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.
The Latest
Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...
New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...
Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...
SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...
Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...
AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...
If you were lucky, you found out about the massive CrowdStrike/Microsoft outage last July by reading about it over coffee. Those less fortunate were awoken hours earlier by frantic calls from work ... Whether you were directly affected or not, there's an important lesson: all organizations should be conducting in-depth reviews of testing and change management ...
In MEAN TIME TO INSIGHT Episode 11, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Secure Access Service Edge (SASE) ...
On average, only 48% of digital initiatives enterprise-wide meet or exceed their business outcome targets according to Gartner's annual global survey of CIOs and technology executives ...
Artificial intelligence (AI) is rapidly reshaping industries around the world. From optimizing business processes to unlocking new levels of innovation, AI is a critical driver of success for modern enterprises. As a result, business leaders — from DevOps engineers to CTOs — are under pressure to incorporate AI into their workflows to stay competitive. But the question isn't whether AI should be adopted — it's how ...
