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Intelligent Workloads UI overview

The Intelligent Workloads Summary page serves as your central operational cockpit, bringing full-stack dependencies, golden metrics, and custom business KPIs into a single unified view. This guide walks through using the Summary page components to monitor transaction health in real time and accelerate triage when performance degrades. As you scroll, the layout systematically guides your investigation from customer-facing impact straight to technical performance drivers.

The breakdown below uses a checkout transaction degradation as a recurring example to demonstrate how each view functions during an active incident.

Screenshot of the Intelligent Workloads summary page showing KPI tiles, golden metrics, and participating entities

Access Intelligent Workloads

After creating Intelligent Workloads, you can access them from the main Workloads page:

  1. Go to one.newrelic.com > All capabilities > Workloads.
  2. Use the Type filter to select Intelligent.
  3. Click a workload to open its dashboard.

AI Summary

Located at the top of the Summary page, the AI Summary automatically analyzes real-time performance data — including metrics, traces, and entity health — across all participating entities in your workload to accelerate incident response. Click Generate insights to instantly surface performance anomalies and get suggestions on where to begin your investigation. For instance, during a sudden checkout slowdown, the AI Summary can analyze your dependency chain and highlight high-latency database calls before you pull a single trace.

Requirements:

중요

Pricing: AI insights generation incurs additional costs based on your New Relic AI usage. For more on New Relic AI pricing, see New Relic AI pricing documentation.

Workload KPIs

Positioned directly below the AI Summary, custom KPI tiles track key business indicators — such as order completion rates — directly alongside technical performance. Tracking KPIs allows your team to define system health by customer experience, alerting you the moment a business outcome is threatened. If your Checkout Success Rate KPI drops from 99% to 92%, you immediately know customer purchases are failing, rather than it being a benign background CPU spike.

You can display up to 3 KPIs on the Summary page at once. Two default KPIs are automatically added when you create an Intelligent Workload:

  • Transaction Throughput: Tracks the total volume of incoming requests processing through your selected transaction over time.
  • Transaction Error Rate: Monitors the percentage of failed transactions, giving you an immediate baseline of transaction reliability.

Learn more about managing KPIs →

Focal transaction golden metrics

Three side-by-side charts highlight Response Time, Throughput, and Errors scoped specifically to your focal transaction — the core transaction chosen when building your workload. Unlike standard APM views that mix all service traffic together, these golden metrics isolate the exact execution path of that central workflow. When your checkout KPI drops, reviewing these golden metrics helps you validate whether a simultaneous latency spike correlates with the business impact.

Participating entities

The bottom section breaks down performance across the top 20 services, databases, and serverless components actively processing your focal transaction. Scanning response time, throughput, and error rates across these dependencies helps you isolate precisely which microservice is failing. For example, sorting participating entities by response time during a checkout incident might reveal that a downstream payment-gateway database component accounts for 85% of total transaction latency, pointing you straight to the primary driver of degradation.

Dynamic Flow Map

The Dynamic Flow Map is a visualization tool that displays aggregated trace data to show how performance changes in upstream and downstream dependencies impact your focal service. By highlighting correlated anomalous latency and errors in traffic between services, the map helps you isolate performance bottlenecks across your transaction flow.

Screenshot of the Dynamic Flow Map showing service dependencies for a transaction flow

If you notice missing connections or disconnected service nodes, see Troubleshooting Workloads to check agent trace sampling and instrumentation requirements.

중요

You cannot change the focal transaction after creating Intelligent Workloads. To monitor a different transaction, create a new workload.

Next steps

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