A Guide to Tracing large-scale Inference Systems : Unlocking Deep Visibility with Jaeger

Imagine you're running a large-scale real-time inference system. The data is streaming in, the GPUs are humming, but something isn't quite right. Response times seem off. Latency issues are popping up, but where exactly are these bottlenecks? Enter Jaeger, your guide in this distributed tracing odyssey.🔎

🧪 Let's start by instrumenting inference services, API gateways, and other microservices. Use OpenTracing or OpenTelemetry SDKs for standardized traces.

from opentracing import Tracer
tracer = Tracer()

💼 Next, configure applications to send traces to a Jaeger agent or a collector sidecar. These components will be responsible for collecting and aggregating traces.

env:
  - name: JAEGER_ENDPOINT
    value: http://jaeger-collector.<namespace>.svc:14268/api/traces

🚀 Deploy Jaeger's backend components like the collector and query service on Kubernetes, where the magic of storage and analysis happens.

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: simple-prod

🏷️ Enrich your traces with useful tags and log information. More context, fewer headaches.

span.set_tag("http.status_code", 200)

⚙️ Don't forget to set appropriate sampling rates. We want a comprehensive picture, but not at the cost of overhead.

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: with-sampling
spec:
  strategy: production
  collector:
    options:
      log-level: debug

📊 Use Jaeger's UI to visualize the request flow across services and pinpoint slow paths.

🔧 Jaeger offers comprehensive waterfall timelines for end-to-end latencies, allowing you to identify the exact points of delay.

🔍 With Jaeger, isolate whether bottlenecks are in the client, network, or backend services.

⚖️ Gauge the impact of model latency on the overall response time and catch inference lags.

⏰ Set up latency Service Level Indicators (SLIs) in Jaeger to keep an eye on performance.

📉 Drill down on specific traces to diagnose the root cause for outliers and anomalies.

🎯 Lastly, use the insights from Jaeger to optimize bottleneck services.

With distributed tracing infrastructure in place, Jaeger provides the much-needed visibility into the performance of your real-time inference systems, making it a key tool for maintaining low latency at scale. ⏱️