Woodpecker
A Self-Service AI Platform
From Data Exploration to Model Deployment
Woodpecker is a container-based self-service AI platform
that empowers enterprise analysts to independently manage their analytics pipelines.
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Provide an optimized environment
for AI model development
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All-in-one support for model
development, training, and deployment
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Provide graph visualization solutions
for intuitive data exploration -
Ensure efficient resource management
of AI infrastructure
Features
Woodpecker offers a variety of model development tools, including Jupyter, R studio, VS Code. Enabling anyone to start machine learning projects with ease.
- Stable AI Infrastructure
Management - Support Kubernetes-based
clustering and container monitoring
- Stable AI Infrastructure
- Convenient AI Model
Development Setup - Easily build AI model development
environments without complex
infrastructure setups
- Convenient AI Model
- Optimized Analysis Images
- Provide images with sample code
and essential libraries pre-installed
- Diverse Development Environments
- Support multiple languages
and IDEs, including Python and R
- Data Visualization
- Deliver deep insights with tools
for pattern analysis and outlier detection
- Model Training Scheduling
- Offer job scheduling, automation
features for AI model training tasks
- Automated Model
Deployment APIs - Simplifies AI model deployment
to perform real-time predictions
and inferences
- Automated Model
- Query Editor
- Access databases directly
and execute SQL commands seamlessly
Monitoring View
Home
The Home page of Woodpecker serves as a unified interface for
real-time monitoring of project resources (CPU, memory, disk) and instant access to analytical tools. It provides a comprehensive view of model training schedules, a model bookmarking feature, and notification alerts for important updates.
Resource
The Resource monitoring page displays resource utilization for AI model development environments and deployment tasks through intuitive graphs. It supports efficient resource management by providing detailed, time-based insights into actual resource usage and comprehensive *GPU information.
· GPU Details: GPU Memory, GPU Clock, Memory Clock, GPU Utilization, Persistence Mode, Power Usage, Power Limits, Temperature, Fan Speed
Schedule Timeline
The Schedule Timeline offers a clear, intuitive overview of all user schedules. It organizes reservation and recurring schedules in chronological order and includes detailed information about users, servers, and schedule-specific tasks.
Workspace
Project Overview
The Project Overview page simplifies the creation of AI model development environments. Users can monitor the real-time status of created projects and use the provided analytical tools for seamless, one-stop processes of data exploration, model development, and training.
Model Serving
The Model Serving page automates API endpoint generation by allowing users to upload models and input basic information. The generated URL enables instant model invocation and real-time result utilization.
Query Editor
The Query Editor provides direct access to databases, enabling users to execute SQL commands and visualize data in various chart formats. This functionality simplifies the analysis of complex data patterns and helps uncover hidden anomalies intuitively.