Is Serverless Computing Truly Without Servers?

When using serverless computing, developers won’t interact with or manage servers. Instead, the developer’s primary role is to focus on coding. The cloud provider, meanwhile, is responsible for maintenance, scaling, and provisioning. 

Servers still run in the background of serverless computing. Rather than the developer managing servers, operating systems, networks, and other parts of the infrastructure, the cloud provider does this. So, the main difference between servers and serverless is that developers don’t directly manage serverless systems.

Cloud providers with serverless computing include: 

• AWS Lambda: Run code to respond to HTTP requests, file uploads, database changes, and other event types. 
• Azure Functions: Operated by Microsoft and integrated throughout Azure. 
• Google Cloud Functions: Serverless computing for code snippets triggered by Google Cloud events. 

When using serverless computing, you’ll normally use a pay-per-execution model – meaning that you pay based on how many times your code is executed. Memory allocation and the duration of your code executions will also play a role. 

There are benefits and drawbacks to this pricing model. It’s very cost efficient because you only play for the computing time you use, but high-traffic apps might be more expensive. You’ll also have no upfront costs or commitments, but cost monitoring is crucial. 

Another benefit is that you’ll get automatic scaling for traffic spikes; on the flip side, expect latency during your initial startup time (also known as “cold starts”).

• Long-running processes: Consider the execution time limits on serverless computing.
• Fine-grained control requirements: Remember that serverless is less hands-on with the infrastructure; you can always pick something with better customization if needed.
• High-traffic/predictable workloads: Use a server-based model if you already know your traffic numbers or anticipate more.

Serverless computing is used in these instances: 

• Image processing and resizing: When users upload an image, serverless computing may resize/change it.
• Chatbots/virtual assistants: Serverless computing is used for natural language request processing and to answer customers with limited human input.
• IoT data processing: Serverless functions may analyze data streams and also handle them.
• Backend mobile and web app APIs: Developers might use serverless computing for building APIs.