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bugfender

PHP Debugging: How to Find and Fix PHP Errors

May 5, 2026 By Aleix Ventayol In Bugfender
PHP applications are often tricky to debug. A combination of loose typing, complex logic and a lack of runtime visibility can make it hard to catch errors before they reach our users. But if you’re using PHP, there’s no need to stress. This guide will equip you to understand why PHP applications break, return the wrong data or behave differently across environments. We’ll cover logs, runtime checks, Xdebug, IDE tools, request debugging, and production visibility.
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perforce

Establishing a Multicloud Data Strategy for the AI Era

May 5, 2026 By Perforce In Perforce
In my experience working with enterprise leaders, the journey to the cloud rarely follows a straight line. Many organizations set ambitious goals to move all operations to the cloud. They quickly find that certain legacy systems must remain on-premises. This reality results in a complex, hybrid multicloud environment. That means they need to adopt a new strategy for managing test data.
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How Keploy Works with Claude: Generate, Fix & Heal API Tests Automatically

May 4, 2026 By Keploy In Keploy
In this video, I walk through how Keploy works with Claude to make testing faster and more reliable for developers. You’ll see how to use Claude with Keploy to generate test cases for a new feature, based on your application context and API behavior. I also cover what happens when a Keploy test fails because of a breaking change, regression, or an expected product update.
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How to scale Gen AI to billions of rows in BigQuery at a fraction of the cost

May 4, 2026 By Google Cloud Tech In Google BigQuery
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.
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Enterprise AI Infrastructure Security Series - 7) Monitoring & Auditing

May 4, 2026 By ClearML In ClearML
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.
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ClearML

Why RBAC Isn't Enough: Real Tenant Isolation in Kubernetes AI Environments

May 4, 2026 By Adam Wolf In ClearML
Role-based access control is essential, but it’s not isolation. When multiple AI teams share a Kubernetes cluster, RBAC controls what they can do; it doesn’t control what they can reach, what they can see, or what happens when something goes wrong in a neighboring workload. This is the first post in our four-part series on Kubernetes Security for Enterprise AI Environments.
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kong

From Kafka Chaos to Control: A Practical Guide to Governing Real-Time Data

May 4, 2026 By Hugo Guerrero In Kong
Most engineering teams adopt Apache Kafka for one simple reason: it works. It scales effortlessly, it is incredibly reliable, and it powers real-time systems across almost every industry. But as your Kafka usage expands across different teams, regions, and external consumers, success creates a brand new problem. Kafka is a massive data firehose, and without the right nozzle, it quickly becomes unmanageable.
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