What is AWS Lambda?
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.
With Lambda, you can run code for virtually any type of application or backend service – all with zero administration. Just upload your code, and Lambda takes care of everything required to run and scale your code with high availability.
Following are some of the features of AWS Lambda
- Extend other AWS services with custom logic – AWS Lambda allows you to add custom logic to AWS resources such as Amazon S3 buckets and Amazon DynamoDB tables, so you can easily apply compute to data as it enters or moves through the cloud.
- Build custom backend services – You can use AWS Lambda to create new backend application services triggered on demand using the Lambda application programming interface (API) or custom API endpoints built using Amazon API Gateway.
- Bring your own code – With AWS Lambda, there are no new languages, tools, or frameworks to learn. Lambda natively supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby code.
- Completely automated administration – AWS Lambda manages all the infrastructure to run your code on highly available, fault tolerant infrastructure, freeing you to focus on building differentiated backend services.
- Built-in fault tolerance – AWS Lambda maintains compute capacity across multiple Availability Zones (AZs) in each AWS Region to help protect your code against individual machine or data center facility failures.
- Automatic scaling – AWS Lambda invokes your code only when needed, and automatically scales to support the rate of incoming requests without any manual configuration. There is no limit to the number of requests your code can handle.
- Only pay for what you use – With AWS Lambda, you pay for execution duration rather than server unit. When using Lambda functions, you only pay for requests served and the compute time required to run your code.
- Flexible resource model – Choose the amount of memory you want to allocate to your functions, and AWS Lambda allocates proportional CPU power, network bandwidth, and disk input/output (I/O).
Following is high level overview of Lambda Execution model
When is AWS Lambda Introduced ?
How does aws lambda work?
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.
Use AWS Lambda and Amazon Kinesis to process real-time streaming data for application activity tracking, transaction order processing, clickstream analysis, data cleansing, log filtering, indexing, social media analysis, IoT device data telemetry, and metering.
When to use aws lambda?
AWS Lambda makes it easy to execute code in response to events, such as changes to Amazon S3 buckets, updates to an Amazon DynamoDB table, or custom events generated by your applications or devices.
With Lambda, you do not have to provision your own instances; Lambda performs all the operational and administrative activities on your behalf, including capacity provisioning, monitoring fleet health, applying security patches to the underlying compute resources, deploying your code, running a web service front end, and monitoring and logging your code.
What is Lambda function ?
The code you run on AWS Lambda is uploaded as a “Lambda function”. Each function has associated configuration information, such as its name, description, entry point, and resource requirements. The code must be written in a “stateless” style i.e. it should assume there is no affinity to the underlying compute infrastructure.
- Each Lambda function receives 512 MB of non-persistent disk space in its own /tmp directory.
- You can package the code (and any dependent libraries) as a ZIP and upload it using the AWS CLI from your local environment, or specify an Amazon S3 location where the ZIP file is located. Uploads must be no larger than 50MB (compressed).
- AWS Lambda automatically monitors Lambda functions on your behalf, reporting real-time metrics through Amazon CloudWatch, including total requests, account-level and function-level concurrency usage, latency, error rates, and throttled requests.
- AWS Lambda functions can be configured to run up to 15 minutes per execution. You can set the timeout to any value between 1 second and 15 minutes.
What languages does aws lambda support ?
AWS Lambda natively supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby code, and provides a Runtime API which allows you to use any additional programming languages to author your functions.
What is AWS lambda layers ?
A Lambda layer is a .zip file archive that can contain additional code or other content. A layer can contain libraries, a custom runtime, data, or configuration files.
Layers provide a convenient way to package libraries and other dependencies that you can use with your Lambda functions. Using layers reduces the size of uploaded deployment archives and makes it faster to deploy your code. Layers also promote code sharing and separation of responsibilities so that you can iterate faster on writing business logic.
Benefits of AWS Lambda Layers