Serverless Computing

Building, deploying, and scaling applications can be tedious and time-consuming when you have to manage servers and infrastructure tasks.

Serverless computing eliminates these hurdles, enabling you to focus on coding and business logic.

What Is Serverless Computing?

Serverless computing is a modern approach to software development where developers build and deploy products, with cloud platforms providing the servers. It enables teams to focus exclusively on writing and shipping features, rather than maintaining backend infrastructure.

Serverless does not mean the absence of servers. Instead, all server activities are handled by the platform provider.

How Does Serverless Computing Work?

Serverless runs your code on demand in response to events, while the provider handles provisioning, scaling, and runtime management. It's designed to be event-driven and stateless, with each function execution independent of previous runs.

There are two common forms of serverless compute:

• Function-as-a-service (FaaS): Developers deploy and run small, modular functions directly to the cloud infrastructure in response to specific events. You can write and update code and dependencies, then upload them. The serverless platform deploys these functions to its runtime environment.

• Backend-as-a-service (BaaS): The cloud provider offers pre-built backend services and infrastructure, letting developers write frontend code only. The platform abstracts database management, authentication, storage, and notifications. They also provide APIs and SDKs that help connect with the application backend more easily.

Below are the core mechanisms of serverless compute:

Event Triggers

Serverless platforms are built around event-driven architecture. These are mechanisms that initiate the execution of functions in response to activities in the system. Events can originate from various sources, such as HTTP requests, file uploads, database changes, or scheduled tasks.

When an event occurs, like a database update, the cloud provider triggers the corresponding function. The provider allocates RAM and CPU automatically, spins up a container for it, executes code, and then tears the environment down when complete. Since the event automatically invokes a function, you don't have to run a continuous server. 

Automatic Scaling 

The serverless platform monitors the incoming events and scales the function instances as needed. For example, if it receives 1,000 requests, it can create a corresponding number of containers to handle the load. The platform scales automatically and rapidly without requiring you to define rules.

Statelessness

Functions operate independently without retaining data between invocations. This means each execution starts with a fresh environment.

A typical developer workflow looks like this:

1. Writing code: Developers write code in the language of their choice. Most platforms support high-level languages, such as Python, JavaScript, Java, and Go.

2. Deploying code to a platform: The code is then deployed to a serverless platform. Common platforms include Amazon Web Services (AWS) Lambda, Google Cloud Platform (GCP) Cloud Functions, and Azure Functions.

3. Configuring triggers: The dev configures triggers like API endpoints, message subscriptions, and timers. 

4. Infrastructure management: The provider handles the provisioning of the environment on each execution.

Billing in Serverless Computing

Most platforms bill users on a pay-per-use model where you are charged for the actual resources consumed, not pre-allocated servers. Unlike in PaaS, you do not pay for idle capacity.

Key billing factors include the execution time, total number of times the serverless function is triggered, and CPU and memory usage. 

Key Benefits

Below are some advantages to using serverless computing:

Faster Application Development

With serverless, you don't have to perform any backend configurations, which means you can deploy resources in a much shorter period than using other cloud computing models.

Because the provider handles all infrastructure-related tasks, developers spend more time on business logic and less on DevOps. The backend code is less complicated, as devs only create simple functions that perform unique tasks, which means fewer bug fixes and code maintenance.

Faster Scaling

As mentioned before, serverless platforms come with built-in auto-scaling. If your marketplace app experiences a sudden surge in popularity from a successful marketing campaign, and you use functions in the checkout process, you can rake in sales without ever needing to tweak the policy.

Multi-Language Support

Major serverless platforms support many prominent programming languages and frameworks, meaning you can use familiar tools and libraries without getting locked into something unfamiliar because it's the only thing available.

Cuts Costs

Serverless platforms provide cost savings compared to other cloud services, as you only pay for the duration of runtime and requests, with no charges when idle. However, total costs may change depending on the usage of other external services.

Limitations of Serverless Computing

While it is powerful, it also presents some drawbacks that you should consider. These include:

Vendor Lock-in

Migrating serverless applications can be difficult because each cloud provider has its own systems, APIs, and integrations. Vendors create a tight interdependence between your code and their environment.

The high abstraction in serverless platforms means you cannot configure or extract servers, making multi-cloud challenging. In most cases, you end up using resources provided by the vendor, adding another layer of difficulty to migration. For instance, when using AWS Lambda, you use AWS-specific event formats, SDKs, and identity and access management (IAM) policies, so switching clouds typically means adapting to new infrastructure and rewriting your triggers and code.

Limited Customization

With serverless, you have limited control over your environment. You cannot access the underlying servers or operating system or customize the runtime environment.

While this is the biggest selling point, it also means you must work within the provider's constraints. You might need a level of fine-tuned performance that's impossible for a serverless solution to provide.

Unpredictable Costs for Some Workloads

While they can be cost-effective, they may also become expensive if not well-managed. When triggered, unoptimized functions can drive many executions and increase runtime costs.

Also, applications with high variations in monthly usage will have less predictable billing.

Cold Starts

Serverless functions encounter high latency when invoked after being idle. This can delay responses and affect user experience.

Debugging Complexities

The event-driven nature makes traditional debugging and monitoring harder. It can be difficult to trace the end-to-end execution flow of some functions. Conventional monitoring tools may not properly capture everything you need, so you may need to use specialized ones, which can add to your costs.

When To Use Serverless Computing

Below are some top use cases of serverless computing:

API Backends

Serverless functions make great REST API and GraphQL endpoints and can be paired with managed backends (BaaS) for auth, databases, and storage through APIs.

Scheduled Jobs

Serverless platforms provide a scalable, efficient way to run recurring tasks or cron jobs. By using built-in services, you can schedule the execution of tasks at specific intervals and times. 

Real-Time Data Processing

Serverless platforms are designed to respond to events (like data entry or an incoming message) from queuing systems. When one of these events occurs, the provider triggers the matching function, speeding up data processing. Additionally, serverless architectures integrate seamlessly with databases and analytics tools, making them well-suited for real-time scenarios.

For example, serverless is well-suited for aspects of video call management. A user creating a call can trigger a function that generates a meeting ID and related details. Another function can run when someone joins the call, connecting them to the meeting and displaying their name.

CI/CD Pipelines

Serverless can significantly streamline CI/CD pipelines, enabling faster deployments. A function can be triggered by version control events to run tests, build artifacts, or deploy changes. Upon a commit, the function can run tests, build a container, and deploy to production.

Frequently Asked Questions