Select and configure head and tail sampling strategies for tracing costs.
npx skills add https://github.com/jagreehal/autotel --skill tune-sampling
Please help me install this Agent Skill. Skill: tune-sampling Source: https://github.com/jagreehal/autotel/tree/main/packages/autotel/skills/tune-sampling Command: npx skills add https://github.com/jagreehal/autotel --skill tune-sampling
This Skill provides strategies to manage tracing costs and visibility by selecting appropriate head and tail sampling methods, ensuring critical data is retained without incurring excessive expenses.
Use the tune-sampling skill to determine the most effective sampling approach for your observability needs, balancing cost and data retention.
High-intent search queries and answers about installing and using this skill.
Head sampling makes early trace collection decisions to save resources, while tail sampling evaluates complete traces to retain critical data. This Skill provides strategies to balance tracing cost and data quality across diverse application scenarios using both methods.
You can reduce observability costs by applying intelligent sampling strategies to high-volume API services. This Skill guides you in configuring head and tail sampling methods to balance trace visibility with your specific budget constraints.
Yes, customer-controlled sampling allows you to incorporate customer debug headers into sampling decisions. This Skill explains how to enable customers to request full trace capture on demand while maintaining standard cost-management sampling for general traffic.
AI-aware sampling is useful when you need to incorporate AI-generated spans into your trace collection decisions. This Skill covers how to apply these sampling methods in distributed systems to ensure meaningful observability data is retained.
Choosing the best tracing sampling strategy requires evaluating cost, performance, and data importance. This Skill helps you select and configure appropriate head or tail sampling approaches to optimize data quality and manage resource expenses in distributed systems.
AgentientImplement head-based, tail-based, and hybrid log and trace sampling.
weirdgmeInstrument distributed systems with OpenTelemetry and correlate logs, metrics, and traces.
TheBushidoCollectiveInstrument applications with Sentry transactions, spans, and distributed tracing.
roanbrasilTrace LLM calls and track token costs across LangSmith, LangFuse, and Phoenix.
