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Right-sizing your resources in the cloud can go a long way to avoid wasting $$$s. Most people over-provision just about everything thinking they may need the extra capacity. One tool on AWS that can help with right-sizing is AWS Compute Optimizer.
AWS Compute Optimizer can analyze your resources and provide recommendations to you. It supports EC2 instances, EBS volumes, AWS Lambda, and much more. With AWS Lambda, you pay based on the amount of memory allocated to your function. AWS Compute Optimizer will recommend the best values to use.
This really interesting example setup from Zechariah Kasina shows how you can use Compute Optimizer with Lambda functions, Eventbridge, and SSM Param Store to automatically keep your config optimal.
Practice Verified Codes and Commands:
1. Enable AWS Compute Optimizer:
aws compute-optimizer update-enrollment-status --status Active
2. Get Recommendations for Lambda Functions:
aws compute-optimizer get-lambda-function-recommendations --function-arn <your-lambda-function-arn>
3. Automate Recommendations with EventBridge and SSM:
aws events put-rule --name "ComputeOptimizerLambdaRule" --event-pattern "{\"source\":[\"aws.compute-optimizer\"],\"detail-type\":[\"Compute Optimizer Recommendation\"]}"
aws events put-targets --rule "ComputeOptimizerLambdaRule" --targets "Id"="1","Arn"="<your-lambda-function-arn>"
4. Update Lambda Configuration with SSM Parameters:
aws ssm put-parameter --name "/lambda/optimal-memory" --value "256" --type "String" aws lambda update-function-configuration --function-name <your-lambda-function-name> --memory-size $(aws ssm get-parameter --name "/lambda/optimal-memory" --query "Parameter.Value" --output text)
What Undercode Say:
Optimizing cloud resources is crucial for cost efficiency, and AWS Compute Optimizer is a powerful tool to achieve this. By leveraging AWS Compute Optimizer, you can ensure that your Lambda functions are running with the optimal memory allocation, thereby reducing costs. The integration of EventBridge and SSM Parameter Store allows for automated updates, ensuring that your configurations are always optimal.
In addition to AWS-specific commands, it’s important to understand general Linux and Windows commands that can aid in cloud resource management. For instance, on Linux, you can use `top` or `htop` to monitor resource usage, and on Windows, `perfmon` can be used for similar purposes.
For further reading on AWS Compute Optimizer, visit the AWS Compute Optimizer Documentation.
Remember, the key to effective cloud management is continuous monitoring and optimization. Use tools like AWS Compute Optimizer, and always stay updated with the latest best practices in cloud architecture.
For more advanced configurations, consider exploring AWS CloudFormation templates to automate the setup of your cloud resources. This will not only save time but also ensure consistency across your environments.
In conclusion, optimizing your cloud resources is not just about reducing costs; it’s about ensuring that your applications run efficiently and reliably. By using AWS Compute Optimizer and integrating it with other AWS services, you can achieve a well-optimized cloud environment that meets your performance and budgetary needs.
For more detailed examples and tutorials, check out the AWS Compute Optimizer User Guide.
References:
initially reported by: https://www.linkedin.com/posts/darryl-ruggles_optimize-aws-lambda-costs-with-automated-activity-7302500646400786432-uznZ – Hackers Feeds
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