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AWS Lambda

AWS Lambda is a serverless computing service that allows you to run code in response to events and has the added benefit of automatically managing the underlying compute resources. Among these events may be a change in status or an update, such as a user adding an item to his or her shopping cart on an ecommerce website, among others.

Why use Lambda?

Using AWS Lambda, you may add custom logic to other AWS services, or you can use it to build your own backend services that operate at the same high levels of scalability, performance, and security as AWS. When a variety of events occur, such as HTTP requests via Amazon API Gateway, adjustments to objects in Amazon Simple Storage Service (Amazon S3) buckets, table updates in Amazon DynamoDB, and state transitions in AWS Step Functions, AWS Lambda automatically runs code. All of your computational resources are managed by Lambda, which runs your code on high-availability infrastructure. There are several aspects to this, including server and operating system maintenance; capacity provisioning; automatic scaling; distribution of security patches; and code and log monitoring and archiving. Only the code must be supplied.

How it Works

An event-driven computing service, AWS Lambda can run code for practically any application or backend service without the need to provision and manage servers. AWS Lambda can be triggered from more than 200 services and software-as-a-service (SaaS) applications.

File Processing:

AWS Lambda data processing can be triggered in real time via Amazon Simple Storage Service (Amazon S3), or an Amazon EFS file system can be connected to offer massively parallel shared access for large-scale file processing.

Stream Processing:

With the help of AWS Lambda and Amazon Kinesis, you can perform real-time streaming analysis of application activity, transaction order processing and clickstream analysis among other things.

Web Applications:

Make use of the scalability and high availability provided by AWS Lambda and other AWS services to create robust web apps that scale up and down automatically.

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IoT Backends

AWS Lambda may be used to build serverless backends for web, mobile, IoT, and third-party API requests.

Mobile Backends

 

Authentication and processing of API requests can be accomplished with AWS Lambda and Amazon API Gateway backends. When you use AWS Amplify, you can quickly interface your backend with your iOS, Android, Web, and React Native frontends.

Features:

Custom logic can be used to extend other AWS services

AWS Lambda let you apply compute to data as it enters or moves through the cloud by allowing you to add custom logic to AWS resources such as Amazon S3 buckets and Amazon DynamoDB tables. 

AWS Lambda is a simple service to learn how to use. Creating your function begins with uploading your code (or generating it directly in the Lambda interface) and selecting the memory size, timeout duration, and AWS Identity and Access Management (IAM) role you want it to have. Then, you provide the AWS resource that will be used to activate the function, which can be a specific Amazon S3 bucket, Amazon DynamoDB table, or Amazon Kinesis stream, among other things. In response to the change in resource, Lambda will execute your function, launching and managing computing resources as necessary to keep up with the number of incoming requests.

Create your own unique backend services

When utilising Amazon API Gateway to establish custom API endpoints, you can create new backend application services that are triggered on demand using the Lambda application programming interface (API) or the Lambda application programming interface (API). The use of Lambda to process custom events rather than servicing them on the client helps you avoid client platform variances, save battery drain, and make updates easier to implement and maintain.

Bring your own code 

There are no new programming languages, tools, or frameworks to learn when using AWS Lambda. You are free to utilize any third-party library you like, including native libraries. A Lambda Layer can be used to package any code (including frameworks, SDKs, libraries, and other types of code) so that it can be managed and shared across numerous functions with ease. Lambda supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby code natively, and it also provides a Runtime API that allows you to author your functions in any more programming languages. Lambda is available in English and Spanish.

Automation of administration

AWS Lambda takes care of all the infrastructure so you can focus on designing unique backend services that are highly available and fault-tolerant. Using Lambda, you never have to worry about scaling or adding more servers as your consumption grows, because the underlying operating system (OS) is always updated. AWS Lambda takes care of all the administration, maintenance, and security fixes for you, and it provides built-in logging and monitoring using Amazon CloudWatch.

Built-in tolerance for failures

Because of the numerous Availability Zones (AZs) in each AWS Region, AWS Lambda helps safeguard your code from machine or data centre facility outages. Amazon Lambda and its functions deliver dependable, repeatable operational performance. AWS Lambda is built to ensure high availability for both the service and the functions it manages on the AWS cloud. It does not have scheduled downtimes or maintenance windows.

Container images can be used to package and deliver applications

Functions may be packaged and deployed as container images using AWS Lambda, making it easier for clients to construct Lambda-based apps using familiar container image tools and workflows. Its operational simplicity, automatic scaling with sub-second startup times and high availability are only some of the advantages that customers gain from Lambda. With Lambda and containerized applications, enterprises can employ a standardized set of technologies, making central governance tasks like security scanning and image signing simpler.

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Automatic scalability

AWS Lambda executes your code only when it is required, and it automatically scales to accommodate the volume of incoming requests without the need for any manual configuration. There is no limit to the number of requests that your code can handle. AWS Lambda normally begins running your code within milliseconds of an event occurring. Because Lambda scales automatically, performance remains consistently excellent even as the number of events per second rises. Because your code is stateless, Lambda may spawn as many instances as necessary without requiring you to wait for significant deployment and configuration delays.

Connect to relational databases via a web browser

Using Amazon RDS Proxy, you may take use of fully managed connection pools for relational databases, which are otherwise unavailable. When thousands of concurrent connections to relational databases are managed efficiently, it becomes simple to develop highly scalable, secure Lambda-based serverless applications that interact with relational databases. RDS Proxy currently provides support for MySQL and Aurora databases. If you are using the Amazon RDS console or the AWS Lambda console, you can configure RDS Proxy for your serverless apps.

Relational databases should be connected

If you are running a relational database, you can take use of fully managed connection pools provided by Amazon RDS Proxy. When thousands of concurrent connections to relational databases are managed properly, it becomes simple to develop extremely scalable and secure Lambda-based serverless applications that interface with relational databases. As of right now, RDS Proxy provides support for both MySQL and Aurora databases. If you are using the Amazon RDS console or the AWS Lambda console, you can use RDS Proxy for your serverless apps.

Control over performance at the granular level

With Provisioned Concurrency, you may have greater control over the performance of your serverless applications. The Provisioned Concurrency feature, when enabled, keeps functions initialized and hyper-ready to reply in double-digit milliseconds or less. Provisioned Concurrency is an excellent choice for any AWS Lambda application that requires additional control over the time it takes for functions to start. Concurrency requirements for your application can be easily configured and adjusted. Depending on demand, you can scale it up, down, or turn it off completely. Utilize Provisioned Concurrency to achieve consistent performance for latency-sensitive applications without having to change your code or manage compute resources.

Connect to networked file systems

With Amazon Elastic File System (EFS) for AWS Lambda, you can securely read, write, and persist huge volumes of data with low latency, at any scale. It is not necessary to create code or download data to temporary storage in order to process it. This saves you time and simplifies the code, allowing you to concentrate on your business logic. EFS for Lambda is well suited for a variety of use scenarios, including processing or backing up massive amounts of data, as well as importing big reference files or models. By using EFS for AWS Lambda, you can also transfer files between serverless instances or container-based apps, and you can even execute machine learning (ML) inference by using AWS Lambda.

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Execute code in response to requests from Amazon CloudFront.

Amazon CloudFront events, such as content requests to or from origin servers and viewers, can trigger the execution of your code across many AWS locations across the world using [email protected] It becomes easier to deliver richer, more tailored content to your end consumers while maintaining reduced latency as a result of this.

Coordinate different functions

Make use of Amazon Web Services’ Step Functions to coordinate several AWS Lambda functions for complex or long-running activities. It is possible to create workflows that activate a group of LambdA functions by using sequential, parallel, branching, and error-handling steps in the Step Functions library. You can create stateful, long-running processes for apps and backends using Step Functions and Lambda.

Security model that is integrated

To enable safe code access to other AWS services, the built-in software development kit (SDK) of AWS Lambda interfaces with AWS Identity and Access Management (IAM). As a default, Amazon Web Services Lambda executes your code within an Amazon Virtual Private Cloud (VPC). In order to take advantage of custom security groups and network access control lists, you can configure AWS Lambda resource access behind your own VPC as an option. This enables Lambda function access to your resources within a VPC in a safe and secure manner. AWS Lambda complies with SOC, HIPAA, PCI, and ISO standards.

Controls are based on trust and integrity.

Code signing for AWS Lambda allows you to ensure that only unaltered code published by authorized developers is deployed in your Lambda functions by using the Code Signing API. You only need to build digitally signed code artifacts and configure Lambda functions to check the signatures when the code is being deployed. When working in big teams, this boosts the speed and agility of your application development while also ensuring that strict security standards are followed.

Pay as you go

AWS Lambda charges execution time rather than server unit. With Lambda functions, you only pay for requests served and compute time used. Billing is done in millisecond intervals, allowing for easy and cost-effective scaling from a few per day to thousands per second. With Provisioned Concurrency, you only pay for the concurrency you use. When Provisioned Concurrency is enabled, you pay for requests and execution time.

Adaptable resource model

AWS Lambda allocates proportional CPU power, network bandwidth, and disc I/O to your functions based on the memory you choose.

Synchronize Lambda with your favorite tools

AWS Lambda extensions simplify monitoring, observability, security, and governance. Lambda invokes your function in a secure and isolated execution environment. Lambda extensions run alongside your function code in Lambda’s environment. With Lambda extensions, you may send function logs, metrics, and traces to whatever destination you want. The Lambda execution environment allows you to incorporate security agents with minimum operational overhead and no performance impact.

Graviton2 functions improve pricing performance by up to 34%.

AWS Lambda functions operating on Graviton2, AWS’s Arm-based processor architecture, outperform x86-based functions by up to 34%. This includes serverless online and mobile backends, data, and media processing. Graviton2 functions offer lower latency, higher performance, lower cost, and the best power efficiency currently offered on AWS.

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