Datadog × Namify
Datadog x Namify, from security blind spots to full production visibility
100% of successful exploits captured vs. less than half under legacy approach
blind to threats to full production visibility
Members read free
Unlock the full breakdown
Enter your email to open every case study in the library: the full screenshot, why it works, and the one thing worth stealing. One email unlocks all of them.
Free. No spam. Unsubscribe anytime.
You're in — enjoy the library.
Why it works
The story leads firmly with the before-state of not knowing: Namify could see logs but could not correlate them into a coherent picture of what attackers were doing. The SQL injection incident is a concrete, high-stakes scene that makes the visibility payoff tangible rather than abstract. The 100% exploit capture stat is well-placed because it quantifies the gap between blindness and sight rather than claiming a generic efficiency gain. There is a Resilience dimension here too, since the team blocked an active attack while patching, but Clarity is the dominant frame because the core win is seeing what was previously hidden.
Steal this
Use a real incident with a specific attack type and a before/after capture rate to ground abstract observability claims in a moment the reader can picture.
Click to enlarge ↗ This is editorial commentary and curation. The case study, screenshot, and all metrics are Datadog's published work; we link to the source and lead with our analysis.