March 2025: Is Your Data a Mess? Let’s Mesh It Up! & AI workloads

Join us for our upcoming meetup on Thursday, 13th of March, 2025, at 7pm at the Waterford Treasures Museum (X91 K10E). Enjoy an evening of engaging talks, networking opportunities, food, drinks, and exciting spot prizes as we delve into innovative ideas shaping the technology landscape.

Speaker 1: Diren Akkoç – fourTheorem

Diren is passionate about building scalable, resilient data architectures in the cloud. With a deep focus on serverless, observability, and modern approaches like Data Mesh, she helps teams move beyond data silos and unlock real business value. She enjoys sharing insights through blogs, talks, and hands-on projects, always aiming to make complex ideas simpler and more practical.

Tech Talk: Is Your Data a Mess? Let’s Mesh It Up!

Why is seamless access to data at scale still such a challenge? Traditional data architectures often lead to bottlenecks, endless backlogs, and frustrated teams. Enter Data Mesh, a modern approach that decentralises data ownership, empowers teams, and treats data as a product. In this talk, Diren will break down what Data Mesh is, why it matters, and how organisations can shift from data chaos to a scalable, self-serve data ecosystem. Is your data a mess? Let’s mesh it up and find out.

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Speaker 2: Rafael Sadykov - IBM

Rafael thrives on applying advanced mathematics and computer science to solve complex problems. With expertise in Financial Mathematics, Risk Management, and Quantitative Finance, he develops robust mathematical models and contributes to formal software verification. He enjoys blending research with practical software development, always striving to turn analytical insights into real-world solutions.

Tech Talk: AI workloads: A Platform perspective

In this session, we'll explore scalable AI development and deployment from a developer's perspective. Building and deploying AI solutions can be complex, but with the right tools and strategies, we can simplify the process and enhance efficiency. We'll dive into:

• Deploying AI on OpenShift: Leveraging containerized models with OpenShift AI
• Serverless AI and APIs: Creating robust REST/gRPC endpoints using OpenShift Knative
• MLOps: Streamlining CI/CD for AI models with ArgoCD and OpenShift Pipelines
• Monitoring: Gaining insights and maintaining performance with Grafana