'telemetry' 검색 결과

Design error handling, structured logging, and observability with OpenTelemetry (traces, metrics, logs), error classification, recovery patterns (retry with jitter, circuit breaker, bulkhead, timeout), error budgets/SLOs with burn rate alerts, and production incident triage. Use when user asks to implement error handling, logging, monitoring, observability, OpenTelemetry, error boundaries, circuit breakers, retry logic, or SLO tracking. Do NOT use for incident runbooks (use runbook-gen), vendor-specific APM setup (Datadog, Sentry agent config), or K8s debugging.

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Provides monitoring and observability best practices covering the three pillars (logs, metrics, traces), OpenTelemetry instrumentation, Prometheus/Grafana dashboards, SLO-based alerting, and APM strategies. Use when setting up monitoring, observability, prometheus, grafana, opentelemetry, alerting, tracing, logging, metrics, dashboards, SLOs, or APM.

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Capture outbound HTTP and telemetry from a CLI harness at runtime. Covers capture-channel selection (transcript file vs verbose-fetch stderr vs outbound proxy vs on-disk state), hook-driven per-event capture vs long-running session capture, JSONL output format for diff-friendly artifacts, and the observability table that maps each target to the cheapest channel that captures it. Use when a static finding needs runtime confirmation, when a payload shape is needed for a client re-implementation, or when dark-vs-live disambiguation requires watching what the binary actually sends.

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Use when monitoring, tracing, or debugging agentic workflows in production. Keywords: observability, tracing, OpenTelemetry, Langfuse, latency, token cost, loop detection, telemetry.

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Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.

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Spring Boot 4 observability with Actuator, Micrometer, and OpenTelemetry. Use when configuring health indicators, health checks, custom metrics, distributed tracing, production endpoint exposure, Kubernetes probes, Cloud Run probes, logging, or monitoring. Covers Actuator endpoint security, Micrometer Timer/Counter/Gauge patterns, OpenTelemetry span customization, liveness/readiness probe setup, and metric tag best practices.

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Use when CPU usage is high, memory grows unboundedly, goroutines leak, mutex contention shows in traces, or escape analysis suggests excess heap allocation. Triggers: net/http/pprof endpoint exposure, go tool pprof analysis, flamegraph generation, allocs vs inuse_space heap profiles, runtime/trace event timeline, mutex profiling, block profiling, goroutine dumps, GC pressure measurement. NOT for non-Go languages, distributed tracing (use OpenTelemetry skill), or production telemetry pipelines.

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Monitor reviewed Grafana telemetry and freshness evidence for IoT devices and edge fleets. Use for smart devices, home automation sensors, remote equipment, wind turbines, space hardware, device-fleet freshness, missing telemetry, and bounded edge-health comparisons.

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Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails. Use when connecting Arduino sensors to Azure, sending MQTT telemetry to IoT Hub, adding an edge gateway, or sending cloud-to-device commands.

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Instruments a web app to send telemetry to Azure Application Insights: SDK setup, configuration, and telemetry patterns. Use when the user wants to enable monitoring, request tracking, or logging to App Insights for a web application.

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Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. USE FOR: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM...

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Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best prac...

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Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.

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Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.

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Claude API (platform.claude.com) の組織管理・Admin API (sk-ant-admin)。 users, invites, workspaces, API keys, service accounts, RBAC (groups / roles), Workload Identity Federation (WIF, federation issuers / rules), Usage & Cost API, rate / spend limits, Analytics API, Compliance API (transcripts, access transparency log), Plugins API, OpenTelemetry telemetry, CMEK, zero data retention (ZDR), data residency, inference hooks。

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Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.

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Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.

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Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.

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Design and implement observability and SRE controls including SLO/SLI, OpenTelemetry instrumentation, alerting, dashboards, and incident readiness. Use when tasks involve telemetry coverage, operational reliability metrics, incident response, or runbook quality.

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LoRaWAN and sub-GHz (433 / 868 / 915 MHz) attack methodology — LoRaWAN ABP/OTAA join attack, network/session key reuse, frame counter replay, downlink injection on TTN/Helium-style networks, sub-GHz protocol replay (KeeLoq garage doors, fixed-code remotes, TPMS spoofing, smart plug telemetry), HackRF / RTL-SDR / Flipper Zero workflows, signal analysis with Inspectrum / Universal Radio Hacker, and reconstruction of proprietary packet formats. Use for LoRaWAN deployments (smart cities, asset tracking, industrial telemetry), or any wireless device using the unlicensed 433/868/915 MHz bands (garage openers, doorbells, IoT sensors, RC equipment).

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ECC로 Nasiko CLI 설치 상태를 확인하고 고정 버전의 설치와 삭제를 진행합니다. 변경 전 미리보기와 설치 동의, 삭제 대상의 관리 여부 확인을 거칩니다.

• Nasiko CLI 설치 상태 확인
• 검증된 버전의 설치 내용 사전 확인
• ECC가 관리하는 CLI 삭제

Review OmniRoute audit logs and request history from the command line. Filter records by actor, action, or time, manage access rules, and export logs or compare operational data for compliance reviews.

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• Investigate audit events for a user and time range
• Export records for a compliance review
• Create and evaluate access rules

Detect and classify unusual readings from Cognitum Seed devices, including spikes, flatlines, and drift. Review anomaly scores, recommend quarantine for scores above 0.9, and save detected patterns for future reference.

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• Investigating unusual device readings
• Checking health before advancing a firmware canary
• Triaging health alerts across a device fleet

Export recorded AI usage costs and budgets as Prometheus metrics or JSON. Feed external dashboards with totals, model tier breakdowns, session costs, and budget utilization, or send the same data to a webhook endpoint.

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• Refreshing cost metrics for Grafana or Prometheus
• Sending a one-time cost report to a webhook
• Providing budget utilization data for monitoring