Serverless computing is a cloud execution model where you run code in managed, auto-scaling functions (Function-as-a-Service) and managed backend services without provisioning or maintaining servers. You pay for actual execution, and the provider handles scaling, patching, and capacity.
What it is
"Serverless" does not mean there are no servers. It means the servers are invisible to you: the cloud provider runs, scales, and patches them, and you simply ship code. The two most common forms are Function-as-a-Service (FaaS), where small functions run in response to events (an HTTP request, a queue message, a file upload), and managed backend services such as serverless databases, authentication, storage, and message queues that you consume through an API instead of operating yourself.
Why it matters
Serverless shifts undifferentiated operational work — capacity planning, OS patching, load balancing, autoscaling — from your team to the platform. That lets a small team ship features quickly and lets the application scale automatically from zero to thousands of concurrent executions and back down again. Because billing is tied to actual invocations and run time, idle workloads cost little or nothing, which is attractive for spiky, unpredictable, or low-volume traffic.
How it works
You deploy a function or service; the platform keeps it dormant until an event arrives, then spins up an execution environment to handle it and tears it down when traffic subsides. When no warm instance exists, the first request pays a cold start — the extra latency of initializing the runtime and your code. Functions are also typically stateless and have execution-time and memory limits, so persistent state lives in managed databases, caches, or object storage rather than in the function itself.
Benefits and tradeoffs
Benefits: no server management, automatic scaling, pay-per-use billing, and faster delivery for event-driven and bursty workloads. Tradeoffs: cold-start latency on infrequently used paths, execution time and payload limits, harder local debugging and observability, the risk of provider lock-in through proprietary services, and costs that can climb above dedicated compute at sustained high volume.
When to use it
Serverless is a strong fit for event-driven processing, scheduled jobs, lightweight APIs, webhooks, glue code between systems, and traffic that is spiky or hard to forecast. It is usually a weaker fit for long-running compute, very latency-sensitive hot paths where cold starts hurt, and steady high-throughput workloads where always-on containers or virtual machines are cheaper and more predictable. Many production systems are hybrid: serverless for the bursty edges, containers for the steady core.
Related terms
Serverless overlaps with several adjacent concepts. Edge functions are a serverless variant that runs close to users for lower latency, while microservices are a complementary architecture often deployed serverlessly. For steady, container-based workloads teams frequently reach for Kubernetes instead, and the automation that ships any of these into production is covered under DevOps Solutions.
In short, serverless trades fine-grained control for managed scaling and pay-per-use simplicity — an excellent default for event-driven and unpredictable workloads, and a poor one for steady, latency-critical compute.
FAQ
Does serverless mean there are no servers?
No. Servers still run your code; you just don't provision, patch, or scale them. The cloud provider manages all of that infrastructure for you, so the servers are invisible from your point of view.
What is a cold start in serverless?
A cold start is the extra latency when a function has to spin up a fresh execution environment before it can run, because no warm instance is available. It mostly affects infrequently called or latency-sensitive endpoints, and can be reduced with smaller bundles, lighter runtimes, or provisioned concurrency.
Is serverless cheaper than running servers?
It depends on traffic. Serverless bills per execution, so it is often cheaper for spiky or low-volume workloads where idle servers would waste money. For steady, high-volume traffic, dedicated or containerized compute can be more cost-effective.
Building on serverless? Talk to an Apex IT Solutions engineer about whether a serverless, containerized, or hybrid architecture fits your project.