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New Relic Integrates with NVIDIA NIM

New Relic is integrating its platform with NVIDIA NIM inference microservices to reduce the complexity and costs of developing, deploying, and monitoring generative AI (GenAI) apps.

Customers can use New Relic AI monitoring to gain broad visibility across the AI stack for applications built with NVIDIA NIM, all with a simplified setup and enhanced data security. This complements the security features and ease of use of NVIDIA NIM’s self-hosted models, which accelerates generative AI application delivery. Together, New Relic integrated with NVIDIA NIM can help customers adopt AI faster and achieve quicker ROI.

“In today’s hyper-competitive market, organizations cannot afford to wait years for AI ROI,” said New Relic CEO Ashan Willy. “Observability solves this by providing visibility across the AI stack. We are pioneering AI observability by extending our platform to include AI apps built with NVIDIA NIM. Combining NVIDIA’s AI technology with our expertise in observability and APM gives enterprises a competitive edge in the AI race."

“As enterprises race to adopt generative AI, NVIDIA NIM can help businesses quickly deploy applications in production,” said NVIDIA Director of AI Software Amanda Saunders. “New Relic’s integration with NVIDIA NIM enables IT and development teams to optimize their AI applications by rapidly observing and responding to operational insights.”

New Relic AI monitoring provides a broad view of the AI stack, along with key metrics on throughput, latency, and costs while ensuring data privacy. It also traces the request flows across services and models to understand the inner workings of AI apps. New Relic extends its in-depth monitoring to NVIDIA NIM, supporting a wide range of AI models including–Databricks DBRX, Google's Gemma, Meta's Llama 3, Microsoft's Phi-3, Mistral Large and Mixtral 8x22B, and Snowflake's Arctic. This helps organizations deploy AI applications built with NVIDIA NIM confidently, accelerate time-to-market, and improve ROI.

Key features and use cases for AI monitoring include:

- Full AI stack visibility: Spot issues faster with a view across apps, NVIDIA GPU-based infrastructure, AI layer, response quality, token count, and APM golden signals.

- Deep trace insights for every response: Fix performance and quality issues like bias, toxicity, and hallucinations by tracing the lifecycle of AI responses.

- Model inventory: Easily isolate model-related performance, error, and cost issues by tracking key metrics across NVIDIA NIM inference microservices in one place.

- Model comparison: Compare the performance of NVIDIA NIM inference microservices running in production in a single view to optimize model choice based on infrastructure and user needs.

- Deep GPU insights: Analyze critical accelerated computing metrics such as GPU utilization, temperature, and performance states; understand context and resolve problems faster.

- Enhanced data security: In addition to NVIDIA’s self-hosted model’s security advantage, New Relic allows you to exclude monitoring of sensitive data (PII) in your AI requests and responses.

This integration follows New Relic's recent addition to NVIDIA’s AIOps partner ecosystem. Leveraging NVIDIA AI’s accelerated computing, New Relic combines observability and AI to streamline IT operations and accelerate innovation through its machine learning, and generative AI assistant, New Relic AI. New Relic offers the most expansive observability solution with 60+ AI integrations including NVIDIA GPUs and NVIDIA Triton Inference Server software.

New Relic AI monitoring is available as part of its all-in-one observability platform and offered via its usage-based pricing model.

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New Relic Integrates with NVIDIA NIM

New Relic is integrating its platform with NVIDIA NIM inference microservices to reduce the complexity and costs of developing, deploying, and monitoring generative AI (GenAI) apps.

Customers can use New Relic AI monitoring to gain broad visibility across the AI stack for applications built with NVIDIA NIM, all with a simplified setup and enhanced data security. This complements the security features and ease of use of NVIDIA NIM’s self-hosted models, which accelerates generative AI application delivery. Together, New Relic integrated with NVIDIA NIM can help customers adopt AI faster and achieve quicker ROI.

“In today’s hyper-competitive market, organizations cannot afford to wait years for AI ROI,” said New Relic CEO Ashan Willy. “Observability solves this by providing visibility across the AI stack. We are pioneering AI observability by extending our platform to include AI apps built with NVIDIA NIM. Combining NVIDIA’s AI technology with our expertise in observability and APM gives enterprises a competitive edge in the AI race."

“As enterprises race to adopt generative AI, NVIDIA NIM can help businesses quickly deploy applications in production,” said NVIDIA Director of AI Software Amanda Saunders. “New Relic’s integration with NVIDIA NIM enables IT and development teams to optimize their AI applications by rapidly observing and responding to operational insights.”

New Relic AI monitoring provides a broad view of the AI stack, along with key metrics on throughput, latency, and costs while ensuring data privacy. It also traces the request flows across services and models to understand the inner workings of AI apps. New Relic extends its in-depth monitoring to NVIDIA NIM, supporting a wide range of AI models including–Databricks DBRX, Google's Gemma, Meta's Llama 3, Microsoft's Phi-3, Mistral Large and Mixtral 8x22B, and Snowflake's Arctic. This helps organizations deploy AI applications built with NVIDIA NIM confidently, accelerate time-to-market, and improve ROI.

Key features and use cases for AI monitoring include:

- Full AI stack visibility: Spot issues faster with a view across apps, NVIDIA GPU-based infrastructure, AI layer, response quality, token count, and APM golden signals.

- Deep trace insights for every response: Fix performance and quality issues like bias, toxicity, and hallucinations by tracing the lifecycle of AI responses.

- Model inventory: Easily isolate model-related performance, error, and cost issues by tracking key metrics across NVIDIA NIM inference microservices in one place.

- Model comparison: Compare the performance of NVIDIA NIM inference microservices running in production in a single view to optimize model choice based on infrastructure and user needs.

- Deep GPU insights: Analyze critical accelerated computing metrics such as GPU utilization, temperature, and performance states; understand context and resolve problems faster.

- Enhanced data security: In addition to NVIDIA’s self-hosted model’s security advantage, New Relic allows you to exclude monitoring of sensitive data (PII) in your AI requests and responses.

This integration follows New Relic's recent addition to NVIDIA’s AIOps partner ecosystem. Leveraging NVIDIA AI’s accelerated computing, New Relic combines observability and AI to streamline IT operations and accelerate innovation through its machine learning, and generative AI assistant, New Relic AI. New Relic offers the most expansive observability solution with 60+ AI integrations including NVIDIA GPUs and NVIDIA Triton Inference Server software.

New Relic AI monitoring is available as part of its all-in-one observability platform and offered via its usage-based pricing model.

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...