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Modern software systems generate a tremendous amount of telemetry data, across infrastructure, application layers, user interactions, and business logic. With the rise of cloud-native architectures, microservices, and serverless computing, the volume, velocity, and variety of this data have exploded. Developers and DevOps engineers are now responsible not just for shipping code, but for ensuring its performance, reliability, and impact on end-user experience.
Enter New Relic, a powerful observability platform that unifies logs, metrics, and traces into a single pane of glass, allowing teams to detect issues faster, understand root causes more precisely, and optimize software with a deep, contextual view of how applications behave in production. This blog explores in depth how New Relic enables full-stack observability, why unifying telemetry matters, and how developers can leverage it to transform operational challenges into business value.
In legacy monitoring setups, logs, metrics, and traces are stored and accessed via separate tools, each offering partial, fragmented views. Metrics from Prometheus or DataDog. Logs from ELK or Splunk. Traces from Jaeger or Zipkin. These disconnected systems create silos of insight, forcing developers to manually stitch together a narrative during incidents or postmortems.
This leads to:
New Relic eliminates these barriers by creating a telemetry-unified platform. By consolidating metrics, events, logs, and traces, commonly known as MELT data, into a single, high-fidelity data lake, New Relic allows engineering teams to observe, correlate, and act within one experience. This full-stack observability enables teams to get ahead of outages, reduce operational toil, and make engineering decisions based on real-time application behavior.
In debugging scenarios, logs are often the most direct and detailed form of feedback. They capture everything from stack traces and error messages to custom instrumentation events. But when logs live in a siloed system, engineers are forced to context-switch, navigating from one dashboard to another, manually copying trace IDs or timestamps to find relevant log lines.
With New Relic’s Logs-in-Context, this entire experience changes. Log data is automatically collected and tagged with relevant metadata such as trace ID, span ID, and application/service name. This metadata allows logs to be seamlessly integrated with the rest of the telemetry, such as:
When a developer inspects a failed transaction, they can instantly pivot from the APM view to relevant logs, filtering by error code, response time, or user session ID. This drastically reduces debugging time and improves MTTR. Logs-in-Context also supports structured logging, enabling teams to add JSON attributes for richer analysis and automated parsing.
The power of unified logs in New Relic lies in its ability to remove noise and increase signal. Engineers no longer dig through gigabytes of logs; instead, they investigate only what matters, with full confidence in the relevance and context.
New Relic’s MELT model is foundational to its observability approach. It collects four distinct types of telemetry signals:
By co-locating these signals in a unified data lake, New Relic allows engineers to ask questions like:
This MELT integration transforms New Relic into a powerful platform for both reactive troubleshooting and proactive performance engineering.
In cloud-native, microservices-based applications, a single user request may traverse a dozen different services before receiving a response. This creates immense complexity. One slow service, or a network hop, can degrade the entire experience.
New Relic’s Distributed Tracing provides end-to-end visibility into these requests by capturing spans across services. Each span records timing, success/failure, and metadata. Together, spans build a full trace, a visual map of a request’s journey through the system.
Key benefits for developers:
Distributed Tracing integrates with OpenTelemetry and New Relic APM agents. Developers can visualize trace data within milliseconds of sending it, enabling real-time debugging and architectural optimization.
While traces and logs offer deep insight, they can be storage-heavy. New Relic’s metrics-first design philosophy focuses on capturing key performance indicators (KPIs) efficiently, with the option to dive into detailed telemetry only when required.
Metrics are:
Developers can create custom metrics, such as conversion rates, queue depths, or cache hit ratios, and store them for historical reporting. Metrics also power alerting, ensuring fast response when things deviate from the norm.
For example, a spike in 5xx errors triggers an alert. Developers can then drill into the time window, correlate logs and traces, and resolve the issue.
This metrics-to-traces workflow makes observability both cost-effective and insightful.
New Relic supports OpenTelemetry (OTel), the industry-standard for vendor-neutral telemetry. Developers can export OTel-compliant data from any service, using collectors or SDKs, and send it to New Relic.
Benefits of OTel integration:
Once ingested, OpenTelemetry traces, metrics, and logs become first-class citizens in New Relic. They can be visualized, queried, and correlated just like data from native agents. This flexibility is invaluable for large organizations with polyglot architectures or hybrid stacks.
Modern systems emit millions of telemetry signals per minute. Finding the root cause in this sea of data is daunting. New Relic’s Applied Intelligence (NRAI) solves this by using machine learning to detect anomalies, predict incidents, and auto-correlate related alerts.
Capabilities include:
Applied Intelligence is particularly useful in DevOps and SRE environments where false alerts are costly. It helps teams focus on what matters, improves SLAs, and reduces on-call fatigue.
Why do developers choose New Relic?
For developers, New Relic means spending less time firefighting and more time building. It enables high-velocity engineering by removing blind spots, aligning system health with user experience, and delivering fast feedback loops.
Within hours, you’ll be monitoring real user interactions, system health, and service behavior, all from a single, developer-friendly platform.
In today’s fast-moving digital landscape, software is the business. Performance issues don’t just affect systems, they impact users, revenue, and reputation. With New Relic’s full-stack observability, developers gain unprecedented visibility into the code they write, the services they call, and the experiences they power.
By unifying logs, metrics, and traces, and layering on intelligence, correlation, and open standards, New Relic transforms telemetry data into actionable insight. It is not just a monitoring tool, but an engineering intelligence platform that empowers developers to build reliable, performant, user-centric applications.
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