Cloud and Kubernetes Optimization for Amazon Web Services
Automatically determine the cloud and Kubernetes resources required to reduce cost and maximize performance in AWS
Amazon EC2 Optimization
Densify’s machine learning analyzes workload patterns to determine the optimal size and family for your AWS Elastic Compute Cloud (EC2) instances, enabling you to:
- Reduce application performance and stability issues associated with under allocating resources to your instances
- Increase utilization and lower costs by ensuring that you are not overallocating capacity to your instances
- Avoid leaving CPU, memory or other resources stranded by picking the wrong instance family
Optimization details for your AWS EC2 instances
Amazon RDS Optimization
Optimize your AWS Relational Database Services (RDS) using Densify’s machine learning based analysis, ensuring that you:
- Reduce application performance and stability issues associated with under allocating resources to your database
- Increase utilization and lower costs, for one of the most expensive service types, by ensuring that you are not overallocating capacity to your database
- Avoid leaving CPU, memory or other resources stranded by picking the wrong instance family
- Protect your existing RI investment by identifying when an RDS instance is covered by an RI and deferring the recommendation until it expires
Optimization details for your AWS RDS instances
See the Benefits of Optimized Cloud & KUBERNETES Resources
Densify is the only way to precisely match your apps’ demands to the right cloud supply.
Amazon ASG Optimization
Densify analyzes the utilization and scaling behavior of AWS Auto Scaling Groups (ASGs) and performs simulations to determine their optimal configuration, enabling you to:
- Analyze whether scaling groups are elastic, or are constrained by resource configurations
- Automatically assign the right instance size and family for nodes in your ASG
- Determine optimal scaling parameters such as the minimum and maximum size of your ASG
- Highlight when your scaling policies should be reviewed because nodes are not being added and removed in line with workload demand
Optimization analysis of AWS Auto Scaling groups
Amazon EKS Clusters Optimization
Densify’s analytics predictively, precisely and continuously determine the appropriate resource settings for your AWS Elastic Kubernetes Service (EKS) containers and nodes allowing you to:
- Avoid application performance and stability issues
- Visualize the overall resource health of your entire Kubernetes environment with Histograms
- Increase node and cluster utilization by avoiding allocating too much CPU and memory to your applications
- Automatically assign the ideal amount of CPU and memory for the nodes and node groups in your clusters
- Determine the right instance families for your nodes
- Automatically model scaling behavior to optimize scale groups
- Lower your cloud bill by deploying fewer nodes for the same containers
Densify automatically analyzes thousands of containers to determine optimal settings
Visualize Utilization Metrics for Your AWS Infrastructure
Provides instant access to visualize CPU, Memory, Network and Disk I/O utilization metrics for your EC2, RDS, and ASG instances, enabling you to:
- Confidently implement Densify’s optimization recommendations by visualizing historical utilization patterns.
- Understand the scaling behavior of ASGs using the number of in-service instances metric.
- Select the historical period, hourly or daily time granularity, and multiple statistics of interest including the peak, sustained, average and minimum.
- Compare the utilization of different resources using the four available charts or by selecting multiple metrics on a single chart.
Densify’s Metrics Viewer lets you explore your EC2, RDS, and ASG instances’ historical utilization data
Enable Collaboration with Product & Application Owners
Densify automatically produces Impact Analysis and Recommendation Reports to share with stakeholders, letting you:
- Clearly articulate details for every optimization recommendation, including predicted utilization, effort level, and cost impact
- Include as an attachment to ITSM change tickets or integrate into business collaboration and approval workflows using Densify’s API
The Densify Impact Analysis Report for AWS communicates the projected impact of recommended changes to app owners to help with approvals
Integration with Automation API’s and IaC
Integrate With CI/CD Pipelines & Automation Tools
- Free your teams from manually selecting resources
- Eliminate errors – use APIs to tie directly into infrastructure as code templates like Terraform or AWS CloudFormation
- Ensure Performance by continuously aligning resources with application requirements
Learn more about Managing Container Infrastructure & Performance.
So, you’re looking for the right instance type for your public cloud workload, but how do you decide?
Learn major trends across major cloud providers such as Amazon Web Services (AWS), Microsoft Azure Cloud and Google Cloud Platform (GCP). Read this article Public Cloud IaaS Catalogs Update.
