Provisioning your own VMs and managing them is still work, even with Terraform doing the heavy lifting — sometimes the better answer is to hand that work to the cloud provider entirely. This module covers serverless computing: Functions as a Service like AWS Lambda, Azure Functions, and Google Cloud Functions, and the event-driven architecture that ties them together.
It also covers API gateways for exposing serverless functions as APIs, auto scaling and elasticity patterns, choosing managed services over self-managed infrastructure, and the basics of multi-cloud and hybrid cloud patterns — plus the real cost and performance trade-offs that come with going serverless.
Watch the lessons in order, then continue on to CI/CD Pipelines.
What "serverless" actually means, how FaaS platforms bill by execution instead of uptime, and when that trade-off makes sense.
Writing and deploying your first function on each of the major platforms, and the similarities in triggers, runtimes, and cold starts.
Designing systems around events instead of direct calls, using queues and message buses to decouple services from each other.
Fronting a set of functions with an API gateway to handle routing, authentication, and rate limiting for a serverless backend.
How cloud platforms scale resources up and down automatically with demand, and the patterns that make an application actually elastic.
Weighing convenience and reduced operational burden against cost and control when choosing a managed service over running your own.
Why some organizations spread workloads across multiple providers or mix cloud with on-premises infrastructure, and the added complexity it brings.
Cold starts, execution limits, and per-invocation pricing — where serverless shines and where a traditional server is still the better fit.