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What to measure in a bot cycle
Model a cycle as one logical unit of work, then record its meaningful parts. A single logical API operation may involve multiple physical HTTP requests if the client retries or follows redirects, so measuring only the overall operation can hide the source of delay.
- Cycle span: the elapsed time for one complete logical cycle.
- Local-work spans: meaningful work between requests, such as signal evaluation or preparing an order.
- HTTP client spans: one span for each outbound request attempt, with request duration and available HTTP attributes.
- Retry context: resend ordinal, response status or error, and any separately measured waiting or connection time.
This is an application of OpenTelemetry tracing concepts, not a trading-bot span model mandated by OpenTelemetry. The HTTP conventions describe request lifecycles and include http.request.resend_count for repeated requests where supported: OpenTelemetry semantic conventions for HTTP spans.
Instrument outbound requests without creating noisy metrics
OpenTelemetry defines http.client.request.duration as an HTTP client duration histogram measured in seconds. The HTTP metrics conventions recommend standard attributes; the exact fields emitted depend on your instrumentation library and version. Check the conventions and what your library actually emits before building queries or dashboards: OpenTelemetry semantic conventions for HTTP metrics.
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For each request, capture the duration and available standard context such as method, server address, response status, and error type. Add a route or path only when it is a stable template rather than a unique value for every request. For example, /orders/{order_id} is a safer metric dimension than /orders/834712.
Metric cardinality grows with the number of distinct combinations of attribute values. Putting raw URLs, order IDs, or account IDs into metric labels can create an unbounded number of combinations and increase memory costs. Prefer stable, low-cardinality dimensions for metrics; retain request-specific details in traces when appropriate. OpenTelemetry explains this distinction and the cost of cardinality in its metrics documentation.
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Make retries and rate-limit delays visible
Do not treat a logical API call as one physical request when the client can retry. Keep a span for each resend where instrumentation permits, and record http.request.resend_count so the attempt order is clear. Then inspect the response status, attempt count, and elapsed waiting time. A long logical call can result from time spent waiting between attempts rather than from one slow server response.
The OTLP Specification 1.11.0 identifies HTTP 429, 502, 503, and 504 as retryable responses. It says clients should honor Retry-After when present, and use exponential backoff if a retryable response has no such header; jitter is recommended for connection retries. This is general OTLP guidance, not a replacement for the rules or rate limits of a particular trading venue: OpenTelemetry OTLP Specification 1.11.0.
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Diagnose a slow cycle step by step
- Define the cycle boundary. Create a parent span for one complete logical cycle. Add child spans for meaningful local work and every outbound API request.
- Check one slow trace. Compare the cycle’s elapsed time with its child spans. Identify which request or local step accounts for the time, including time spent in retry waits where measured.
- Inspect a slow request. Compare its duration, destination or server address, method or stable route template, response status or error, and resend count. Compare connection duration separately if your instrumentation measures it.
- Look for time outside HTTP spans. If the recorded requests do not explain the cycle duration, examine the local-work spans between them. This narrows the investigation to work the request timings cannot explain.
- Compare with ordinary cycles. Use traces to inspect individual slow examples alongside representative cycles. Check whether the same request, response, retry pattern, or local step recurs.
- Check emitted conventions. Verify the instrumentation’s version and configuration. HTTP semantic conventions have mixed stability, and older instrumentations may keep emitting earlier conventions by default. Confirm the actual names and attributes before changing dashboards or queries.
Use traces and metrics for different views
Traces help explain an individual cycle by showing its request lifecycle and component spans. Metrics summarize request-duration distributions across many cycles. OpenTelemetry describes the distinction this way: “Unlike request tracing, which is intended to capture request lifecycles and provide context to the individual pieces of a request, metrics are intended to provide statistical information in aggregate.” See OpenTelemetry: Metrics.
Use the http.client.request.duration histogram to spot distribution shifts or long tails across calls, then use traces to inspect examples from the affected periods. Compare request-level values with cycle duration and local-step spans. The available OpenTelemetry guidance establishes neither a trading-bot performance threshold nor a ranking of exchange latency; interpret the measurements against your own workload and venue requirements.
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What telemetry can—and cannot—tell you
Request-level telemetry can distinguish a slow outbound attempt from repeated attempts and from time spent in locally instrumented work. It can also show which destination, method, response, or resend pattern is associated with slow cycles. It does not, by itself, establish why an exchange responded slowly, what rate limits apply to your account, or what latency is acceptable for a particular strategy. Those questions require the relevant venue’s API terms and context about your bot and client.
OpenTelemetry semantic conventions aim to provide common naming across telemetry signals; the documentation reports a last-modified date of September 28, 2026: OpenTelemetry semantic conventions.
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