Extreme Elasticity with Tablets, Raft and Kubernetes by Maciej Zimnoch
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Recent ScyllaDB versions have improved elasticity using Tablets and Raft-based Consistent Topology Changes, allowing for fast bootstrapping and parallel scaling. A demo presents doubling cluster size and autoscaling after crossing 90% disk utilization.
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As AI reshapes expectations in retail and B2B commerce, organizations are recognizing a critical reality: meaningful AI outcomes depend on well-structured, adaptable infrastructure. In this session, Seth Earley is joined by Phil Ryan - AI strategist, search technologist, and founder of Glass Leopard Technologies - for a candid conversation on what it truly means to engineer systems for scale, agility, and intelligence.
Phil draws on more than two decades of experience leading search and AI initiatives for enterprise organizations. Together, he and Seth explore the challenges businesses face when legacy architectures limit personalization, agility, and real-time decisioning - and what needs to change to support agentic technologies and next-best-action capabilities.
Key themes from the webinar include:
Composability as a prerequisite for AI油- Why modular, loosely coupled systems are essential for adapting to rapid innovation and evolving business needs
Search and relevance as foundational to AI油- How techniques honed-in enterprise search have laid the groundwork for more responsive and intelligent customer experiences
From MDM and CDP to agentic systems油- How data platforms are evolving to support richer customer context and dynamic orchestration
Engineering for business alignment油- Why successful AI programs require architectural decisions grounded in measurable outcomes
The conversation is practical and forward-looking, connecting deep technical understanding with real-world business needs. Whether youre modernizing your commerce stack or exploring how AI can enhance product discovery, personalization, or customer journeys, this session provides a clear-eyed view of the capabilities, constraints, and priorities that matter most.Cracking the Code - Unveiling Synergies Between Open Source Security and AI.pdf
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Extreme Elasticity with Tablets, Raft and Kubernetes by Maciej Zimnoch
- 1. A ScyllaDB Community Extreme Elasticity with Tablets, Raft and Kubernetes Maciej Zimnoch Senior Software Engineer
- 2. Maciej Zimnoch Scylla Operator maintainer Previously worked on Scylla Manager, Instant Messaging servers, SDN and LTE networks
- 3. Life before Tablets and Raft Elasticity improvements Demo - Doubling cluster size Demo - Autoscaling after crossing 90% disk utilization Agenda
- 4. Life before Tablets and Raft
- 5. Scaling Scaling was slow due to: Synchronous scaling - missing topology change coordinator Data streaming - big datasets
- 6. Bootstrapping with VNodes slow slow Bootstrapping Streaming Ready
- 14. Scaling Recent ScyllaDB versions include multiple elasticity improvements. Most notable ones: Tablets and Tablets Load Balancer Consistent Topology Changes - based on Raft
- 16. Parallel scaling
- 17. Parallel scaling
- 19. Demo setup apiVersion: scylla.scylladb.com/v1alpha1 kind: ScyllaDBDatacenter metadata: name: scylla spec: rackTemplate: nodes: 1 racks: - name: a - name: b - name: c rack-a rack-b rack-c
- 20. Demo setup apiVersion: scylla.scylladb.com/v1alpha1 kind: ScyllaDBDatacenter metadata: name: scylla spec: rackTemplate: nodes: 2 racks: - name: a - name: b - name: c rack-a rack-b rack-c
- 21. Demo
- 22. Autoscaling - 90% disk utilization Demo
- 23. Demo setup rack-a rack-b rack-c clients write HPA HPA HPA *HPA - Horizontal Pod Autoscaler Target - 90% disk utilization Each HPA* scales rack independently based on rack disk usage. When target utilization is crossed, new Scylla Node is added.
- 24. Demo