observability
Observability is a category skill for log analytics and trace investigation in OpenSearch. It routes you to specialized skills for querying logs to spot errors and patterns, or for investigating distributed traces to debug latency and service dependencies.
Observability helps you query logs and investigate traces in OpenSearch to identify error patterns and anomalies.
AI-generated summary based on this skill's SKILL.md
Install
opensearch-project/opensearch-agent-skills/observability · repository language: Python
git clone https://github.com/opensearch-project/opensearch-agent-skills
cp -r opensearch-agent-skills/skills/opensearch-skills/observability ~/.claude/skills/observabilitynpx skillfed install opensearch-project/opensearch-agent-skills/observabilityFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How do I query logs in OpenSearch?
Observability in OpenSearch provides log querying capabilities to help you search and filter log data. You can use OpenSearch Query Language (OQL) or Piped Processing Language (PPL) to construct queries that identify specific events, error messages, or patterns across your logs. Observability routes you to specialized skills that guide you through query syntax, index selection, and result filtering for effective log analysis.
Can observability help me analyze error patterns in my logs?
Yes. Observability is designed to help you query and analyze logs to identify error patterns and anomalies. By using log analytics features, you can spot recurring errors, track their frequency, and correlate them with other system events. Observability connects you to tools and guidance for discovering patterns automatically and understanding what's driving errors in your stack.
How do I investigate distributed traces to debug latency issues?
Observability supports distributed trace investigation to help you debug latency and understand service dependencies. You can examine trace spans to find slow operations, track requests across services, and identify where delays occur. Observability routes you to trace debugging skills that help you visualize service interactions and pinpoint performance bottlenecks in your distributed system.
What is observability's role in monitoring stack health?
Observability provides real-time monitoring of stack health and performance metrics. It helps you track system vitals, detect anomalies, and correlate logs with traces to troubleshoot complex issues. By combining log analytics, trace investigation, and metric monitoring, Observability gives you a complete view of your system's state and helps you respond quickly to problems.
How does observability correlate logs and traces?
Observability enables you to correlate logs and traces to troubleshoot complex system issues. By linking log entries to their corresponding trace spans, you can see the full context of an error or performance problem—from the initial request through all service calls and their logs. This correlation helps you understand root causes faster and debug distributed systems more effectively.
SKILL.md
rendered from the published skill — quoted content, verbatim
Observability
Category skill for log analytics and trace investigation with OpenSearch.
Skills
| Skill | Description |
|---|---|
| log-analytics | Query and analyze log data — error patterns, log volume, anomaly detection, PPL queries |
| trace-analytics | Investigate distributed traces — slow spans, error spans, service maps, agent invocations |
When to Use
| User Intent | Skill |
|---|---|
| Query logs, analyze errors, discover patterns, check log volume |
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skills/opensearch-skills/observability/SKILL.md
skills/opensearch-skills/observability/log-analytics/SKILL.md
skills/opensearch-skills/observability/log-analytics/log-analytics.md
skills/opensearch-skills/observability/ppl-reference.md
skills/opensearch-skills/observability/trace-analytics/SKILL.md
skills/opensearch-skills/observability/trace-analytics/traces.md