This is a repackaged open source software product wherein additional charges apply for custom operational agents. Includes GPU and memory alerts, model serve health checks, automatic restart on failure, and resource tracking. Run AI inference with built-in reliability.
GigaOps AI Runtime Guard provides production-grade reliability for DeepSeek-R1 on Ubuntu 24. Built by Gigabits, it monitors and protects AI inference workloads.
Key Features:
GPU/Memory Alerts: Real-time notifications when GPU memory, system RAM, or temperature exceed thresholds.
Model Serve Health: Periodic inference probes confirm the model is responding correctly.
Auto-Restart: Detects crashed or hung model processes and restarts with cooldown logic.
Resource Tracking: Historical GPU utilization, memory usage, and inference throughput.
Security Hardening: Firewall rules, SSH key-only auth, and non-root model execution by default.
One-Command Diagnostics: Run gigaops ai-report for infrastructure and model health.
Ideal For: Teams deploying DeepSeek-R1 for AI inference who need automated recovery and GPU monitoring.
Highlights
GPU and memory monitoring for DeepSeek-R1 on Ubuntu 24. Real-time alerts when GPU memory, system RAM, or temperature exceed safe thresholds for AI inference workloads.
Model serve health checks confirm DeepSeek-R1 responds correctly. Auto-restart recovers crashed or hung model processes with cooldown logic. Resource tracking shows historical utilization.
DeepSeek-R1 on Ubuntu 24 deployed with firewall rules, SSH key-only auth, and non-root execution. One-command diagnostics with gigaops ai-report for AI infrastructure health.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
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.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
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 EC2 instance type you run this software on. Each dimension maps to one AWS instance size, so pricing scales with the compute, memory, GPU, or storage capacity you select. Smaller general-purpose instances cost less per hour, while GPU, memory-optimized, and bare-metal instances carry higher hourly rates. Compute-optimized, memory-optimized, storage-optimized, accelerated GPU, and inference instance families are all supported. You control cost by choosing an instance that fits your workload. Charges accrue only while an instance runs, with no upfront commitment.
Top-of-mind questions for buyers
What does one hourly unit cover for this software?
Each hourly unit covers one running EC2 instance of the type you select. The rate combines the software license and covers a single instance for each hour it runs. The instance size you pick sets its compute, memory, GPU, and storage capacity, which determines your hourly rate.
Am I charged when I stop or pause an instance?
Software charges accrue only while an instance runs. If you stop an instance, the hourly software charge stops. Stopped instances may still incur separate AWS storage fees for attached volumes, but the software license meters running hours only. There is no upfront commitment.
How do I lower my cost if my workload is small?
Choose an instance type that matches your workload. Smaller general-purpose instances carry lower hourly rates. GPU, memory-optimized, storage-optimized, and bare-metal instances carry higher rates for heavier work. You pay per hour for one instance at a time, so running fewer or smaller instances reduces cost.
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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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This is a repackaged open source software product wherein additional charges apply for custom operational agents. Includes model health monitoring, resource tracking, auto-restart on failure, and GPU/CPU alerts. Run local AI inference with built-in reliability.
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