Connect AWS Compute Optimizer with GitHub and automate your FinOps workflows, faster

See How OpenOps Combines AWS Compute Optimizer and GitHub to Optimize FinOps Processes

Discover real-world FinOps use cases built with AWS Compute Optimizer, GitHub, and OpenOps. Explore how automation can help you manage cloud spend, streamline resource ownership, and drive financial accountability across your teams.

Automated Infrastructure Optimization in CI/CD Pipelines

Integrate AWS Compute Optimizer recommendations directly into your GitHub Actions workflows to automatically optimize EC2 instances, Lambda functions, and EBS volumes based on actual usage patterns. This integration enables development teams to receive cost optimization suggestions as pull request comments, ensuring infrastructure efficiency is considered during code reviews. Teams can automatically apply right-sizing recommendations before deploying to production, reducing cloud costs by up to 25% while maintaining performance standards.

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Performance-Driven Resource Recommendations for Applications

Leverage AWS Compute Optimizer's machine learning insights within GitHub repositories to optimize application performance based on workload characteristics. The integration analyzes your application's resource utilization patterns and provides tailored recommendations for instance types, memory configurations, and compute resources. Development teams receive actionable insights through GitHub issues, enabling data-driven decisions about infrastructure scaling and resource allocation that align with application performance requirements and cost optimization goals.

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Cost Governance Through Automated Optimization Tracking

Establish comprehensive cost governance by tracking AWS Compute Optimizer recommendations and implementation status through GitHub project boards and issues. This integration creates automated workflows that monitor optimization opportunities, track cost savings achieved, and maintain audit trails of infrastructure changes. Finance and engineering teams gain visibility into optimization initiatives, enabling better budget planning and ensuring continuous cost optimization practices are embedded into the development lifecycle.

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Frequently Asked Questions About AWS Compute Optimizer and GitHub Integrations

New to FinOps automations? Do not worry! Below you will find most relevant answers to common questions about how integration between AWS Compute Optimizer and GitHub works.

How does AWS Compute Optimizer integrate with GitHub for infrastructure optimization?

AWS Compute Optimizer analyzes your compute resources and generates rightsizing recommendations. When integrated with GitHub, these optimization insights can be automatically committed to your infrastructure-as-code repositories, enabling version-controlled infrastructure improvements and seamless collaboration between DevOps teams on cost optimization initiatives.

Can GitHub Actions automatically implement AWS Compute Optimizer recommendations?

Yes, GitHub Actions can be configured to automatically retrieve AWS Compute Optimizer recommendations via APIs and update your Terraform or CloudFormation templates. This creates an automated pipeline for implementing rightsizing suggestions while maintaining proper code review processes and deployment controls.

What cost savings can I expect from AWS Compute Optimizer GitHub integration?

Organizations typically see 15-25% reduction in compute costs by implementing Compute Optimizer recommendations. GitHub integration accelerates this process by automating recommendation tracking, enabling faster implementation cycles, and providing collaborative workflows that ensure optimization suggestions are systematically reviewed and deployed.

How does version control help with AWS compute resource optimization decisions?

Version control through GitHub creates an audit trail of all infrastructure changes, including compute optimizations. This enables teams to track performance impacts, rollback problematic changes, compare optimization strategies over time, and maintain compliance documentation for infrastructure modifications and cost reduction efforts.

What GitHub workflows work best for managing AWS Compute Optimizer recommendations?

Effective workflows include automated pull requests for optimization recommendations, scheduled GitHub Actions to fetch new suggestions, branch protection rules requiring review of infrastructure changes, and integration with issue tracking to monitor implementation progress and measure cost savings impact.

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How OpenOps Works

OpenOps makes it easy to connect AWS Compute Optimizer with GitHub - no code necessary.

Choose a FinOps Optimization Template

Kickstart your FinOps journey with a catalog of pre-built templates. Customize workflows to your cloud goals - or create new ones from scratch using OpenOps' no-code building blocks.

Connect Your Cloud and FinOps Tools

Easily integrate OpenOps with your cloud environment and FinOps stack. Start with any CSP access level and instantly fit OpenOps into your existing processes, teams, and reporting systems.

Keep Humans in the Loop

Streamline approvals, ownership, and communication with built-in stakeholder workflows. OpenOps connects data across your cloud infrastructure to help you manage FinOps collaboration at scale.

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Secure by Design

OpenOps is dedicated to delivering top-tier security and compliance for all cloud operations. By adhering to the highest industry standards and maintaining a transparent, flexible approach, OpenOps ensures that businesses can manage their financial operations with confidence and peace of mind.

Quick setup with minimal access

OpenOps only requests necessary permissions, keeping exposure and data access to a minimum.

Transparent permission management

OpenOps provides full visibility into permissions, access, and usage.

Safe remediation

Set up custom authorizations to keep stakeholders in the loop and avoid blind automation.

You maintain full control

No agent is required in your ecosystem; you retain complete authority over permissions.

Security first approach

Human oversight and compliance-driven controls provide extra protection and safeguard data.

Leverage existing permissions

OpenOps utilizes the existing cloud security model and doesn't require breaking it with admin-level credentials to run automations.

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