add telemetry doc (opea-project#536)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

comps/cores/telemetry/README.md

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+# Telemetry for OPEA
+
+OPEA Comps currently provides telemetry functionalities for metrics and tracing using Prometheus, Grafana, and Jaeger. Here’s a basic introduction to these tools:
+
+![opea telemetry](https://raw.githubusercontent.com/Spycsh/assets/main/OPEA%20Telemetry.jpg)
+
+## Metrics
+
+OPEA microservice metrics are exported in Prometheus format and are divided into two categories: general metrics and specific metrics.
+
+General metrics, such as `http_requests_total `, `http_request_size_bytes`, are exposed by every microservice endpoint using the [prometheus-fastapi-instrumentator](https://github.com/trallnag/prometheus-fastapi-instrumentator).
+
+Specific metrics are the built-in metrics exposed under `/metrics` by each specific microservices such as TGI, vLLM, TEI and others. Both types of the metrics adhere to the Prometheus format.
+
+### General Metrics
+
+To access the general metrics of each microservice, you can use `curl` as follows:
+
+```bash
+curl localhost:{port of your service}/metrics
+```
+
+Then you will see Prometheus format metrics printed out as follows:
+
+```yaml
+HELP http_requests_total Total number of requests by method, status and handler.
+# TYPE http_requests_total counter
+http_requests_total{handler="/metrics",method="GET",status="2xx"} 3.0
+http_requests_total{handler="/v1/chatqna",method="POST",status="2xx"} 2.0
+...
+# HELP http_request_size_bytes Content length of incoming requests by handler. Only value of header is respected. Otherwise ignored. No percentile calculated.
+# TYPE http_request_size_bytes summary
+http_request_size_bytes_count{handler="/metrics"} 3.0
+http_request_size_bytes_sum{handler="/metrics"} 0.0
+http_request_size_bytes_count{handler="/v1/chatqna"} 2.0
+http_request_size_bytes_sum{handler="/v1/chatqna"} 128.0
+...
+```
+
+### Specific Metrics
+
+To access the metrics exposed by each specific microservice, ensure that you check the specific port and your port mapping to reach the `/metrics` endpoint correctly.
+
+For example, you can `curl localhost:6006/metrics` to retrieve the TEI embedding metrics, and the output should look like follows:
+
+```yaml
+# TYPE te_embed_count counter
+te_embed_count 7
+
+# TYPE te_request_success counter
+te_request_success{method="batch"} 2
+
+# TYPE te_request_count counter
+te_request_count{method="single"} 2
+te_request_count{method="batch"} 2
+
+# TYPE te_embed_success counter
+te_embed_success 7
+
+# TYPE te_queue_size gauge
+te_queue_size 0
+
+# TYPE te_request_inference_duration histogram
+te_request_inference_duration_bucket{le="0.000015000000000000002"} 0
+te_request_inference_duration_bucket{le="0.000022500000000000005"} 0
+te_request_inference_duration_bucket{le="0.00003375000000000001"} 0
+```
+
+These metrics can be scraped by the Prometheus server into a time-series database and further visualized using Grafana.
+
+Below are some default metrics endpoints for specific microservices:
+
+| component     | port  | endpoint | metircs doc                                                                                             |
+| ------------- | ----- | -------- | ------------------------------------------------------------------------------------------------------- |
+| TGI           | 80    | /metrics | [link](https://huggingface.co/docs/text-generation-inference/en/basic_tutorials/monitoring)             |
+| milvus        | 9091  | /metrics | [link](https://milvus.io/docs/monitor.md)                                                               |
+| vLLM          | 18688 | /metrics | [link](https://docs.vllm.ai/en/v0.5.0/serving/metrics.html)                                             |
+| TEI embedding | 6006  | /metrics | [link](https://huggingface.github.io/text-embeddings-inference/#/Text%20Embeddings%20Inference/metrics) |
+| TEI reranking | 8808  | /metrics | [link](https://huggingface.github.io/text-embeddings-inference/#/Text%20Embeddings%20Inference/metrics) |
+
+## Tracing
+
+OPEA use OpenTelemetry to trace function call stacks. To trace a function, add the `@opea_telemetry` decorator to either an async or sync function. The call stacks and time span data will be exported by OpenTelemetry. You can use Jaeger UI to visualize this tracing data.
+
+By default, tracing data is exported to `http://localhost:4318/v1/traces`. This endpoint can be customized by editing the `TELEMETRY_ENDPOINT` environment variable.
+
+```py
+from comps import opea_telemetry
+
+
+@opea_telemetry
+async def your_async_func():
+    pass
+
+
+@opea_telemetry
+def your_sync_func():
+    pass
+```
+
+## Visualization
+
+### Visualize metrics
+
+Please refer to [OPEA grafana](https://github.com/opea-project/GenAIEval/tree/main/evals/benchmark/grafana) to get the details of Prometheus and Grafana server setup. The Grafana dashboard JSON files are also provided under [OPEA grafana](https://github.com/opea-project/GenAIEval/tree/main/evals/benchmark/grafana) to visualize the metrics.
+
+### Visualize tracing
+
+Run the following command to start the Jaeger server.
+
+```bash
+docker run -d --rm \
+-e COLLECTOR_ZIPKIN_HOST_PORT=:9411 \
+-p 16686:16686 \
+-p 4317:4317 \
+-p 4318:4318 \
+-p 9411:9411 \
+jaegertracing/all-in-one:latest
+```
+
+Access the dashboard UI at `localhost:16686`.