What is AWS Lambda

What is AWS Lambda?

AWS Lambda is a serverless computing service that enables users to run applications or service codes without the issue of managing servers. You need to create an AWS Lambda function that supports your programming language and upload it to the console and run it.

Its infrastructure is elastic, efficient, and available in many regions, making it easier to run administration tasks like scaling and server maintenance.

Most functions can handle different applications backends, computing tasks, and integration with other AWS services. It optimizes code execution that improves performance using the provisioned currency that helps improve the functions' response time. It's cheap as you only pay for what you need and use.

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Why Amazon Lambda?

When working with applications, AWS Lambda provides a computing service that provides database service and HTTP gateway service. It also integrates with all Amazon Web Services products, making implementing serverless easier. It works with most programming languages making it an excellent option to use.

How does AWS Lambda Works?

Every Lambda function has its container, and once a function gets created, it gets executed using different clusters of machines provided by Amazon Web Services. Each container has its allocation of resources(CPU and RAM). 

AWS takes care of infrastructure like underlying machines, providing better network, e.t.c. AWS Lambda has immutable instances where you can't use them after their termination. Most of them help ensure there is on-demand usage, and it helps execute the code concurrently. 

Once a user uploads the code into the Lambda, depending on the programming language. Users can trigger the AWS Lambda using different AWS services. The lambda code gets executed, and some of the things that happen, e.g., push notifications, data stream collection, modifying tables, HTTP requests, table updates, e.t.c.

Features of AWS Lambda

Some of the features of AWS Lambda include:

• You use your code. You use the programming language you prefer from Java, Go, PowerShell, Node.js, C#, and Python.
• It uses functions for deployment and packaging.
• It supports relational databases like MySQL and Aurora.
• It connects to shared file systems like Amazon Elastic File System (EFS).
• It has  Lambda@Edge that users can use to run code on different AWS locations.
• It has an SDK that integrates well with AWS Identity and Access Management (IAM) to secure the code and ensure it meets the compliance regulations, i.e., SOC, HIPAA, and PCI.
• It has a good resource model that gives you the power to allocate memory to specific functions.
• You can integrate it with other AWS services to improve observability and governance.

What Is A Lambda Function In AWS?

Lambda function is a computing resource that helps users run code in Lambda. It mainly focuses on the events the code has to process to pass the process into the function or other AWS services. 

It helps perform tasks like OS patching, provisioning, access control, right-sizing, e.t.c. Packaging functions-they compress all the lambda functions, i.e., the dependencies.

What’s the Process For Creating AWS Lambda Function?

There are several steps for creating an AWS Lambda function. Users have to follow the following steps below when creating a Lambda function:

1. Sign in to your AWS account and access the AWS Management Console.
2. Enter your logins and password.
3. Under the AWS Services tab, choose Lambda(Run code Without Thinking about servers) option.
4. Create the function by clicking on the Create function button.
5. Fill the following Function Type: Author from scratch, Name, Runtime, Role: Choose an existing role / Create any custom rule, Existing Role: lambda_basic_execution.
6. Upload your code under the Lambda function space.
7. Write your code in your preferred language.
8. Under the Skill ID verification, choose Disable option.
9. Add more options to the function like memory, execution timeout, and environment variables.
10. Click on the Save option and copy the ARN number.

AWS Lambda pricing

AWS Lambda charges users according to the requests the function handles and the time the code takes to execute. A request happens when there is execution depending on some of the services that trigger notifications events, i.e., Amazon EventBridge. It can also helpinvokeg calls using the API Gateways or AWS SDK. The duration normally ranges from the start of execution until termination.

During deployment, you set the memory for every function, and you get an allocation of CPU and other application resources.

If you have more memory, it will lead to a CPU increase. There are two types of architecture, x86 and Arm architecture. They have different performances and prices.

Some of the pricing lists of AWS Lambda include:

Free tier

It runs up to one million requests with a computation of 400,000 GB seconds per month on x86 and Graviton2 processors, which is free.

Billing for usage

It charges $0.20 per 1M requests for a duration of $0.0000166667 for every GB-second on x86 architecture while the same amount for a duration of $0.0000133334 for every GB-second on the Arm architecture. These prices are for the US East location, and the prices vary according to the location you use.

For Lambda Ephemeral Storage, the cost will depend on the storage allocation and the duration calculated in milliseconds. The storage ranges from 512 MB and 10,240 MB with an increment of 1 MB. They charge $0.0000000309 for every GB-second.

Provisioned Concurrency Pricing

You can enable this type of pricing if you need more control over your serverless application. They charge for the amount of concurrency you configure, the period for configuration, and Requests. If there are excess requests than the configured concurrency, it gets included in the payments.

You pay $0.0000041667 for every GB-second for x86 architecture and $0.0000033334 for every GB-second for arm architecture.

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Data Transfer & Other Charges

These charges are on the data that moves in and out of the Lambda functions. It usually is free for AWS Lambda Functions under the following services: Amazon Elastic Container Registry (ECR), Amazon Simple Storage Service (S3), Amazon Glacier, Amazon Kinesis, Amazon Simple Queue Service (SQS), Amazon DynamoDB, Amazon Simple Email Service (SES), Amazon Simple Notification Service (SNS), Amazon Elastic File System (EFS), and Amazon SimpleDB.

You only get charged if the Lambda functions you configured use other AWS services.

Lambda@Edge Pricing

You get charged according to the total requests a function handles per application. The pricing is $0.60 per 1 million requests. On duration, it charges $0.00005001 for every GB-second used.

Advantages of AWS Lambda

AWS Lambda has a lot of benefits for the users when running their applications. Some of the advantages of using AWS Lambda include:

• It promotes innovation.AWS Lambda gives developers more time to focus on development while it takes charge of infrastructure management. It helps in improving the business logic of the applications.
• It uses millisecond metering. When calculating the billing, AWS Lambda charges per 1 millisecond (ms) when the code runs and how many times the code gets triggered. It makes the rates cheap when you pay for execution time instead of server units.
• It creates a rich ecosystem. Lambda provides several AWS products for performing different functions. Some of them include  AWS Serverless Application Repository for deploying serverless applications and AWS Serverless Application Model for building and integrating serverless applications with environments like  AWS Cloud9. It helps in ensuring we have a good ecosystem for building serverless applications.
• Easy to scale.AWS Lambda makes it easy to scale applications by running the event-triggered codes in parallel and making the processing of each event individually. It provides more power in managing all the functions.
• It gives applications a modern look. It has functions that use machine learning and artificial intelligence models in applications. It helps perform most tasks like analyzing videos, natural processing activities, e.t.c.
• You pay for what you use and need. When they fo the billing, you only get charged for the resources you need. It depends on the requests, location, and execution duration.
• It does not use servers. Lambda Infrastructure runs code on different  Availability Zones (AZs), making code deployment easier. They are available and responsible for maintenance, administration, and patching of the infrastructure. It makes it easier to run applications without servers. The infrastructure also improves monitoring and logging, ensuring the integration with other AWS services like  CloudWatch Logs, Amazon CloudWatch, and AWS CloudTrail.

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Use cases of AWS Lambda

Some of the uses of AWS Lambda include:

Running web and mobile backends. You can use it to run your applications, and it helps in making them secure and scalable to improve user experience.
Has machine learning insights. It helps provide infrastructure development when processing data for your machine learning models.
Event-driven applications. It improves communication between different app services, reducing costs and preventing the app from crashing and using more resources.
Processing data. It matches all the data processing during code execution, ensuring you can scale to your desired level.
Limitations of AWS Lambda
Despite having benefits, it also has disadvantages. Some of the limitations of AWS Lambda include:

• It is only suitable for large projects.
• They dont give you the power to use third-party apps outside their platform. Instead, you have to use third-party apps from the platform, giving them more control over your application.
• It has computational issues. AWS Lambda can manage applications with functions that use a lot of processing.
• It has a limit of 1000 concurrent executions, leading to DoS (Denial of Service) of your application.
• Most of the AWS Lambda functions have limited execution time. Most of them get deactivated if they run for more than five minutes.
• When implementing functions like JVM, it takes some time for them to start up for upto 10seconds.
• When you use Virtual Private Cloud to provide more security, AWS Lambda will not perform well, leading to delays.