# serverless computing

> cloud computing model

**Wikidata**: [Q3958022](https://www.wikidata.org/wiki/Q3958022)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Serverless_computing)  
**Source**: https://4ort.xyz/entity/serverless-computing

## Summary
Serverless computing is a cloud computing model where the cloud provider manages infrastructure and automatically scales resources based on demand, allowing developers to focus on writing code without worrying about server management.

## Key Facts
- Serverless computing is a cloud computing model where infrastructure management is handled by the cloud provider.
- It's also known as Function as a Service (FaaS) and is an execution model within applications architecture.
- It's distinct from peer-to-peer computing models.
- Popular serverless platforms include AWS Lambda, Google Cloud Functions, Azure Functions, and Oracle Cloud Functions.
- It's categorized under cloud computing and execution models.
- The concept has a Wikipedia page with multiple language translations.
- It has a Stack Exchange tag for developers to discuss related topics.

## FAQs
### Q: What is the main difference between serverless computing and traditional cloud computing?
A: In traditional cloud computing, developers manage servers and infrastructure, while in serverless computing, the cloud provider automatically manages and scales resources based on demand.

### Q: What are some popular serverless platforms?
A: Major providers include AWS Lambda (Amazon Web Services), Google Cloud Functions, Azure Functions, and Oracle Cloud Functions.

### Q: How does serverless computing work?
A: Developers write and deploy individual functions that execute only when triggered, with the cloud provider automatically scaling resources as needed.

### Q: What are the advantages of serverless computing?
A: It allows developers to focus on code rather than infrastructure management, reduces costs by paying only for actual compute time, and automatically scales to handle varying workloads.

## Why It Matters
Serverless computing represents a significant shift in how applications are deployed and managed in the cloud. By abstracting away infrastructure management, it enables developers to focus on writing code and delivering business value rather than dealing with server provisioning, scaling, and maintenance. This has democratized cloud computing by making it more accessible to developers with varying levels of infrastructure expertise. The model has fundamentally changed application architecture by promoting microservices and event-driven architectures, where individual functions can be developed, deployed, and scaled independently. Its impact extends across industries, enabling faster development cycles, reduced operational overhead, and more efficient resource utilization.

## Notable For
- Serverless computing is distinguished by its automatic scaling and resource management, eliminating the need for developers to provision or maintain servers.
- It's categorized as an execution model within applications architecture, positioning it as a specialized approach to cloud computing.
- The model is designed to optimize costs by charging only for actual execution time rather than maintaining idle resources.
- It enables event-driven architectures where functions are triggered by specific events rather than being continuously running.
- Major cloud providers have invested heavily in serverless platforms, making it a mainstream cloud computing paradigm.

## Body
### Definition and Core Concept
Serverless computing, also known as Function as a Service (FaaS), represents a cloud computing model where the cloud provider manages infrastructure and automatically scales resources based on demand. In this execution model, developers focus on writing code without worrying about server management, provisioning, or scaling.

### Relationship to Other Concepts
Serverless computing is positioned as an execution model within applications architecture, subclassing both cloud computing and general execution models. It's fundamentally different from peer-to-peer computing models, which distribute tasks across networked computers without central management.

### Popular Implementations
Major cloud providers have developed serverless platforms:
- **AWS Lambda**: Amazon Web Services' serverless computing platform, with 14 Wikipedia sitelinks indicating its prominence.
- **Google Cloud Functions**: Google's serverless compute platform.
- **Azure Functions**: Microsoft's serverless offering.
- **Oracle Cloud Functions**: Oracle's serverless platform.
- **Cloudflare Workers**: A JavaScript edge runtime environment that provides serverless capabilities.
- **App Engine**: A serverless application platform for apps and backends.

### Technical Characteristics
The serverless model operates on the principle of event-driven execution. Developers deploy individual functions that execute only when triggered by specific events (such as HTTP requests, database changes, or message queue events). The cloud provider automatically scales resources to handle varying workloads, starting and stopping instances as needed.

### Evolution and Adoption
Serverless computing has evolved as a response to the growing complexity of cloud infrastructure management. It represents a shift from traditional server-based architectures to more flexible, scalable, and cost-effective approaches. The model has gained significant adoption across various industries, particularly in microservices architectures where individual components can be developed and deployed independently.

### Impact on Development
The serverless paradigm has transformed application development by:
- Reducing operational overhead
- Enabling faster deployment cycles
- Optimizing resource utilization
- Lowering costs through pay-per-use models
- Supporting event-driven architectures

### Challenges and Considerations
Despite its advantages, serverless computing presents challenges such as:
- Cold start times for functions
- Limited execution time (typically seconds)
- Potential vendor lock-in
- Complex debugging and monitoring
- Increased complexity in certain use cases

### Future Directions
The serverless computing landscape continues to evolve with:
- Improved performance and reduced cold start times
- Enhanced support for complex workloads
- Integration with more development frameworks
- Increased security features
- Broader adoption across enterprise applications

### Community and Resources
The serverless computing community has established resources including:
- Stack Exchange tag for developer discussions
- Multiple language Wikipedia translations
- Academic publications categorizing it under computer science
- GitHub topics for related projects and tools

```json
{
  "@context": "https://schema.org",
  "@type": "Thing",
  "name": "Serverless computing",
  "description": "A cloud computing model where the cloud provider manages infrastructure and automatically scales resources based on demand.",
  "sameAs": ["https://en.wikipedia.org/wiki/Serverless_computing", "https://www.wikidata.org/wiki/Q328"],
  "additionalType": "Execution model"
}

## References

1. [Source](https://kanger.dev/stack/serverless-monitoring-tools-platforms)