H100 GPUs are best for flexibility, fast iteration, and custom CUDA work. TPU v5p wins on GCP for large-scale LLM training with better cost efficiency and scaling.
Engineers rely on rollback to keep systems stable—but sometimes it isn’t possible. This article explores irreversible changes and why baking and testing matter.
In this article, I want to take a closer look at the pitfalls of popular SaaS scaling strategies, drawing on my own experience, and share the lessons learned.
Cloud systems drift when exceptions accumulate, and decisions lose connection to original objectives. Clear requirements and early security design prevent sprawl.
AI-driven development is outpacing security teams. This piece examines where AI-powered security actually help, where they fail, and how teams can use them responsibly.
Microservices introduce distributed-systems complexity most teams underestimate: failures, coordination drag, observability sprawl, and ballooning costs.
Agent identity and its audit history will enforce zero-trust access for agents based on both identity and past behavior. This makes agent access more secure and reliable.
Keep GenAI cheap and fast: cache aggressively, route models by confidence, cap tokens and tools, compress context, and monitor cost per successful outcome.
Modify URI-based API versioning to use date-based versions, easing operations, ensuring immutability, and also separating core logic from API responses.
The blog introduces you to the four pillars of observability, AWS and Azure cloud-native services, and ROI to help in architects and engineer's quest for system clarity.
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