Introducing Intelligent Workloads, Providing Business-Aligned Observability

In the early days of software monitoring, a "green light" on a dashboard was enough. If the server was up and the application was responding, engineering teams felt confident that the business was running smoothly. But as we transitioned from monolithic applications to distributed microservices, and now to ephemeral, agentic AI-driven architectures, that green light has become a dangerous oversimplification.

Today’s engineering leaders—the DevOps architects and SRE "guardians" of the stack—face a paradox: they have more data than ever, yet less clarity. They can see individual service metrics, but struggle to see the end-to-end business flow. They can monitor a container, but can't easily quantify how a 500ms lag in a specific transaction impacts the company’s bottom line. This disconnect creates a visibility gap, where revenue is lost, engineering toil thrives, and mean time to resolution (MTTR) stretches from minutes to hours.

Today, we are closing that gap. We are thrilled to announce the launch of Intelligent Workloads, now in preview. Intelligent Workloads is not just a monitoring update; but is a fundamental shift in how organizations observe, manage, and optimize their most critical business processes. By automating service discovery, providing AI-driven insights, and aligning technical health with business KPIs, New Relic transforms observability from a maintenance task into a strategic driver of revenue protection.

The Crisis of Complexity

Before we dive into what Intelligent Workloads can do, let’s address the reality of the modern tech stack. Organizations are moving toward "ephemeral architectures"—environments that are temporary, dynamic, constantly evolving, and often powered by autonomous AI agents. In this landscape, the traditional approach to workloads (manually grouping entities) has hit a breaking point for three specific reasons:

The Toil of Manual Maintenance

In a distributed system, things change every second—new containers spin up, services are redeployed, and dependencies shift. If your monitoring tool requires you to manually update tags or filters every time a service changes, you aren't an engineer, you’re a tool maintainer. This manual toil leads to stale data and visibility gaps precisely when you need them least: during an incident.

Fragmented and Unreliable Health Signals

Most monitoring tools offer a shallow definition of health. If a child entity in a nested workload fails, that failure often stays hidden, failing to bubble up to the top-level view. Conversely, noisy alerts from irrelevant entities can trigger false positives, leading to alert fatigue. When your health signals are inaccurate, you can’t trust them for automated alerting.

The Business Disconnect

There is currently a massive wall between a red status light on a technical dashboard and the actual business impact. When a system degrades, leadership asks, “How many users are being affected? Is this impacting our checkout experience? What is the revenue risk?” Currently, most teams have to piece this together manually across multiple tools.

Introducing Intelligent Workloads: 360-Degree Contextual Observability

Intelligent Workloads was built to solve these specific challenges. It defines a collection of entities—infrastructure, applications, and services—into a custom view that provides a summary of performance, user impact, and business outcomes. Here is how Intelligent Workloads redefines the standard for observability.

Business-Aligned Observability: Defining Healthy on Your Terms

For the first time, you can align system performance with specific business goals. Intelligent Workloads allow you to set custom KPIs (like abandoned carts, checkout duration, or revenue per minute) directly alongside your technical metrics.

Intelligent Automation & Frictionless Setup

We believe you should spend your time fixing problems, not configuring tools. Intelligent Workloads use intelligent recommendations to identify your most critical business transactions (what we call Focal Transactions) and turns them into observable workloads with a single click.

By pivoting directly from APM and our Transaction 360 views, your team can move from initial setup to issue detection in seconds. We’ve also introduced Ephemeral "Test-Drive" Views, allowing engineers to validate workload configurations and membership rules before saving them, reducing configuration waste.

AI-Driven Insights & the Command Center

Cutting through the noise requires more than just charts; it requires analysis. Our AI-powered Command Center acts as a force multiplier for your SRE team. It automatically:

• Analyzes performance anomalies.
• Highlights the significant deviations (the "Golden Signals") that actually matter.
• Provides prioritized recommendations for investigation, so your team doesn't have to guess where to start.

Taking a Closer Look

To understand the power of Intelligent Workloads, let’s look at the specific capabilities that differentiate it from traditional, static monitoring solutions.

Transaction 360 & Focal Transaction Discovery

Traditional monitoring is often service-centric. Intelligent Workloads are transaction-centric. With Focal Transaction Discovery, the system identifies the "heartbeat" of your business—the traces that pass through critical paths. It maps every service, database, and infrastructure component involved in that specific transaction, ensuring you have a complete map of the dependency chain.

Nested Health Visibility (The "Bubble-Up" Effect)

In complex systems, workloads are often nested within other workloads. Previously, a failure deep within a sub-layer might not trigger a higher-level alert. Intelligent Workloads ensure that health signals from nested layers bubble up to the top. For example, if a low-level microservice in a payment sub-workload fails, the top-level checkout workload reflects that status immediately.

Flexible Health Definitions & Entity Knock-outs

Not every entity is created equal. Sometimes, a service is relevant to a workload but shouldn't trigger a critical health status if it fails (e.g., a non-essential logging service). Intelligent Workloads allow you to "knock out" specific entities from the health definition. This provides a high-integrity health signal that reflects the actual user experience rather than just a collection of noisy metrics.

Multi-Step Process Visualization (PathPoint Integration)

Modern business processes—like a user signing up, verifying an email, and making a first purchase—are multi-step journeys. Intelligent Workloads allows you to represent, monitor, and visualize these processes as a cohesive flow. This bridges the gap between a series of disconnected traces and a unified business story.

Time is Money

While the technical features are designed for the guardians of the stack, the business benefits of Intelligent Workloads extend to the entire organization.

Accelerated Revenue Protection

The ultimate goal is reducing MTTR. By automating the discovery of end-to-end flows and using AI to prioritize investigations, teams resolve incidents faster. In the world of e-commerce or SaaS, ten minutes of saved downtime can translate into millions of dollars in protected revenue.

Quantification of Technical Issues

Intelligent Workloads empower engineering leaders to speak the language of the business. Instead of reporting "High CPU usage on Node X," a VP of Engineering can report "A latency spike in the checkout service is currently impacting 15% of users and puts $50k of hourly revenue at risk." This transparency builds trust and allows for better-informed resource allocation.

Operational Efficiency and Lower TCO

Manual monitoring is expensive—not just in software costs, but in human hours. By eliminating the toil of manual updates and reducing alert fatigue, Intelligent Workloads lower the total cost of ownership (TCO) of your observability stack. Your best engineers can focus on building new features rather than babysitting dashboards.

Future-Proofing for Agentic AI

As we move toward Agentic AI workloads, where AI agents perform autonomous tasks within your infrastructure, systems will become more ephemeral and unpredictable. Intelligent Workloads is designed for this future. Its dynamic membership and flexible health definitions provide the guardrails needed to innovate with AI without losing visibility into service reliability.

Do More with Intelligent Workloads

We are often asked how this compares to other major players in the space.

• Vs. Datadog: While Datadog offers "dynamic entity workloads" focused on containers and security, they often lack the deep integration between technical health and business-aligned KPIs. Intelligent Workloads goes beyond infrastructure tagging to provide a 360-degree view of the transaction and its financial impact.
• Vs. Dynatrace: Currently, Dynatrace does not offer a comparable workload functionality that aggregates and summarizes diverse entity types into a unified business-aligned view with the same level of flexibility and automated "bubble-up" health logic.

Intelligent Workloads take the best of our entity-based models and combine them with an opinionated, proactive view of your system. We aren't just giving you a box of parts, we’re giving you the blueprint and the assembly line.

How to Get Started

The transition from reactive troubleshooting to strategic observability doesn't have to be a months-long project. Because Intelligent Workloads is built on top of our existing platform, you can begin seeing value almost immediately.

1. Identify Your Focal Transactions: Use the automated discovery tools to find the transactions that drive your revenue.
2. Create Your First Workload: Use the "One-Click" recommendation to spin up a view of that transaction.
3. Define Your Business KPIs: Connect your technical health to the metrics that matter to your stakeholders.
4. Engage the AI Command Center: Let our AI analyze your flows and provide your first set of optimization recommendations.

Observability as a Competitive Advantage

In a world where software drives your business, the health of your digital systems is inseparable from the health of your company. You can no longer afford to operate with fragmented visibility or manual processes that can't keep up with the speed of modern cloud-native architectures.

Intelligent Workloads is the bridge. It connects the "how" of engineering (the services, the traces, the infrastructure) to the "why" of the business (the revenue, the users, the growth). It transforms your team from firefighters into strategic partners, providing the high-integrity data needed to navigate the complexities of today and the AI-driven innovations of tomorrow.

The era of static, noisy monitoring is over. Welcome to the era of precision, business-aligned observability.

Ready to see the big picture? Schedule a demo of Intelligent Workloads today or sign up for the preview, and see how we can help you protect your revenue and empower your engineering teams.