Life Is But A Stream

Migrating an entire bank's infrastructure without losing a single transaction sounds impossible. Yet, OCBC successfully modernized  their event-driven architecture across Singapore, Malaysia, and Hong Kong with zero data loss.

In this episode, George Goh (Executive Director at OCBC) joins Joseph Morais and Sami Amed (Staff Solutions Engineer at Confluent) to pull back the curtain on a massive data streaming migration, how the team executed a flawless migration of thousands of producers and consumers in a single weekend. 

George discusses how OCBC built a resilient, multi-region data streaming platform that maintains performance even during data center failures, all while meeting strict regulatory requirements in one of the world's top financial hubs.

You'll Learn:

How OCBC moved thousands of microservices with zero data loss in six hours

Why stretched clusters and capacity planning are critical for disaster recovery

How monitoring and developer experience drive platform adoption at scale

From capacity planning for disaster recovery to developer experience improvements, this conversation reveals the architectural decisions, operational discipline, and partnership that made zero data loss possible at enterprise scale.

About the Guest: 
George Goh leads the Cloud Middleware Engineering and Services team at OCBC Group, which provides OpenShift, Apache Kafka®, and Redis across all locations where the bank operates. Previously serving senior services and consulting roles at Red Hat and VMware, he now relishes the added challenge of defining technologies within the bank and building talented teams to run them.

Guest Highlights:

"We moved thousands of microservices over from the old platform to the new platform over the course of maybe 12 hours over a weekend. We got Singapore, Malaysia, Hong Kong, everybody on board and moved at the same time with zero data loss."

"It was done in six hours, but it took six months to plan."

"I was focused on a three letter word, BIM—benchmarks, integration and migration. I was saying that three times a day, three days a week until everybody knew what I was talking about."

Chapters:

[01:41] Why Singapore Is a Global Finance Hub

[03:47] Data Streaming Goodness 

[05:09] Building a Resilient Multi-Site Architecture

[06:59] The Reality of Migration Planning

[09:49] Capacity Benchmarks & Day Two Operations

[12:33] The Shift from Buy to Build

[19:20] Scaling Adoption Across the Organization

[21:50] Beyond the Stream

[25:43] The Impact: Thousands Migrated Overnight

[28:00] Best Practices & High Availability

[30:58] Future Vision: Less Overhead, More Innovation

[33:37] Quick Bytes

[35:24] Joseph’s Top 3 Takeaways

Dive Deeper into Data Streaming:

EP1—Stream On: Unleashing Innovation With Data Streaming | Life Is But A Stream

EP2—Processing Without Pause: Continuous Stream Processing and Apache Flink® | Life Is But A Stream

EP3—The Connective Tissue: Shift Left to Turn Data Chaos to Clarity | Life Is But A Stream

Links & Resources:

Connect with Joseph: @thedatagiant

Joseph’s LinkedIn: linkedin.com/in/thedatagiant

George’s LinkedIn: linkedin.com/in/georgegoh

Learn more at Confluent.io

UTM link for simplecast: https://www.confluent.io/life-is-but-a-stream-show/?utm_source=simplecast&utm_medium=podcast&utm_id=tm.content_life-is-but-a-stream-busie

UTM link for YouTube: https://www.confluent.io/life-is-but-a-stream-show/?utm_source=youtube&utm_medium=video&utm_id=tm.content_life-is-but-a-stream-busie



Our Sponsor:  

Your data shouldn’t be a problem to manage. It should be your superpower. The Confluent data streaming platform transforms organizations with trustworthy, real-time data that seamlessly spans your entire environment and powers innovation across every use case. Create smarter, deploy faster, and maximize efficiency with a true data streaming platform from the pioneers in data streaming. Learn more at confluent.io.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What does it take to run real-time safety checks on every prompt sent to an AI companion platform serving 60 million monthly users? For Character.AI, the answer was rethinking the entire data pipeline—without rethinking the budget. By building on WarpStream's Kafka-compatible, bring-your-own-cloud architecture, the team found a way to process massive prompt and response payloads in near real time, at a fraction of the cost of traditional Kafka.

 

In this episode, Maor Bril, Chaos Catalyst & Technical Staff Member at Character.AI, joins Joseph Morais to break down how WarpStream's agent-based, object-storage-backed design let a small team capture full prompts and responses for safety classification and model A/B testing, route client and server events without added infrastructure, and even build a custom feature store with Bento-powered Managed Pipelines—all while running on otherwise idle GPU-node CPUs.

You'll Learn:

How a Kafka-compliant, BYOC architecture cut Character.AI's streaming costs by 85–90%

Why trading a few seconds of latency unlocked massive savings and simpler operations

How to repurpose idle GPU-node compute to run data pipelines at zero marginal cost

Chapters:

[00:11] Character.AI Intro 

[02:04] Data Streaming Goodness 

[18:22] Beyond the Stream

[26:14] Quick Bytes

[30:06] Joseph’s Top Takeaways

About the Guest: 

Maor Bril is Chaos Catalyst & Technical Staff Member at Character.AI, where he has spent over two years leading infrastructure and product efforts beyond core one-on-one chat, including data pipelines, labs initiatives, and new product lines. He originally built much of Character.AI's data infrastructure and continues to work across platform, safety, and experimentation systems supporting the company's AI entertainment platform.

Guest Highlight:

"WarpStream is the most boring product I've ever got to work with. In infra, that's the biggest compliment you can ever give someone. It just works."

Dive Deeper into Data Streaming:

EP1—Stream On: Unleashing Innovation With Data Streaming | Life Is But A Stream

EP2—Processing Without Pause: Continuous Stream Processing and Apache Flink® | Life Is But A Stream

EP3—The Connective Tissue: Shift Left to Turn Data Chaos to Clarity | Life Is But A Stream

Get Connected:

Connect with Joseph: @thedatagiant

Joseph’s LinkedIn: http://linkedin.com/in/thedatagiant

Maor’s LinkedIn: https://www.linkedin.com/in/maorbril/

Our Sponsor:  

Your data shouldn’t be a problem to manage. It should be your superpower. The Confluent data streaming platform transforms organizations with trustworthy, real-time data that seamlessly spans your entire environment and powers innovation across every use case. Create smarter, deploy faster, and maximize efficiency with a true data streaming platform from the pioneers in data streaming. Learn more at confluent.io.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Real-time data and AI are converging—and companies that have already solved the data pipeline problem are pulling ahead fast. Wix processes over 40 billion interactions every day across hundreds of millions of websites, and the architecture behind that scale didn't happen by accident. It was built, lane by lane, around the principle that your upstream data must be at least as fast as your fastest use case.

In this episode, Josef Goldstein, Head of R&D for the Big Data Platform at Wix.com, joins Joseph Morais to unpack how Wix evolved from a batch-based Hadoop architecture to a fully streaming-first platform on Confluent Cloud. The conversation covers Wix's multi-lane data architecture—from petabyte-scale data lakes to sub-second algorithmic decisions—how they approach data contracts and governance at distributed scale, and why Confluent Freight Clusters became a strategic unlock for cost and elasticity. Josef also explains how Wix is now wiring real-time stream processing directly into context layers for agentic AI systems.

You'll Learn:

How to architect a multi-lane data streaming system that serves use cases from sub-second ML inference to petabyte-scale analytics

Why upstream data quality, governance, and metadata are the real prerequisites for production-grade agentic AI

How Confluent Freight Clusters reduced costs and unlocked elastic scale for Wix's highest-volume, latency-tolerant data streams

About the Guest: 
Josef Goldstein is an Israeli software engineer and engineering manager specializing in big data infrastructure and real-time analytics. With over 15 years of experience in developing data-intensive SaaS applications, Goldstein has built and led high-performing teams in the technology sector. Since 2021, he has served as the Head of R&D for Wix's Big Data and Analytics Platform, where he oversees the infrastructure and tools enabling data-driven decisions for the company's users and operations.

Guest Highlight:

"You understand that you need to be on the upstream side of the house as fast as your fastest lane. Otherwise, none of that is possible."

Chapters:

[00:00] Wix.com Overview and Customer Base

[07:08] Segment 1: Data Streaming Goodness

[24:24] Segment 2: Beyond the Stream

[45:37] Segment 3: Quick Bytes

[47:08] Joseph’s Top Takeaways

Dive Deeper into Data Streaming:

EP1—Stream On: Unleashing Innovation With Data Streaming | Life Is But A Stream

EP2—Processing Without Pause: Continuous Stream Processing and Apache Flink® | Life Is But A Stream

EP3—The Connective Tissue: Shift Left to Turn Data Chaos to Clarity | Life Is But A Stream

Get Connected:

Connect with Joseph: @thedatagiant

Joseph’s LinkedIn: http://linkedin.com/in/thedatagiant

Josef’s LinkedIn: https://www.linkedin.com/in/josefgoldstein/

Our Sponsor:  

Your data shouldn’t be a problem to manage. It should be your superpower. The Confluent data streaming platform transforms organizations with trustworthy, real-time data that seamlessly spans your entire environment and powers innovation across every use case. Create smarter, deploy faster, and maximize efficiency with a true data streaming platform from the pioneers in data streaming. Learn more at confluent.io.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Most enterprises don't need to build AI models from scratch—they need to put AI to work. That requires a data foundation that is real-time, reliable, and ready to serve intelligent systems at scale.

In this episode, Varun Jasti, Solution Architect at AWS, joins host Joseph Morais to explore how AWS and Confluent are co-architecting the infrastructure layer for agentic AI. Varun draws a direct parallel between multi-agent system design and microservice architecture—explaining why Apache Kafka® on Confluent Cloud is the natural backbone for agent-to-agent coordination, stateful memory, and scalable provisioning.

You'll Learn:

Why AI value depends on data accessibility—not model sophistication alone

How multi-agent architectures mirror microservice design, and why Kafka is the connective tissue

How the AWS and Confluent partnership abstracts AI infrastructure so teams can focus on outcomes

About the Guest: 
Varum Jastim is a Solution Architect at AWS, and an AI/ML enthusiast that likes building on the cloud to architect solutions for AWS Partners who need to adhere to federal compliances and regulations. His areas of interest are Computer Vision and Generative AI.

Guest Highlight:

"The average company is not an AI lab. Their job is not to say, 'How do I create a great AI model?' Their job is, how do I use AI to create business value? And I believe that's the core mission of AWS and Confluent to get together and figure out how we make AI accessible to the customer." 

Chapters:

[01:23] Why AI Feels Different

[04:07] What Makes AI So Provocative

[07:46] Amazon Bedrock AgentCore Explained

[09:20] Real-Time Context Engine

[11:57] Scaling Multi-Agent Systems

[16:01] Where to Run Agents

[18:36] Security and Guardrails

[26:24] Global GenAI Architecture

[29:21] What's Next at AWS

Dive Deeper into Data Streaming:

EP1—Stream On: Unleashing Innovation With Data Streaming | Life Is But A Stream

EP2—Processing Without Pause: Continuous Stream Processing and Apache Flink® | Life Is But A Stream

EP3—The Connective Tissue: Shift Left to Turn Data Chaos to Clarity | Life Is But A Stream

Get Connected:

Connect with Joseph: @thedatagiant

Joseph’s LinkedIn: http://linkedin.com/in/thedatagiant

Varun’s LinkedIn: https://www.linkedin.com/in/varun-jasti-1a21b21b9/

Our Sponsor:  

Your data shouldn’t be a problem to manage. It should be your superpower. The Confluent data streaming platform transforms organizations with trustworthy, real-time data that seamlessly spans your entire environment and powers innovation across every use case. Create smarter, deploy faster, and maximize efficiency with a true data streaming platform from the pioneers in data streaming. Learn more at confluent.io.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The average grocery store has 65 to 80% inventory accuracy. One in 10 products is out of stock at any moment. For an industry operating on razor-thin margins and competing against digital-native challengers, that data gap is existential.

In this episode, Kevin Johnson, CEO of Focal Systems, sits down with Joseph to explore how his team is using computer vision, data streaming, and stateful stream processing to close that gap at scale.

Kevin walks through how Focal moved from brittle, homegrown pipelines to a fully managed streaming platform—unlocking new use cases including virtual store walk, planogram compliance, and real-time theft detection—all without the operational overhead of managing infrastructure.

You'll Learn:

How Focal Systems uses stateful stream processing with Apache Flink® to convert millions of shelf images into real-time store actions

Why homegrown data pipelines fail at scale—and how managed infrastructure freed Focal's engineers to focus on innovation

How real-time data unlocked unplanned use cases, from virtual store walk to computer-vision-driven theft detection

About the Guest: 
Kevin Johnson, CEO of Focal Systems, has 30 years of experience successfully starting, growing, and managing businesses domestically and internationally. Particular emphasis on business transformation — changing companies from slow to high growth, money-losing to profitable, industry-lagging to industry-leading, and from founder leadership to professional management.

Guest Highlight:

"If you built this rickety data pipeline—congratulations. That's your job for the rest of your life is to keep that thing operating. Or would you like to work on this new thing and, you know, maybe something else and value added? And so I think that's where you get full buy-in. That's where you hit the tipping point. It's like, oh wait, I could outsource this and I can go focus on the new. If you can outsource the things that somebody else has done and done really well, and it scales and it's robust, it's an easier decision. If you've got interesting problems to work on, they'll take it, you know?"

Chapters: 

[01:07] Guest Introduction + Focal Systems Overview 

[10:19] Segment 1: Data Streaming Goodness

[16:08] Segment 2: Beyond the Stream 

[25:56] Segment 3: Quick Bytes

[31:38] Segment 4: Joseph’s Top Takeaways

Dive Deeper into Data Streaming:

EP1—Stream On: Unleashing Innovation With Data Streaming | Life Is But A Stream

EP2—Processing Without Pause: Continuous Stream Processing and Apache Flink® | Life Is But A Stream

EP3—The Connective Tissue: Shift Left to Turn Data Chaos to Clarity | Life Is But A Stream

Get Connected:

Connect with Joseph: @thedatagiant

Joseph’s LinkedIn: linkedin.com/in/thedatagiant

Kevin’s LinkedIn: linkedin.com/in/kevinhjohnson

Resources:

Learn more about Focal Systems: https://focal.systems/

Learn more at Confluent.io

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.