Ep

Описание: Welcome to the Jon Myer Podcast, powered by Myer Media! Today we're exploring the intersection of open source databases, Kubernetes orchestration, and the explosive growth of AI workloads with Peter from Percona.

We discuss why traditional thinking about databases is shifting, how organizations are adapting their infrastructure for generative and agentic AI, and what opportunities exist in the open source ecosystem that too many companies are overlooking.

Key Topics Discussed:
✅ Why Kubernetes is finally ready for database workloads (and how it matured)
✅ Percona's Kubernetes operators for MySQL, Postgres, MongoDB, and Valkey
✅ Breaking misconceptions: Data safety and performance on Kubernetes
✅ How open source databases like Postgres caught up to AI demand with PG Vector
✅ Model Context Protocol (MCP) support coming to mainstream databases
✅ The hidden costs of AI: Why observability and efficiency matter more than output
✅ Avoiding vendor lock-in: Why open source guarantees freedom as costs scale
✅ Data governance and training data quality for AI agents
✅ Infrastructure as code: When Kubernetes makes the most sense
✅ 2026 challenges: Data growth, cost management, and maintaining skills

Peter's Insights:
💡 "Open source always catches up with demand. What fuels innovation is the demand itself"
💡 "AI makes it easy to create code, but it won't be production-ready. That's when you need observability to spot inefficiencies"
💡 "If you're planning high resource usage, you need the freedom to shop around—that's what open source guarantees"
💡 "Database observability isn't sexy dinner conversation, but it's critical when your AI costs are sky-high"
💡 "Easy is easy at first, but vendor lock-in becomes painful when you make it big"

This conversation cuts through the AI hype to address the foundational infrastructure decisions that will make or break your scaling strategy—from training data quality to avoiding cloud platform lock-in.
Guest: Peter, Percona
Host: Jon Myer
Resources: percona.com | GitHub | Engineering Blog
Subscribe for more conversations about databases, cloud infrastructure, AI workloads, and open source strategy.
#OpenSource #Kubernetes #Databases

YouTube Timeline:
0:00 - Welcome & Introduction
0:54 - What Percona is doing with Kubernetes databases
2:42 - Why wasn't Kubernetes traditionally used for databases?
4:25 - The shift: Why organizations are adopting Kubernetes now
5:15 - Which workloads and organizations benefit most from Kubernetes
6:22 - Misconceptions about running databases on Kubernetes
7:34 - Are open source databases ready for AI workloads?
9:30 - Will AI drive new database features?
10:23 - How databases evolved with social media (and will with AI)
11:30 - Under-discussed opportunities: Training data and observability
13:37 - Why backend efficiency isn't dinner table conversation
14:32 - Spotting the right time to invest in emerging areas
16:23 - Challenges for 2026: Data growth and efficiency
17:55 - The vendor lock-in trap with proprietary databases
19:39 - Is this a technology or organizational strategy problem?
21:55 - The lost art of understanding infrastructure components
24:06 - Emerging trends: Data governance, observability, cost management
25:09 - Where to find more information about Percona
26:02 - Closing thoughts & thank you

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