Proposal: Add AI-driven Network Anomaly Detection Plugin and OpenTelemetry Export for Pixie #2271

Background

Pixie provides deep, eBPF-based visibility into Kubernetes clusters, automatically capturing
network and application telemetry without manual instrumentation. However, while Pixie
offers powerful query and visualization capabilities (via PxL and Vizier), it currently lacks
a built-in mechanism for automated anomaly detection or OpenTelemetry-native export
of detected network irregularities.

This limits the ability of operators to detect and correlate real-time operational anomalies
(such as unexpected service-to-service communication, latency spikes, or throughput drops)
directly within Pixie’s observability workflow or external telemetry pipelines.

Problem Statement

Existing open-source tools like Zeek or Suricata perform deep packet inspection but are not
optimized for the dynamic, container-based nature of cloud-native microservices. Pixie already
solves visibility at scale but does not yet provide AI-assisted detection or direct
integration with the OpenTelemetry ecosystem.

Proposed Solution

Introduce a lightweight, optional plugin for Pixie that performs operational anomaly detection
on network traffic metrics and exports the results through OpenTelemetry.

1. AI-driven Anomaly Detection Layer

   • Implement a Pixie plugin or PxL script extension that computes simple
     streaming anomaly scores on traffic metrics (latency, request rate, error rate, byte count).
   • Techniques: EWMA, robust z-scores, Isolation Forest, or simple autoencoders
     (depending on available library support and compute limits).
   • Tag anomalies with metadata such as service_a, service_b, namespace, and anomaly.score.

2. OpenTelemetry Export Integration

   • Extend Pixie’s existing OpenTelemetry export capabilities to include these anomaly events
     as metrics or logs.
   • Allow configuration of anomaly thresholds and export frequency via Pixie’s plugin interface.

3. Example Output

   - name: px.anomaly.network.latency_spike
     attributes:
       src_service: checkout
       dst_service: payment
       namespace: production
       anomaly.score: 0.94
     timestamp: 2025-11-11T12:00:00
   

Benefits

• Enables real-time operational anomaly detection without additional instrumentation.

• Bridges Pixie’s in-cluster visibility with the broader OpenTelemetry and AIOps ecosystem.

• Provides actionable alerts and insights directly in the Pixie UI and external dashboards (Grafana, Datadog, etc.).

Scope & Alignment

• Keeps focus on observability and performance analysis, not security or intrusion detection.

• Aligns with the goal of improving AI-driven insights in Pixie’s roadmap.

• Can be developed as an independent plugin, avoiding changes to Pixie’s core.