Save costs by paying only for the compute time you use—by the millisecond—instead of provisioning infrastructure upfront for peak capacity.

Optimize code execution time and performance with the right function memory size. Respond to high demand in double-digit milliseconds with Provisioned Concurrency.

AWS Lambda: How it works

AWS Lambda is a serverless, event-driven compute service that lets you run code for virtually any type of application or backend service without provisioning or managing servers. You can trigger Lambda from over 200 AWS services and software as a service (SaaS) applications, and only pay for what you use.

Use Amazon Simple Storage Service (Amazon S3) to trigger AWS Lambda data processing in real time after an upload, or connect to an existing Amazon EFS file system to enable massively parallel shared access for large-scale file processing.

Diagram showing how Serverless stream processing works. Social media stream is loaded into Amazon Kinesis, then Lambda is triggered. Lambda runs code that generates hashtag trend data, and the data is stored in DynamoDB for easy querying.

Diagram showing how Amazon S3, API Gateway, AWS Lambda, and DynamoDB work together to retrieve weather data for a web or mobile application.

Build serverless backends using AWS Lambda to handle web, mobile, Internet of Things (IoT), and third-party API requests.

Diagram showing how Amazon API Gateway, AWS Lambda, and Amazon SNS work together to help users receive status updates notifications in a mobile application.

Offline cloud migration moves data and applications from the organization’s on premises automation infrastructure to the cloud without relying on the internet. This strategy is frequently applied when a company has enormous data that would take too long to send over the internet.

Online cloud migration transfers digital assets and applications from a local data center to a cloud-based infrastructure via the internet without hindering the business’s regular operations.

5 Common ‘Post Cloud Migration Risks’ That Need Attention!

1) Weak Architecture and Unnecessary Computing Costs.

2) Lack of Understanding of Workload Ecosystem.

3) Security and Compliance Requirements.

4) Lack of Visibility into Performance and Usage.

5) Lifecycle Management and Cost Leakage.