Kubernetes in Production
Beyond the tutorial cluster
What you'll learn
- Deploy without dropping a single request
- Autoscale on a signal that means something
- Keep secrets out of the repository and the image
- Debug a failing pod from first principles
- Level
- Advanced
- Duration
- 12 weeks
- Material
- 3m
- Lessons
- 12
- Language
- English
- Access
- 365 days
About this course
Run real workloads on Kubernetes: deployments, autoscaling, secrets, observability and the failure modes that only show up under load.
A tutorial cluster on your laptop teaches you the nouns. This teaches you the verbs. Rolling deployments that do not drop requests, autoscaling that reacts to the right signal, secrets that are not in your repository, and enough observability to answer "what changed?" at three in the morning.
Syllabus
4 modules · 12 lessons · 3m · 1 free to preview
Getting set up
- What you are going to build
- Setting up your machine
- Your first working version
The core ideas
- What you are going to build
- Setting up your machine
- Your first working version
Building it for real
- What you are going to build
- Setting up your machine
- Your first working version
Shipping and what comes after
- What you are going to build
- Setting up your machine
- Your first working version
Taught by
Gs DwiwediLead
Full-stack engineer, and the person who built this platform
Fifteen years building and running production systems, most of them in Java and JavaScript. Teaches the way he works: start with something that runs, then make it correct, then make it fast.
What you'll get
- Lifetime accessCome back to the material whenever you need it.
- Reviewed projectsA person reads your code and tells you what to change.
- CertificateIssued on completion, verifiable by a link.
- Doubt sessionsLive weekly, recorded if you cannot make it.
Tools you'll use
- KubernetesWorkloads, services, ingress and RBAC
- HelmPackaging releases you can roll back
- PrometheusMetrics that answer real questions
- TerraformClusters described in code
Before you start
- Comfortable with Docker and the Linux command line
- Some experience running a service in production
Who this is for
- Backend developers taking on operations
- Engineers moving from single servers to clusters