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Introduction to Serverless With AWS Lambda and Bitrise API: Part 1

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Learn how to use the AWS Lambda, as well as design and build a Serverless function to trigger Bitrise builds with Bitrise API via the custom Lambda function.
Join the DZone community and get the full member experience. In the early days of software development, anyone seeking to develop a web, mobile, or backend application had to own the hardware required to run a server, which is an expensive process. Then, when cloud computing came, it became possible to lease server space or a number of servers remotely. The developers and companies who rent these fixed units of server space generally overbuy to ensure that a spike in traffic or activity won’t exceed their monthly limits and break their applications. Because of this, a lot of the server space that gets paid for can be wasted. As a result of this, serverless computing allows developers to purchase backend services on a pay-per-use basis, which means that only what they use must be paid for. In a serverless environment, a cloud provider (AWS, Azure, or Google Cloud) dynamically allocates resources to run code. The cost is only incurred when the code is actually executed. The code that is usually executed is called stateless containers, which can be triggered by a variety of events, for instance: database events, call API endpoint, and cron jobs. Serverless computing refers to the ability to run these functions without maintaining your own servers. The term « serverless » doesn’t refer to the absence of servers, but rather to the fact that the servers, operating systems, network layer, and rest of the infrastructure have already been configured so you can focus on writing the application code. AWS Lambda is a compute service that lets you run code without provisioning or managing servers. Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, code monitoring and logging. — AWS Lambda Documentation.

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