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Pinecone

Pinecone Assistant: A Managed Knowledge Layer for Production AI Applications Multi-domain RAG in n8n: why one knowledge base is not enough Allspice Transforms the Culinary Experience with Semantic Search Powered by Pinecone | Pinecone Building RAG workflows in n8n: choosing the right Pinecone node Knowledge needs a meta-knowledge layer Garbage Day: How Pinecone Safely Deletes Billions of Objects at Scale When "Performance" Means Two Different Things Pinecone BYOC: Pinecone in your AWS, GCP, or Azure account, no vendor access True, Relevant, and Wrong: The Applicability Problem in RAG Use the Pinecone Plugin for Claude Code to develop AI Applications Faster Millions at Stake: How Melange's High-Recall Retrieval Prevents Litigation Collapse Powering High-stakes Patent Search at Scale: How Melange Built a Reliable AI System on Pinecone | Pinecone Pinecone Assistant Node in n8n: Turn Any Data Source Into Knowledge RAG with Access Control Pinecone Dedicated Read Nodes are now in Public Preview Inside Pinecone: Slab Architecture New Bulk Data Operations: Update, Delete, and Fetch by Metadata The Hidden Cost of Building: Lessons from Aquant Simplifying Vector Embeddings with Pinecone Integrated Inference Capabilities Pinecone joins Microsoft Marketplace as a Launch Partner GTM Engineering: Clay + Pinecone for AI-powered Sales Outbound Build an AI knowledge assistant with Google Docs and Pinecone Moving Pinecone forward with Ash Ashutosh as CEO and Edo spearheading our growing AI ambitions as Chief Scientist Pinecone Founder Edo Liberty to Spearhead Pinecone’s Growing AI Ambitions; Appoints Ash Ashutosh as CEO to Expand Vector Database Market Leadership Fast, Accurate Retrieval for Creators at Scale: Delphi’s Path Toward a Million Conversational Agents with Pinecone | Pinecone Announcing Pinecone Pioneers: A Program for Builders, Organizers, and Community Leaders What is Context Engineering? Chunking Strategies for LLM Applications Beyond the hype: Why RAG remains essential for modern AI Obviant Makes 30% More Accurate Defense Acquisition Recommendations Combining Sparse and Dense Retrieval with Pinecone | Pinecone
Monitor Pinecone with Datadog
Gibbs Cullen · 2023-08-03 · via Pinecone

You can now easily view and monitor usage and performance for your AI applications in a single place with Datadog’s new integration for Pinecone.

With Datadog’s monitoring and security platform, you can now meet your team’s observability requirements and gain confidence when deploying large scale, mission critical AI applications to production. The integration also enables you to:

  • Optimize performance and control usage: Observe and track specific actions (e.g. request count) within Pinecone to identify application requests with high latency or usage. Monitor trends and gain actionable insights to improve resource utilization and reduce spend.
  • Automatically alert on metrics: Get alerted when index fullness reaches a certain threshold. You can also create your own customized monitors to alert on specific metrics and thresholds.
  • Locate and triage unexpected spikes in usage or latency: Quickly visualize anomalies in usage or latency in Pinecone’s Datadog dashboard. View metrics over time to better understand trends and determine the severity of a spike.

Datadog’s out-of-the-box dashboards and recommended monitors will also help you quickly view your metrics and avoid rate-limit errors or excessive latencies. For example, the index fullness monitor will automatically have a threshold of =>80%, alerting you to scale up your index to prevent performance degradation.

Out-of-box dashboards for Pinecone in Datadog

Out-of-box dashboards for Pinecone in Datadog

Getting started with the integration is simple. Existing Datadog customers will create and copy an API key in Pinecone and add the required information to the configuration tab within their Datadog account. If you are not already on Datadog, you can sign up and get started with a free trial. Visit the integration documentation to learn more and start building today.