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New Relic Adds Automatic Logs in Context to APM

New Relic announced enhancements to its Application Performance Monitoring (APM) to automatically collect logs in context with application metrics and traces.

Logs are critical for observability, and automatically coupling logs collection with APM allows engineers to immediately investigate relevant logs associated with their other telemetry data, helping them troubleshoot their applications faster. This new feature improves upon the already 3X+ more value that New Relic customers receive compared to other observability platforms, which require 13+ different SKUs with disjointed experiences and legacy product-based pricing models.

Collecting logs can be a complex, manual, and often frustrating experience. Developers often have to request access to specific hosts and configure non-standard log forwarding to collect application logs separate from their APM metrics. To address these common limitations, New Relic updated its Java, Ruby, and .NET APM agents to automatically collect and ingest application logs. With this new feature, New Relic is making logging easier for developers by simplifying log forwarding directly from the APM agent, providing logs in context, and enhancing the APM UI to surface relevant logs that are automatically associated with other telemetry data for APM to reduce context-switching. Engineers no longer need to worry about manual and non-standard log forwarding, and will still get granular configuration options to tailor log collection with the option to opt out anytime.

“Our customers have told us that they experience two primary problems when it comes to logging: first is the ability to collect log data; second is contextualizing the data to make it actionable. When troubleshooting an issue, our customers shouldn’t have to context switch across the UI to navigate the wealth of available information,” said New Relic SVP and Product GM, Wendy Shepperd. “Now with a single agent deployment for the supported application languages, engineers get a simple yet holistic solution to quickly see and act on all their telemetry in context. The new functionality curates the data automatically, such as entity GUIDs for related APM service entities, including application logs, so that highly correlated telemetry logs are already visible right out of the box.”

With the latest versions of Java, Ruby, and .NET agents for supported frameworks, New Relic customers can view application logs in context of APM metrics, traces and events, removing the need to switch between screens; collect and forward logs to New Relic with little to maintain or relying on manual configurations; and access logs inside APM with enhanced UI improvements. In addition, the update includes robust support to ensure security, compliance and control:

- Data Security: Mask, obfuscate, and prevent sending PII, PHI, or any other sensitive data via detailed security configurations.

- Ingest Control: Use in-agent log sampling to manage ingested volume and avoid double-billing to continue to receive 3X more value than alternate log management solutions.

- Compliance: Log collection disabled by default for HIPAA, FedRAMP and accounts where High Security Mode is in use, even after the agent is upgraded.

- Opt-out Anytime: Turn off automatic forwarding by configuring your agent anytime or from the data management hub in New Relic.

New Relic Application Performance Monitoring with the automatic logs-in-context feature is generally available for Java 7.7.0, Ruby 8.7.0, and .NET 9.7.2 agent versions. New Relic will enable automatic logs in context for Node.js, Python, Go, and PHP agents over the coming quarters.

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New Relic Adds Automatic Logs in Context to APM

New Relic announced enhancements to its Application Performance Monitoring (APM) to automatically collect logs in context with application metrics and traces.

Logs are critical for observability, and automatically coupling logs collection with APM allows engineers to immediately investigate relevant logs associated with their other telemetry data, helping them troubleshoot their applications faster. This new feature improves upon the already 3X+ more value that New Relic customers receive compared to other observability platforms, which require 13+ different SKUs with disjointed experiences and legacy product-based pricing models.

Collecting logs can be a complex, manual, and often frustrating experience. Developers often have to request access to specific hosts and configure non-standard log forwarding to collect application logs separate from their APM metrics. To address these common limitations, New Relic updated its Java, Ruby, and .NET APM agents to automatically collect and ingest application logs. With this new feature, New Relic is making logging easier for developers by simplifying log forwarding directly from the APM agent, providing logs in context, and enhancing the APM UI to surface relevant logs that are automatically associated with other telemetry data for APM to reduce context-switching. Engineers no longer need to worry about manual and non-standard log forwarding, and will still get granular configuration options to tailor log collection with the option to opt out anytime.

“Our customers have told us that they experience two primary problems when it comes to logging: first is the ability to collect log data; second is contextualizing the data to make it actionable. When troubleshooting an issue, our customers shouldn’t have to context switch across the UI to navigate the wealth of available information,” said New Relic SVP and Product GM, Wendy Shepperd. “Now with a single agent deployment for the supported application languages, engineers get a simple yet holistic solution to quickly see and act on all their telemetry in context. The new functionality curates the data automatically, such as entity GUIDs for related APM service entities, including application logs, so that highly correlated telemetry logs are already visible right out of the box.”

With the latest versions of Java, Ruby, and .NET agents for supported frameworks, New Relic customers can view application logs in context of APM metrics, traces and events, removing the need to switch between screens; collect and forward logs to New Relic with little to maintain or relying on manual configurations; and access logs inside APM with enhanced UI improvements. In addition, the update includes robust support to ensure security, compliance and control:

- Data Security: Mask, obfuscate, and prevent sending PII, PHI, or any other sensitive data via detailed security configurations.

- Ingest Control: Use in-agent log sampling to manage ingested volume and avoid double-billing to continue to receive 3X more value than alternate log management solutions.

- Compliance: Log collection disabled by default for HIPAA, FedRAMP and accounts where High Security Mode is in use, even after the agent is upgraded.

- Opt-out Anytime: Turn off automatic forwarding by configuring your agent anytime or from the data management hub in New Relic.

New Relic Application Performance Monitoring with the automatic logs-in-context feature is generally available for Java 7.7.0, Ruby 8.7.0, and .NET 9.7.2 agent versions. New Relic will enable automatic logs in context for Node.js, Python, Go, and PHP agents over the coming quarters.

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

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