HollandTech’s Blog

What a company really spends its money on is the gathering: getting everyone pointed the same way, getting a decision to actually happen, getting one change past four teams and out of the door.

Every year, roughly 2% of the whisky in every cask in Scotland breathes out through the wood and is gone.

There's a lump of granite off the Ayrshire coast that used to be a volcano.

Every enterprise technology programme for forty years has been the same project: getting what people know out of their heads and into a system.

The board has seen the demo and wants the autonomous agent live by Q3.

You size a GKE cluster for thirty small stateful workloads, each with a modest PVC.

Eighteen months ago, a senior exec at a global consulting firm asked me whether we could build RAGs.

You put your AI agent in a container.

Agentic AI on your laptop is one thing — worst case it trashes your machine.

Somewhere between 'ask Claude for a quick opinion' and 'Claude is writing our Jira tickets,' we lost the plot.

AI agents will get you to dev-done at record speed — right up until you realise you're miles past the actual problem. 80% of projects still spend 80% of their time at 80% complete.

Your exec promised a customer that AI would 'just know' the answer to any question across every database in the org.

Too many architecture reviews are just debates about which vendor's service logo to put on the diagram.

We never really needed ten thousand DevOps engineers.

Google says Vertex AI is the managed future of ML on GCP.

The Highest Paid Person's Opinion isn't always wrong — but it needs a reality check from the people who actually build things.

VPC Service Controls prevent data exfiltration from GCP projects.

Understand when to use Kubernetes and when to go serverless in your cloud-native architecture.

Tiny Jira tickets.

The 'missionaries vs mercenaries' framing is lazy and wrong.

A thousand tiny Lambda functions scattered everywhere with no ownership, no contracts, and no way to test them locally.

Pipeline jockeys cranking YAML.

AI-enabled revenue feels a lot like tulip bulbs in 1637.

Most Kubernetes abstractions add complexity for complexity's sake.

Most contracts last three to six months.

Post-merger tech consolidation is one of the most expensive, least glamorous problems in enterprise IT.

Everyone preaches 'find vulnerabilities earlier.'

Azure DevOps Pipelines is the CI/CD system enterprise teams end up with because they're an Azure shop.

When a century-old manufacturer tries to 'go digital,' the cultural collision is spectacular.

Most Kubernetes comparisons are feature matrices written by people who've read the docs.

After a year of running KubeFlow across multiple client deployments, I can confidently say: the platform that promises end-to-end ML on Kubernetes delivers end-to-end frustration instead.

The Infrastructure as Code wars are over.

Vendor consultants optimise for showcasing their platform's capabilities, not for your team's ability to maintain it.

Not everyone can 'just use the cloud.'

Every organisation wanted an MLOps platform circa 2020.

Nobody is running workloads portably across clouds.

I've deployed Kubernetes manifests with both Helm and Kustomize across half a dozen enterprise clients.

ECK just went GA and we're running Elasticsearch on Kubernetes in production.

Everyone adopted Istio because everyone else was adopting Istio.

Service Fabric got a lot right — stateful services, the actor model, rolling upgrades with health checks.

We were using FluxCD to reconcile Kubernetes state from git before anyone called it GitOps.

The Databricks sales demo runs on a public workspace with default networking and an unlimited budget.

Software as a service is a quiet revolution, dramatically changing the way we do things.

Since the 1950s we've been looking for better ways to build software.

The cloud wars are raging.