AWS Trainium and AWS Inferentia Monitoring

Gain full visibility into real-time chip performance to optimize resource utilization, troubleshoot issues, and seamlessly scale ML infrastructure.

Improved Performance and Resource Efficiency

Prevent resource waste while ensuring fast and efficient ML performance
Avoid overspending and prevent performance bottlenecks with real-time monitoring of resource usage
Lower costs and maximize AWS hardware ROI by improving the efficiency of ML operations

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Proactive Issue Detection and Reliability

Identify and resolve potential hardware or software issues to avoid costly downtime
Maintain smooth and reliable ML operations with proactive monitoring of Trainium and Inferentia instances
Visualize and manage alerts for your ML infrastructure with out-of-the-box dashboards and monitors in Datadog

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Complete Visibility Into LLM Operations

Easily manage, optimize, and scale your infrastructure with full insight into your AI and LLM workloads
Allocate resources efficiently as workloads grow with real-time insights
Ensure your training jobs can handle increased workloads without delays or performance degradation with Datadog’s real-time monitoring

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Generative AI Monitoring

Monitor your Foundation Model usage, API performance, and error rate with runtime metrics and logs.

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Platform Datasheet

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The Essential Monitoring and Security Platform for the Cloud Age

Datadog brings together end-to-end traces, metrics, and logs to make your applications, infrastructure, and third-party services entirely observable.

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Next-generation ML Monitoring

Monitor and your entire machine learning stack with Datadog.

Amazon Neuron

Avoid overspending on underutilized hardware and prevents performance bottlenecks.

OpenAI

Monitor token consumption, API performance, and more.

NVIDIA DCGM Exporter

Gather metrics from NVIDIA’s discrete GPUs, essential to parallel computing.

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ML Monitoring Resources

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Machine Learning Monitoring

OpenAI Monitoring

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