5 Ways to Supercharge Your Projects With Serverless Functions

Learn how you could optimise your projects using Serverless Functions to great effects.

If you’re like me, you’ve probably come across tweets or blog posts ranting about the usefulness of serverless functions — Amazon Prime Video recently dumped Serverless because it was costing too much. And you’re wondering about what the best use cases for serverless functions are.

Prime Video service dumps AWS Lambdas, cuts AWS bill 90% — The Stack

Welp! In this article, you will learn about the unique characteristics of serverless functions, and we would spotlight how they could be used for maximum benefits.

Background

The concept of serverless functions, also known as Function-as-a-Service (FaaS), has evolved significantly over the past decade, becoming one of the most popular paradigms in modern cloud computing.

Serverless functions allow developers to write code that runs in response to events without having to worry about provisioning, scaling, or managing the underlying infrastructure.

Quickly, it gained popularity due to three salient characteristics:

1. Scalability: Serverless functions automatically scale to handle varying levels of traffic, without requiring manual intervention.
2. Cost Efficiency: With serverless, users only pay for the actual compute time consumed by their functions, rather than paying for idle resources.
3. Simplicity: Serverless platforms abstract away the complexities of managing servers, networking, and operating systems.

Serverless Ecosystem Expansion

As serverless computing gained traction, a broader ecosystem began to develop around it. Several trends and advancements contributed to its widespread adoption:

1. Containerization and Microservices: The rise of containers (e.g., Docker) and microservices architecture played a crucial role in the adoption of serverless functions. Containers made it easier to package and deploy small, isolated units of code, while microservices encouraged breaking down monolithic applications into smaller, more manageable components. Serverless functions fit perfectly into this paradigm, as they could be used to implement individual microservices or tasks.
2. Managed Services: Cloud providers began offering a wide range of managed services (e.g., databases, authentication, messaging), which could be easily integrated with serverless functions. This further reduced the operational burden on developers, as they could rely on these managed services for critical infrastructure needs.
3. Development Frameworks and Tools: The serverless ecosystem grew to include various frameworks and tools that simplified the development and deployment of serverless functions. Frameworks like the Serverless Framework, AWS SAM (Serverless Application Model), and Terraform made it easier to define and manage serverless applications.
4. Edge Computing: The emergence of edge computing extended the serverless model even further. Providers like Cloudflare Workers and AWS Lambda@Edge allowed developers to run serverless functions closer to end-users, reducing latency and improving performance for globally distributed applications.

Pros of Using Serverless Functions

1. Cost Effectiveness: Compared to compute resources (ex. Amazon ECs, Azure App Services) which have a fixed cost (ex. $100/month), serverless functions are usually billed per execution, for a tiny fraction of the cost (ex. $0.2 per million executions). No upfront costs. Might be worth switching if the math (and tradeoffs) works out in your favour.
2. On-Demand Scalability: They automatically scale up or down based on demand, handling spikes in traffic without manual intervention. This ensures that your application remains responsive under varying loads. You don’t need to guess or over-provision resources to handle potential peaks, as the serverless platform manages scaling for you.
3. Faster Time to Market: Serverless is ideal for prototyping and testing new ideas without the need for complex infrastructure setup, allowing for rapid iteration.
4. High Availability and Resilience: Designed to be highly available and resilient, they are distributed across multiple datacenters. This ensures that your application remains available even in the event of infrastructure failures. Additionally, if a function fails, the serverless platform can automatically retry or redirect the request to another instance.
5. Low Latency: Many serverless platforms allow you to deploy functions at the edge, closer to your users. This reduces latency and improves performance for globally distributed applications.

Hmm... Thinking of switching already?… You might… want to wait! Let’s talk about the tradeoffs first.

Cons of Using Serverless Functions

1. Cold Start Latency: When a serverless function hasn’t been used for a while, the platform might need to spin up a new machine to handle the request. In Azure Functions, I’ve had cold start delays as long as 6 seconds, which would be unacceptable in production apps.
2. Limited Execution Time: Serverless functions typically have a maximum execution time (timeout) imposed by the provider. This can be a limitation for tasks that require long processing times.
3. State Management: Being stateless by nature, managing state across multiple functions or invocations requires external storage solutions like Amazon DynamoDB, Redis, etc.
4. Vendor Lock-In: Serverless architectures often tie you closely to a specific cloud provider’s ecosystem (e.g., AWS, Azure, Google Cloud), requiring the use of abstraction layers or frameworks that support multiple cloud providers, and keep your business logic decoupled from provider-specific services as much as possible.
5. Limited Language and Runtime Support: Serverless platforms typically support a specific set of programming languages and runtimes. If your preferred language or runtime isn’t supported, you may need to use less familiar tools or face limitations.

Bearing all that in mind, the best use cases for serverless will be the intersection between “we could use the pros” and “we don’t mind the cons” 😆. Let’s explore some of them.

Best Use Cases For Serverless Functions

1. Event-Driven Triggers: Serverless functions excel in scenarios where code needs to be executed in response to events such as HTTP requests and webhooks (ex: Stripe, Zapier, etc), database updates, file uploads, or messages in a queue.
2. Backend for Mobile/Web App Prototypes: (With emphasis on prototypes) Serverless functions allow you to quickly prototype and test new features or services without the overhead of setting up infrastructure.
3. Scheduled Tasks and Cron Jobs: Serverless functions are perfect for running scheduled tasks (ex: daily, nightly backups, periodic reports, etc) without needing to maintain a dedicated server.
4. IoT Applications: Serverless functions can process data from IoT devices, handle device events, and manage communication between devices and the cloud.
5. Real-Time Data Processing: Serverless functions can process data in real-time as it arrives, making them ideal for handling streams of data from IoT devices, sensors, or social media feeds.

One of those use cases appeal to you? Great! Now, to getting the best results…

How to Get the Best Results from Serverless Functions

1. Take advantage of event-driven triggers where possible
2. Keep your business logic abstracted from the cloud provider’s code
3. Manage cold starts using strategies like provisioned concurrency or minimise dependencies to reduce cold start latency
4. Set appropriate timeouts to prevent long-running functions from consuming unnecessary resources
5. Utilise centralised datastores such as Redis and Document DBs to keep state
6. Leverage services managed by thecloud provider-managed services (e.g., databases, queues) to reduce operational complexity and improve scalability.

And we that, it’s… Till next time, folks! 👋🏽