What is AWS Lambda?
How does AWS Lambda work?
AWS manages AWS Lambda’s whole infrastructure layer. AWS handles updating the underlying machines, minimizing network conflicts, and other issues on its own, thus customers don’t have much visibility into how the system works.
AWS Lambda is a serverless computing service that automatically executes code in response to specific events, without the need for managing underlying infrastructure. It operates by receiving an event trigger from sources such as an API call, file upload to S3, or changes in a DynamoDB table. Once triggered, Lambda executes the corresponding code and scales automatically based on the incoming event volume, ensuring optimal resource usage. The main economic advantage of AWS lambda is that you pay for your lambda service only when your code is running.
Additionally, adopting AWS Lambda can help you save time on operational responsibilities because the service is fully controlled. While this means you give up the freedom of operating your own infrastructure, you can spend more time concentrating on the application code when there is no infrastructure to maintain.
- A separate container is used to run each Lambda function, and each function is packaged into a new container when it is created by Lambda, which then runs that container on a multi-tenant cluster of servers run by AWS.
- Every function’s container is given the required amount of RAM and CPU power before the functions begin to operate.
- The RAM allotted at the beginning is multiplied by the length of time each function ran after it has finished.
- The consumers are then charged in accordance with the memory allotted and the length of time it takes for the function to finish.
The ability to execute several instances of the same function, or various functions from the same AWS account, is one of the unique architectural features of AWS Lambda. Furthermore, Lambda is unaffected by variations in frequency caused by the time of day or day of the week; you are only charged for the compute that your friends require. Because of this, developing highly scalable cloud computing solutions is an excellent fit for AWS Lambda.
What is AWS Lambda used for?
There are many different use cases where AWS Lambda is the best fit for the prescribed workload. A few of them are listed below:
Scalable APIs
One HTTP request can be served by a single Lambda function execution when creating APIs using AWS Lambda. Through Amazon API Gateway, different API components can be forwarded to various Lambda functions. Different components of your API can scale differently depending on the level of usage since AWS Lambda automatically adjusts individual functions in response to demand. This enables flexible and affordable API installations.
Data Processing
Lambda functions are ideal for handling event-based data. AWS Lambda is simple to integrate with data sources like Amazon DynamoDB, and you can set up a Lambda function to be called in response to particular sorts of data events. Lambda is an excellent fit for things like notifications, counters, and analytics.
Task Automation
AWS Lambda is perfect for automating a variety of business operations that don’t always require a full server due to its event-driven paradigm and flexibility. This could involve executing scheduled tasks that clean up your infrastructure, processing data from online forms, or on-demand data movement across several datastores.
AWS Lambda-supported languages & runtimes
These runtimes are all offered on an Amazon Linux or Amazon Linux 2 environment and are all maintained by AWS. You may develop your Lambda functions and integrate them with other AWS services more easily by using the SDKs that AWS offers for each of the supported languages.
- Node.js 8.10
- Node.js 10.x (normally the latest LTS version from the 10.x series)
- Node.js 12.x (normally the latest LTS version from the 12.x series)
- Python 2.7
- Python 3.6
- Python 3.7
- Python 3.8
- Ruby 2.5
- Java 8 (This includes JVM-based languages that can run on Java 8’s JVM — the latest Clojure 1.10 and Scala 2.12 both run on Java 8 so can be used with AWS Lambda)
- Java 11
- Go 1.x (latest release)
- C# — .NET Core 1.0
- C# — .NET Core 2.1
- PowerShell Core 6.0
AWS Lambda Use Cases
- Web applications:
Programmers can create web apps that scale up and down and operate across different data centers by integrating AWS Lambda with other AWS services. - Mobile backends:
For the authentication and processing of API requests, you can construct backends utilizing AWS Lambda and Amazon API Gateway. For instance, Bustle uses AWS Lambda and Amazon API Gateway to run a serverless backend for its Bustle iOS app and websites. - IoT backends:
To handle web, mobile, Internet of Things (IoT), and third-party API requests, you can construct serverless backends using AWS Lambda. - Data Changes:
Every time a value in a DynamoDB database changes, AWS Lambda can be used to execute data validation, filtering, sorting, or other transformations, and then load the converted data into another data store. Developers can set up a Lambda function to be called anytime a DynamoDB table is updated since Amazon provides interaction between DynamoDB, Amazon’s NoSQL database that employs a JSON-based query language, and AWS Lambda. You may do a variety of tasks inside and outside of AWS using Lambda functions, like sending notifications via Amazon SNS, writing to additional DynamoDB tables, maintaining Cognito identity pools, and more. - Real-time stream processing:
For application activity tracking, transaction order processing, click stream analysis, data purification, metrics generation, log filtering, indexing, social media analysis, and IoT device data telemetry and metering, AWS Lambda and Amazon Kinesis can be used.
Conclusion
AWS Lambda is a versatile serverless computing service offered by Amazon Web Services (AWS) that allows developers to perform a wide range of tasks, from processing data streams and handling API requests to integrating with other AWS services. By abstracting server management away from the developer, Lambda enables IT professionals to focus on writing and optimizing their application code without the overhead of maintaining infrastructure.
AWS manages the scaling and availability of the service automatically, ensuring high performance under varying workloads. With support for several programming languages, including Node.js, Python, Java, and C#, AWS Lambda caters to diverse development environments. Tools like Maven and Gradle further simplify building and deploying the functions. This flexibility and integration capability make AWS Lambda an essential tool for modern, cloud-based development.
FAQs:
Q: How to deploy AWS Lambda?
A: You can deploy AWS Lambda by writing a function in a supported language, packaging it with its dependencies, and uploading it through the AWS Management Console, AWS CLI, or an automation tool like AWS CloudFormation or Terraform.
Q: What are the 3 components of AWS Lambda?
A: The three components of AWS Lambda are the function (your code), event source (the trigger that invokes the function), and execution environment (the runtime where your code executes).
Q: What is the advantage of using AWS Lambda?
A: AWS Lambda eliminates the need to manage servers, automatically scales based on demand, and charges only for the compute time used during function execution.
Q: Is AWS Lambda an ETL tool?
A: No, AWS Lambda is not an ETL tool, but it can be used to perform ETL tasks such as data transformation and loading when integrated with services like S3, DynamoDB, or RDS.
Q: What is the disadvantage of AWS Lambda?
A: One disadvantage of AWS Lambda is its execution time limit of 15 minutes, which may not be suitable for long-running processes.
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