Integration Architecture
Last updated
Last updated
Swarm’s Integration Architecture provides a modular and scalable framework to connect client applications with the platform’s AI services, enabling seamless interaction for training, inference, and fine-tuning tasks. This architecture ensures high performance, security, and ease of use.
Workflow
Client Applications:
Applications such as web apps, mobile platforms, or enterprise systems interact with Swarm’s AI services.
Requests include training jobs, inference predictions, or fine-tuning tasks.
API Gateway:
Acts as a centralized entry point for client requests, ensuring secure and authenticated communication.
Handles traffic management, request routing, and monitoring.
Provides RESTful and gRPC interfaces for integration flexibility.
AI Services:
Processes client requests through dedicated pipelines for:
Training: Initiates distributed training tasks using Swarm’s GPU infrastructure.
Inference: Provides real-time or batch predictions with low latency.
Fine-tuning: Customizes pre-trained models for specific use cases using efficient LoRA techniques.
Monitoring:
Tracks the performance and progress of ongoing tasks.
Real-time dashboards and alerts ensure visibility into resource utilization, latency, and service reliability.
Logs and metrics are available for audit and optimization purposes.
Integration Examples
Training Integration:
A client submits a training job via the API Gateway with datasets and hyperparameter configurations.
Swarm allocates resources, trains the model using distributed GPUs, and returns the trained model to the client.
Inference Integration:
A mobile app sends real-time inference requests to the API Gateway.
Swarm’s dynamic batching processes requests through inference servers, ensuring fast and accurate predictions.
Fine-Tuning Integration:
An enterprise system uploads domain-specific datasets for fine-tuning a pre-trained model.
Swarm customizes the model and deploys it for immediate use in the client application.
Key Features
Scalable API Gateway: Handles large-scale client requests with secure, efficient routing.
Flexible AI Services: Supports end-to-end workflows for training, inference, and fine-tuning.
Real-Time Monitoring: Ensures operational transparency and proactive issue resolution.
Seamless Integration: Provides SDKs and APIs for rapid deployment in diverse application ecosystems.
Swarm’s Integration Architecture empowers developers to integrate AI capabilities into their applications effortlessly, delivering robust, scalable, and high-performance solutions.
