DevOps & SRE Learning Paths
Go from "never used this" to "ready to implement it and defend it in a production outage or an interview." Each path is a sequence of levels built from hands-on tasks with real verification steps.
Shell Scripting
Master bash scripting, command-line pipelines, input validation, positional arguments, looping, file parsing, and defensive programming for automation.
Linux Systems
Understand kernel diagnostics, process states, signals, memory hierarchy, system call tracing, networking diagnostics, and storage optimization.
Git & Version Control
Learn the object model first, then everything falls out of it: the three trees, branches as pointers, merge and rebase mechanics, remotes and refspecs, reflog recovery, bisect forensics, history rewriting and repository trust.
Docker & Containers
From namespaces and cgroups to a shipped image: layers and copy-on-write, Dockerfiles, multi-stage builds, volumes, the container network model, registries, Compose and hardening.
Kubernetes
From the reconciliation loop to production operations: workloads, scheduling, the pod network, RBAC, autoscaling, upgrades and etcd — pinned to Kubernetes 1.36.
Helm
Charts, values and releases: the object model behind helm upgrade, the template language in the forms you actually write, dependencies and OCI distribution, hooks and chart tests, and the upgrade failures that only appear on the second deploy.
Ansible
Master enterprise Ansible automation: Agentless SSH, Inventory design (group_vars/host_vars), Idempotent playbooks, Jinja2 templating, Variable precedence, Handlers, Task Blocks & Rescue error handling, Modular Roles & Galaxy, Ansible Vault secrets, and AWX / Ansible Tower job templates.
Terraform
From the declarative model to a production three-tier build: providers and resources, plan reading, the type system, state and remote backends, modules, workspaces, provisioners, CI/CD, policy as code, multi-cloud and a 100-error troubleshooting catalogue.
Jenkins & CI/CD
Delivery end to end: declarative Jenkins pipelines, shared libraries and ephemeral agents, then Google Cloud Build and Cloud Deploy, deployment strategies, supply-chain signing and a pipeline you can defend commit by commit.
AWS Operations
Run AWS the way it fails: the blast-radius model, IAM evaluation order, VPC routing and private connectivity, EC2 and EBS ceilings, RDS failover, EKS identity and capacity, then a landing zone you break on purpose.
GCP Operations
Master production GCP operations: Resource Hierarchy & Labels, IAM & Service Account delegation, Shared VPCs & Firewall Tags, GCE MIGs & SUD/CUD cost optimization, GCS WORM Lifecycles, GKE Pod IP & Workload Identity, Cloud Logging Sinks, and Pub/Sub & BigQuery analytics.
Cloud Cost Optimization
Cloud spend as an engineering discipline: the layer model, tagging and baselining, right-sizing without causing outages, CPU architecture migration, Spot and commitments, Karpenter and cluster cost tooling, storage, network and the observability bill.
12 of 12 tracks are live today — the rest are being written from the same production failures that power the war rooms.