Cutting Costs by 81%: Azure Spot VMs Drive Cost Efficiency for Jewelry AI Vision

  • Azure Cloud Cost Optimization
  • Azure Migration
  • Cloud computing
  • Cloud Cost optimization 
  • Cloud Infrastructure architecture 
  • Cloud Infrastructure Management
  • Hybrid Cloud Integration
  • Large Data Processing
Cutting Costs by 81%: Azure Spot VMs Drive Cost Efficiency for Jewelry AI Vision

 

Client: a leading Thai jewelry manufacturer

The Challenge

 

A leading Thai jewelry manufacturer wanted to optimize production by analyzing worker activity across 200-250 workstations. However, processing 2TB of daily video data for real-time insights presented a massive computational challenge. They needed a secure solution for extracting key details (feature extraction & classification) to identify inefficiencies and make data-driven decisions.

2-2.5 TB Daily Video

Processing a staggering 2TB of video data daily from each workstation poses a significant computational challenge.

AI-powered Insights

The client needs to extract key details from video data (feature extraction and classification) to identify patterns and inefficiencies in worker performance.

Secure Video Data

Safeguarding sensitive worker activity and production data is crucial (compliance & security).

Cost optimization

The initial Network Video Recorder (NVR) solution proved to be quite expensive to operate. With 200 workstations each recording 9 hours of video daily, this amounted to approximately 1800 hours of video data that needed to be processed overnight. The client required an optimized solution for handling such large volumes of data in a cost-effective manner.

Our Solution

We calculated that the NVR solution proposed by the developers is quite expensive. It would require a lot of CPU to make the project financially viable

Infrastructure Costs Estimation

We proposed a significant cost optimization for this AI vision processing infrastructure by leveraging Azure Spot Virtual Machines (VMs). Spot VMs offer unutilized Azure compute capacity at deep discounts compared to traditional on-demand pricing.

This makes them ideal for workloads like video processing that can tolerate short interruptions.

Infrastructure Costs Estimation with Spot Instances

Infrastructure Costs Estimation with Spot Instances

Here’s a breakdown of the estimated cost savings:

  1. Original Cost (On-demand pricing): $5,363 per month (as shown in the table)
  2. VMSS Cost with Spot VMs: $430 per month (significant reduction from $4,700)
  3. Total Estimated Cost with Spot VMs: $1,100 per month

Projected Savings: $4,263 per month

By utilizing Spot VMs for the VMSS instances, we can achieve a substantial cost reduction of approximately 81% compared to the initial estimate. This translates to savings of $4,263 per month.

Additional Benefits:

  • Scalability: Azure’s cloud infrastructure allows scaling Spot VMs up or down as needed, ensuring efficient resource utilization.
  • Performance: Spot VMs deliver high performance ideal for demanding workloads like video processing.

Considerations: While rare, Spot VMs can be interrupted when needed by Microsoft for other purposes. But our DevOps architect designed the architecture to handle these interruptions gracefully, ensuring minimal disruption to client’s AI vision processing tasks.

Using Azure’s scalable cloud infrastructure, we built a secure AI vision system. This system seamlessly processed the massive video data, extracted crucial insights, and provided real-time feedback for optimizing production processes.

  • Designed a scalable and secure cloud architecture on Azure to handle the massive data volume and real-time processing requirements.
  • Developed pipelines for efficient data ingestion, storage, and processing

Deployment diagram

Deployment diagram for AI Vision

Results

By implementing Azure’s scalable cloud infrastructure and AI vision system, the Thai jewelry manufacturer achieved significant productivity gains with data-driven insights. This translated to tangible benefits:

  • Reduced Operational Costs: The client achieved a substantial cost reduction of 81% compared to the initial Network Video Recorder (NVR) solution. This translates to a staggering monthly savings of $4,263. By leveraging Azure Spot VMs, the overall operational cost dropped from an estimated $5,363 per month to a highly optimized $1,100 per month.

  • Improved Production Efficiency: The real-time insights extracted from video data allowed the manufacturer to identify inefficiencies and optimize production processes. This resulted in increased productivity, leading to a positive impact on their bottom line.

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We leverage cutting-edge technology to empower businesses. Contact us today!

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