Cloud Native London, June 2025

*Please note change of venue*

Hi folks!

Welcome to our June Cloud Native London meetup! Join us to hear from our two great speakers and network with your fellow techies over pizza and drinks, or alternatively chat and following along on Youtube!

6:00 Pizza and drinks
6:30 Welcome
6:45 Building a Healthy Platform Engineering Stack with Open-Source Feature Flags (Matt Elwell, Flagsmith)
7:15 The Missing Manual: Transforming AI Research into Resilient Distributed Systems (Peter Bhabra, Doubleword)
7:45 Wrap up

See you there!

Cheryl (@oicheryl)

Building a Healthy Platform Engineering Stack with Open-Source Feature Flags (Matt Elwell, Flagsmith)
Platform engineering offers a cure for inefficient and opaque legacy systems, but only with the right stack. This talk will cover how open-source feature flags and observability can work together to give flexibility and visibility into the SDLC and let teams improve builds and monitor results. We'll also discuss the importance of open standards in feature flagging and observability, particularly with the current rise of OpenFeature, a CNCF incubating project that follows in the footsteps of OpenTelemetry. OpenFeature adoption is growing fast among engineers and just took KubeCon by storm!

Matt is the CTO at Flagsmith. After years of agency work as a Software Engineer, Matt now spends his time building Flagsmith as the CTO, running the engineering team.

The Missing Manual: Transforming AI Research into Resilient Distributed Systems (Peter Bhabra, Doubleword)
The AI hype cycle has everyone focused on the latest model benchmarks and parameters counts, but deploying these systems at scale requires an intricate distributed systems architecture that often goes undiscussed. While researchers celebrate perplexity scores and hallucination rates, engineering teams struggle with the hidden complexity of transforming research breakthroughs into production-ready systems.
This talk pulls back the curtain on the "missing manual" of AI infrastructure – the critical components beyond the inference engine that determine real-world success. Drawing from hard-won lessons building large-scale AI systems at Doubleword, I'll navigate the complex ecosystem required to operationalise AI, including orchestration challenges, observability requirements, hardware optimisation strategies, and the intricate dance between custom schedulers and autoscalers.
Whether you're dealing with multi-modal inference, complex API gateways, vector databases, or document processing pipelines, you'll learn practical patterns for building resilient AI systems that can scale. Attendees will leave with a comprehensive framework for thinking about AI as a distributed system problem, not just a modelling challenge, and concrete strategies to bridge the gap between cutting-edge research and production-ready infrastructure.

Engineering leader specialising in scalable systems at the intersection of product and technology. Built data platforms for surgical robotics at CMR Surgical before joining Doubleword to architect AI inference systems that balance performance, cost, and simplicity. Having transitioned from traditional distributed systems to AI infrastructure, I offer insights on containerising workloads and building resilient platforms—sharing practical lessons for teams deploying AI at scale.
https://www.linkedin.com/in/peter-bhabra/

Check out https://www.oicheryl.com/cloudnativelondon if you're interested in speaking or sponsoring.