Introducing AWS Resource Scheduler: Automate and Optimize Your AWS Resources for Cost Savings

I'm excited to share that Cloudstaff, a leader in cloud-based workforce solutions, has open-sourced a powerful tool to help you automate the management of your AWS resources and optimize costs: AWS Resource Scheduler.

As part of our commitment to the tech community, we're giving back by open-sourcing tools like AWS Resource Scheduler. We believe that collaboration and shared innovation drive technological advancement and community growth.

This tool is the outcome of our cloud cost optimization efforts, which have helped us reduce our overall cloud costs by 47%.

?? What is AWS Resource Scheduler?

AWS Resource Scheduler is a Python module designed to automate the start and stop operations for various AWS resources, including EC2 instances, Auto Scaling Groups (ASG), ECS services, RDS databases, and Aurora clusters.

?? Key Features:

• Resource Bundling: Create groups of resources using names or tags that need to be started or stopped together—for example, for a specific project or team.
• Multi-Region and Multi-Account Support: Manage resources across multiple AWS regions and accounts seamlessly.
• Dependency Management: The scheduler checks for resources to become healthy before moving to the next, allowing you to define the sequence and dependencies.
• IaC Compatibility: No need to change tags or infrastructure—compatible with tools like AWS CDK and Terraform.
• Comprehensive Resource Support: Start/stop EC2 instances, RDS databases, Aurora clusters, and scale ASGs and ECS services up or down.
• Scheduling and Notifications: Schedule operations based on predefined configurations and receive notifications via Google Chat, Slack, or Microsoft Teams.

?? Why This Matters for AWS Cost Savings

In today's cloud-driven world, managing costs is crucial. AWS Resource Scheduler helps you optimize costs by ensuring that resources are only running when needed. By automating start and stop operations, you can reduce unnecessary expenditure on idle resources.

According to recent reports, companies can save up to 40% on their AWS Compute bills by automating resource management and shutting down non-critical resources during off-hours.

?? Get Started

The tool is available on GitHub and PyPI:

• GitHub Repository: https://github.com/cloudstaff-apps/aws-resource-scheduler
• PyPI Package: https://pypi.org/project/aws-resource-scheduler/

Installation and use is as simple as:

pip install aws-resource-scheduler
aws-resource-scheduler -f config.yml -w stage -r ec2,rds,asg,ecs -a stop        

Configuration and usage instructions are available in the README.

?? Deploy as AWS Lambda with S3 Configuration Support

If you'd like to deploy AWS Resource Scheduler as an AWS Lambda function, we have created a ready-to-use package:

• Serverless Deployment: Package the scheduler as a Lambda function and deploy it directly to AWS Lambda using the provided instructions.
• Remote Configuration with S3: Store your configuration files in Amazon S3 buckets. The Lambda function can fetch the latest configurations at runtime using the CONFIG_S3_BUCKET and CONFIG_S3_KEY environment variables.
• Flexible and Scalable: Leverage AWS Lambda's scalability to handle varying workloads efficiently while only paying for the compute time you consume.

Read more about the same on README-lambda.md

?? Join the Community

We welcome contributions, issues, and feature requests. Let's collaborate to make cloud resource management more efficient!

?? Spread the Word

If you find this tool useful, please share it with your network.

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