Cloud computing has transformed how businesses operate, allowing them to scale resources up and down on demand without having to maintain expensive infrastructure. Serverless computing takes this a step further, allowing developers to run code without provisioning or managing servers at all. Here’s an overview of this emerging technology and why it may be the next evolution of cloud.
What is Serverless Computing?
With traditional cloud computing, you rent virtual machines and pay for the time that they are running. This is known as Infrastructure as a Service (IaaS). With serverless computing, also known as Functions as a Service (FaaS), you deploy code and the cloud provider runs it for you automatically without having to manage any servers.
You are billed based on compute time used to execute your code. When your code is not running, you don’t pay anything. This makes serverless perfect for workloads that are event-driven, intermittent, or have variable compute demands.
Key Benefits of Serverless
No server management: Forgetting servers entirely allows development teams to focus on writing code, not ops. The cloud provider handles capacity planning, deployments, scaling, patching, and more.
Pay per execution: Never pay for idle capacity again. You are charged millisecond increments of compute time rather than hourly or monthly rental fees. This can significantly reduce costs for infrequent workloads.
Auto-scaling: Serverless platforms scale your code automatically, spinning up more compute resources as needed to handle load. This makes serverless a great fit for spiky or unpredictable workloads.
Faster development: Skip provisioning infrastructure and configuring environments. Just deploy code and let the platform take care of the rest. This accelerates development cycles.
Open source support: Most serverless platforms work with popular open source tools like Terraform, allowing infrastructure as code approaches.
Common Serverless Use Cases
Here are some of the most popular uses cases for serverless architectures:
- Web and mobile backends – Serverless is perfect for REST APIs, realtime messaging, file processing, and more for web/mobile apps.
- Data processing – Schedule recurring jobs to clean, transform, and move data with no servers to manage.
- ETL pipelines – Build complex extract, transform, load processes that auto-scale to meet demand.
- IoT backends – Handle high volume, intermittent streams of data from IoT devices.
- Chatbots – Easily create bots that can scale conversational workloads as needed.
Potential Drawbacks to Consider
Of course, serverless computing isn’t perfect for every workload. Some key drawbacks to consider include:
- Stateless only – Serverless functions should be stateless, which may require rearchitecting more monolithic apps. External data stores can provide persistence.
- Cold starts – When functions first run after being idle, they incur latency for launching container infrastructure, which impacts response times.
- Monitoring overhead – Distributed tracing is required to monitor serverless apps since they run in a shared, opaque environment.
- Vendor lock-in – There can be some lock-in to a specific cloud provider’s proprietary services. Some open source options help alleviate this.
- Cost optimization – Pay per execution pricing can be complex to estimate and optimize, especially for workloads with sustained usage.
- Debugging difficulties – Ephemeral functions executing in a remote environment can make debugging tricky compared to local development and testing.
The Bottom Line
Serverless represents a major leap forward in abstracting infrastructure away from developers. While still an emerging technology, it offers a compelling value proposition – no ops, infinite scale, and low costs for intermittent workloads. As platforms mature and address drawbacks around state, cold starts, and debugging, expect serverless adoption to accelerate across startups and enterprises alike. The next phase of cloud dominance may very well be driven by serverless computing.
Serverless computing allows developers to deploy code without managing servers. It provides automatic scaling and pay per execution billing, making it ideal for intermittent or spiky workloads. While still maturing, serverless offers a glimpse into the future of cloud and where it may be headed next.
Glossary
- IaaS: Infrastructure as a Service, the cloud provider hosts hardware like servers and storage for you to use. Examples are AWS EC2, Azure Virtual Machines.
- FaaS: Functions as a Service, a serverless model where you deploy code snippets and the provider runs them for you automatically. Examples are AWS Lambda, Azure Functions.
- REST API: REST or RESTful APIs allow systems to access and manipulate data using standard HTTP requests like GET, POST, PUT, DELETE. Common in web and mobile apps.
- ETL: Extract, Transform, Load, the process of pulling data out of one or more sources, cleaning or modifying it, then loading it into a destination. Commonly used for moving data into data warehouses.
