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Herdora

Consulting
Real-time performance tracking and optimization for AI models efficiency
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Role Consulting

Herdora is an advanced AI performance monitoring system that provides real-time insights and continuous optimization to ensure peak performance of your models.

Key Features:

  • Intelligent performance monitoring
  • Continuous optimization
  • Alerts with answers
  • Automated GPU profiling
  • Root cause analysis
  • Layer-by-layer visualization

Use Cases:

  • Monitoring production traffic
  • Identifying performance bottlenecks
  • Simulating workloads before deployment
  • Visualizing model performance
  • Optimizing model updates

Benefits:

  • Improved model performance
  • Faster issue resolution
  • Informed decision-making
  • Reduced downtime
  • Enhanced competitive advantage
  • Profiles PyTorch code using kandc.ProfilerWrapper and kandc.ProfilerDecorator to capture CPU/CUDA timing and memory
  • Captures model execution traces with kandc.capture_model_class, kandc.capture_model_instance, and kandc.capture_trace
  • Parses and analyzes trace files via kandc.parse_model_trace to produce structured trace analysis outputs
  • Initializes and tracks experiment runs with kandc.init, kandc.log, kandc.finish and Run.log/log_artifact/run.finish
  • Uploads metrics and artifacts via kandc.APIClient (create_run, log_metrics, create_artifact) and returns dashboard URLs
  • Automatically captures source code snapshots (respects .gitignore) and exposes env vars to configure code capture
  • Operates in online, offline, or disabled run modes for cloud streaming or local-only profiling storage
  • Ingests Weights & Biases runs via W&B API key for no-code analysis and crash detection
  • Generates AI-powered crash reports and optimization suggestions for training runs (Keys & Caches)
  • Sends real-time alerts and Slack notifications for training/inference issues (Keys & Caches)
  • Offloads Python functions to cloud GPUs using Chisel decorators and the chisel CLI
  • Runs cloud GPU jobs on A100 variants with automatic GPU detection and multi-GPU configurations
  • Streams live job output and provides web UI job tracking for cloud GPU executions
  • Authenticates via browser-based browser auth and supports secure credential storage for cloud job access
  • Provides timing helpers kandc.timed and kandc.timed_call to record function execution times programmatically
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