Overview
Distributed Load Testing on AWS automates software applications testing at scale and at load to help you identify potential performance issues before application release. This AWS Solution creates and simulates thousands of connected users, generating transactional records at a consistent pace without the need to provision servers. This solution also allows you to run tests across multiple AWS Regions.
Benefits
Test the load capabilities of your software using independent Amazon Elastic Container Service (Amazon ECS) on AWS Fargate containers.
Customize your application tests by creating custom JMeter scripts.
Schedule load tests to automatically begin either at a specified date or on recurring dates.
View live data for a running test using this solution's web console.
Technical details
You can automatically deploy this architecture using the implementation guide and the accompanying AWS CloudFormation template for AWS Regions.
Step 1
An Amazon API Gateway API invokes the solution's microservices (AWS Lambda functions).
Total results: 4
- Headline
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Small & Medium Business
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New to AWS
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Application Development & DevOps
Total results: 1
- Publish Date
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- Version: 3.3.2
- Released: 11/2024
- Author: AWS
- Est. deployment time: 15 mins
- Estimated cost: See details
"At Calabrio, our mission is to help contact centers work smarter, faster and better. We needed to design a new, high-performing feature for a major customer -- fast. We used Distributed Load Testing on AWS to test our system’s performance at scale, without the need for costly enterprise testing licenses or writing custom orchestration code for open-source tools. With this AWS Solution, we designed and executed tests at six times the expected traffic volume and launched the new feature successfully and ahead of schedule."
Related content
Whether you’re a private enterprise or a public sector service, you need confidence that your application can scale with increased user loads. Distributed Load Testing on AWS allows you to automate application testing, understand how it will perform at scale, and fix bottlenecks before releasing your application.