Most companies use serverless technology and services like AWS Lambda to deploy their applications. It helps eliminate infrastructure management that takes more time and requires companies to employ someone in charge. It has made the development and deployment of applications fast and scalable compared to when they used physical servers. It has managed to help more companies use fewer finances as you only pay for what you use. According to Datadog, AWS Lambda was the most used serverless platform for their customers, accounting for around 50%. The article will look at AWS Lambda, how it works, and its advantages and disadvantages to help you understand how you can use it.
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.
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.
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.
Some of the features of AWS Lambda include:
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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.
There are several steps for creating an AWS Lambda function. Users have to follow the following steps below when creating a Lambda function:
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:
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.
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.
AWS Lambda has a lot of benefits for the users when running their applications. Some of the advantages of using AWS Lambda include:
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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:
If you plan to use serverless infrastructure in deploying your apps, AWS Lambda is a good option you can use. It has features that make it easier to use, scale and run code without worrying about the infrastructure.
It promotes productivity and increases leads as most developers and teams spend more on the other aspects of the applications.
The team can spend more time looking at the customer feedback, fixing bugs, and performing updates without worrying about the infrastructure.
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AWS Lambda is a serverless computing service that helps developers and companies run code without setting up and configuring servers.
Examples of Lambda in AWS includes events that update or change in the state, i.e., ecommerce website or shopping carts.
Lambda is for carrying out event-driven programming, and it's mainly for providing serverless platforms, while EC2 uses containers to create virtual machines for running code.
You can use AWS Lambda when you work with custom processing or if you want to have access to several services.
Serverless is a model developers use to build and run different applications without setting up and configuring servers.
Serverless involves deployment and running of apps without servers, while cloud involves running applications with the help of servers that you can access anywhere.
Lambda is Function as a Service(FaaS)
Serverless AWS Lambda enables users to deploy and run applications without setting up servers.