Scaling Groups
- Manually Determine the right instance type & size without considering actual Pods requirements
- Running on-demand infrastructure
The Solution
Advanced automation, optimization, and simplicity to increase resource utilization and save up to 90% on cloud infrastructure costs.
Spot by NetApp’s Ocean Approach:
- Manage one cluster with multiple compute launch specifications
- Automatic node provisioning based on Pod requirements
- Run mission-critical and production workloads on optimal blend of spot, reserved and on-demand capacity
Solution benefits
Cluster auto scaling
As you deploy Tasks and Containers, Ocean scales the number of instances in the cluster to meet your application demand.
Node auto provisioning
Ocean learns what resources (CPU, Memory, Ports) your Tasks need and decides what is the best instance size or type to accommodate those requirements.
Maximum resource utilization
Containers are first-class citizens. Ocean studies the actual Containers requirements and matches ECS Tasks and Services with the most efficient and optimized mix of EC2 Instances, making sure the instances are highly utilized.
90% Less on infrastructure costs
Ocean reliably uses EC2 spot instances to save up to 90% on infrastructure cost with an enterprise-grade SLA.
Cost management
Ocean lets you track your ECS cluster costs by Services and Applications. Using a show-back calculation to present visibility inside each Task and container across compute, networking and storage costs.
Enterprise-grade SLA
Reduce the risk of human errors by automating the management of your compute infrastructure and discover errors before they happen.
