Peterson Nwoko
Senior Cloud Engineer, Andela
Lagos, Nigeria
Actions
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
Links
Area of Expertise
Topics
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.
From Prompts to Autonomous Systems: Architecting Production-Ready AI Agents on Google Cloud
AI applications are rapidly evolving from simple prompt-response systems to autonomous agents capable of reasoning, using tools, and executing complex workflows. However, while many developers can build impressive demos, very few systems are designed to operate reliably in production.
This talk explores how to design production-ready AI agent systems using modern cloud architecture patterns inspired by Google Cloud infrastructure. We will walk through the architecture behind modern agent systems and examine how orchestration layers, tool integrations, memory management, and observability work together to enable reliable automation.
Using real engineering patterns, the session will demonstrate how components such as Vertex AI-style model inference, serverless execution layers similar to Cloud Run, event-driven messaging, and persistent memory stores can be combined to build scalable AI agents capable of interacting with APIs, processing tasks, and executing workflows autonomously.
Attendees will gain practical insights into designing AI systems that move beyond prototypes and deliver real operational value. The session will include a live demonstration of an AI agent system running locally while reflecting the architecture used in production cloud environments.
Whether you are building internal automation tools, developer assistants, or intelligent workflow systems, this session provides architectural guidance for taking AI agents from experimentation to production deployment.
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top