Stanislav Hejny
101 lines
4.7 KiB
Python
101 lines
4.7 KiB
Python
from opentelemetry import metrics, trace
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from opentelemetry.sdk.metrics import MeterProvider
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from opentelemetry.sdk.trace import TracerProvider, Tracer
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from opentelemetry.sdk.trace.export import BatchSpanProcessor
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from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
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from prometheus_client import start_http_server
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from opentelemetry.exporter.prometheus import PrometheusMetricReader
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from opentelemetry.sdk.resources import SERVICE_NAME, Resource
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import os
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def initialize_trace(app = None, name = None) -> Tracer:
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# Resource can be required for some backends, e.g. Jaeger or Prometheus
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# If resource wouldn't be set - traces wouldn't appear in Jaeger.
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# The 'name' value is the name shown in Jaeger.
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resource = Resource(attributes={
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SERVICE_NAME: name if name else os.environ.get('APPLICATION_NAME', 'Python App')
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})
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#
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# 1. Tracing (Jaeger) configuration
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# ----------------------------------
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#
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# Configure the OTLP exporter (or HTTP exporter the same way)
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# the recommended configuration is via environment variables. The mandatory ones:
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# OTEL_EXPORTER_OTLP_ENDPOINT: "http://jaeger:4317"
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# OTEL_EXPORTER_OTLP_INSECURE: "true"
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# for more see here: https://opentelemetry-python.readthedocs.io/en/latest/exporter/otlp/otlp.html
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# alternatively these values can be provided as input values to OTLPSpanExporter() constructor.
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#
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# otlp_exporter = OTLPSpanExporter()
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# or provide endpoint explicitly, as
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otlp_exporter = OTLPSpanExporter(endpoint="http://jaeger:4317")
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#
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# Initialize the tracer provider. This is abstract API call.
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# The actual implementation is given by the included dependency
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# The opentelemetry default is the OTLP trace provider.
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provider = TracerProvider(resource=resource)
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# Add the exporters to the batch span processor
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span_processor = BatchSpanProcessor(otlp_exporter)
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provider.add_span_processor(span_processor)
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# Sets the global default tracer provider
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trace.set_tracer_provider(provider)
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#
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# logging.info(' * Instrumenting application..... ')
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# if Flask, then use:
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# FlaskInstrumentor().instrument_app(flask_app)
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# if FastAPI, then use
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# FastAPIInstrumentor.instrument_app(app)
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#
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# Python Flask is now automatically instrumented to export details of each REST endpoint call.
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# For Django based app, use 'opentelemetry-instrumentation-django' import instead. see here:
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# https://opentelemetry-python.readthedocs.io/en/latest/examples/django/README.html for example
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#
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# If the used library has no instrumentation support in opentelemetry.io, then the trace
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# can be started manually. In this code,
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# 'trace' should be global shared variable, initialized once per application (see tracing.py)
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# 'tracer' can be shared global or local variable, application can use multiple uniquely
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# named tracers, Jaeger will group the generated traces by the name of the tracer
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# that was used to start the Span. See this example code:
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#
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# tracer = trace.get_tracer(name)
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#
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# @app.route("/server_request")
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# def server_request():
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# with tracer.start_as_current_span(
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# "server_request",
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# context=extract(request.headers),
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# kind=trace.SpanKind.SERVER,
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# attributes=collect_request_attributes(request.environ),
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# ):
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# # do the work here, like logging.info something and return response
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# logging.info(request.args.get("param"))
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# return "served"
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#
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# Note:
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# the otlp code looks for HTTP header named 'traceparent' that, if present, should contain
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# the otlp parent span identification, and the span created here will be made a child
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# of that parent span, indicating visually the progression of requests via different services
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# for as long as the current span is provided in the traceparent header to next service.
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# 2. Metrics (Prometheus) configuration
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# -------------------------------------
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#
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# Start Prometheus client
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start_http_server(port=9464, addr="localhost")
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# Initialize PrometheusMetricReader which pulls metrics from the SDK
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# on-demand to respond to scrape requests (unlike Jaeger, which worls with push model - application
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# pushes traces when those become available to Jaeger's collector. Prometheus works with pull model
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# where it periodically polls pre-configured and/or discovered endpoints for metrics.
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reader = PrometheusMetricReader()
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provider = MeterProvider(resource=resource, metric_readers=[reader])
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metrics.set_meter_provider(provider)
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return trace.get_tracer(name)
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