Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
A practical tour of how software supply chain attacks reach your build, and the controls that actually stop them.
A practical field guide to the secure coding habits that stop the vulnerabilities attackers actually exploit in production.
AI apps add a new attack surface on top of the old ones. This is the map: the threats unique to LLMs and agents, and the controls that actually contain them.
Autonomous agents take real actions, so a single injected instruction can cause real damage. Here is how to contain them.
You cannot prove an LLM app is safe by reading its prompt. Here is how to adversarially test it before attackers do.
AIOps applies machine learning to your operational telemetry to cut alert noise, catch anomalies early, and speed up incident response.
A working security engineer's tour of the ten failure modes unique to LLM apps, each paired with a fix you can ship this sprint.
AI coding assistants ship fast but frequently introduce security flaws, so treat their output as untrusted and gate it before merge.
A practical guide to resolving Terraform provider version conflicts and lock file checksum errors across modules, developers, and CI pipelines.
A practical guide to renaming resources, migrating backends, and splitting or merging Terraform state without destroying and recreating infrastructure.
Terraform's errors are scarier than the fixes. This is the map to the ones everyone hits: what each message means, the safe way out, and how to avoid losing state.
A "Cycle" error means two Terraform resources depend on each other; here is how to find the loop and break it cleanly.
