What if # AI could fix the blind spots in distributed tracing? A cognitive self-adaptive system using Jaeger & Open Tracing goes way beyond the usual 1-5% sampl
An AI-powered system aims to improve distributed tracing by addressing the limitations of traditional sampling methods. This cognitive self-adaptive system leverages Jaeger and Open Tracing to go beyond the typical 1-5% sampling rates, offering a more comprehensive view of system performance. AI
IMPACT This approach could lead to more efficient and comprehensive monitoring of complex software systems.