
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.
The Latest
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...