Charles Adetiloye

A drone doesn't care what time it is. It takes off when the mission says so, lands when the battery says so, and uploads its logs whenever the LTE link or WiFi finally cooperates.

This talk demonstrates how declarative Beam YAML pipelines, combined with LLM-powered agentic architectures, unlock real-time predictive intelligence on high-velocity sensor streams — using UAV flight telemetry as a live use case. We show how parameterized Beam YAML templates dynamically...

A fully autonomous VTOL logistics fleet has been flying mathematically optimized delivery corridors for 14 months. Every flight clears health checks. Every autopilot recovery is clean. No alerts fire. No reports are filed. On paper the operation is running perfectly. A single Apache Beam...

This session explores how Large Language Models (LLMs) can be integrated into Apache Beam tooling to enable agentic orchestration of YAML-defined workflows. We present a system where LLMs parse, validate, and execute Beam YAML pipelines, acting as autonomous agents that enhance workflow...

We have developed BeamStack, a toolkit tailored to enhance the deployment and management processes of ML and GenAI workloads on Kubernetes. It diminishes the intrinsic complexities associated with the managing of Kubernetes clusters and the deployment of Apache Beam workloads. Fundamentally,...

At MavenCode, we consult, develop and train on how to implement large-scale production-grade Machine learning workflows all on Kubernetes, and Apache Beam has gradually become a defacto standard for us in handling large-scale ML workloads In recent years, the adoption of Kubernetes as a...

The need for a highly efficient data processing workflow is fast becoming a necessity in every organization implementing and deploying Machine Learning models at scale. In most cases, ML teams leverage the managed service solutions already in place by the cloud infrastructure provider they...

At SmartDeployAI, we build data workflow pipelines for running large scale Industrial IoT applications. Our software platform is a shared multi-tenant Kubernetes cluster environment where multiple workflow pipelines can be bootstrapped and scheduled to run concurrently.