Distributed systems, observability and AI engineering — each pattern gets a genre: a silent hero, a noir detective, a night at the theatre.
Twenty-three names in a catalogue is a memory problem. One car you can walk around is something else. Nine patterns pinned to a seat plant, an ECU, a brake stack and a gear selector, with six live diagrams and C# that compiles.
A small bot needs to read one calendar. Its manager refuses to hand over a password, and that refusal is the whole reason four different technologies exist. Six live diagrams, including a clickable relationship map and a JWT you can tamper with.
Four services, six repositories, and one configuration that holds them all together. An architect's walkthrough of the launch sequence, plus an honest argument about where configuration belongs, and why that answer decides how your worst night goes.
340 stores, 200 suppliers, and one dashboard that has to be right by 06:00. What Azure Data Factory does, the mess it was invented to replace, and why rerunning a failed pipeline is either boring or catastrophic depending on a decision you made weeks earlier.
A .NET monolith becomes four microservices on Azure. One hero builds the cluster from a text file; the other keeps the show running at 3 AM. Six live diagrams, real Terraform and YAML, and an approval gate you can actually approve or reject.
How one database table and one transaction can absorb broker outages, retries, and traffic spikes, so your microservices do not have to. It never trends, and it is holding up more production systems than the technology people talk about.
A request died somewhere across forty services, with no clear cause and no witness. Using three signals and one shared trace ID, a single waterfall chart can crack the case in one screen.
You have hired a brilliant improv actor for a role that must be performed the same way, eight shows a week. Schemas, validators, a deterministic orchestration pattern and evals — with a live interactive demo.
A village once drowned in its own ledgers, until a magician named Apache Spark learned to move mountains of data at once. A simple, illustrated story about how Spark works, and how Databricks trained him.