Infrastructure11 topics
Infrastructure, DevOps and the cloud
Infrastructure is everything that turns code into something running that you can observe, change and roll back. This section covers 11 topics in four groups: DevOps and the pipeline that builds one artifact and promotes it unchanged, the three major clouds and how each contains a mistake, MLOps — the same problems again for a model instead of a binary — and the monitoring that makes an incident answerable at three in the morning.
What is inside
Each area below is a group of topics. Open one to read its pages.
- DevOpsThe process, the unit and the loop: merge habits, image layers, and reconciliation.CI/CDDockerKubernetes
- CloudOne durable mechanism per provider — authorisation, boundaries, and two control planes.AWSGCPAzure
- MLOpsA model is a build artifact from four inputs. Everything else follows from taking that seriously.PipelinesServingVector DBs
- MonitoringWhat you record, and who you are allowed to wake up because of it.LoggingSLOOn-call
Where to start
- Setting up deliveryCI/CD first — continuous integration is a habit about merge frequency, not a server that runs tests.
- Containers still feel like magicDocker explains why Dockerfile order decides build time, and why a container is a process rather than a small machine.
- Picking or auditing a cloudThe three cloud pages compare no service catalogues. Start with AWS for how a request is actually authorised.
- Nobody knows if it worksLogging, then Alerting. The first decides whether a later question has an answer; the second, who gets woken.
Other sections
- DevelopmentSoftware development is the work of deciding where the boundaries in a system go, what runs on each side of them, and what moving one of those boundaries will cost once the code is live. This section covers 28 topics — architecture, the browser, five backend runtimes, four mobile platforms, language models and the databases underneath all of it. Every page turns on the constraint that actually separates the options, rather than on the API surface.
- QAQuality assurance is the practice of deciding what to check, running those checks often enough to be worth having, and knowing what changes when the thing under test stops giving the same answer twice. This section covers 9 topics in three groups: the types of testing everyone half-remembers, automation with Playwright, Cypress and Selenium, and testing products built on language models — where an assertion becomes a score rather than an equality.
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