Resource Optimization within a DevOps Toolchain

A DevOps graphic

Relieve Developers From The Burden Of Estimating The Resource Requirements Of Their Code

DevOps means speed, release frequency, control and reliability, yet most organizations are leaving the critical element of specifying resources up to best efforts and guesswork.  Like the quality of code that is written, the resources you provide your applications or processes have a direct impact on performance, efficiency and cost.

Don’t leave it to guesswork.

Densify enables a DevOps integrated approach to Resource Management by providing:

  • Precision analytics that examine workloads deeply and constantly to inject the right resource specifications for every workload
  • Flexible ways to integrate into processes and workflows that end in automated execution of the optimal resource settings for every application

Continuous Resource Optimization
within a DevOps Toolchain


Analyze detailed utilization patterns against cloud instance and container configurations, using sophisticated policies, to recommend optimal resource settings.

Socialize recommendations using Densify’s reporting engine, and optionally tie into approval workflows (e.g. Jira, ServiceNow) to allow app owners to understand and safely adopt changes.

Integrate with tools like Terraform using the Densify API to enable seamless execution of resource optimization recommendations, fully honoring approval processes.

Detect and eliminate operational risks, and not just waste, by automatically identifying undersized cloud instances, poorly performing scale groups, and misconfigured container requests and limit.

Continuous Optimization That Fits into Your CI/CD Framework

Are your teams hard coding instance types and resources into IaC frameworks? HashiCorp Terraform and AWS CloudFormation simplify and automate the process of managing and provisioning infrastructure. But often resource specifications are hard coded, meaning that unless there is intervention, that instance will always be what is specified at deploy time. A small modification of your infrastructure as code templates can ensure your cloud apps get exactly the cloud resources they need at the lowest possible cost.

Introduction to Optimization as Code

The Solution: Optimization as Code

The Densify analytics engine uses patented machine learning to continuously model your apps’ utilization patterns to determine if the resources they have are optimal. Densify then generates recommendations for optimal instance types and size or resources in the case of containers.  The result is that you can:

  • Inject these findings into your instances as tags (optional)
  • Automatically create “App Owner Reports” for transparency to app and business owners. These can be delivered via change tickets
  • Generate machine-readable output for actioning by automation processes

By replacing fixed resource assignments in your templates with calls to reference Densify’s recommendations, your workloads can be automatically provisioned to the best-fit instances. As resource demands change over time or newer instance types are introduced by cloud providers, your infrastructure remains optimized. 

provider "aws" {
  region = "${var.aws_region}"
resource "aws_instance" "web" {
  name = "Web Server"
  #instance_type = "m4.large"
  instance_type = "${lookup(local.densify_spec,"appr_type") == "all" ? lookup(local.densify_spec,"rec_type") : lookup(local.densify_spec,"cur_type")}"
  ami = "${lookup(var.aws_amis, var.aws_region)}"
Optimization as code dynamically adjusts the instance type, ensuring your apps always get the resources they require

Everybody Wins

Bridge the Gap Between App Developers, CloudOps, & Finance

Developers are freed from the burden of having to guess at and update resource or instance specifications.

Cloud operations teams can provide API-based optimization services to app teams, enabling them to run a safe and efficient environment

Finance benefits from the dramatically-improved cost efficiency that comes with machine learning

Raiffeisen Bank Aval

Raffeisen shares OpenShift optimization with Jenkins CI/CD. Watch how Raiffeisen Bank saves 50% on the frequency of resource expansions, an overall reduction in resources required, and the alleviation of the risk of instability caused by container memory shortages.