ebpf
for kernel developers, SREs
Why this scored 0
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Signal history
7-day window (free)The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
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Dropping eBPF CPU Cost by About 90% With Memoization
Memoization cuts eBPF CPU overhead by ~90%, boosting kernel tracing performance. · for kernel engineers
lobstersCooling 2 · ebpfdevtools45d ago - 217
I Replaced kube-proxy with eBPF in Production (And Why My Monitoring Went Blind for 6 Hours)
ebpf replaced kube-proxy · for security engineers
devtoSteadysecurity84d ago - 316
Dropping eBPF CPU Cost by About 90% with Memoization (Not AI Gen)
Memoization cuts eBPF CPU usage by ~90%, improving performance for kernel workloads. · for kernel developers, SREs
hackernewsSteadydevtools44d ago - 46
How Do I Profile eBPF Code?
Optimize eBPF code · for performance engineers
hackernewsSteadydevtools93d ago