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New Relic AI Monitoring (AIM) Launched

New Relic launched New Relic AI monitoring (AIM), an APM solution for AI-powered applications.

New Relic is pioneering AI observability with AIM to provide engineers unprecedented visibility and insights across the AI application stack, making it easier to troubleshoot and optimize their AI applications for performance, quality, cost, and responsible use of AI. With 50+ integrations and features like LLM response tracing and model comparison, AIM helps teams build and run LLM-based applications with confidence.

“With every organization integrating AI into their products and processes, AI workloads are now part of modern organizations’ application architectures,” said New Relic Chief Product Officer Manav Khurana. “With AI monitoring, we have applied our deep expertise from inventing cloud APM to providing end-to-end visibility into AI-powered applications to help businesses manage performance, costs, and the responsible use of AI.”

Key features and use cases include:

- Auto instrumentation: New Relic agents come equipped with all AIM capabilities, including full AI stack visibility, response tracing, model comparison, and more for quick and easy setup.

- Full AI stack visibility: Holistic view across the application, infrastructure, and the AI layer, including AI metrics like response quality and tokens alongside APM golden signals.

- Deep trace insights for every LLM response: Trace the lifecycle of complex LLM responses built with tools like LangChain to fix performance issues and quality problems such as bias, toxicity, and hallucination.

- Compare performance and costs: Track usage, performance, quality, and cost across all models in a single view; optimize use with insights on frequently asked prompts, chain of thought, and prompt templates and caches.

- Enable responsible use of AI: Ensure safe and responsible AI use by verifying that responses are appropriately tagged to indicate AI-generated and are free from bias, toxicity, and hallucinations using response trace insights.

- Instantly monitor your AI ecosystem: The most comprehensive solution for monitoring the entire stack of any AI ecosystem with 50+ integrations and quickstarts including:
Orchestration framework: LangChain
LLM: OpenAI, PaLM2, HuggingFace
Machine learning libraries: Pytorch, TensorFlow
Model serving: Amazon SageMaker, AzureML
Vector databases: Pinecone, Weaviate, Milvus, FAISS
AI infrastructure: Azure, AWS, GCP

AIM is now available in early access to New Relic users.

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New Relic AI Monitoring (AIM) Launched

New Relic launched New Relic AI monitoring (AIM), an APM solution for AI-powered applications.

New Relic is pioneering AI observability with AIM to provide engineers unprecedented visibility and insights across the AI application stack, making it easier to troubleshoot and optimize their AI applications for performance, quality, cost, and responsible use of AI. With 50+ integrations and features like LLM response tracing and model comparison, AIM helps teams build and run LLM-based applications with confidence.

“With every organization integrating AI into their products and processes, AI workloads are now part of modern organizations’ application architectures,” said New Relic Chief Product Officer Manav Khurana. “With AI monitoring, we have applied our deep expertise from inventing cloud APM to providing end-to-end visibility into AI-powered applications to help businesses manage performance, costs, and the responsible use of AI.”

Key features and use cases include:

- Auto instrumentation: New Relic agents come equipped with all AIM capabilities, including full AI stack visibility, response tracing, model comparison, and more for quick and easy setup.

- Full AI stack visibility: Holistic view across the application, infrastructure, and the AI layer, including AI metrics like response quality and tokens alongside APM golden signals.

- Deep trace insights for every LLM response: Trace the lifecycle of complex LLM responses built with tools like LangChain to fix performance issues and quality problems such as bias, toxicity, and hallucination.

- Compare performance and costs: Track usage, performance, quality, and cost across all models in a single view; optimize use with insights on frequently asked prompts, chain of thought, and prompt templates and caches.

- Enable responsible use of AI: Ensure safe and responsible AI use by verifying that responses are appropriately tagged to indicate AI-generated and are free from bias, toxicity, and hallucinations using response trace insights.

- Instantly monitor your AI ecosystem: The most comprehensive solution for monitoring the entire stack of any AI ecosystem with 50+ integrations and quickstarts including:
Orchestration framework: LangChain
LLM: OpenAI, PaLM2, HuggingFace
Machine learning libraries: Pytorch, TensorFlow
Model serving: Amazon SageMaker, AzureML
Vector databases: Pinecone, Weaviate, Milvus, FAISS
AI infrastructure: Azure, AWS, GCP

AIM is now available in early access to New Relic users.

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

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 ...