cloud resource optimization

Cloud optimization is the process of correctly selecting and assigning the right resources to a workload or application. When workload performance, compliance, and cost are correctly and continually balanced against the best-fit infrastructure in real time, efficiency is achieved.

Resource optimization is the set of processes and methods to match the available resources (human, machinery, financial) with the needs of the organization in order to achieve established goals.


Densify provides a cloud and container resource management and visibility platform, using machine learning to recommend precise resource requirements for optimal application performance. With Densify, your cloud spend is under control and your apps perform better as they get precisely matched across AWS.

Densify features include:

Machine learning cloud resource management infrastructure
Performance improvement recommendations
Cloud cost intelligence reporting
Slack integration for automation
Container and node optimization


A long-established leading specialist insurance and reinsurance business, Atrium lacked visibility into their Amazon EC2 Reserved Instances (RI) usage and coverage. This was further amplified by the need to maximize utilization and reduce overall cloud spend. By partnering with Densify, Atrium was able to create a process to help convert the existing RIs into an optimal set of RIs that precisely matched workload demands. As a result, Atrium’s RI investment increased from 75% to 95% in 5 months, reducing overall cost of infrastructure.

Spotinst’s Elastigroup platform is a SaaS-based cluster orchestration and scaling service that provides optimization and automation for cloud infrastructure. The Spotinst team helps customers save up to 90 percent on their computing costs. Spotinst helps eliminate operational overhead and infrastructure complexity from web applications, containers, scientific computing, rendering, financial simulation, Hadoop, Spark, caching tiers, and more.

Spotinst’s Elastigroup Enterprise features include:

Easy provisioning and management of your infrastructure.
Price prediction algorithms to offensively rebalance clusters.
High availability, and achieves Enterprise-grade SLA.
Ability to run Kubernetes or ECS containers without provisioning, scaling, or managing underlying VMs.


Today, Duolingo manages over 100 microservices on AWS, giving its teams the ability to deploy their own services with speed and ease. Using Spotinst, Duolingo reduced its overall compute costs by over 60 percent in one quarter and its total AWS costs by 25 percent. The money that Duolingo saves using Spotinst is put toward new product development.
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Spotinst is a rare and fantastic service. Our team started using the product, and—within a week—we started realizing significant cost savings. We’ve also found Spotinst’s customer service to be great.


Turbonomic’s Application Resource Management for AWS provides full stack, application aware visibility. This allows customers to rapidly assess on-premises environments prior to migration. Turbonomics determining the exact resources required in AWS and calculates the precise resources required to assure application performance at the lowest cost. Customers use Turbonomic to successfully manage their hybrid cloud environments at scale.

Turbonomic’s Application Resource Management for AWS features include:

Rapid, agentless evaluation of AWS ROI via a data driven hybrid cloud strategy
AI engine assures performance and business policy adherence
Full-stack, continuous optimization of Kubernetes on AWS
Trustworthy decision-making for better Reserved Instance pool utilization

Gonzaga University

Gonzaga University, a private university with 7,500 students in Spokane, Washington, using Turbonomic across their hybrid cloud estate to assure application performance, optimize cost and leverage automation to elevate their IT operations. Turbonomic manages hundreds of virtual machines and instances automation decisions to drive better performance, assess which workloads should move to AWS, and free up time for Gonzaga’s team to adopt more advanced AWS services.
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Turbonomic’s has enabled us to drive better efficiency on-premises but more importantly our hybrid environment is just happy. We no longer get alerts from our VMware anymore. Using Turbonomic’s automation has allowed us to shift our focus to our AWS deployment where Turbonomic is helping us to assess what we still have on-premises and manage our existing footprint ensuring that our instances will be accurately sized to assure performance and prevent overspend.