To find what is slowing a trading-bot cycle, trace the whole cycle and give each outbound HTTP request and meaningful local step its own span. Compare the request spans with the cycle’s total duration: repeated requests and backoff point to retry-related delay, while unexplained gaps point to work happening locally or time not captured by your instrumentation. Use traces to inspect individual slow cycles and duration histograms to spot patterns across many cycles.
What to measure in one bot cycle
A logical trading-bot operation may generate several physical HTTP requests—for example, if a client retries or follows a redirect. Treating all of them as one API-call duration can hide where time went.
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- Define a logical cycle. Create a parent span for one complete cycle. Add child spans for meaningful local work and for each outbound API operation. This is a practical application of tracing concepts, not a span model prescribed specifically for trading bots.
- Instrument each outbound request. Record its duration, destination, HTTP method, response status or error, and any available low-cardinality route template. OpenTelemetry defines
http.client.request.durationas a histogram measured in seconds; consult the HTTP metrics conventions for the relevant attributes and instrumentation details. - Preserve physical attempts. Give each resend its own span where instrumentation supports it, and record
http.request.resend_count. This lets you distinguish one slow request from several attempts plus time spent waiting between them. See OpenTelemetry’s HTTP span conventions. - Compare spans with the parent cycle. Identify which child spans account for elapsed time. If request spans explain most of a slow cycle, inspect their destination, method, status or error, duration, and resend count. If they do not, inspect local-step spans and any time gaps that your instrumentation does not cover.
How to tell whether requests or local work dominate
Start with an individual slow trace. Compare the cycle’s total duration against the durations and ordering of its child spans. An API span that dominates the timeline is evidence to investigate that request; a cycle that remains slow without a correspondingly long HTTP span directs attention to local work or missing instrumentation. This is a diagnostic method, not a published performance result or proof of a specific cause.
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- Duration: the HTTP client request duration, in seconds when using
http.client.request.duration. - Destination and operation: server address, method, and a stable route template if one is genuinely available.
- Outcome: response status or error type.
- Attempts: resend ordinal and the number and spacing of attempts.
- Other measured time: connection duration, if your instrumentation reports it separately.
Compare slow traces with ordinary cycles from the same bot and operating context. The cited OpenTelemetry sources do not establish a universal acceptable trading-bot cycle time, exchange ranking, or venue-specific latency target.
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How retries and rate limits can add latency
A logical API call can include multiple physical requests. Inspect every attempt and the time between attempts rather than treating the logical call as a single server response. A long total may reflect repeated requests or retry waiting, not just execution time for one request.
The OTLP Specification 1.11.0 identifies HTTP 429, 502, 503, and 504 responses as retryable. Its guidance says to honor Retry-After when present; when a retryable response lacks that header, it specifies exponential backoff. Jitter is recommended for connection retries. This is OTLP guidance, not a substitute for an exchange’s API documentation or terms. Check the venue and client library’s actual retry behavior before changing policy.
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Traces help explain one cycle by showing its request lifecycle and individual pieces. Metrics summarize behavior across many requests, making duration histograms useful for spotting shifts or long tails that merit trace inspection. 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 the OpenTelemetry metrics documentation.
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Check what your instrumentation actually emits
HTTP semantic conventions have mixed stability, and some older instrumentation retains previously emitted conventions by default. Before building queries or changing dashboards, verify the library version and configuration and inspect the attributes and metric names it emits. OpenTelemetry explains its shared naming approach in its semantic conventions documentation.
The exact instrumentation, retry settings, venue rate limits, and alert thresholds depend on the bot’s language, API client, exchange, and telemetry backend. The OpenTelemetry references provide a common vocabulary and general guidance, not exchange-specific rules or tested performance targets.
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