Insights
We write about what we have built, what broke, and what we would do differently. Engineering perspectives on cloud, data, and platform — without the vendor spin or the content marketing calendar.
Categories
A look at the semantic layer problem: why inconsistent metric definitions create organisational noise, and the architectural decision that resolves it.
Coming soonThe infrastructure choices that look fine at 1,000 users and become expensive at 100,000. What we've seen repeatedly, and what to do instead.
Coming soonThe failure modes that show up reliably across Kubernetes migrations — and the patterns that make the difference between a smooth cutover and a painful one.
Coming soonA practical breakdown of what a semantic layer actually is, when you need one, and how to build it without over-engineering it.
Coming soonWhy teams that install the right tools still ship slowly — and the organisational and process factors that actually drive deployment frequency.
Coming soonThe lakehouse vs warehouse debate misses the actual decision. Here's the framework we use to recommend the right architecture for a given organisation.
Coming soonWhat investors and technical advisors actually look at during infrastructure due diligence — and how to avoid the six issues that most commonly surface.
Coming soonA practical breakdown of what India's DPDP Act 2023 requires at the infrastructure layer — data residency, access controls, audit trails, and consent management.
Coming soonKafka is often over-specified and sometimes under-specified. The criteria that determine whether your architecture needs a streaming backbone or a well-tuned batch pipeline.
Coming soonWhat internal developer platforms are actually solving for — and why most IDP implementations fail to reduce the friction they were built to address.
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The problems we write about are ones we've seen in production. If any of it sounds familiar, we'd be glad to have a direct conversation.
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