The following article describes Serverless Computing.
Basically, developers can create and deploy applications using the serverless computing. In fact, it is a cloud computing model that developers can use without having to worry about managing the underlying infrastructure, including servers and hardware. According to the demands of the application, cloud providers in this approach automatically manage resource scalability, maintenance, and allocation. Therefore, developers don’t bother about provisioning, scaling, or server management; they just concentrate on writing code and defining functions that run in response to events.
Examples of Serverless Computing
The following list shows some examples of serverless computing platforms.
- AWS Lambda. The serverless platform from Amazon Web Services enables programmers to respond to events and triggers by running code. It connects with other AWS services and supports a number of programming languages.
- Azure Functions. Similarly, event-driven, serverless computing functions are made possible by Microsoft’s solution. It works smoothly with the other Microsoft Azure services.
- Google Cloud Functions. Likewise, developers can run code in response to events from multiple Google Cloud services using the serverless platform from Google Cloud.
Real-life Applications of Serverless Computing
The following list shows some real-life applications of serverless computing.
- Web Applications. In general, serverless systems allow programmers to create backend services, APIs, and other online application components. So, with this method, development is made easier and automated scalability based on customer demand is ensured.
- IoT Applications. In similar way, processing data from devices connected to the Internet of Things (IoT) is a good use case for serverless computing. When devices submit data, serverless functions can be triggered, allowing for real-time processing and analysis.
- Data Processing. Also, data from diverse sources can be processed and transformed using serverless platforms. For instance, Serverless functions can handle data processing for databases, queues, and streaming services.
- Microservices. Further, building and deploying microservices, which are compact, independent parts of an application, is possible with serverless computing. Hence, a distinct serverless function can be built for each microservice.
- Batch Jobs. Without the need to maintain dedicated servers, serverless solutions can manage scheduled tasks or batch processing, where code is run frequently.
- Event-driven Workflows. Similarly, serverless functions that are triggered by events can be used to coordinate complex processes with numerous steps and services.
- Image and Video Processing: Moreover, you can edit and manipulate photos and movies using serverless services. For example, you can do it by creating thumbnails or using filters.
In short, serverless computing makes it easier to design applications, lowers operational costs, and offers cost savings by only billing for the actual processing power needed when a function is executed.
Further Reading
Cloud Computing with Amazon Web Service (AWS)
Getting Started Your Journey into Cloud With AWS
How to Work With AWS Management Console?
What are the Important Components of AWS
Understanding Amazon EC2 and How Does it Work
Features and Benefits of Amazon S3 Bucket
Demystifying Serverless Computing from the Ground Up
Different Types of Load Balancers in AWS
20+ Students’ Project Ideas Using Elasticsearch
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