What is AWS Lambda?
A compute service, AWS Lambda allows a user to run code without any servers. It automatically manages and provisions the underlying compute resources. Lambda requires zero administration when it comes to running code for virtually any type of application or backend service. It only runs the code when needed and can also scale on its own. The good news is that you only pay for the computing time, and not when the code is not running.
Other AWS services can be extended by using Lambda with custom logic or creating a back-end service that operates on AWS performance, security, and scale. Lambda uses high-availability compute infrastructure and does all the resource administration including operating system and server maintenance, code and security patch deployment, code monitoring and logging, as well as capacity provisioning and automatic scaling. It only requires the code from a user. Lambda functions in different languages such as Java, Python, Go, Node.js, and so on. It also uses both container and serverless tools like Docker Command Line Interface (CLI), AWS Serverless Application Model (SAM), build, test, and deploy the functions. AWS offers 140 services for which you can either set up a code to automatically trigger it or you can enable it from any mobile or web app.
How does AWS Lambda work?
The code you want to run on this Function-as-a-Service platform is called a Lambda function. Once it is created it is saved and ready whenever triggered just like a formula in a spreadsheet. Along with the function name and resource requirements, it also includes code and associated information. Since it is not attached to any infrastructure, Lambda can swiftly launch as many copies of the function as required to meet the scale of incoming events. Once the code is loaded in the platform, it can associate your function with certain AWS resources. An example of this can be the Amazon DynamoDB table, Amazon SNS notification, or Amazon Kinesis stream, a certain Amazon S3 bucket. As the resource changes, it executes the function and manages it to accommodate incoming requests.
When should I use AWS Lambda?
AWS Lambda can be used in several application scenarios. The only condition is that your application code is run using Lambda standard runtime environment and within the resources that it offers.
Lambda only requires you to be responsible for your code. It manages all the other resources including the balance of memory, network, and CPU. This means you cannot log in to compute instances or even customize the operating systems on the provided runtimes. It is only due to these limitations that Lambda can perform the administrative and operational activities on its own.
AWS does offer other compute services that let you manage your own compute resources. This includes Amazon Elastic Compute Cloud (Amazon EC2) which allows you to customize the whole software stack network, operating systems, and security settings. AWS Elastic Beanstalk let you deploy and scale applications on to Amazon Elastic Compute Cloud.
What are the benefits of AWS Lambda?
Serverless and Stateless — This is the biggest benefit of AWS Lambda, that it runs automatically without needing any infrastructure. Prepare a code and upload it to Lambda as a zip file or container image.
It automatically scales the application as a response to each event. While the code runs parallel and processes all the triggers, scaling according to the workload. It is capable to process a few requests per day to hundreds of them per second.
AWS Lambda only charges for the compute time a user consumes. Thus, you never have to pay for infrastructure, and a user is charged based on milliseconds. So, you are being charged for code executes and whenever the code is triggered.
AWS Lambda enables users to optimize code execution time by opting for the correct memory size for the function. Provisioned Concurrency allows you to keep your functions initialized and hyper-ready to react within a few milliseconds.