I’m a self-learner, passionate about Cloud and DevOps, and an avid bookworm. Find out more about me , browse my blog , or reach out . You can also check out my resume .
Rethinking Developer CLI Tools for the AI Agent Era
AI agents use our developer tools, but an error code often leaves them guessing. I explore how failure context, structured diagnostics, and recovery guidance could help them choose a safe next step.
What If We Could Debug LLMs Instead of Retraining Them?
Exploring whether larger AI models could help maintain smaller ones by debugging their weights instead of always retraining them.
Kubernetes OCI Image Volumes Explained
Exploring Kubernetes OCI Image Volumes (KEP-4639): mounting container images as read-only volumes, separating model weights from application images, and testing it locally with kind.
Trying Pele as My Hugo Blog Mermaid Renderer
A small change to my Hugo blog: render Mermaid diagrams with Pele, match the site theme, and make them easier to read on a phone.
The Bitter Lesson, LLMs, and Learning From Experience
LLMs inherit knowledge from human-generated data, while reinforcement learning helps AI learn from action and feedback. The future may combine both.
Jev Is the Missing Piece in Production AI Systems
Production AI should not send every event to a reasoning model. Jev offers a cheap decision layer that can route, score, and escalate work first.
Caching in the AI Era
LLM caching isn鈥檛 response caching. It鈥檚 KV state caching: here鈥檚 how it works, what it costs, and how to structure prompts to actually get hits.
Protecting Yourself from Malicious AUR Packages
Supply-chain attacks hit the AUR. Here鈥檚 what happened and how to protect yourself.
The Summarized World
Are we losing depth in the age of short-form content ?
System Design Notes: Split Brain in Docker Swarm
Split Brain in distributed systems, such as Docker Swarm, occurs when a network partition causes nodes to lose communication with one another. This results in two or more subsets of nodes thinking they are the leader or primary controller of the cluster. This inconsistency can lead to: Data corruption Conflicting operations Duplicate tasks being executed How it Happens Network Partition: A temporary network failure splits the nodes into two or more isolated groups. Leader Election Conflict: Each isolated group might independently attempt to elect a leader. Independent Decisions: Each group operates as a separate cluster, leading to inconsistent states. In a Docker Swarm cluster: Nodes are classified into managers and workers. Managers coordinate service orchestration and maintain the cluster state. If a partition occurs: Each group of managers may elect its own leader. This results in multiple active leaders (split brain) and service conflicts. Consequences of Split Brain Data Inconsistency: Multiple leaders might make conflicting updates. Duplicate Workloads: Services may be scheduled redundantly. Unrecoverable State: Independent decisions by both partitions can be hard to reconcile. Reduced System Reliability: The system becomes unpredictable or unusable. Prevention Techniques in Docker Swarm Docker Swarm uses the following techniques to avoid split-brain scenarios: ...