Cloud
You Probably Don't Need Kubernetes
Kubernetes solves real problems at scale, but many teams adopt it prematurely. How to know if you need it, simpler alternatives, and what K8s adoption actually costs.
7 min read
Insights
Practical perspectives on enterprise software development, infrastructure automation, and cloud engineering from our project experience.
Architecture
The Strangler Fig Pattern: Legacy Migration Without the Big Bang
How to migrate away from legacy systems incrementally using the strangler fig pattern. Real strategies for routing traffic, managing data, and avoiding migration project death spirals.
10 min read
Infrastructure
Linkerd vs Istio: Choosing the Right Service Mesh
A practical comparison of Linkerd and Istio service meshes. Resource footprint, operational complexity, feature differences, and how to choose the right mesh for your Kubernetes clusters.
9 min read
DevOps
Lessons From Production Incidents
Patterns we've seen across dozens of production outages: what causes them, what makes response faster or slower, and how to build systems that recover gracefully.
7 min read
Strategy
Why Most Digital Transformations Fail
The critical mistakes that cause enterprise transformation projects to miss their objectives—and the patterns we've seen in projects that succeed.
8 min read
Cloud
Choosing Between AWS, Azure, and GCP
A practical guide to choosing between major cloud providers. What actually matters, what doesn't, and how to make the decision without analysis paralysis.
8 min read
Architecture
Scaling Your Database Without the Headaches
When your database becomes a bottleneck, you have options. Understanding the tradeoffs of different scaling strategies helps you choose the right approach for your situation.
8 min read
Automation
When Self-Service Infrastructure Actually Works
Self-service portals promise to reduce IT bottlenecks, but many fail. What separates the ones that get adopted from the ones that get ignored.
6 min read
DevOps
Building Observability That Actually Helps
Most teams have too much monitoring data and not enough insight. How to build observability that surfaces real problems without drowning in noise.
8 min read
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