Peterson Nwoko
Senior Cloud Engineer, Wolters Kluwer
Lagos, Nigeria
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Peterson is a Senior Cloud and DevOps Engineer with deep experience building scalable platforms across Azure, AWS, and GCP. He specializes in automation, observability, CI/CD, and infrastructure-as-code, helping teams improve reliability and deliver faster. His work focuses on creating efficient, developer-friendly cloud systems and simplifying complex engineering challenges
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Ingress Was the Easy Part: What We Learned Running Nginx and Gateway API in Real Kubernetes Clusters
Ingress is often treated as a solved problem in Kubernetes until clusters grow, teams multiply, and production traffic becomes unforgiving. In this session, I’ll share real operational lessons from running Nginx ingress in Kubernetes and the challenges that pushed us toward evaluating Gateway API.
We’ll walk through the practical problems teams encounter in real clusters: ingress configuration sprawl, unclear ownership, security boundaries, and brittle deployments. I’ll show how Kubernetes-native constructs Ingress, Gateway API, and related policies behave under real pressure, what improved, and what new complexities emerged.
This talk is not about tools, but about decisions, trade-offs, and lessons learned operating Kubernetes ingress in production environments.
Scaling Observability with OpenSearch: A DevOps Approach
Modern cloud environments generate massive amounts of logs, metrics, and traces—but without a scalable observability strategy, they quickly become noisy, expensive, and operationally overwhelming. In this session, I will walk through a DevOps-driven framework for implementing OpenSearch as a high-performance observability platform capable of handling real-time ingestion at scale while keeping search fast and costs predictable.
I’ll cover the architectural patterns, pipelines, and indexing strategies that allow teams to reliably ingest terabytes of logs, enrich them, route them intelligently, and create structures optimized for fast troubleshooting. Attendees will also see practical techniques for reducing cluster load, improving retention strategies, tuning queries, and building dashboards that cut MTTR dramatically.
Whether you are migrating from Elasticsearch, centralizing observability, or scaling OpenSearch for multi-cloud workloads, this talk provides a field-tested blueprint for building an observability system that is resilient, efficient, and engineered for growth.
API Observability in the Cloud: Detecting Failures Before Users Do
Many teams deploy APIs without truly understanding how they behave in production. Latency spikes, partial outages, and downstream failures often go unnoticed until users complain.
In this session, I’ll show how DevOps engineers can implement effective API observability using cloud-native and open-source tooling. We’ll break down what to measure (RED and USE metrics), how to correlate logs and traces across microservices, and how to design alerts that actually signal real problems.
The talk is grounded in real operational scenarios from cloud environments, including multi-service architectures and third-party API dependencies.
Attendees will leave with a clear mental model for monitoring APIs as first-class production systems.
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