Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Pyroscope + Proxymock to Solve Performance Problems
This video provides a step-by-step demonstration of how to record an application's real-world traffic and generate an automated sandbox environment for debugging and testing.
Cut AI coding defects by 33% #mcpserver #aicoding #aiagents #grafana #aitools
We spend thousands of dollars "token maxing" and running endless debugging cycles just to walk our LLMs through a problem. But is the AI actually failing, or are we just withholding the right environment? Giving your AI assistant its own sandbox to test hypotheses might just be the missing link in your development workflow.
Flamegraphs Find It. Replay Proves It.
I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU.
Stop Writing Log Lines: Use eBPF to Catch PII and Credentials
Tired of out-of-control log expenses and manual logging discipline? Discover next-generation observability with Speedscale. By using eBPF to record full-fidelity data right off the wire, you can instantly run full-text searches, track down leaking PII, and securely map out credentials across HTTP, Postgres, gRPC, and more—all without writing a single log line. Learn more: speedscale.com.
Fighting AI Slop: The Missing Ingredient for Clean Code #coding #AI #devops #cleancode #aiagents
Fighting AI Slop: The Missing Ingredient for Clean Code.
eBPF: Preventing Garbage HTTP Payloads When Reading Kernel Scatter-Gather Buffers
Recently someone on our team opened a traffic snapshot and found an HTTP request that was captured with our eBPF capture agent, nettap. Our protocol dissector parsed most of the response correctly, but that correctness ended once the response headers were processed. What they ended up with was a recording of an HTTP request/response where the response body was just an incorrect collection of garbage binary data when it should have been JSON text.
The Best Model Is a Routing Decision
I spent the day at NVIDIA thinking I’d be learning about all the newest models and RAM throughput achievements. Instead, a version of the future started to crystallize where AI really is good enough, pervasive and cheap(er). Let me share some of my observations and conclusions.