UNLOCKED SEATTLE 2026
REAL-WORLD LESSONS FROM TEAMS RUNNING PRODUCTION SYSTEMS
Real systems. Real lessons.
From the engineers who run them.
Engineers from Uber, Netflix, Apple, Google, and across the Valkey ecosystem walk through how they're building for AI, caching, and distributed systems at scale.
May 7, 2026
T-Mobile Park, Seattle, WA
$99 early bird pricing ends April 17!
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Hear from teams running systems at scale
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What Engineers Learned at Unlocked
Your resharding process is causing latency events you can't fully explain or predict
The on-call rotation is carrying risk that better Day 2 operational patterns would eliminate
Tail latency is inconsistent in ways that throughput metrics aren't surfacing
Hosts & Keynotes
Madelyn Olson
Principal Software Engineer, Maintainer of the Open-Source Valkey Project
Khawaja Shams
CEO & Co-Founder
Jacob Murphy
Staff Software Engineer, Maintainer of the Open-Source Valkey Project
Speakers
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Dmitry Polyakovsky
Consulting Member of Technical Staff
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Jim Brunner
Software Development Engineer
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Allen Samuels
Principal Software Engineer
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Sunjeet Singh
Staff Software Engineer
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Kishor Yadav Kommanaboina
Staff Software Engineer
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Tirtha Chatterjee
Software Engineer
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Yang Zhao
Senior Software Engineer
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Brian Martin
Co-Founder
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Nilanshu Sharma
Senior Software Engineer
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Vu Pham
Senior Staff Software Engineer
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Daniela Miao
Co-Founder & CTO
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Deepak Nandihalli
Software Engineer
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Yang Yang
Senior Staff Engineer
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Ratna Kumar Kovvuri
Staff Software Engineer
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Slava Markeyev
L6 Software Engineer
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Madelyn Olson
Principal Software Engineer
Agenda
The 3AM Test: Why Boring Systems Let You Sleep At Night
How Valkey is evolving Day 2 operations for predictable systems at scale
Valkey and Semantic Caching
Stop paying for repeated LLM calls when queries mean the same thing
Tweaking Valkey for High Write Rate Workloads
How to handle replication lag, memory pressure, and contention at high write rates
valkey-swift: Lessons from building a production-grade Valkey client library in Swift
Building clients that survive worst-case production scenarios
Building a Data-Plane Healer for Valkey Cluster at Scale
When cluster self-healing fails and how to recover from topology drift
Beyond fork(): Memory-Efficient Snapshots for Valkey
Stop doubling memory just to take a snapshot
Geo-Replication with Valkey
How Apple keeps Valkey clusters in sync across regions without losing data
Efficiency at Scale: Our Journey from Redis to Valkey
Optimizing access patterns and memory to scale beyond Redis limits
Foundations for High-Throughput Storage Envoy Plugins
When your proxy becomes the bottleneck and how to fix it
Scaling Search with Multithreading and Hybrid Queries
Combining vector, text, and filters in a single high-performance query
Secure, Scalable TLS Enhancements to Harden Valkey
Automatic TLS rotation, client auth, and guardrails without downtime
Towards Faster Inference: With KV Cache and Beyond
Not All RESP Clients Are Created Equal
What to do when you can't rely on connection pooling at scale
Thinking beyond demand filled caching: how versioned caches dominate Netflix
How Netflix uses versioned caches to avoid common scaling issues
Stress-Testing Valkey with the "Valkey Lab" Benchmarking Tool
Measure real performance gains with workloads that match production
Ghost in the Machine: Finding Hidden Headroom in Saturated Clusters
Why 100% CPU doesn’t mean your cluster is out of capacity
The 3AM Page: Tales From The Trenches
Raw, unscripted production horror stories and how to prevent them