Engineering notes / AWS platform operations
Practical explanations of GitOps, Amazon EKS, AI-assisted operations, and the engineering controls that make automation trustworthy.
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Practical architecture for CTOs, platform leaders, and engineers who need the operating decision and the implementation detail to make sense together.
An AI agent can follow its task correctly while acting on a wrong understanding of the environment. Engineers need a live view of its work and a stop mechanism outside the agent.
AI monitoring works best when the agent knows what healthy looks like, how services connect and what changed. A short report gives engineers a useful place to start.
An agent can understand each tool separately and miss how Git, CI, Argo CD, AWS, controllers and service dependencies affect one another. It needs the path from the original request to recovery.
Give each change the smallest environment needed for a confident review, and keep shared staging for work that genuinely needs a common state.
One commit can describe the full source state in a monorepo. The preview still needs clear rules for builds, data, dependencies, cost and cleanup.
A pull request in one repository describes one service. A useful preview must also choose known versions for every service around it and record them in one place.
We have seen tidy CIDR plans become a limit once EKS pods, load balancers, endpoints, peering and new environments start consuming addresses.
Installing Argo CD is usually straightforward. The harder work is deciding repository ownership, permissions, promotion, deletion, recovery and what a healthy result means.
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