AWS Emulator went generally available on 11 November 2026. Ten questions, one CI run against release 1.0.341: install and signature check, start-up cost, CLI, boto3 and Terraform, a 22-experiment comparison with moto, Lambda, service reach, the published fidelity scores, IAM, state, and a pipeline recipe.
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Testing Infrastructure Code: terraform test, Mock Providers and a Policy Gate in CI
A Terraform module for a clinical-document bucket tested three ways in CI with no cloud account: fourteen unit tests on a mocked provider that pass on Terraform 1.16 and OpenTofu 1.12, ten deliberate defects that the tests must catch, and a policy gate over the JSON plan.
Read more →SQL Server 2025 for Architects: The Vector Type and Native JSON
What the SQL Server 2025 vector and json types do when you run them: exact and approximate search, what still needs the preview switch, what an index costs on writes, and when one engine is enough. Every result comes from the container image in a CI pipeline.
Read more →Keeping Secrets Out of Terraform State: Ephemeral Resources and Write-Only Arguments
Marking a value sensitive hides it on the console and still writes it to state. Ephemeral resources and write-only arguments let a secret pass through a run without being recorded. The same secret created both ways on Terraform 1.14 and OpenTofu 1.11, with every file searched for it afterwards.
Read more →Security as Code: Why the Best DevSecOps Teams Treat Vulnerabilities Like Bugs, Not Afterthoughts
The first time I watched a security vulnerability slip through our CI/CD pipeline and make it to production, I felt the same sinking feeling every engineer knows: that moment when you realize the system you trusted has a blind spot. It was 2019, and we had what we thought was a mature DevOps practice. Automated […]
Read more →MLOps vs LLMOps: A Complete Guide to Operationalizing AI at Enterprise Scale
Understand the critical differences between MLOps and LLMOps. Learn prompt management, evaluation pipelines, cost tracking, and CI/CD patterns for LLM applications in production.
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