AWS Compute Optimizer Explained

AWS offers an AWS Compute Optimizer service as a response to their customers' needs—an announcement highlighting that organizations are actively looking for the resource management and optimization services that Densify offers today. AWS Compute Optimizer is validation for Densify and designed for a subset of AWS customers only.

No Auto Scaling Group (ASG) Scaling Recommendations

Applications require elasticity and it can be difficult to determine what node types, sizes, and scaling parameters should be used within ASGs. Densify analyzes both the instances within the scale group and scaling parameters to recommend both the perfect instance type and changes to the minimum and maximum settings to better reflect actual demand patterns.

No Container & Node Optimization Recommendations

Densify runs on containers and understands that there is an ability to over allocate resources as CPU and memory resources may be assigned to running containers, but not actually leveraged. Densify leverages machine learning and predictive analytics to optimize container resources at the container, pod, and node levels.

14 Days of Data for Analysis

Densify understands that 14 days of data is not enough to capture business cycles and other patterns and that recommendations based on short dataset can result in degraded application performance. Densify by default gathers and analyzes 60 days of existing performance data, provides full policy control over the period of data to analyze, and will show you how to match your applications’ needs with the right cloud infrastructure within 24 hours.

Optimization Only If You Live in the U.S., Ireland, and Brazil

If you have IaaS services in Canada, London, mainland Europe, Asia, or Australia, you’re out of luck with AWS Compute Optimizer today. Densify is a SaaS platform and can make recommendations regardless of where your business and infrastructure is hosted.

Single-Cloud Analysis

Densify is a true hybrid cloud resource management solutio and considers not only Amazon Web Services, but Microsoft Azure, Google Cloud, VMware, IBM Cloud, and containers. Densify can take the analysis a step further and show different instance types and costs across multiple clouds to enable migration planning or multicloud resilient deployments.

No Existing RI Awareness When Suggesting Optimization

Densify is RI-aware and considers your standard RI coverage, deferring change until coverage ends, ensuring you protect your existing investments.

No Cross-Vendor CPU Recommendations

There are unique performance differences between AMD, Intel, and ARM processors and having recommendations that consider different manufacturers guarantees you’ll get the best performance.

No Automation

Recommendations to optimize are even better when there is automation to execute the changes. Densify coined the term optimization as code and integrates with a wide variety of the tools you’re already using in your CI/CD pipeline to automate the changes to your infrastructure and save you time.

No RDS or Spot Instance Recommendations

Databases often have complex usage patterns across CPU, memory and I/O, and may have cyclical or sporadic loads, making them difficult to optimize. Densify provides analytics to ensure that your RDS selection and sizing is correct, helping you avoid risk and cost.

No Reporting for Change Management

Densify offers all customers an application owner report, API-accessible and easily integrated with in your ITSM or collaboration tools, to facilitate communication with stakeholders and support your business’ approval workflows.

A Non-Configurable Machine Learning Engine to Generate Recommendations

Densify does not hide their recommendation logic on how relative performance is assessed and offers granular and robust policy control to ensure your business always gets the right recommendations.

No Integrations with Third-Party Tools (Datadog, New Relic, Dynatrace, etc.)

Densify integrates with a variety of third-party monitoring tools to ingest additional performance and application metrics. This ensures that the application resiliency and performance is the highest priority and that all compute metrics (including memory) are considered when making optimization recommendations.

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