CLOUD / DEVOPS / AGENTIC AI
I’m Adekunle. I bring cloud, DevOps, and AI together—automating infrastructure, making releases repeatable, and keeping production observable.
01 / WHAT I BRING
From the infrastructure underneath to the intelligence on top. Build for the people using it, the engineers operating it, and the business depending on it.
A solid foundation for everything that comes next. Scalable AWS environments, thoughtful network design, and security built into the architecture.
From VPC segmentation and routing to compute, storage, and identity, I connect the pieces into infrastructure that serves the application and the people behind it.
Connect development and operations through automation. CI/CD pipelines, versioned infrastructure, container platforms, and release practices that make production changes repeatable and reviewable.
I work across the DevOps lifecycle: source control, infrastructure provisioning, configuration management, CI/CD, container orchestration, and production feedback. Build once, promote the same artifact between environments, review infrastructure plans, and pair each release with health checks and a rollback path.
Know what is happening, why it matters, and where to look next. Service health dashboards, actionable alerts, and a connected view of metrics, logs, and traces.
Start with the user journey, then instrument the signals that explain it: request rate, errors, latency, resource saturation, and dependencies. Pair dashboards with alert ownership, incident context, and practical runbooks so visibility leads to action.
Connecting AI reasoning with useful tools and dependable infrastructure. A focus on coding agents and workflows that help teams investigate, build, and automate with human oversight.
I’m exploring coding agents, context-aware workflows, and tool-connected systems. My focus is on useful automation with clear boundaries, inspectable steps, and human checkpoints.
EXPLORATION TOOLKITCodex · Claude Code · LangGraph · Model Context Protocol
DEVOPS IN PRACTICE
DevOps connects the people building software with the people operating it. I turn that connection into automated pipelines, reproducible environments, and clear operating practices.
Turn a source change into a versioned artifact with repeatable checks before it gets near production.
Make environments reproducible through reviewed infrastructure code and consistent configuration.
Give each release a controlled path forward and an understood route back when a health check fails.
Bring production signals back into engineering decisions so each change starts with better context.
Continuous feedback is part of delivery.Production signals, incident learning, and team feedback shape the next improvement.
02 / UNDER THE HOOD
Architecture is easier to understand when you can follow it. Explore cloud architecture, a DevOps pipeline, agent workflows, and observability—one step at a time.
A resilient application path
An illustrative AWS request path, from the public edge to private application services and persistent data.
$ Follow a request through the system
Across the system: identity, network boundaries, logs, and metrics.
03 / HOW I APPROACH THE WORK
A deployment is one moment. Operating the system is the longer story. My DevOps approach connects architecture, delivery, and operations so the team has a clear path forward.
Explore the engagement blueprints01 / UNDERSTAND THE SYSTEM
Map the workload, dependencies, failure modes, and business priorities. Agree what reliability, recovery, security, and cost need to look like before choosing the architecture.
WORKLOAD → TRADE-OFFS → ACCEPTANCE CRITERIA02 / MAKE CHANGE REPEATABLE
Keep infrastructure in version control. Automate the repeatable steps, review the changes, test the recovery path, and make environment configuration explicit.
INFRASTRUCTURE AS CODE → CI/CD → CONTROLLED RELEASES03 / CLOSE THE OPERATING LOOP
Connect service health, logs, metrics, and traces to an owner and a response. Document the decisions and runbooks so the system stays understandable after the handover.
MONITOR → INVESTIGATE → RECOVER → IMPROVECURIOSITY, BACKED BY LEARNING
AWS architecture and networking. Infrastructure automation and container platforms. Ongoing exploration of coding agents, tool orchestration, and observable AI workflows.
04 / FROM CHALLENGE TO DELIVERY
Reference blueprints for common infrastructure challenges. Explore the proposed scope, delivery milestones, and acceptance checks for an engagement.
You need to move an application or modernize an existing AWS environment without losing control of dependencies, data, or the cutover.
A staged migration with a rehearsed rollback path and an operating model your team can own.
Inventory workloads, network paths, data dependencies, and operational constraints. Agree recovery objectives and identify what can move together.
Define network boundaries, least-privilege access, environment separation, remote state, and audit logging in versioned infrastructure.
Test data movement, application behavior, backup restoration, and a rollback sequence in a representative environment before the production change window.
Move traffic in controlled stages, watch application and database signals, and verify the agreed acceptance checks before closing the rollback window.
WHAT YOU TAKE AWAY
05 / WHAT’S NEXT?
Planning a migration? Untangling deployments? Missing the signals that explain an incident? Tell me where you are now and what needs to work better.