Serverless computing is a cloud computing execution model that provisions computing resources on demand and offloads all responsibility for common infrastructure management tasks. They are auto scalable so it can handle extremely active traffic periods.
Serverless computing does-not means there are no physical servers utilized, of course there are servers, but we don't have to manage them, in background cloud provider manage (provisioning, scheduling, scaling, patching and more) for us, this gives developers more time to develop and optimize their front-end application code and business logic. And with serverless, customers never pay for idle capacity. They pay only for the resources required to run their applications, and only when those applications are running.
Serverless is a polyglot environment, enabling developers to code in any language or framework - Java, Python, node.js - with which they're comfortable. Because serverless scales up and down on demand in response to workload, it offers significant cost savings for spiky workloads. But it does not offer the same savings for workloads characterized by predictable, steady or long-running processes; in these cases, a traditional server environment might be simpler and more cost-effective.
Serverless Implementations differ across service providers, and capabilities vary, including supported runtimes, authentication, scaling and monitoring.
Serverless architectures are well-suited for event-driven, IOT and stream-processing workloads most notably open-source Apache Kafka event streaming platform.
Benefits:
- Pay only for the time for our code will run.
- Developer don't have to take care of servers or infrastructure, it maintains by cloud provider, so
they can focus more on development and business logic.
- API Management & Integrated event sources.
- Serverless scales up and down on demand in response to workload
