Systems | Development | Analytics | API | Testing

Release day shouldn't mean chasing answers across Jira. SmartBear Zephyr is the Jira-native testing system of record that empowers your team to deliver better software, faster. In this demo, see how Zephyr Skills for Rovo bring test management and automation insights directly into Jira. Connect planning, testing, and delivery in a single, unified workflow within the Atlassian system of work so your team can make faster, more confident release decisions.

Post-training is rapidly becoming a critical phase of enterprise AI development. To get reliable output from an AI model, organizations must align its terminology (e.g., abbreviation) to fit their specific use cases. But getting started shouldn't require heavy computing resources—you can quickly train an open-source model right on your local device. In this tutorial, we sit down with the ASAP_DPO_Finetuning Cloudera AMP to demonstrate exactly how to align a language model to specific industry standards—in this case, Oil & Gas abbreviations.

AI tools promise speed — but what does AI modernization actually mean in practice? In this video, learn how the best AI tools can accelerate application modernization without increasing risk. We cover how AI tools analyze large legacy codebases, support refactoring, and speed up modernization—when paired with expert human oversight. You’ll learn: Whether you’re exploring AI tools or already modernizing, this video shows how combining AI acceleration with experienced engineers leads to better outcomes.

For many, running generative AI over massive datasets has felt out of reach due to costs and slow processing times. Others settle for traditional ML techniques that require specialized skill sets and often deliver lower-quality results. With optimized mode for BigQuery AI functions, you can now get LLM-quality results at a fraction of the cost and at BigQuery speeds. In this video, we’ll show you how BigQuery uses model distillation and embeddings to process massive datasets, reducing query latency and token consumption.

KCP automatically generates custom Terraform modules, allowing you to provision your entire target infrastructure and networking in just a few minutes for Kafka migrations.

In this final video of our enterprise AI security series, we cover ClearML's monitoring and audit trail capabilities — the visibility layer that ties everything together. We walk through the platform's operational dashboards, task-level audit surfaces, cost attribution, and external integration points, showing how ClearML delivers live operations and compliance-ready audit out of the box.

Tired of waiting days for App Store review every time you need to ship a fix? In this video we break down how Over-the-Air (OTA) updates work for React Native apps and how Codemagic CodePush lets you push hotfixes, run experiments, and do controlled rollouts without touching the App Store or Google Play.

Discover the importance of optimization when operationalizing a data lakehouse for production workloads. We break down the journey of bringing a lakehouse into production—from choosing your data file format (Parquet) and table format (Iceberg) to plugging in your catalog and compute engines. Finally, learn why balancing ingestion jobs with critical table management services makes all the difference when moving beyond single-node workloads.

Make your Honeybadger Insights system dashboards dynamic with parameterized widget queries. In this walkthrough, Ben shows how to take a dashboard built from data reported by the Honeybadger CLI agent — load average, memory used, disk used across a fleet of hosts — and filter the whole view down to a single host with one parameter. What you’ll see: One dashboard, many views — no duplicate widgets, just a shareable URL.