New Relic Launches Industry’s 1st OpenAI GPT Observability Integration
SAN FRANCISCO, March 15, 2023 — New Relic, the all-in-one observability platform for every engineer, today announced a first-of-its-kind machine learning operations (MLOps) capability that allows engineering teams to monitor applications built with OpenAI’s GPT Series APIs.
With just two lines of code, engineering teams can monitor OpenAI completion queries while simultaneously tracking performance and cost metrics in real-time in a single view with New Relic. This new integration allows New Relic to ingest raw OpenAI data and helps companies leverage the power of emerging AI technologies like OpenAI’s ChatGPT to accelerate innovation and business goals while balancing considerations to cost.
This integration expands New Relic’s catalog of supported data and extends New Relic’s access to a wider audience of developers. Engineers can quickly deploy the OpenAI quickstart from New Relic Instant Observability and access this capability for free with no credit card required and minimal setup by signing up for a forever free New Relic account.
“This is an exciting time for companies who are embracing GPT and building modern applications with Generative AI,” said New Relic Chief Growth Officer and GM of Observability Manav Khurana. “Observability is a game changer when it comes to helping companies extract value from GPT. We are making it so that any engineer using GPT APIs can easily monitor their cost and performance with easy set-up and at no cost. This aligns with our mission to put the power of observability into the hands of every engineer.”
Companies around the world are embracing GPT to power help desk tickets and live chat logs, develop content and images, and accelerate semantic searches. New Relic monitoring for OpenAI is fast, easy to use, and unlocks real-time metrics that can help engineering teams optimize usage, reduce costs, and achieve better results.
The new capability allows engineers to:
- Get started for free: Access to New Relic Instant Observability and our out-of-the-box GPT monitoring solution is the first of its kind, and included at no additional cost for New Relic full platform users.
- Easy installation: With just two lines of code, users can import the monitor module from the nr_openai_monitor library and automatically generate a dashboard that displays a variety of key GPT performance metrics.
- Monitor cost: Usage of OpenAI’s Davinci model costs can add up quickly and make it difficult to operate at scale. New Relic provides engineering teams with real-time cost tracking of their GPT usage.
- Optimize performance: New Relic gives engineering teams insight into the average response time and other key performance metrics around GPT requests, allowing engineers to optimize usage and ensure the best possible response times.
- Analyze prompts and responses: New Relic provides valuable information about the usage, speed, and effectiveness of GPT to help engineering teams achieve better results from their ML models.
The OpenAI GPT integration with New Relic is included at no additional cost to New Relic full platform users. New Relic supports all current OpenAI GPT versions including the recently released GPT-4. For more information on how to set up New Relic MLOps or integrate GPT applications in your observability infrastructure, visit the New Relic documentation here or read the blog post.
To sign up for a forever free account, visit this webpage.
About New Relic
As a leader in observability, New Relic (NYSE: NEWR) empowers engineers with a data-driven approach to planning, building, deploying, and running great software. New Relic delivers the only unified data platform that empowers engineers to get all telemetry—metrics, events, logs, and traces—paired with powerful full stack analysis tools to help engineers do their best work with data, not opinions. Delivered through the industry’s first usage-based consumption pricing that’s intuitive and predictable, New Relic gives engineers more value for the money by helping improve planning cycle times, change failure rates, release frequency, and mean time to resolution.
Source: New Relic