Systems | Development | Analytics | API | Testing

What's New in Confluent Clients for Kafka: Python Async GA, Schema Registry Upgrades

Hey, fellow Apache Kafka developers! It’s time for another update on the Confluent client ecosystem. Following our recent architectural milestones, we’re excited to announce the release of librdkafka 2.13.0, which powers the latest versions of our Python, JavaScript, .NET, Go, and C/C++ clients. In this release, you’ll find numerous improvements to the Python experience as well as critical security and Schema Registry enhancements for everyone.

Evolve25: Event Intro & Today's Cloudera with our CEO Charles Sansbury

Cloudera CEO Charles Sansbury kicks off Evolve 25 New York by defining the "Era of Convergence" and the rise of Private AI. Discover how Cloudera is managing over 25 exabytes of data to help global leaders move from horizontal AI use cases to business-unit centric ROI. Charles details the strategic acquisitions of Octopai and Taikun, explaining how they bridge the gap between "Command & Control" and "Cloud Convenience." Learn how to operationalize high-fidelity data to drive "Everywhere AI" across hybrid environments without compromising security.

From Instinct to Operating System: How Wistia Turned Strategy Into a Scalable Machine

In the early days of a company, decisions move quickly because the founder carries most of the context. Priorities are clear. Communication is simple. The team is small enough that alignment happens without much effort. As a company grows, that stops working. More customers introduce new use cases. More products create more tradeoffs.

Automate Your Data Workflows: Connect Databox MCP to Make.com

In this video, we show you how to connect Databox to Make using the Model Context Protocol (MCP). Learn how to give your automated workflows and AI tools direct access to your live business metrics, empowering you to easily fetch context, analyze data, and build data-driven automations faster than ever. Links & Resources: About this series: This video is part of our "Chat with Your Data" series, where we explore the Databox MCP.

Demo days: Reliability Under Pressure: How to Build Self-recovering Data Pipelines

Modern data pipelines don’t fail loudly. A schema change slips through. A few bad records halt ingestion. Dashboards go stale. Engineers rerun backfills. Warehouse costs spike. Business teams begin to question the data. Pipeline instability and silent failures remain some of the biggest bottlenecks for analytics teams operating at scale.

Using the Step Library in Bitrise

See what the Bitrise Step Library can do for you with Senior Solutions Engineer Ben Boral. Instead of relying on custom scripts for functionality, you can use these off-the-shelf components to quickly build a workflow. These steps are open source, allowing you to view their code, fork them, and make changes, or you can write a custom script directly in the Workflow Editor.

How to parallelize tasks using Bitrise pipelines

Pipelines allow you to organize your CI/CD tasks into modular workflows that can run sequentially or in parallel. In this demo, Senior Solutions Engineer Ben Boral shows a simple pipeline that runs a fast linting check first, then executes two test suites in parallel to reduce wall clock time, and gates the build step on the success of those tests - speeding up the feedback loop and avoiding wasteful tasks.

Reviewing your build in Bitrise: Build Details page

In this demo, Naveen Nazimudeen, Solutions Engineer at Bitrise, explores the Build Details page and shows how to quickly get to the root cause of a failed build. He looks at key tabs like Build Logs, Tests (including flaky test detection and quarantine), Artifacts, Build Cache, and VM Monitoring for performance and out-of-memory debugging.

Cloud-Native Performance Engineering: Tools and Strategies for AWS, Azure and GCP

There’s a moment every cloud team eventually faces. Dashboards look green. CPU is stable. Memory isn’t spiking. Auto-scaling is configured. And yet, users say the system feels slow. Welcome to cloud-native performance engineering. After working across environments hosted on Amazon Web Services, Microsoft Azure and Google Cloud Platform, I’ve realised something important: Cloud doesn’t eliminate performance problems. It simply changes their shape.

From Hospitals to Home Care: Digital Innovations in Healthcare

What exactly comes to your mind when we say ‘Digital Advancements’? What’s the first thing you think of when you hear the word? Is it cloud technology? Digital transformation? Gen-AI? Blockchain? Or everything that caters to Digital Transformation as a whole? We know that the last sentence is the one you’ll prefer. But has it ever come across your mind why digital transformation solutions are taking all the limelight from different industries?