Datadog announced a new integration that monitors OpenAI API usage patterns, costs and performance for various OpenAI models, including GPT-4 and other completion models.
Datadog's observability capabilities simplify the process of data collection through tracing libraries so that customers can easily and quickly start monitoring their OpenAI usage.
As adoption of OpenAI's newest generative AI model scales and more teams within organizations experiment with ChatGPT, the ability to understand user interactions with GPT-powered applications is vital for identifying opportunities to fine-tune models and enhance user experiences. Monitoring usage of the API and token consumption is also essential in controlling spend and improving application performance. By providing actionable insights into the API's usage, latency and costs, organizations will be able to use AI models more effectively so that they can focus on what matters most—improving day-to-day operations and innovating on products and services.
Datadog's integration with OpenAI enables organizations to:
- Understand Usage: With an easy setup process, users can quickly realize comprehensive insights into overall OpenAI usage of APIs, token consumption and costs split by service, teams and API keys with Datadog's out-of-the-box dashboards. Preconfigured out-of-the-box alerts also help users stay on top of OpenAI API rate limits.
- Optimize Performance: By tracking API error rates, rate limits and response times, Datadog allows users to identify and isolate application performance issues from API performance issues. Furthermore, users can view their traces and logs containing prompt and completion examples to understand key application bottlenecks and user behaviors.
- Track Costs: Users can review token allocation and analyze the associated costs of OpenAI API calls. Datadog offers insights into token allocation by model, service and organization to help teams manage their expenses more effectively and avoid unexpected bills.
- Cover Multiple AI Models: In addition to covering the GPT family of large language models, Datadog's integration enables organizations to track performance, costs and usage for other OpenAI models, including Ada, Babbage, Curie and Davinci.
"ChatGPT has become a powerful tool for software development, content creation and more. As users continue to experiment with AI models, teams across an organization—from engineering and marketing to legal and finance—need the ability to understand how the models are performing and how much time, money and resources users are dedicating to OpenAI models," said Yrieix Garnier, VP of Product at Datadog. "Datadog's integration with ChatGPT provides out-of-the-box dashboards users can leverage to monitor for rate limits and track internal usage patterns, costs and API performance, so that they can get a clear picture of ChatGPT allocation and consumption throughout the organization."
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