Michael Uanikehi specializes in architectural accuracy and operational efficiency at the convergence of product engineering and infrastructure automation. As CTO, he is responsible for Kubernetes deployments, CI/CD pipelines, and distributed cloud services. He highlights scalability problems, technical debt management solutions, and the discipline necessary to sustain uptime while developing novel concepts.
What components of your job do you believe most people do not understand right now?
Many people believe that I spend my whole day programming, despite the fact that this is only a small portion of my present responsibilities. I spend most of my time making judgments about improving infrastructure dependability, comparing cloud provider costs, evaluating architectural diagrams, fine-tuning team procedures, and fixing systemic performance concerns. It combines engineering expertise with operational tradeoffs.
What procedures have you automated to increase your team’s speed and efficiency?
We created an internal developer platform using Argo CD and Terraform modules to reduce the need for manual intervention in our deployment pipeline. Currently, all engineers may configure and deploy services using Git-based approaches. This saved us hours of planning effort each week and made it easier to maintain consistent configurations across environments.
When do you decide to modify a project rather than improve it?
We frequently rewrite where performance difficulties stem from fundamental flaws, such as insufficient asynchronous handling in Node.js or excessive coupling with data flow. We fix issues like n+1 queries and memory leaks that occur in isolated occurrences. A rewrite is expensive, so I only greenlight it when the maintenance cost exceeds the cost of rebuild and testing.
What changes would you make if you could go back and redesign the system?
Initially, we combined all of our logging, monitoring, and tracing into a single stack with no backups. It became a single point of failure during periods of high ingestion rates. Independent observability layers for Loki, Tempo, and Prometheus have now been developed, along with fallback mechanisms.
How do you handle incident response inside your organization?
We treat incident response as if it were a production-ready system. We use a PagerDuty + Slack integration, predefined escalation policies, and RCA templates in Notion. We emphasize system recovery above diagnosis after events and conduct cold postmortems within 24 hours. No guilt, but facts, analysis, and records.
Which technologies presently excite you, assuming they are used correctly?
Event-driven architecture. If you understand idempotency, back pressure, and message ordering, systems like Kafka or NATS can be quite useful. However, a lack of awareness of data contracts or Dead Letter Queues (DLQs) might cause production turmoil.
What does technical excellence mean to you, as a leader?
Implementing clean code alone is inadequate; you must also guarantee that your systems can manage faults, grow reliably, and preserve visibility. I want our leads to understand how to assess infrastructure expenses, enforce performance limitations, and consider variables other than product logic, such as latency, resilience, and developer experience.
Finally, how can someone develop in your position while leading a huge team?
I occasionally code, but the majority of my growth comes from system reviews, threat modeling conversations, and collaborative debugging with our senior engineers. On weekends, I read RFCs, look into open-source projects like Envoy and Vitess, and conduct chaotic engineering experiments.
Michael Uanikehi’s ability to conceive at a high level is obvious in his work on container runtime difficulties and fault-tolerant architectural design. His approach to technical leadership is collected, clear, and firmly based on production realities.
Bio
Michael Uanikehi is a Senior DevOps Engineer at the London Stock Exchange Group, an AWS Community Builder, and an active open-source contributor. He has led and delivered critical financial engineering projects and enhanced tools like AWS Lambda Powertools, the Terraform AWS Provider, amazon-efs-utils, Kubernetes and numerous other OSS initiatives. Michael shares his expertise through Dev.to deep dives, conference talks, and free mentorship workshops, championing inclusive DevOps practices that empower developers to build resilient, secure, and efficient cloud systems.
