GigaOps GPU Monitor on DeepSeek-R1 with WebUI. Includes GPU utilization tracking, model health checks, automatic restart on failure, and memory alerts. Run AI inference workloads with built-in observability.
GigaOps GPU Monitor delivers a ready-to-run DeepSeek-R1 deployment with integrated AI workload monitoring built by Gigabits. It provides the operational layer that bare AI model servers lack.
Key Features:
GPU Utilization Tracking: Real-time GPU load, memory, temperature, and throughput metrics via local dashboard.
Model Health Checks: Periodic inference validation to confirm the model responds correctly.
Auto-Restart: Detects unresponsive model processes and restarts them with configurable cooldown.
Memory Alerts: Notifications when GPU or system memory exceeds safe thresholds.
Resource Dashboard: Unified view of GPU, CPU, memory, and disk for the AI workload.
One-Command Diagnostics: Run gigaops ai-report for model and infrastructure health summary.
Ideal For: Teams running DeepSeek-R1 for AI inference who need GPU monitoring and automatic recovery without a full MLOps stack.
Highlights
GPU utilization tracking for DeepSeek-R1 with Open WebUI. Real-time monitoring of GPU load, memory, temperature, and inference throughput via local dashboard.
Model health checks validate DeepSeek-R1 responds correctly. Auto-restart detects unresponsive processes and recovers them with configurable cooldown. Memory alerts prevent OOM failures.
DeepSeek-R1 AI model with Open WebUI deployed and ready for inference. GPU, CPU, and memory unified dashboard. Run gigaops ai-report for complete model and infrastructure health.
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Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
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If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
You pay by the hour for the software running on your chosen Amazon EC2 instance. The rate depends only on which instance type you select. Options span many families, including general-purpose (m, t), compute-optimized (c), memory-optimized (r, x, z, u), storage (d, i, h), and accelerated computing (g, p, inf, trn, vt, dl). Sizes range from nano and micro up to metal and multi-xlarge configurations. Larger or more specialized instances carry a higher hourly rate. You run the software as a 1-Click image on AWS and are billed for the hours you use.
Top-of-mind questions for buyers
What does one billing unit represent for this software?
One unit is one hour of the software running on a single Amazon EC2 instance of the type you select. You are billed per hour that the instance runs. The instance type you choose sets the hourly software rate.
Am I charged the software fee when my instance is stopped?
The software fee meters running hours only. A stopped instance does not accrue software charges. Note that underlying AWS resources, such as attached storage, may still incur separate AWS fees while the instance is stopped.
How do I run this product, and what am I actually paying for?
You launch it as a 1-Click image on AWS. The charge covers the packaged software running on your chosen EC2 instance, billed hourly. AWS compute costs for the instance itself are separate and set by AWS, not included in this software rate.
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Vendor refund policy
The instance can be terminated at anytime to stop incurring charges. No refund available.
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An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
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