Understanding Serverless Computing for the Beginner


Serverless computing has been gaining a lot of traction in recent years as a way to build and run applications without having to manage the infrastructure. For many developers and companies, serverless offers a highly scalable and cost-effective approach to deploying apps and services.

But for those new to the concept, serverless can seem confusing at first. In this beginner‘s guide, we‘ll break down what serverless is, how it works, the benefits it offers, and more. By the end, you should have a solid understanding of this emerging technology and be able to decide if serverless is right for your needs.

What Exactly is Serverless Computing?

The term "serverless" is somewhat misleading – there are still servers involved! But serverless computing allows you to build and run applications without having to provision or manage any backend infrastructure.

With traditional server-based architectures, you would have to manually spin up servers, decide how to scale them, and continuously monitor and manage them. Serverless computing takes all that overhead away and lets you simply deploy your code. The cloud provider (AWS, Azure, Google Cloud, etc.) handles provisioning servers on-demand to run your code and scaling them as needed.

So in serverless, the servers are still there, but all the infrastructure management is abstracted away. You don‘t have toReserve instances, update configurations, or monitor infrastructure health – the cloud provider takes care of that for you. This allows you to focus solely on writing code.

Serverless computing is driven by events and triggers. Your code is run only when it needs to, in response to a specific event like an HTTP request, database change, file upload, scheduled task, and so on. The cloud provider handles executing your code at scale when the trigger occurs and bills you only for the compute time used running your code.

This event-driven execution model brings several advantages:

• No idle capacity – You pay only for the time your code runs. No need to pay for idle servers waiting for requests.

• Auto-scaling – Serverless apps scale up and down automatically based on demand. No manual intervention needed.

• High availability – Serverless apps have built-in redundancy and fault tolerance for high availability.

• Faster development – Serverless removes infrastructure management overhead, allowing you to focus on writing code.

So in summary: serverless computing allows you to deploy applications and services without having to manage any servers yourself. The cloud provider runs your code on-demand in response to events and handles all the infrastructure for you.

A Brief History of Serverless

The origins of serverless computing trace back to a few key developments:

• Platform-as-a-Service – PaaS solutions like Heroku allowed developers to deploy apps without managing servers. PaaS abstracted infrastructure but still required running dedicated app servers.

• Function-as-a-Service – FaaS took abstraction further by letting developers deploy single functions without ANY infrastructure. AWS Lambda pioneered this in 2014.

• Containers – Container technologies like Docker enabled functions to be packaged as lightweight, portable containers rather than virtual machines. This helped facilitate the rise of serverless FaaS.

So serverless computing integrates these key innovations:

• Event-driven computing – Code runs in response to events rather than being continuously running.

• FaaS architecture – Infrastructure is fully managed, only code is deployed.

• Containerization – Code is packaged in lightweight containers for portability and efficiency.

Together, these concepts have enabled the serverless model we know today of only writing code and having it instantly deployable on-demand.

How Serverless Computing Works

Under the hood, a serverless platform consists of a few key components:

Function – The core unit of code you write and deploy. Each function contains application logic that handles a specific task.

Runtime – The execution environment that runs the code for a function. This provides language/framework support like Node.js, Python, .NET Core, Java, etc.

Triggers – The event source that invokes a function, like an HTTP request, database event, file upload, scheduled task, etc.

Storage – Stateless functions can connect to external storage like a database to persist data when needed.

When a trigger occurs, the serverless platform handles everything required to execute the function:

1. Starts up a runtime instance with the requested resources (memory, CPU, etc).
2. Loads code for the target function.
3. Executes the function, which runs application logic.
4. Returns the output to the invoker.
5. Shuts down the runtime instance after execution.

Developers simply write and upload functions without having to configure runtimes, scale resources, or manage any servers. The platform handles all that automatically.

Serverless computing uses a pay-as-you-go pricing model based on function invocations and resources used. So you only pay for the time your functions run – no paying for idle capacity.

Benefits of Using Serverless Computing

Serverless offers a number of advantages over traditional server-based architectures:

Scalability – Serverless apps scale seamlessly without capacity planning. Just deploy more functions to handle more load.

Cost – Pay only for compute time used running your functions. No paying for idle servers.

Speed – Get to market faster by just writing code, without infrastructure overhead.

Flexibility – Serverless FaaS provides more flexibility than PaaS or containers.

Availability – Built-in redundancy and fault tolerance ensures high availability.

Productivity – Allows developers to focus on writing code rather than infrastructure.

Serverless computing works great for event-driven workloads that are intermittent or unpredictable in demand. Use cases like data processing pipelines, CRON jobs, IoT backends, and web/mobile APIs are all good fits.

Applications that require consistent uptime or need sustained compute power are less ideal for serverless. But overall, serverless offers significant advantages for deploying modern apps at scale.

Serverless Use Cases

Here are some common use cases where developers and companies are utilizing serverless architectures:

Web APIs

Exposing backend services via API endpoints is a prime use case for serverless. You can build web APIs that scale seamlessly without any infrastructure management. Serverless platforms make it easy to create HTTP-based APIs using functions.

Mobile Apps

Mobile apps need backends that can handle bursts of traffic and scale elastically. Serverless provides an excellent approach for offloading intensive tasks from mobile apps by exposing cloud functions.

Data Processing

For stream, batch, and ETL data processing, serverless functions are lightweight and scalable. Serverless is great for tasks like image processing, database events, file uploads, etc.

Cron Jobs & Scheduled Tasks

Any regular batch jobs, scheduled tasks, or cron jobs are a perfect use case for serverless. You can invoke functions based on time, schedule, or calendar events.

IoT & Streaming Applications

Serverless works well for IoT applications that process large streams of data from sensors and devices. Functions can ingest, analyze, and store IoT data at scale.

Drawbacks & Limitations

Serverless isn‘t a silver bullet though – there are some drawbacks to consider:

• Cold starts – Initial request latency can be slow while starting up a new function instance.

• Testing and debugging – Can be harder to test and debug functions running in a serverless environment.

• Lock-in – Vendor lock-in can occur if relying too heavily on provider-specific features.

• Stateless only – Serverless functions should be stateless, requiring external data stores.

• Complex coordination – Orchestrating many functions can require more architectural effort.

• Cost at scale – Can be more expensive for high-volume, sustained workloads.

Understanding the limitations and architecting around them is key to successfully leveraging serverless.

Top Serverless Providers

All major cloud platforms now offer serverless computing services:

AWS Lambda – The most mature serverless platform with the richest set of capabilities.

Azure Functions – Microsoft‘s serverless offering that includes Durable Functions for complex workflows.

Google Cloud Functions – Provides good integration with other Google Cloud services.

Cloudflare Workers – Runs JavaScript functions at the edge across Cloudflare‘s global network.

IBM Cloud – Built on open source Apache OpenWhisk serverless platform.

Alibaba Function Compute – Serverless solution on Alibaba Cloud.

There are also many open source serverless projects like OpenFaas, Fission, Knative, and OpenWhisk.

When evaluating options, consider factors like language support, tooling, ecosystem, costs, and ease of development/deployment.

Architecting Serverless Solutions

Here are some tips for architecting effective serverless solutions:

Think Small – Decompose larger applications into smaller functions for more scalability.

Design Stateless – External storage like databases should hold state, not functions.

Fail Fast – Handle errors gracefully and fail fast to avoid prolonged issues.

Idempotent Functions – Ensure functions can safely run multiple times without side effects.

Audit Everything – Implement robust logging to audit performance, failures, costs, etc.

Leverage Services – Use complementary managed services for databases, storage, messaging, etc.

Watch Out For Lock-in – Abstract proprietary interfaces to prevent excessive vendor lock-in.

Test Extensively – Lack of access to backends means rigorously testing functions locally.

Monitor Closely – Collect metrics on invocations, durations, failures, costs, etc.

A well-architected serverless application optimizes for scalability, resilience, and efficiency.

The Future of Serverless Computing

Serverless adoption is rapidly accelerating as developers embrace the benefits of event-driven computing, reduced operational complexity, and infinite scalability.

Cloud vendors are aggressively innovating new serverless services and capabilities as well:

• Stateful services – Adding stateful function support like databases and messaging

• Faster cold starts – Improving cold start latency for enhanced performance

• More hardware integration – Tighter integration with hardware like GPUs for ML/data workloads

• Expanded use cases – Growing serverless usage for apps, websites, ML, data analytics, etc.

Open source – Continued open source serverless innovation outside of hyperscalers

The end result is developers will be able to build and scale a wider range of applications faster than ever before, fully realizing the promise of serverless computing.

Conclusion

Serverless represents a major evolution in cloud computing, allowing developers to build and run applications without managing any infrastructure. By leveraging serverless, companies can accelerate time-to-market, reduce costs, and scale seamlessly.

This beginner‘s guide provided an introduction to serverless – what it is, how it works, use cases, benefits, and more. We covered the key concepts you need to understand to evaluate if serverless is right for your needs.

While serverless isn‘t a perfect fit for every workload, its flexibility and scalability offer significant advantages for modern applications. As the technology continues maturing, we‘ll see serverless become the norm for deploying robust cloud-native apps and services.