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135 results for “Trace a slow request” · 1–12
Guide · Observability ·
A queued background job gives an initial tracing project a concrete question: did the delay occur before the worker started or during execution?
Read guide: A first distributed trace from request to background jobExplainer · Observability ·
Concurrent spans, retries and selected samples explain what a trace reveals about one request and where an investigation needs another observation.
Read explainer: Reading time, concurrency and gaps in a distributed traceExplainer · Observability ·
Traces, metrics and logs answer different investigation questions. Context propagation and the Collector connect those signals from application to responder.
Read explainer: How OpenTelemetry connects a request across servicesGuide · Observability ·
Follow a slow AI request from Cloudflare to an instrumented origin, configure sampling, and verify that the trace preserves the evidence needed to investigate.
Read guide: Tracing an AI request through Cloudflare and its originExplainer · AI in production ·
ninfer-ext trades a smaller EXL3 file for more decoding work in its published tests. The saved memory matters when it lets a request fit that would otherwise fail.
Read explainer: Why ninfer-ext’s smaller EXL3 model can run more slowlyGuide · Observability ·
Tail sampling selects recorded traces by error, latency and other evidence. A checkout timeout shows how routing, waiting time and memory affect the trace a responder can retrieve.
Read guide: OpenTelemetry tail sampling through a checkout failureGuide · Observability ·
Build a latency SLI from Prometheus histogram buckets, include failed requests, and compare classic and native queries with a worked search-service example.
Read guide: Measuring a latency SLO with Prometheus histogramsNews · Platform engineering ·
Host-memory throttling can keep an inference process alive while its requests slow down. Effective kubelet settings and request deadlines explain the tradeoff.
Read news: How Kubernetes Memory QoS affects inference under pressureGuide · Observability ·
Regional failures can disappear in fleet averages. Grafana queries, population labels and linked traces help responders find the affected requests.
Read guide: Grafana dashboards for incident responseNews · Observability ·
Kubernetes attributes connect agent calls to pods, workloads and paging routes. A processor migration can break those connections while telemetry still flows.
Read news: OpenTelemetry’s Kubernetes attributes processor reaches v1Guide · Observability ·
A client-side SSE probe separates first answer text from normal completion. Fixed arrivals and outcome counts show whether a serving change delivers more useful answers.
Read guide: Measuring streaming LLM latency from first text to completed workNews · Observability ·
Apigee separates model latency and token use from MCP tool traffic. Tool filters narrow a slow-assistant investigation, while proxy policies determine which charts populate.
Read news: Apigee adds model and MCP tool performance dashboards