devopsdiary

field diary · 12 chapters · free, no signup

Learn DevOps by walking one pipeline, from ls to a canary release.

Every topic gets three passes: a plain-English explanation, a real-life analogy you already understand, and a lab you can actually run on your own laptop. Then you play with it until it sticks.

no accounts · no cloud bill · runs on Windows, macOS or Linux

tools you will actually touch bashgitdocker docker composekuberneteshelm github actionsterraformansible nginxprometheusgrafana lokiargo cdtrivy aws free tier

how it works

Three passes over every single topic.

Most DevOps material either drowns you in vocabulary or gives you commands to copy with no idea what they do. Each topic here is written the way a patient senior would explain it at a whiteboard.

pass one

Plain language

What the thing is, what problem it was invented for, and where it sits in the pipeline — in short sentences, with the jargon defined the first time it appears.

pass two

A real-life analogy

Every abstract idea is mapped to something you have already lived through: a tiffin box, a kitchen during dinner rush, a hostel water tank, an airport security queue.

pass three

Hands on the keys

A short lab with the exact commands, the output you should expect, and one thing to deliberately break — because you only really learn a system by watching it fail.

sample · chapter 07, topic 3

What a lesson looks like

This is a real excerpt, not a mockup. Docker images are one of the ideas people nod along to for months without ever picturing correctly, so it gets an analogy, a diagram in words, and a command whose output you can compare against your own screen.

real life

An image is a recipe printed on a card. A container is the dish you cooked from it tonight. You can cook the same card a hundred times in a hundred kitchens and get the same dish — and throwing away tonight's dish never damages the card.

Each layer of an image is one more line written on that card. Change the last line and you only re-cook the last step; change the first line and everything after it has to be made again. That is the whole secret to fast builds.

terminal · your laptop
docker build -t notes-api:v1 .
=> [1/5] FROM node:20-alpine       CACHED
=> [2/5] COPY package*.json ./     CACHED
=> [3/5] RUN npm ci                CACHED  ← 42s saved
=> [4/5] COPY . .                  0.2s
=> [5/5] RUN npm run build         3.1s
=> exporting layers                0.4s
Successfully tagged notes-api:v1

docker run -d -p 3000:3000 notes-api:v1
c3f9a1b2d4e5

curl -s localhost:3000/health
{"status":"ok","uptime":1.42}
now break it

Move one line and watch the cache die

Put COPY . . above RUN npm ci, rebuild, and time it. Every code change now re-installs every dependency. That one-line mistake is the most common reason a team's pipeline takes nine minutes instead of one.

the syllabus · read in order, or jump to what you need

Twelve log entries, beginning to on-call.

progress nothing finished yet — chapter 01 takes about 25 minutes
01START HERE Foundations: what DevOps actually is Why the wall between "developers" and "operations" existed, what broke because of it, and what teams changed to fix it. The vocabulary chapter — read this one even if you are in a hurry. waterfall vs agilethe wall of confusionCALMSDORA metricsSRE vs DevOpsplatform teams no setup ~25 min read 02 Linux and the shell you live in Nearly every server you will ever touch is Linux. Files, permissions, processes, packages, services and logs — plus enough bash scripting to automate your own boring work. filesystem tourpermissions & sudopipes & grepprocesses & signalssystemdssh keysbash scriptscron terminal lab ~45 min 03 Networking without the textbook What actually happens between typing a URL and seeing a page — IP, DNS, ports, TCP, TLS, proxies and load balancers — taught as a debugging skill rather than a diagram to memorise. IP & subnetsDNS recordsports & socketsTCP vs UDPHTTP methods & codesTLSreverse proxyload balancingfirewalls terminal lab ~40 min 04 Git, branches and working with humans Git as a save-game system for code. Commits, branches, merges, rebases, the reflog escape hatch, and the review habits that decide whether a team ships daily or monthly. the three areasbranchingmerge vs rebaseconflictspull requeststrunk-based devtags & versioningundoing mistakes terminal lab ~40 min 05 Continuous integration: the robot reviewer Build, test and package on every push. Writing your first GitHub Actions workflow, the testing pyramid, caching, matrix builds, artifacts, and how to keep secrets out of your repo. what CI solvesworkflow anatomyrunners & jobstest pyramidcachingmatrix buildsartifactssecretsflaky tests github lab ~50 min 06 Containers and Docker "It works on my machine" ends here. Images, layers, Dockerfiles, volumes, networks, Compose, registries and multi-stage builds that cut an image from 1.1 GB to 90 MB. containers vs VMsimages & layersDockerfilebuild cachevolumesnetworkscomposeregistriesmulti-stagedebugging docker lab ~55 min 07 Kubernetes, explained slowly The scary chapter, taken one object at a time. Pods, deployments, services, ingress, config, secrets, probes, autoscaling, Helm — and a repeatable routine for debugging a broken pod. why orchestrationcontrol planepodsdeploymentsservicesingressconfigmaps & secretsprobesresourcesHPAhelmkubectl debugging kind/minikube lab ~70 min 08 Infrastructure as code Stop clicking in consoles. Terraform for creating infrastructure, Ansible for configuring it, why state files matter so much, and how to avoid the classic "someone changed it by hand" outage. declarative vs imperativeterraform basicsstate & lockingvariables & outputsmodulesdriftansible playbooksidempotencyimmutable infra terraform lab ~55 min 09 Continuous delivery and releasing safely Getting a tested build into production without holding your breath: environments, promotion, blue-green, canary, feature flags, rollbacks, database migrations, and GitOps with Argo CD. CD vs deploymentenvironmentsartifact promotionblue-greencanaryfeature flagsrollbackdb migrationsgitops pipeline lab ~50 min 10 Observability, alerting and on-call Logs, metrics and traces; Prometheus and Grafana; the difference between an alert worth waking up for and noise; SLOs and error budgets; and how to run an incident without panicking. three signalsstructured logsmetric typesPromQL basicsdashboardsalert designSLI/SLOerror budgetsincident rolespostmortems prometheus lab ~60 min 11 DevSecOps: security you can automate Secrets management, least privilege, dependency and image scanning, supply-chain basics, and the handful of pipeline checks that stop the majority of embarrassing mistakes. shift leftsecrets managementleast privilege & IAMSAST/DAST/SCAimage scanningsupply chain & SBOMhardeningcompliance basics scan lab ~45 min 12FINISH Portfolio, interviews and what comes next Four portfolio projects worth putting on a CV, how to talk about them, the questions interviewers actually ask, a home-lab setup that costs nothing, and how to keep learning after this diary ends. 4 projectswriting your READMEinterview questionsfree home labcertificationswhat to read next career ~35 min

a plan that fits a job

Four weeks, an hour a day.

If you have more time, do the labs twice — once following along, once from memory. The second run is where the learning happens.

week one

Ground floor

Chapters 01–04. Get comfortable in a terminal and stop being afraid of Git. Finish by pushing a branch, opening a pull request and merging it yourself.

week two

Automate the boring

Chapters 05–06. A green pipeline on every push, and your own app running in a container you built. This is the week it starts feeling real.

week three

Run it like production

Chapters 07–09. A local cluster, infrastructure defined in code, and a canary release you can roll back on purpose.

week four

Keep it alive

Chapters 10–12. Dashboards, one alert worth waking up for, a scan in the pipeline, and a portfolio project written up properly.