Operations | Monitoring | ITSM | DevOps | Cloud

Zendesk is a goldmine of customer insights, but extracting that value from its usage is not simple. Teams trying to export data from Zendesk often run into paywall restrictions, API rate limits, and third-party tools that promise simplicity but falter at scale. For organizations integrating support data into BI platforms, migrating systems, or automating reporting pipelines, these challenges stall analytics and strategy.

The OpenTelemetry Astronomy Shop is a widely used demonstration environment designed to illustrate the concepts and practical implementation of observability in distributed systems. Built as a microservice-based e-commerce application, the demo provides developers with a near real-world environment where they can explore how telemetry data—metrics, logs, and traces—can be collected, processed, and visualized.

Industrial data strategy often feels like a choice: keep legacy systems or replace them outright. But neither extreme is ideal. Full replacements are disruptive and costly, while avoiding change leaves businesses stuck with tools that limit growth. The better path is incremental. Each organization has different needs, and modernization works best when you build on proven systems while adding new capabilities.

Database latency rarely starts in your app layer because it’s almost always a query doing more work than it should. Metrics tell you when that happens, but slow-query logging tells you which statement did it and how. That’s gold for tracking down missing indexes, inefficient filters, or accidental full scans. Pair the logging with a some lightweight counter metrics, and you get both an early warning and a clear path to a fix.

John Q Martin, Technology & Alliances Partner Manager at Redgate, covers 10 mistakes he's made when migrating databases to the cloud - and the strategies he now implements to avoid them happening again. But first, John explains exactly why databases are the hardest part of cloud migration.

Redgate Test Data Manager’s September release introduces AI dataset generation, streamlined database connectivity, and improved validation. These updates eliminate manual work and configuration errors while maintaining security and data quality standards.