Metropolis Microservices
NVIDIA now offers a unique suite of cloud-native microservices and reference applications to help you fast track the development and deployment of vision AI applications from the edge to any cloud.
Metropolis microservices provide powerful, customizable, cloud-native building blocks to develop vision AI applications and solutions. These let you unlock business insights for a wide range of spaces, ranging from retail stores and warehouses to airports and roadways. The microservices are brought to life with reference applications that track and understand people flow, create occupancy heatmaps, and more.
No matter how your application is built, cloud-native or not, Metropolis microservices can be a part of your solution development. They make it far easier to build, test, and scale deployments from edge to cloud with enhanced resilience and security.
Why It Matters to Your Workflow
Faster Time to Solution
Powerful, turnkey, API-driven, customizable vision AI building blocks accelerate application development.
Flexible Deployments
Cloud-native, industry-standard technologies enable seamless and scalable deployments anywhere, from the edge to any cloud.
Reusable Across Use Cases
Develop once and leverage across many use cases with our modular microservice architecture.
How Metropolis Microservices Will Help You
Build Complete Vision AI Solutions
To take your apps to the next level, Metropolis microservices provide a growing suite of analytics features that go beyond perception and computer vision. These capabilities help describe what’s happening, reveal patterns, and predict what might happen next–all from objects’ movements and behaviors.
Supercharge your solution with the abilities to perform higher-order analytics on perception metadata or aggregate metadata across sensors for full space awareness. They thus help enable sophisticated features such as multi-camera tracking and few-shot learning.
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Quickly Adapt to Your Use Cases
Metropolis microservices enable configurability and customizability at many levels to suit your unique use cases. Quickly adapt your vision analytics solution to new environments with our GUI-based camera calibration tool, intuitively mapping between pixel and physical space.
In addition to the reference app structure and microservice configuration, developers can also change the pretrained models, the APIs, and even the microservice code itself. No-code tools such as NVIDIA TAO are also available to help easily retrain AI models.
Seamlessly Integrate With Standard Interfaces
Cloud-native microservice architecture enables the high flexibility, scalability, and maintainability that are increasingly important for the fast-moving world of AI solution development and deployment.
These microservices and reference applications are built with industry standards like Kubernetes, Helm, Spark, Kafka, ELK stack, and others. In addition, they all have well-defined REST APIs to allow seamless integration with or within your existing applications and solutions.
Get Started With Metropolis AI Workflows
Discover cloud-native, pre-packaged reference applications to accelerate your AI solution development.
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Multi-Camera Tracking
Track objects across large spaces with many cameras to improve operational efficiency and safety in places like retail stores, warehouses, and more.
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Occupancy Analytics
Provide analytics on people movements such as space occupancy, time inside or outside ROI, movement patterns, etc. It also supports retail store analytics.
Retail Loss Prevention
Augment existing checkout kiosks with visual recognition capabilities that can adapt continuously to changing environments without needing much data.
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Watch GTC Talk
Develop with Metropolis Microservices
Take advantage of these powerful and customizable cloud-native building blocks for your next vision AI solution.
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Detection, Tracking, and Embedding
Detect, track, and generate embedding for objects within each camera stream. The microservice can handle multiple camera streams concurrently.
Multi-Camera Tracking
Track movement of objects across multiple cameras.
Behavior Analytics
Determine behaviors and anomalies in movement of objects.
Behavior Learning
Reveal and predict behavior patterns using clustering and deep learning. Learning is continuous.
Similarity Search
Perform high-throughput vector similarity search using Milvus database.
Video Management and Storage
Discover, connect, and manage cameras. Also, manage video streaming and storage.