The serverless compute service AWS Lambda executes your code in response to events and manages the underlying compute resources for you automatically. These can be updates or status changes, like when a customer adds something to their shopping cart on an e-commerce website. You can build your own backend services that function at AWS scale, performance, and security, or you can use AWS Lambda to augment existing AWS services with custom functionality. In reaction to a variety of events, such as HTTP requests made through Amazon API Gateway, alterations made to objects in Amazon Simple Storage Service (Amazon S3) buckets, table updates in Amazon DynamoDB, and state changes in AWS Step Functions, AWS Lambda automatically executes code. As a leading software development company, we are explaining what the important key features of AWS Lambda are with details.
Lambda executes your code on high availability compute infrastructure and handles all compute resource administration. This covers patch deployment, capacity provisioning and automatic scaling, code monitoring and logging, and server and operating system maintenance. You only need to provide the code.
Key product features
Other AWS services can be expanded with custom logic
You can simply apply computation to data as it enters or moves across the cloud with the help of AWS Lambda, which enables you to add custom logic to AWS resources like Amazon S3 buckets and Amazon DynamoDB tables.
With AWS Lambda, getting started is simple. By uploading your code (or generating it directly in the Lambda console) and selecting the memory, timeout duration, and AWS Identity and Access Management (IAM) role, you first establish your function. The AWS resource to use to activate the function is then specified; this could be a specific Amazon S3 bucket, Amazon DynamoDB table, or Amazon Kinesis stream. Lambda will execute your function when the resource changes, launching and managing the computing resources as necessary to keep up with incoming requests.
Create unique backend services
With the help of the Lambda application programming interface (API) or unique API endpoints created with Amazon API Gateway, you may utilise AWS Lambda to develop new backend application services that are activated on demand. Instead of handling custom events on the client, Lambda handles them, which helps you avoid client platform variances, save battery life, and facilitate easier upgrades.
Carry your own coding
When using AWS Lambda, there are no new programming languages, tools, or frameworks to learn. Any third-party library, including native ones, may be used. You can manage and share any code (including frameworks, SDKs, libraries, and more) simply across numerous functions by packaging it as a Lambda Layer. In addition to natively supporting Java, Go, PowerShell, Node.js, C#, Python, and Ruby code, Lambda offers a Runtime API that enables you to write your functions in any other programming language.
Full automation of administration
You can concentrate on creating unique backend services since AWS Lambda takes care of managing the infrastructure needed to run your code on highly available, fault-tolerant infrastructure. With Lambda, you never have to worry about scaling or adding more servers as your demand increases or updating the underlying operating system (OS) when a patch is issued. Your code is automatically deployed by AWS Lambda, which also manages all administration, maintenance, and security fixes. Amazon CloudWatch also offers built-in logging and monitoring capabilities.
Integrated Fault tolerance
To assist in safeguarding your code against individual machine or data center facility outages, AWS Lambda maintains compute capacity across multiple Availability Zones (AZs) in each AWS Region. The service’s functions and AWS Lambda both offer predictable and dependable operating performance. High availability is a feature that AWS Lambda is built to offer for both the service and the operations it does. There aren’t any scheduled downtimes or maintenance windows.
Functions packaged and deployed as container images
Customers can create Lambda-based apps quickly and easily, utilizing familiar container image tooling, workflows, and dependencies, thanks to AWS Lambda’s support for function packaging and deployment as container images. Customers also profit from Lambda’s operational simplicity, automated scaling, high availability, pay-per-use invoicing approach, and native interfaces with more than 200 AWS services and software-as-a-service (SaaS) programs. Using a standard set of tools across their Lambda and containerized applications allow enterprise customers to streamline central governance requirements like security scanning and image signing.
Functions packaged and deployed as container images
Customers can create Lambda-based apps quickly and easily, utilizing familiar container image tooling, workflows, and dependencies, thanks to AWS Lambda’s support for function packaging and deployment as container images. Customers also profit from Lambda’s operational simplicity, automated scaling, high availability, pay-per-use invoicing approach, and native interfaces with more than 200 AWS services and software-as-a-service (SaaS) programs. Using a standard set of tools across their Lambda and containerized applications allow enterprise customers to streamline central governance requirements like security scanning and image signing.
Scaling automatically
Without any explicit configuration, AWS Lambda automatically scales to meet the volume of incoming requests and only executes your code when necessary. Your code can process an unlimited number of requests. Your code will normally begin running on AWS Lambda within milliseconds of an event. As the frequency of events rises, performance is consistently high because of Lambda’s automated scaling. Your code is stateless, so Lambda can launch as many instances as necessary without having to wait around for extensive deployment and configuration times.
Access relational databases
To benefit from fully managed connection pools for relational databases, use Amazon RDS Proxy. Building highly scalable, secure Lambda-based serverless applications that interface with relational databases is simple because of RDS Proxy’s effective management of thousands of concurrent connections to relational databases. RDS Proxy currently supports MySQL and Aurora. For your serverless apps, you can use RDS Proxy via the Amazon RDS console or the AWS Lambda console.
Performance control on a small scale
You have more control over the efficiency of your serverless applications with provisioned concurrency. When enabled, Provisioned Concurrency maintains initialized and hyper-ready functions that can reply in fewer than ten milliseconds. Any AWS Lambda application needing more control over function start time should use provisioned concurrency. Conveniently configure and modify the concurrent processes required by your application. Adapt it to demand by scaling it up, down, or turning it off entirely. Utilize provisioned concurrency to maintain performance for applications that are sensitive to latency without modifying your code or managing compute resources.
Obtain access to shared file systems
You can securely read, write, and persist huge volumes of data at any scale using Amazon Elastic File System (EFS) for AWS Lambda. Processing data does not require downloading it to temporary storage or adding code to it. You can concentrate on your business logic because the code is simpler and time is saved. For a variety of use cases, such as processing or backing up big data volumes, and importing massive reference files or models, EFS for Lambda is the best option. Additionally, you may use EFS for AWS Lambda to execute machine learning (ML) inference, transfer files amongst serverless instances or container-based apps, or even run ML inference.
Respond to Amazon CloudFront requests by executing code
AWS Lambda may execute your code worldwide across AWS locations in response to Amazon CloudFront events, such as content requests to or from origin servers and viewers.
Coordinate numerous tasks
Create AWS Step Functions workflows to manage a number of AWS Lambda functions for difficult or protracted activities. You may create workflows with Step Functions that use sequential, parallel, branching, and error-handling steps to launch a group of Lambda functions. You can create stateful, lengthy processes for applications and backends using Lambda and Step functions.
Model for integrated security
To enable secure code access to other AWS services, AWS Lambda’s integrated software development kit (SDK) interfaces with AWS Identity and Access Management (IAM). By default, AWS Lambda executes your code inside an Amazon Virtual Private Cloud (VPC). To use unique security groups and network access control lists, you can elect to arrange AWS Lambda resource access behind your own VPC. This gives your resources inside a VPC secure Lambda function access. SOC, HIPAA, PCI, and ISO compliance apply to AWS Lambda. Please refer to the full services in scope for the most recent information on compliance preparedness and Lambda certification.
Integrity and trust regulate
You can confirm that only unaltered code provided by authorized developers is deployed in your Lambda functions by using code signing for AWS Lambda. All you need to do is produce digitally signed code artifacts and set up your Lambda functions to deploy them with the signatures verified. This enforces strict security standards while increasing the speed and agility of your application development, even across big teams.
Pay just for what you really use
Instead of paying per server unit with AWS Lambda, you pay per execution duration. You only pay for requests that are fulfilled and the computing time needed to execute your code when using Lambda functions. Since billing is metered in millisecond increments, it is simple and affordable to automatically scale from a few requests per day to thousands per second. When using provisioned concurrency, you only pay for the concurrency you define for the specified time period and amount. You must additionally pay for requests and the length of the execution when provisioned concurrency is enabled and your function is running. Visit AWS Lambda Pricing for additional information on pricing.
Resource model that is flexible
AWS Lambda allows CPU power, network bandwidth, and disc input/output (I/O) in proportion to the amount of memory you choose to give your functions.
Lambda to your preferred operational tools Resource model that is flexible
Your favorite monitoring, observability, security, and governance solutions can be easily integrated with AWS Lambda. Your function is called by Lambda in an execution environment, which offers a safe and segregated runtime for the execution of your function code. Along with your function code, Lambda extensions execute within the Lambda execution environment. With Lambda extensions, you may send function logs, metrics, and traces to any destination of your choice and collect fine-grained diagnostic data. Additionally, you can incorporate security agents within Lambda’s execution environment with little to no operational expense and an adverse effect on the efficiency of your function. Contact Nettyfy if you want to use AWS Lambda for your next Project.