Skills

Public skills grouped by discipline. The path below is conceptual: cloud and infrastructure feed observability, and AI sits on that telemetry. It is not an employer's architecture.

Cloud
Infrastructure
Observability
AI

Development sits alongside those layers rather than in the pipeline.

Cloud

Public cloud platforms the workloads run on.

Cloud infrastructure, networking, and managed services.
Second cloud platform for workloads and managed services.

Infrastructure

Orchestration, containers, and infrastructure automation.

Container orchestration for the workloads running on top.
Container images and runtime for those workloads.
Infrastructure as code for cloud and platform resources.
Configuration management and operational automation.

Observability

Metrics, logs, traces, and the systems that store them.

Metric collection, recording rules, and alerting.
Dashboards and visualization over metrics, logs, and traces.
Log aggregation queried alongside metrics and traces.
Vendor-neutral instrumentation and telemetry collection.
Log search and operational analytics.

AI

Language-model, retrieval, and automation tooling on the public skills list.

Large language models used as a reasoning and generation layer.
Retrieval-augmented generation over a private document set.
Model Context Protocol for tool and context access.
Workflow automation, including integrations and agents.
Task-oriented agents that call tools and APIs.
Routed access to language-model providers.

Development

Languages and delivery practices used across the work.

General-purpose language for automation and services.
Unix shell for operations and automation.
Version control and collaboration.
Continuous integration and delivery pipelines.

Select a technology to read how it fits. Related tools in the same group highlight; other groups stay quiet.