Systems | Development | Analytics | API | Testing

CVE, CVSS, and the Mistake Most Teams Keep Making

Modern software systems are exposed to a constant stream of disclosed vulnerabilities. Thousands of new issues are published every year across operating systems, runtimes, libraries, and frameworks. Treating all of them as equally urgent is not realistic, and trying to do so often leads to ineffective security work. To manage this volume, the security community relies on two foundational mechanisms: CVE and CVSS.

How To Use Copilot In Software Testing: A Practical Guide For Testers

Software testing is critical in assessing the quality of apps, testers oftentimes have to deal with limited resources when it comes to creating tests, as well as repetitively creating tests for all feature coverage. These factors lead to a significant reduction in both the speed of development and efficiency in the testing process.

Tableau MCP vs. Databox MCP: Enterprise Control vs. AI-Native Speed

The Model Context Protocol (MCP) is reshaping business intelligence. It provides the technical standard for a new class of generative BI tools that let you talk to your data. The engine behind this revolution is the MCP server—the essential component that connects AI models (like Claude or Cursor) to a company’s data. This article examines Tableau’s official MCP server vs. Databox MCP to help you decide between a traditional BI add-on and an AI-native headless platform.

Activation is broken: why most SaaS teams get it wrong and how to fix it

If activation feels fuzzy in your company, you’re not alone. In fact, Rodrigo Fernandez has seen the same pattern across hundreds of SaaS businesses: growth teams get handed “increase activation,” but no one actually owns what activation means, how it’s defined, or how it’s measured. And when activation isn’t owned, it becomes a committee decision. It turns into noise. And your product data stops being useful.

Realtime steering: interrupt, barge-in, redirect, and guide the AI

Start typing, change your mind, redirect the AI mid-response. It just works. That is the promise of realtime steering. Users expect to interrupt an answer, correct its direction, or inject new instructions on the fly without losing context or restarting the session. It feels simple, but delivering it requires low-latency control signals, reliable cancellation, and shared conversational state that survives disconnects and device switches.

Moving Our Observability Data Collector from Sidecars to eBPF

For years, the Kubernetes sidecar pattern has been a practical way to capture observability data. Running a collector alongside each application pod gave us deep visibility into traffic, including full request and response payloads across supported protocols. However, as cloud-native environments have grown more complex, the limitations of sidecars—such as resource overhead, operational complexity, and scaling challenges—have become more apparent.
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Peeking Under the Hood with Claude Code

Claude is one of the go-to AI-native code editors for developers. Because it's a simple chatbot interface housed inside a familiar CLI, it provides a pretty smooth path between traditional IDEs and agentic AI. But what's actually happening behind the scenes when you ask it to write code, generate a test, or debug an issue? Who and what is it talking to behind the scenes? Can I prevent data leakage or do I need to add another layer to my tin foil hat? To answer these questions, I used proxymock to inspect the network traffic flowing from the Claude IDE.

ROI of Digital Twin Testing: Cut Testing Costs by 50%

When engineering leaders review their cloud bills, they often focus on production costs—the infrastructure serving real users, processing real transactions, generating real revenue. But there’s a shadow cost lurking in every cloud environment that often goes unnoticed until it becomes painful: non-production infrastructure.

Talk to Your Test Data: Improve Test Data Management with the Perforce Delphix MCP Server

Many technology leaders face a persistent bottleneck: delivering the right data to the right people at the right time. Despite significant investments in test data management and automation, developers often wait for database refreshes, compliance checks, and answers from infrastructure teams. These delays directly reduce development velocity. A recent shift has occurred in how developers work. AI agents, such as Claude Desktop and Cursor, are now essential coding tools.