move custom tracer to llm filter

arch/Dockerfile

@@ -13,16 +13,20 @@ FROM envoyproxy/envoy:v1.32-latest as envoy
 #Build config generator, so that we have a single build image for both Rust and Python
 FROM python:3.12-slim as arch
 
-RUN apt-get update && apt-get install -y gettext-base curl && apt-get clean && rm -rf /var/lib/apt/lists/*
+RUN apt-get update && apt-get install -y gettext-base curl supervisor && apt-get clean && rm -rf /var/lib/apt/lists/*
 
 COPY --from=builder /arch/target/wasm32-wasip1/release/prompt_gateway.wasm /etc/envoy/proxy-wasm-plugins/prompt_gateway.wasm
 COPY --from=builder /arch/target/wasm32-wasip1/release/llm_gateway.wasm /etc/envoy/proxy-wasm-plugins/llm_gateway.wasm
 COPY --from=envoy /usr/local/bin/envoy /usr/local/bin/envoy
-WORKDIR /config
+WORKDIR /app
 COPY arch/requirements.txt .
 RUN pip install -r requirements.txt
 COPY arch/tools/cli/config_generator.py .
 COPY arch/envoy.template.yaml .
 COPY arch/arch_config_schema.yaml .
+COPY arch/supervisord.conf /etc/supervisor/conf.d/supervisord.conf
+COPY arch/stream_traces.py .
 
-ENTRYPOINT ["sh", "-c", "python config_generator.py && envsubst < /etc/envoy/envoy.yaml > /etc/envoy.env_sub.yaml && envoy -c /etc/envoy.env_sub.yaml --component-log-level wasm:debug 2>&1 | tee /var/log/envoy.log"]
+RUN pip install requests
+
+ENTRYPOINT ["supervisord", "-c", "/etc/supervisor/conf.d/supervisord.conf"]

arch/envoy.template.yaml

@@ -242,11 +242,66 @@ static_resources:
                     typed_config:
                       "@type": type.googleapis.com/envoy.extensions.filters.http.router.v3.Router
 
-    - name: arch_listener_llm
+
+    - name: arch_listener_http_llm
       address:
         socket_address:
           address: 0.0.0.0
           port_value: 12000
+      traffic_direction: INBOUND
+      filter_chains:
+        - filters:
+            - name: envoy.filters.network.http_connection_manager
+              typed_config:
+                "@type": type.googleapis.com/envoy.extensions.filters.network.http_connection_manager.v3.HttpConnectionManager
+                {% if "random_sampling" in arch_tracing and arch_tracing["random_sampling"] > 0 %}
+                generate_request_id: true
+                tracing:
+                  provider:
+                    name: envoy.tracers.opentelemetry
+                    typed_config:
+                      "@type": type.googleapis.com/envoy.config.trace.v3.OpenTelemetryConfig
+                      grpc_service:
+                        envoy_grpc:
+                          cluster_name: opentelemetry_collector
+                        timeout: 0.250s
+                      service_name: arch_gateway
+                  random_sampling:
+                    value: {{ arch_tracing.random_sampling }}
+                {% endif %}
+                stat_prefix: arch_listener_http
+                codec_type: AUTO
+                scheme_header_transformation:
+                  scheme_to_overwrite: https
+                access_log:
+                - name: envoy.access_loggers.file
+                  typed_config:
+                    "@type": type.googleapis.com/envoy.extensions.access_loggers.file.v3.FileAccessLog
+                    path: "/var/log/access_llm.log"
+                route_config:
+                  name: local_routes
+                  virtual_hosts:
+                    - name: local_service
+                      domains:
+                        - "*"
+                      routes:
+                        - match:
+                            prefix: "/"
+                          route:
+                            auto_host_rewrite: true
+                            cluster: arch_listener_llm
+                            timeout: 60s
+                http_filters:
+                  - name: envoy.filters.http.router
+                    typed_config:
+                      "@type": type.googleapis.com/envoy.extensions.filters.http.router.v3.Router
+
+
+    - name: arch_listener_llm
+      address:
+        socket_address:
+          address: 0.0.0.0
+          port_value: 12001
       filter_chains:
         - filters:
             - name: envoy.filters.network.http_connection_manager
@@ -479,6 +534,23 @@ static_resources:
                       port_value: 10001
                   hostname: arch_prompt_gateway_listener
 
+    - name: arch_listener_llm
+      connect_timeout: 5s
+      type: LOGICAL_DNS
+      dns_lookup_family: V4_ONLY
+      lb_policy: ROUND_ROBIN
+      load_assignment:
+        cluster_name: arch_listener_llm
+        endpoints:
+          - lb_endpoints:
+              - endpoint:
+                  address:
+                    socket_address:
+                      address: 0.0.0.0
+                      port_value: 12001
+                  hostname: arch_listener_llm
+
+
 {% if "random_sampling" in arch_tracing and arch_tracing["random_sampling"] > 0 %}
     - name: opentelemetry_collector
       type: STRICT_DNS

arch/stream_traces.py

@@ -30,13 +30,11 @@ def process_log_line(line):
 
 
 with open(envoy_log_path, "r") as f:
-    # Seek to the end of the file so we only read new lines
-    f.seek(0, os.SEEK_END)
     while True:
         line = f.readline()
         if not line:
             time.sleep(1)
             continue
-        tokens = line.split("prompt_gateway: upstream_llm trace details: ")
+        tokens = line.split("gateway: upstream_llm trace details: ")
         if len(tokens) > 1:
             process_log_line(tokens[1])

arch/supervisord.conf

@@ -0,0 +1,25 @@
+[supervisord]
+nodaemon=true
+
+[program:trace_streamer]
+command=python stream_traces.py
+autostart=true
+autorestart=false
+startretries=3
+priority=1
+stdout_logfile=/dev/stdout
+stderr_logfile=/dev/stderr
+stdout_logfile_maxbytes = 0
+stderr_logfile_maxbytes = 0
+
+
+[program:envoy]
+command=sh -c "python config_generator.py && envsubst < /etc/envoy/envoy.yaml > /etc/envoy.env_sub.yaml && envoy -c /etc/envoy.env_sub.yaml --component-log-level wasm:debug 2>&1 | tee /var/log/envoy.log"
+autostart=true
+autorestart=true
+startretries=3
+priority=2
+stdout_logfile=/dev/stdout
+stderr_logfile=/dev/stderr
+stdout_logfile_maxbytes = 0
+stderr_logfile_maxbytes = 0

archgw.code-workspace

@@ -21,22 +21,25 @@
       "path": "e2e_tests"
     },
     {
-      "name": "demos/weather_forecast",
-      "path": "./demos/weather_forecast",
-    },
-    {
-      "name": "demos/insurance_agent",
-      "path": "./demos/insurance_agent",
-    },
+      "name": "chatbot_ui",
+      "path": "demos/shared/chatbot_ui"
+    }
   ],
   "settings": {
+    "[python]": {
+      "editor.defaultFormatter": "ms-python.black-formatter",
+      "editor.formatOnSave": true
+    },
   },
   "extensions": {
     "recommendations": [
       "ms-python.python",
       "ms-python.debugpy",
       "rust-lang.rust-analyzer",
-      "humao.rest-client"
+      "humao.rest-client",
+      "github.copilot",
+      "eamodio.gitlens",
+      "ms-python.black-formatter",
       ]
   }
 }

crates/llm_gateway/src/stream_context.rs

@@ -1,17 +1,18 @@
 use crate::filter_context::WasmMetrics;
 use common::common_types::open_ai::{
     ChatCompletionStreamResponseServerEvents, ChatCompletionsRequest, ChatCompletionsResponse,
-    StreamOptions,
+    Message, StreamOptions,
 };
 use common::configuration::LlmProvider;
 use common::consts::{
     ARCH_PROVIDER_HINT_HEADER, ARCH_ROUTING_HEADER, CHAT_COMPLETIONS_PATH,
-    RATELIMIT_SELECTOR_HEADER_KEY, REQUEST_ID_HEADER,
+    RATELIMIT_SELECTOR_HEADER_KEY, REQUEST_ID_HEADER, TRACE_PARENT_HEADER,
 };
 use common::errors::ServerError;
 use common::llm_providers::LlmProviders;
 use common::pii::obfuscate_auth_header;
 use common::ratelimit::Header;
+use common::tracing::{Event, Span};
 use common::{ratelimit, routing, tokenizer};
 use http::StatusCode;
 use log::{debug, trace, warn};
@@ -23,7 +24,7 @@ use std::rc::Rc;
 use common::stats::{IncrementingMetric, RecordingMetric};
 
 use proxy_wasm::hostcalls::get_current_time;
-use std::time::{Duration, SystemTime};
+use std::time::{Duration, SystemTime, UNIX_EPOCH};
 
 pub struct StreamContext {
     context_id: u32,
@@ -36,7 +37,10 @@ pub struct StreamContext {
     llm_provider: Option<Rc<LlmProvider>>,
     request_id: Option<String>,
     start_time: Option<SystemTime>,
-    ttft_duration: Option<Duration>, // Store the duration directly
+    ttft_duration: Option<Duration>,
+    ttft_time: Option<SystemTime>,
+    pub traceparent: Option<String>,
+    user_message: Option<Message>,
 }
 
 impl StreamContext {
@@ -53,6 +57,9 @@ impl StreamContext {
             request_id: None,
             start_time: None,
             ttft_duration: None,
+            traceparent: None,
+            ttft_time: None,
+            user_message: None,
         }
     }
     fn llm_provider(&self) -> &LlmProvider {
@@ -176,6 +183,7 @@ impl HttpContext for StreamContext {
         );
 
         self.request_id = self.get_http_request_header(REQUEST_ID_HEADER);
+        self.traceparent = self.get_http_request_header(TRACE_PARENT_HEADER);
 
         //start the timing for the request using get_current_time()
         let current_time = get_current_time().unwrap();
@@ -229,6 +237,13 @@ impl HttpContext for StreamContext {
             message.model = None;
         }
 
+        self.user_message = deserialized_body
+            .messages
+            .iter()
+            .filter(|m| m.role == "user")
+            .last()
+            .cloned();
+
         // override model name from the llm provider
         deserialized_body
             .model
@@ -307,6 +322,52 @@ impl HttpContext for StreamContext {
                 .output_sequence_length
                 .record(self.response_tokens as u64);
 
+            if let Some(traceparent) = self.traceparent.as_ref() {
+                let since_the_epoch_ns = SystemTime::now()
+                    .duration_since(UNIX_EPOCH)
+                    .unwrap()
+                    .as_nanos();
+
+                let traceparent_tokens = traceparent.split("-").collect::<Vec<&str>>();
+                if traceparent_tokens.len() != 4 {
+                    warn!("traceparent header is invalid: {}", traceparent);
+                    return Action::Continue;
+                }
+                let parent_trace_id = traceparent_tokens[1];
+                let parent_span_id = traceparent_tokens[2];
+                let mut trace_data = common::tracing::TraceData::new();
+                let mut llm_span = Span::new(
+                    "upstream_llm_time".to_string(),
+                    parent_trace_id.to_string(),
+                    Some(parent_span_id.to_string()),
+                    self.start_time
+                        .unwrap()
+                        .duration_since(UNIX_EPOCH)
+                        .unwrap()
+                        .as_nanos(),
+                    since_the_epoch_ns,
+                );
+                if let Some(user_message) = self.user_message.as_ref() {
+                    if let Some(prompt) = user_message.content.as_ref() {
+                        llm_span.add_attribute("user_prompt".to_string(), prompt.to_string());
+                    }
+                }
+                llm_span.add_attribute("model".to_string(), self.llm_provider().name.to_string());
+                llm_span.add_event(Event::new(
+                    "time_to_first_token".to_string(),
+                    self.ttft_time
+                        .unwrap()
+                        .duration_since(UNIX_EPOCH)
+                        .unwrap()
+                        .as_nanos(),
+                ));
+                trace_data.add_span(llm_span);
+
+                let trace_data_str = serde_json::to_string(&trace_data).unwrap();
+                debug!("upstream_llm trace details: {}", trace_data_str);
+                // send trace_data to http tracing endpoint
+            }
+
             return Action::Continue;
         }
 
@@ -402,6 +463,7 @@ impl HttpContext for StreamContext {
             if self.ttft_duration.is_none() {
                 if let Some(start_time) = self.start_time {
                     let current_time = get_current_time().unwrap();
+                    self.ttft_time = Some(current_time);
                     match current_time.duration_since(start_time) {
                         Ok(duration) => {
                             let duration_ms = duration.as_millis();

crates/prompt_gateway/src/http_context.rs

@@ -18,7 +18,6 @@ use common::{
     errors::ServerError,
     http::{CallArgs, Client},
     pii::obfuscate_auth_header,
-    tracing::{Event, Span},
 };
 use http::StatusCode;
 use log::{debug, trace, warn};
@@ -265,42 +264,6 @@ impl HttpContext for StreamContext {
         }
 
         if end_of_stream && body_size == 0 {
-            if let Some(traceparent) = self.traceparent.as_ref() {
-                let since_the_epoch_ns = SystemTime::now()
-                    .duration_since(UNIX_EPOCH)
-                    .unwrap()
-                    .as_nanos();
-
-                let traceparent_tokens = traceparent.split("-").collect::<Vec<&str>>();
-                if traceparent_tokens.len() != 4 {
-                    warn!("traceparent header is invalid: {}", traceparent);
-                    return Action::Continue;
-                }
-                let parent_trace_id = traceparent_tokens[1];
-                let parent_span_id = traceparent_tokens[2];
-                let mut trace_data = common::tracing::TraceData::new();
-                let mut llm_span = Span::new(
-                    "upstream_llm_time".to_string(),
-                    parent_trace_id.to_string(),
-                    Some(parent_span_id.to_string()),
-                    self.start_upstream_llm_request_time,
-                    since_the_epoch_ns,
-                );
-                if let Some(prompt) = self.user_prompt.as_ref() {
-                    if let Some(content) = prompt.content.as_ref() {
-                        llm_span.add_attribute("user_prompt".to_string(), content.to_string());
-                    }
-                }
-                llm_span.add_event(Event::new(
-                    "time_to_first_token".to_string(),
-                    self.time_to_first_token.unwrap(),
-                ));
-                trace_data.add_span(llm_span);
-
-                let trace_data_str = serde_json::to_string(&trace_data).unwrap();
-                debug!("upstream_llm trace details: {}", trace_data_str);
-                // send trace_data to http tracing endpoint
-            }
             return Action::Continue;
         }
 

demos/llm_routing/README.md

@@ -0,0 +1,19 @@
+# LLM Routing
+This demo shows how you can arch gateway to manage keys and route to appropricate LLM.
+
+# Starting the demo
+1. Please make sure the [pre-requisites](https://github.com/katanemo/arch/?tab=readme-ov-file#prerequisites) are installed correctly
+1. Start Arch
+   ```sh
+   sh run_demo.sh
+   ```
+1. Navigate to http://localhost:18080/
+
+# Observability
+Arch gateway publishes stats endpoint at http://localhost:19901/stats. In this demo we are using prometheus to pull stats from arch and we are using grafana to visalize the stats in dashboard. To see grafana dashboard follow instructions below,
+
+1. Navigate to http://localhost:3000/ to open grafana UI (use admin/grafana as credentials)
+1. From grafana left nav click on dashboards and select "Intelligent Gateway Overview" to view arch gateway stats
+
+# Selecting different LLM
+You can pick different LLM based on header `x-arch-llm-provider-hint` to override default LLM.

demos/llm_routing/docker-compose.yaml

@@ -2,7 +2,7 @@ services:
 
   chatbot_ui:
     build:
-      context: ../../chatbot_ui
+      context: ../shared/chatbot_ui
       dockerfile: Dockerfile
     ports:
       - "18080:8080"
@@ -12,3 +12,21 @@ services:
       - "host.docker.internal:host-gateway"
     volumes:
       - ./arch_config.yaml:/app/arch_config.yaml
+
+  jaeger:
+    build:
+      context: ../shared/jaeger
+    ports:
+      - "16686:16686"
+      - "4317:4317"
+      - "4318:4318"
+
+  prometheus:
+    build:
+      context: ../shared/prometheus
+
+  grafana:
+    build:
+      context: ../shared/grafana
+    ports:
+      - "3000:3000"

demos/shared/chatbot_ui/.vscode/launch.json

@@ -15,19 +15,21 @@
         "LLM": "1",
         "CHAT_COMPLETION_ENDPOINT": "http://localhost:10000/v1",
         "STREAMING": "True",
-        "ARCH_CONFIG": "../demos/weather_forecast/arch_config.yaml"
+        "ARCH_CONFIG": "../../weather_forecast/arch_config.yaml"
       }
     },
     {
+      "python": "${workspaceFolder}/venv/bin/python",
       "name": "chatbot-ui llm",
-      "cwd": "${workspaceFolder}/app",
       "type": "debugpy",
       "request": "launch",
-      "program": "run.py",
+      "program": "run_stream.py",
       "console": "integratedTerminal",
       "env": {
         "LLM": "1",
-        "CHAT_COMPLETION_ENDPOINT": "http://localhost:12000/v1"
+        "CHAT_COMPLETION_ENDPOINT": "http://localhost:12000/v1",
+        "STREAMING": "True",
+        "ARCH_CONFIG": "../../llm_routing/arch_config.yaml"
       }
     },
   ]

demos/shared/chatbot_ui/common.py

@@ -1,3 +1,4 @@
+from datetime import datetime
 import json
 import logging
 import os
@@ -159,13 +160,44 @@ def get_prompt_targets():
             config = yaml.safe_load(file)
 
             available_tools = []
-            for target in config["prompt_targets"]:
-                if not target.get("default", False):
-                    available_tools.append(
-                        convert_prompt_target_to_openai_format(target)
-                    )
+            if "prompt_targets" in config:
+                for target in config["prompt_targets"]:
+                    if not target.get("default", False):
+                        available_tools.append(
+                            convert_prompt_target_to_openai_format(target)
+                        )
+
+                return {tool["name"]: tool["info"] for tool in available_tools}
+            elif "llm_providers" in config:
+                return config["llm_providers"]
 
-            return {tool["name"]: tool["info"] for tool in available_tools}
     except Exception as e:
         log.info(e)
         return None
+
+
+def get_llm_models():
+    try:
+        with open(os.getenv("ARCH_CONFIG", "arch_config.yaml"), "r") as file:
+            config = yaml.safe_load(file)
+
+            available_models = [""]
+            default_llm = None
+            for llm_providers in config["llm_providers"]:
+                if llm_providers.get("default", False):
+                    default_llm = llm_providers["name"]
+                else:
+                    available_models.append(llm_providers["name"])
+
+            # place default model at the beginning of the list
+            if default_llm:
+                available_models.insert(0, default_llm)
+            return available_models
+    except Exception as e:
+        log.info(e)
+        return []
+
+
+def format_log(message):
+    time_now = datetime.now().strftime("%Y-%m-%d %H:%M:%S,%f")[:-3]
+    return f"{time_now} - {message}"

demos/shared/chatbot_ui/run_stream.py

@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple
 from openai import OpenAI
 from dotenv import load_dotenv
 
-from common import get_prompt_targets, process_stream_chunk
+from common import format_log, get_llm_models, get_prompt_targets, process_stream_chunk
 
 load_dotenv()
 
@@ -36,20 +36,28 @@ CSS_STYLE = """
 footer {visibility: hidden}
 """
 
-client = OpenAI(
-    api_key="--",
-    base_url=CHAT_COMPLETION_ENDPOINT,
-)
-
 
 def chat(
     query: Optional[str],
     conversation: Optional[List[Tuple[str, str]]],
     history: List[dict],
+    debug_output: str,
+    model_selector: str,
 ):
     history.append({"role": "user", "content": query})
 
+    if debug_output is None:
+        debug_output = ""
+
     try:
+        headers = {}
+        if model_selector and model_selector != "":
+            headers["x-arch-llm-provider-hint"] = model_selector
+        client = OpenAI(
+            api_key="--",
+            base_url=CHAT_COMPLETION_ENDPOINT,
+            default_headers=headers,
+        )
         response = client.chat.completions.create(
             # we select model from arch_config file
             model="--",
@@ -65,15 +73,20 @@ def chat(
 
     conversation.append((query, ""))
 
+    model_is_set = False
     for chunk in response:
         tokens = process_stream_chunk(chunk, history)
+        if tokens and not model_is_set:
+            model_is_set = True
+            model = history[-1]["model"]
+            debug_output = debug_output + "\n" + format_log(f"model: {model}")
         if tokens:
             conversation[-1] = (
                 conversation[-1][0],
                 conversation[-1][1] + tokens,
             )
 
-            yield "", conversation, history
+            yield "", conversation, history, debug_output, model_selector
 
 
 def main():
@@ -94,8 +107,17 @@ def main():
                             value=get_prompt_targets(),
                             show_indices=False,
                             elem_classes="json-container",
-                            min_height="95vh",
+                            min_height="50vh",
                         )
+                    model_selector_textbox = gr.Dropdown(
+                        get_llm_models(),
+                        label="override model",
+                        elem_classes="dropdown",
+                    )
+                    debug_output = gr.TextArea(
+                        label="debug output",
+                        elem_classes="debug_output",
+                    )
 
             with gr.Column(scale=2):
                 chatbot = gr.Chatbot(
@@ -110,7 +132,9 @@ def main():
                 )
 
             textbox.submit(
-                chat, [textbox, chatbot, history], [textbox, chatbot, history]
+                chat,
+                [textbox, chatbot, history, debug_output, model_selector_textbox],
+                [textbox, chatbot, history, debug_output, model_selector_textbox],
             )
 
     demo.launch(server_name="0.0.0.0", server_port=8080, show_error=True, debug=True)

demos/shared/grafana/dashboards/envoy_overview.json

@@ -192,8 +192,8 @@
       "targets": [
         {
           "disableTextWrap": false,
-          "editorMode": "builder",
-          "expr": "histogram_quantile(0.5, sum by(le) (rate(input_sequence_length_bucket[1h])))",
+          "editorMode": "code",
+          "expr": "histogram_quantile(0.9, sum by(le) (rate(input_sequence_length_bucket[5m])))",
           "fullMetaSearch": false,
           "includeNullMetadata": false,
           "legendFormat": "__auto",
@@ -202,7 +202,7 @@
           "useBackend": false
         }
       ],
-      "title": "input sequence length (p50)",
+      "title": "input sequence length (p90)",
       "type": "timeseries"
     },
     {
@@ -307,7 +307,7 @@
           },
           "disableTextWrap": false,
           "editorMode": "code",
-          "expr": "histogram_quantile(0.5, sum(rate(output_sequence_length_bucket[1h])) by(le))",
+          "expr": "histogram_quantile(0.9, sum(rate(output_sequence_length_bucket[5m])) by(le))",
           "fullMetaSearch": false,
           "includeNullMetadata": false,
           "instant": false,
@@ -317,7 +317,7 @@
           "useBackend": false
         }
       ],
-      "title": "output sequence length (p50)",
+      "title": "output sequence length (p90)",
       "type": "timeseries"
     },
     {
@@ -416,8 +416,8 @@
       "targets": [
         {
           "disableTextWrap": false,
-          "editorMode": "builder",
-          "expr": "histogram_quantile(0.5, sum by(le) (rate(time_to_first_token_bucket[1h])))",
+          "editorMode": "code",
+          "expr": "histogram_quantile(0.9, sum by(le) (rate(time_to_first_token_bucket[5m])))",
           "fullMetaSearch": false,
           "includeNullMetadata": false,
           "legendFormat": "__auto",
@@ -426,7 +426,7 @@
           "useBackend": false
         }
       ],
-      "title": "time to first token (p50)",
+      "title": "time to first token (p90)",
       "type": "timeseries"
     },
     {
@@ -542,28 +542,15 @@
             "uid": "PBFA97CFB590B2093"
           },
           "editorMode": "code",
-          "expr": "histogram_quantile(0.5, sum(rate(latency_bucket[60m])) by (le))",
+          "expr": "histogram_quantile(0.9, sum(rate(request_latency_bucket[60m])) by (le))",
           "hide": false,
           "instant": false,
           "legendFormat": "__auto",
           "range": true,
           "refId": "B"
-        },
-        {
-          "datasource": {
-            "type": "prometheus",
-            "uid": "PBFA97CFB590B2093"
-          },
-          "editorMode": "code",
-          "expr": "histogram_quantile(0.5, sum(rate(time_to_first_token_bucket[60m])) by (le))",
-          "hide": false,
-          "instant": false,
-          "legendFormat": "__auto",
-          "range": true,
-          "refId": "A"
         }
       ],
-      "title": "request latency (p50)",
+      "title": "request latency (p90)",
       "type": "timeseries"
     }
   ],

demos/shared/trace_streamer/Dockerfile

@@ -1,11 +0,0 @@
-FROM python:3.12-slim as arch
-
-WORKDIR /app
-
-RUN pip install requests
-COPY stream_traces.py .
-
-RUN mkdir -p /var/log
-RUN touch /var/log/envoy.log
-
-CMD ["python", "stream_traces.py"]

demos/weather_forecast/docker-compose.yaml

@@ -30,14 +30,6 @@ services:
       - "4317:4317"
       - "4318:4318"
 
-  trace_streamer:
-    build:
-      context: ../shared/trace_streamer
-    environment:
-      - OTEL_TRACING_HTTP_ENDPOINT=http://jaeger:4318/v1/traces
-    volumes:
-      - ~/archgw_logs:/var/log/
-
   prometheus:
     build:
       context: ../shared/prometheus

demos/weather_forecast_signoz/docker-compose.yaml

@@ -25,14 +25,6 @@ services:
     volumes:
       - ./arch_config.yaml:/app/arch_config.yaml
 
-  trace_streamer:
-    build:
-      context: ../shared/trace_streamer
-    environment:
-      - OTEL_TRACING_HTTP_ENDPOINT=http://otel-collector:4318/v1/traces
-    volumes:
-      - ~/archgw_logs:/var/log/
-
   prometheus:
     build:
       context: ../shared/prometheus