Systems | Development | Analytics | API | Testing

3AM Pager: When You Know the Data but Can't Search It

Ever tried searching your entire production stack for one user? Getting paged at 3 AM is bad enough. It’s worse when you only have a single username and zero visibility into what’s actually happening across your microservices. With Speedscale, you can perform full-text searches across every API call and database interaction in real-time. Stop guessing and start debugging with total context.

DLP: The Key to Secure K8s Testing #speedscale #dlp #kubernetes #devops #testing

Testing with production traffic doesn't have to be a security risk. Engineers often avoid production data because of sensitive info like passwords, tokens, and PII. But legacy test data management is too static for modern, fast-changing payloads. Enter the Speedscale Streaming DLP Engine. It automatically detects and redacts sensitive data in real time as it's captured from your environment. You get the realism of production traffic without the risk of a data breach.

Is Claude Code Spying for OpenAI? #speedscale #anthropic #openai #claude #codingagent

While analyzing network traffic, we found huge amounts of telemetry including chat snippets, being sent to statsig.anthropic.com. The irony? Statsig was recently acquired by OpenAI. In this video, we use proxymock to intercept the traffic and show you exactly what’s being sent from your terminal to Anthropic (and technically, OpenAI’s infrastructure).

Peeking Under the Hood of Claude Code

Everyone is talking about Claude Code, but few people understand the machinery running in the background. Today, we’re opening up the terminal to see how Anthropic’s coding agent manages state, runs tests, and fixes its own bugs. From the Model Context Protocol (MCP) to its unique React-based terminal UI, find out what makes Claude Code the most "senior" feeling AI assistant on the market.

Best 5 Container Image Security Platforms for 2026

By 2026, container image security will no longer be evaluated in isolation. For most organizations, the image layer has become one of the primary sources of security debt, quietly accumulating vulnerabilities that multiply across services, clusters, and environments. What has changed is not just the volume of vulnerabilities, but the cost of managing them. Faster release cycles, shorter maintenance windows, and tighter compliance expectations have pushed teams to reconsider whether traditional scanning-and-patching workflows are sustainable at scale.