AWS Lambda is one of the services that fall under the ‘Compute’ domain of services that AWS provides along with Amazon EC2, Amazon EBS, and Amazon Elastic Load Balancing. It allows us to compute code or any application with AWS Lambda. Users can run code for virtually any type of application or backend service. AWS Lambda automatically enables runs code without requiring manual provision or management servers. Users have to write code in one of the languages that the AWS Lambda function supports and upload it to Lambda, and Lambda will take care of it. AWS Lambda supports node.js, java, C sharp, Go, and Python.
Where is Lambda used in Different Businesses?
There are some ways that businesses use AWS Lambda, such as:
- AWS Lambda is used to process images when it is uploaded in an S3 bucket.
- It is used to analyze social media data, which can be useful for different data analysis types.
How does Lambda Work?
Clients send data to the lambda function, and Lambda receives the request, and the data will run on the defined number of containers. The number of containers depends on the volume of data. So, if it is a single request or less request, it runs on a single container. The requests are given to a container to handle. A container contains the code the user has provided to satisfy the query. Moreover, with AWS lambda no need to install software, for example, Webserver and App server in the underlying environment to run a process. However, code libraries can be installed.
AWS Lambda Environment
Underlying infrastructure managed by the provider:
- Scales automatically
- No patching headache
Cannot install the software (e.g., Webserver, App Server) in the underlying environment:
- Code libraries can be install
Easy selection of computing power:
- 123 MB to 3 GB memory
- 1 sec to 15 minutes time limit
No attached hard disk, but the deployment package is size limited
Serverless Use Case
Suited at driven architectures
- Pay as you go
- API gateway integration
- Code is modular without software
- Dependencies, e.g., Python APIs
- More comfortable to migrate cloud-native, green fields apps
- Consider VPC cold start latency
Shines at event architectures
- Native integration with other services
- Example – Triggered by S3, Kinesis
Why AWS Lambda?
Some of these benefits that are offered by AWS Lambda such as:
Scalability: Amazon doesn’t have any servers to provision or to manage, so that means it provides a lot of leverage in scaling lambda functions when the requests grow. Amazon uses containers according to the number of requests. Users do not need to worry about scaling their application or setting up for auto-scaling configuration. Because the scalability part and availability of that environment are taken care of by Amazon and users, they need to focus on their application code and making their customer experience better.
Reduces Servers’ Cost: Lambda reduces the cost of servers.
Automatic Scaling: Lambda also automatically scales applications by a running code in response to each trigger. Code runs in parallel and processes each triggers individually, scaling precisely with the size of the workload. Lambda can scale the application running the code in response to each trigger that it receives.
Metering on the Second: Users only pay the amount of time, which means users don’t need to charge for servers. The only payment required is for the amount of time the code is computed. With AWS Lambda, users will charge for every hundred milliseconds while code executes and the number of times their code is triggered.
Author: SVCIT Editorial
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