Long-form essays from the engineers shipping AI inside payers, hospitals, energy operators and proptech platforms. Written for technology leaders who care more about what runs in production than what trended last week.
How AWS Control Tower sets up multi-account governance the right way: guardrails, account factory, and where it fits versus a hand-built landing zone.
Why data architectures that work today break at 10x scale, the assumptions that fail, and how to design for the next order of magnitude without over-building today.
How to run Spot Instances in production safely: handling interruptions, diversification, and the resilience patterns that capture up to 70% savings without outages.
A deep dive into AWS networking, VPCs, Transit Gateway, and PrivateLink, and how to choose the right connectivity pattern for your architecture and scale.
A decision framework for choosing between Aurora, RDS, and DynamoDB: access patterns, scale, consistency, and cost, matched to what your workload actually needs.
How to use AWS Organizations and Service Control Policies for account-level governance: structure, guardrails, and the controls a production multi-account setup needs.
How to design cloud architectures for portability without over-investing in cloud-agnosticism: where lock-in matters, what to abstract, and the controls an exit needs.
A clear-eyed look at service meshes in 2026: what they solve, the complexity they add, when they are worth it, and how to decide for your architecture.
The hidden costs of monolith-to-microservices migration nobody warns you about: distributed complexity, data, and the disciplined, incremental approach that works.
What GitOps actually changes in day-to-day operations: git as the source of truth, reconciliation, auditability, and the controls a production GitOps setup needs.
What zero-trust networking means for cloud-native systems: identity-based access, microsegmentation, mutual TLS, and the controls to adopt it without breaking everything.
How policy as code enforces security and compliance standards automatically without slowing developers: where to enforce, how to avoid friction, and the controls it needs.
How to configure Kubernetes cluster autoscaling that scales for demand without runaway cost: bounds, policies, and the cost-awareness a production setup needs.
How to right-size Kubernetes with requests and limits grounded in real usage: avoiding over-provisioning and throttling, and the controls a production cluster needs.
Why cost allocation tagging is the unglamorous practice that unlocks cloud cost control: a tagging strategy, enforcement, and the accountability it makes possible.
A practical handbook for setting service level objectives your team can actually hit: choosing SLIs, realistic targets, error budgets, and the operating model behind them.
Why observability belongs in development, not after an incident: instrumenting before you ship, the three pillars, and the practice that makes systems debuggable in production.
Why environment variables fail as secrets management at scale, and how to do it right: centralized storage, dynamic secrets, rotation, and the controls a production system needs.
The real cost of going multi-region is more than duplicated infrastructure: data replication, consistency, operational complexity, and the controls a multi-region system needs.
A practical guide to progressive delivery: canary releases, blue-green deployments, and feature flags, plus the metrics and automation that make rollouts safe.
What golden paths are and how they boost developer productivity: paved defaults, escape hatches, and the platform discipline that makes the right way the easy way.
What a new platform engineering team should build in its first 90 days: sequencing, golden paths, and the foundations that earn adoption instead of resentment.
What a cloud landing zone is and how to get the foundation right the first time: account structure, identity, networking, guardrails, and the controls a production landing zone needs.
A practical look at feature stores: what problems they solve, when you actually need one, the cost of building too early, and how to decide for your ML program.
One long-form essay every other Wednesday. Written by the engineers shipping production AI for our clients, not by a content team. No promotional emails. Unsubscribe in one click.
