deployment
Deployment & Infra
How your code gets from your laptop to running servers — packaging it in containers, putting new versions live without downtime, and describing infrastructure as code.
Start track →Start from zero
Before the senior material: what deployment even is, and the eight words the rest of the track assumes you know.Image layers
Image layers and the build cache: order is everything
An image is a stack of read-only layers, each Dockerfile step cached by its instruction plus input hash. Order steps…
Compose vs k8s
Compose vs Kubernetes: choosing the right orchestration weight
Compose orchestrates containers on one host with a tiny YAML; Kubernetes is a distributed control plane that…
K8s objects
Kubernetes objects: the reconciliation loop behind every Pod, Service, and rollout
Kubernetes is declarative — you submit desired state and controllers reconcile actual toward it forever. The object…
Rollout strategies
Rollout strategies: trading blast radius for resource cost and rollback speed
Recreate, rolling, blue-green, canary — four ways to ship a new version. The choice is a tradeoff between blast radius,…
Iac
Infrastructure as Code: the plan, the state file, and the drift
IaC declares desired infrastructure in version-controlled code; the tool diffs it against a recorded state file and…
Lb levels
Load balancing L4 vs L7: what each layer can and can''''t see
An L4 balancer routes by IP and port without reading the payload — fast but blind to URLs. An L7 balancer terminates…
Secrets at deploy
Secrets at deploy: where they enter, where they leak
Secrets must enter at deploy/runtime, never baked into the image. A Kubernetes Secret is base64-encoded, not encrypted…
Putting it together
Capstone: a deploy is a chain, and the outage lives in the seam
Each deploy stage is correct alone, yet the release breaks where two compose wrong: a rolling update with no readiness…
Docker, deeper
Beyond build: how containers network, persist data, and stay secure.Kubernetes, deeper
Routing, config, health and packaging — running real workloads on K8s.Build with this track
Guided projects that exercise what you learn here.
A concurrent Go ingest service
Build a concurrent ingest/fan-out worker in Go — then operate it: bound the work, apply backpressure, make downstream calls survive failure, ship it in a minimal container, and work a goroutine-leak incident before it eats your memory.
Async Python service, built and operated
Build an async FastAPI ingestion service that validates, pipelines, and survives load — then run it: package it, containerize it with correct PID-1 behaviour, and work the incident when a swallowed CancelledError quietly leaks tasks until the event loop starves.
Static page deploy
Take a static HTML/CSS page from a file on disk to a public URL with a deploy you can re-run — your first real delivery, no build step required.
URL shortener at scale
Build a URL shortener that survives real traffic — then run it: deploy it, watch it, and work the incident when one hot link melts your cache.
Performance
How to find why software is slow and actually make it faster — measure first, then fix the real bottleneck instead of guessing.