February 2026 Summaries

The New Relic Synthetics Recorder is a Chrome extension designed to simplify the creation of Synthetic Step Monitors, essential for ensuring application uptime and functionality. It bridges manual browser interactions with production-ready monitors by capturing user actions like clicks, form inputs, and text entries, and automatically generating the necessary steps for monitoring critical user journeys. The extension offers features such as zero-code script generation, assertion mode for validating page elements, direct export to New Relic, and two-way sync for editing existing monitors. Users can edit and replay scripts locally before deploying them, enhancing workflow efficiency and reducing the technical barrier for team members unfamiliar with complex scripting. The tool emphasizes security by storing API keys in session-only memory and provides a user-friendly interface for both creating new monitors and updating existing ones, thereby improving synthetic monitoring processes.

This guide provides a detailed walkthrough for setting up OpenTelemetry with Azure Functions, specifically for TypeScript projects using ECMAScript Modules (ESM), utilizing the latest OpenTelemetry JS SDK 2.x. It addresses the lack of available guidance for these newer SDK configurations and ESM compilation, especially in the context of Azure's preview OpenTelemetry support. The guide emphasizes understanding the architecture, particularly distinguishing between the Azure Functions Host and the Worker process where the OpenTelemetry SDK operates. It outlines necessary steps such as updating the host.json file, installing relevant npm dependencies, and configuring tracing in a dedicated file to ensure proper instrumentation. The guide also discusses disabling certain Worker OpenTelemetry capabilities and console logging to avoid conflicts and ensure telemetry data is correctly routed to endpoints like New Relic. Additionally, the text highlights the importance of configuring sampling settings and provides insights into logging configurations to optimize telemetry data flow.

OpenTelemetry (OTel) is becoming a standard for modern system instrumentation, but its adoption can present challenges such as fragmented agent strategies and collector blind spots. New Relic is enhancing its commitment to OpenTelemetry by introducing several February releases aimed at simplifying and scaling the adoption process. These releases include Infra NRDOT for OTel-first infrastructure monitoring, hybrid agents that allow the use of OpenTelemetry APIs without disrupting existing workflows, and Collector Observability to manage and monitor OpenTelemetry collectors effectively. The goal is to provide a seamless transition to OpenTelemetry with minimal disruption, enabling teams to modernize at their own pace while maintaining existing observability workflows.

Intelligent Workloads is a new feature by New Relic designed to transform how organizations observe, manage, and optimize business processes by integrating system performance with business outcomes. It addresses the challenges of modern tech stacks, where traditional monitoring falls short in providing a comprehensive view of dynamic and ephemeral architectures. By automating service discovery and using AI-driven insights, Intelligent Workloads allows for the alignment of technical health with business KPIs, reducing manual maintenance and offering high-fidelity health signals. This innovation helps reduce mean time to resolution (MTTR) and improve revenue protection by turning observability into a strategic advantage, enhancing operational efficiency and future-proofing for agentic AI. It stands out from competitors like Datadog and Dynatrace by offering a transaction-centric, business-aligned perspective, facilitating a seamless transition from reactive troubleshooting to proactive system management.

Alerting systems are crucial yet fragile components in managing modern always-on systems, as ineffective alerts can lead to alert fatigue and missed incidents, impacting engineers' trust and response times. New Relic's Smart Alerts aim to enhance alerting by reducing false positives and improving detection accuracy through historical behavior analysis rather than relying on static thresholds, which often require constant manual tuning and can cause inconsistencies across dynamic environments. These alerts are designed to maintain broad alert coverage without increasing cognitive load on engineers, allowing them to focus on genuine issues. Smart Alerts do not perform root cause analysis or provide incident context, but rather focus on the initial detection phase, ensuring alerts are credible and timely. This feature integrates with existing operational practices without requiring teams to overhaul their current workflows, offering a scalable and sustainable solution for modern system reliability.

New Relic has introduced the New Relic Agentic Platform, now in preview, to address the evolving needs of observability in AI-driven and autonomous systems. Unlike traditional observability methods which rely on passive reporting and manual correlation of telemetry data, the Agentic Platform offers a continuous understanding of system behavior by analyzing relationships across services and maintaining context in real-time. This approach is intended to support both human operators and intelligent agents by providing a platform-level intelligence layer that connects telemetry with operational context, thus reducing the complexity and manual effort required for troubleshooting and decision-making. The platform does not replace existing tools but aims to integrate them into a cohesive system that enhances visibility and control as software systems become increasingly autonomous.

Feature flags and dynamic configuration can significantly enhance software delivery by allowing gradual feature releases and minimizing risks, but they often require careful management to prevent outages. AWS AppConfig, a service designed to facilitate safer and faster deployments, has integrated with New Relic Workflow Automation to automate and enhance the safety of feature flag deployments using real-time observability data. This integration enables automatic rollbacks when issues are detected, reducing the time and impact of potential outages. Traditionally, teams needed to manually correlate degraded metrics with feature flag deployments and initiate rollbacks, a process that could take several minutes. With the new integration, any issues detected during a gradual deployment trigger an immediate rollback, minimizing user impact and preserving system stability. The integration leverages AWS SQS and Lambda to ensure a seamless rollback process, using New Relic's telemetry platform to continuously monitor application health and trigger alerts. This collaboration between AWS and New Relic is part of a broader strategy to integrate observability with action, offering potential applications beyond feature flags, such as auto-scaling and service restarts. The goal is to build resilient systems that can adapt intelligently to changing conditions.

New Relic has introduced eBPF: Network Metrics, a novel network visibility tool currently in preview, designed to address network-layer issues in distributed applications without requiring code changes. This tool leverages eBPF technology to capture detailed TCP and DNS telemetry directly from the Linux kernel and integrates the data into a unified workflow alongside Application Performance Monitoring (APM) and infrastructure data. By providing granular insights into network behaviors such as TCP handshake latency, retransmissions, abnormal closures, and DNS resolution failures, it enables teams to efficiently pinpoint root causes of network issues, reducing downtime and context switching. This solution is particularly beneficial in complex, cloud-native environments like Kubernetes, where it attributes network behavior directly to processes or threads, thus streamlining troubleshooting and enhancing visibility without deploying multiple language-specific tools.

Modern software engineers often find themselves balancing between building innovative solutions and addressing urgent system failures, with traditional monitoring systems proving reactive rather than proactive. Despite having extensive dashboards, engineers are frequently alerted to issues only after user experience has already suffered. Common problems include coding anti-patterns like N+1 queries and slow SQL queries, which can be difficult to detect before they cause significant outages. New Relic introduces the Performance Risks Inbox, a proactive solution designed to identify and prioritize coding issues before they escalate, using a holistic approach that correlates telemetry data across the entire stack. This tool aims to transform engineering efforts from reactive firefighting to proactive optimization, enhancing system stability and reducing downtime costs. By providing actionable insights and guiding engineers towards effective solutions, the Performance Risks Inbox helps maintain the creative flow of engineering teams, ultimately protecting business interests and fostering innovation.

New Relic has announced the preview of Database 360 (DB360), a tool designed to unify database query telemetry with full-stack context, thereby enabling quicker identification and resolution of performance issues without needing to switch between multiple tools. DB360 provides a comprehensive database experience by modeling databases as integral entities connected to their dependent services and infrastructure, and it consolidates key diagnostic signals like query details, waits, and locks into a single workflow. This tool aims to streamline the process of detecting and resolving database performance issues, which often span multiple domains, by offering an intuitive interface that allows users to view slow queries, historical stats, and execution plans all in one place. Additionally, it helps teams triage incidents faster by presenting database behavior in the same context used for troubleshooting applications and infrastructure performance, thus reducing the friction of "handoff incidents" among Dev, SRE, and DB teams. DB360 also provides performance, reliability, and cost recommendations, helping teams prioritize impactful changes and proactively address issues in shared database environments.

New Relic has launched Workflow Automation, a no-code and low-code feature integrated into its platform that transforms observability data into actionable responses, enabling automated remediation of detected issues. This tool connects alerts, metrics, and system events to execute predefined actions, such as rolling back deployments or scaling infrastructure in response to anomalies, using a visual interface or natural language prompts powered by New Relic AI. Workflow Automation leverages New Relic's unified telemetry data to make informed decisions and supports a range of integrations, including AWS AppConfig for automated feature flag rollbacks, enhancing operational efficiency by reducing mean time to resolution (MTTR) and minimizing manual intervention. The offering includes a visual builder with YAML flexibility, native data integration, and transparent usage-based pricing, ensuring organizations can scale automation without unexpected costs while maintaining human oversight with approval gates. This innovative platform aims to bridge the gap between problem detection and resolution, significantly enhancing the reliability and efficiency of IT operations.

As AI becomes increasingly integrated into business systems, managing its complexity and ensuring compliance pose significant challenges, a phenomenon referred to as Shadow AI. New Relic addresses these issues through its Catalogs, a centralized inventory that provides a curated source of truth, mapping ownership, governance, dependencies, and operational context. The enhanced Applications Catalog highlights AI usage across services, facilitating compliance and risk management by automatically detecting AI components and bridging accountability gaps. New Relic Teams integration allows instant identification of responsible parties, and compliance scorecards help track adherence to regulatory standards like the EU AI Act. The platform promotes a seamless workflow from discovery to in-depth analysis, enhancing security and productivity by consolidating fragmented data and closing the loop on AI challenges.

New Relic has introduced two new capabilities aimed at enhancing log management by addressing the challenges of data accessibility, compliance, and efficient parsing. The Federated Logs feature allows teams to process and query logs locally, maintaining data sovereignty while providing a unified view and eliminating the need for complex pipelines. This enables real-time troubleshooting and insights without context switching. Additionally, the no-code parsing capability democratizes log data management by allowing engineers to extract insights quickly without needing advanced technical skills. This feature uses a visual builder for log attribute extraction, real-time rule validation, and automated parsing rules, significantly reducing the time from raw logs to actionable insights. These innovations aim to break down data silos and empower engineers to focus on problem-solving rather than managing complex log configurations, representing a paradigm shift in operational efficiency and observability practices.

In a reflection on the importance of observability and innovation, New Relic celebrates the contributions of Black tech pioneers such as Dr. Marian Croak, Mark Dean, Valerie Thomas, and Alan Emtage, who laid the groundwork for today's technological advancements. The company emphasizes the Ghanaian concept of Sankofa, recognizing the significance of learning from past achievements to drive future progress. Highlighting the accomplishments of its team members, New Relic showcases innovations like the New Relic Certified APM Practitioner Associate exam, the Live Tail feature, and a unified cloud platform agent, all of which enhance system efficiency and customer engagement. These efforts underscore New Relic's commitment to fostering a collaborative and innovative work culture, inviting others to join in shaping the future of observability.

New Relic has introduced two new features, Hierarchies and Productivity Insights, to enhance its Teams functionality and address key challenges in modern software development. Hierarchies aims to resolve organizational ambiguity by creating a clear visual representation of the organizational structure, linking services and entities to their owners and context, thereby ensuring accountability and streamlining issue escalation and approval processes. Productivity Insights tackles the problem of fragmented performance data by consolidating various metrics like DORA metrics and Cycle Time into a unified reporting interface, allowing engineering leaders to have real-time visibility into their team's productivity and align their work with business goals. These enhancements are designed to improve developer experience by providing clarity, eliminating silos, and enabling efficient team operations.

New Relic introduces Service Architecture Intelligence (SAI) Scorecards & Gamification and SAI Teams - Hierarchies & productivity metrics, designed to transform service compliance into a competitive and rewarding journey. The initiative features Gamified Team Leaderboards, likened to the "Engineering Olympics," where teams earn Gold, Silver, and Bronze medals based on their performance across relevant scorecards. This visibility aims to foster a culture of accountability, with top-performing teams publicly recognized and underperforming teams identified for resource allocation. Additionally, Service Maturity Levels provide a tactical framework for managers to guide teams through stages of excellence: Basic, Intermediate, and Advanced, with each level corresponding to specific operational standards and practices. By integrating weighted rules into these maturity levels, the gamification model prioritizes what matters most, offering a clear roadmap for engineers and transforming the compliance process into a drive for quality.

The rapid advancement of generative AI and autonomous coding assistants has dramatically accelerated software development, outpacing human management capabilities and leading to a surge in application creation. This boom, however, introduces significant complexity that challenges traditional observability models. New Relic's 2026 AI Impact Report highlights that despite abundant data, engineers struggle with operational burdens, losing substantial time to manual tasks. In response, New Relic Advance 2026 introduces Intelligent Observability, a proactive approach that aligns technical performance with business outcomes, emphasizing the importance of driving business uptime and bridging the gap between engineering metrics and business reality. The platform integrates Intelligent Workloads to automate dependency mapping and aligns these with business KPIs, enhancing incident resolution and engineering prioritization. Enhanced Digital Experience Monitoring (DEM) provides granular insights into micro front-end architectures, while New Relic Lens enables real-time correlation between application performance and external business data. The evolution includes the introduction of Agentic AIOps and the SRE Agent, which autonomously manage incidents, reduce resolution times, and protect business uptime. New Relic also introduces Intelligent Root Cause Analysis (iRCA) and Performance Risks Inbox to shift from reactive to proactive optimization. With a focus on economic efficiency, New Relic addresses the "observability tax" through Cloud Cost Intelligence and Federated Logs, enabling direct log queries at the source. The platform's Pipeline Control feature empowers users to manage data spend effectively, while OpenTelemetry hybrid agents facilitate seamless modernization. By consolidating tools onto a unified platform, New Relic aims to transform observability from passive monitoring to a strategic command center, enhancing business continuity and empowering teams to innovate.

The New Relic SRE Agent is a new AI-driven tool designed to enhance system reliability by supporting human engineers in high-pressure operational environments. By processing live telemetry and system context, it helps surface relevant signals and patterns, allowing engineers to focus more effectively on incident investigation without acting autonomously or overriding human decisions. This capability is integrated into the New Relic Intelligent Observability platform and aims to reduce cognitive load and improve consistency across on-call rotations, facilitating a shift from reactive troubleshooting to structured investigation. The SRE Agent respects existing workflows and operational boundaries, ensuring it complements rather than disrupts current systems, thus allowing teams to incrementally adopt AI into their operations while maintaining control and trust. As systems grow increasingly complex, the SRE Agent serves as a force multiplier, assisting experienced teams in achieving faster diagnosis, more consistent response outcomes, and improved confidence in decision-making.

New Relic has introduced new capabilities, including New Relic Lens, New Relic Notebooks, and Direct Entity & Relationship Querying, aimed at simplifying data discovery and analysis. These features create a unified platform that connects observability data with business outcomes, enabling users to transform data into actionable insights without complex filters or data ingestion fees. New Relic Lens allows for SQL-based querying of multiple external data sources, while New Relic Notebooks facilitate collaborative data analysis through shareable documents combining queries, visualizations, and text. The Direct Entity & Relationship Querying feature simplifies access to previously fragmented entity, relationship, and telemetry data, enhancing the overall data analysis process. These capabilities are designed to streamline complex investigations, accelerate troubleshooting, and improve business outcomes by offering a comprehensive view of the entire environment.

The evolving landscape of AI has transitioned from basic chat interfaces to complex, autonomous agent systems capable of executing intricate business workflows, necessitating advanced monitoring solutions to address the challenges posed by these dynamic environments. Traditional Application Performance Monitoring (APM) tools fall short in providing visibility into these non-linear, probabilistic systems, leading to inefficiencies and a lack of transparency. New Relic's AI Agent Monitoring aims to bridge this gap by offering an expanded suite of capabilities that enhance the visualization, debugging, and optimization of multi-agent systems through a full-stack observability platform. By integrating AI telemetry within the APM experience, it allows for comprehensive tracking of agent interactions, enabling quicker root cause analysis and improved decision-making. The newly introduced features, such as the Agents Service Map and granular behavioral insights, provide a strategic command center for AI monitoring, offering stakeholders across engineering, product management, and compliance a unified view of AI performance and decision logic. With these tools, businesses can more effectively manage AI systems, ensuring reliability, scalability, and alignment with business objectives while minimizing operational costs and risks.

Intelligent Root Cause Analysis (iRCA), introduced by New Relic, addresses inefficiencies in traditional Root Cause Analysis (RCA) by focusing on actual causes rather than symptoms, thereby reducing Mean Time to Resolution (MTTR). Unlike current observability tools that overwhelm engineers with alerts without pinpointing incident sources, iRCA employs a topology graph, causal models, and a ranking algorithm to accurately identify probable root causes quickly. This approach transforms observability from reactive to proactive operations by predicting and preventing issues with automated remediation hooks. By providing complete RCA coverage across complex environments, iRCA aligns observability with business impacts, improving customer experience, system reliability, and engineering productivity, while significantly cutting operational costs.

New Relic has introduced a series of user experience enhancements, including a personalized homepage and modernized UI, aimed at improving platform usability. The new homepage serves as an intelligent launchpad that consolidates critical health data and favorites, streamlining workflows and reducing cognitive load by minimizing context-switching and the need for multiple browser tabs. UI improvements include a minimalistic top bar for better navigation, enhanced data visualizations with new color palettes and gradients, and modern styling elements like softer radii and shadows to create focused views. These updates are designed to provide clearer insights and enable users to prioritize and act on important data immediately, with an opt-in control toggle available during the initial rollout for a smooth transition.

New Relic Outlier Detection, now generally available, offers a proactive approach for SRE and DevOps teams to identify deviations in complex systems, such as Kafka brokers and JVM services, which are often missed by traditional monitoring relying on averages or historical baselines. By comparing entities to their peers in real-time, this tool reduces alert noise and accelerates incident response, addressing issues like missed early warning signs and alert fatigue. Unlike Anomaly Detection, which focuses on individual historical deviations, Outlier Detection leverages group behavior analysis to spot significant deviations within similar entities, thus improving Mean Time to Detection (MTTD) and Mean Time to Resolution (MTTR). The system's flexible configuration and integration with existing observability practices allow teams to tailor alerts and maintain operational standards effectively, ultimately reducing downtime and enhancing system reliability as highlighted in New Relic's Observability Report 2024.

New Relic has introduced a new Change Tracking feature, currently in preview, designed to enhance incident response by integrating delivery events such as deployments and configuration updates directly into the observability workflow. This feature addresses the challenge of disconnected change and observability data, which often complicates incident management in rapidly evolving software environments. Change Tracking allows teams to see change markers alongside performance telemetry, facilitating quicker correlation of incidents with recent changes and improving confidence in rollback and mitigation decisions. By focusing on visibility rather than determining root causes, Change Tracking aims to transform change from a liability into a manageable aspect of system behavior, supporting faster incident response, more effective post-incident analysis, and better release hygiene. As teams adopt this feature, they can expect to see improved reliability without compromising delivery speed, turning visibility into a reliability multiplier.

Steve Cunnew, a Technical Success Manager at New Relic, shares insights from his 25 years of experience in observability and customer experience, emphasizing the critical importance of monitoring all components of an application or service, regardless of perceived significance. He recounts an experience with a performance issue in a financial services application, where the root cause was traced to an unmonitored file server, highlighting the necessity of comprehensive monitoring to avoid blind spots. Cunnew stresses that observability's primary goal is to provide insight into application behavior and performance, allowing for quick resolution of errors and performance degradations. He advises collecting extensive data on infrastructure and services to identify potential impacts on applications and suggests maintaining historical data to reduce the Mean Time to Resolution (MTTR) of issues. While his views represent personal insights rather than official endorsements by New Relic, he encourages readers to engage in further discussions through New Relic's Explorers Hub for additional support and questions.

New Relic has announced a major update to its platform, focusing on a redesigned user interface (UI) and enhanced data visualizations to create a more intuitive and engaging experience for users. The new UI features a minimalistic design with a global search function and easy access to key actions, providing a faster and more intuitive way to navigate and find information. Enhanced data visualizations include vibrant color palettes, gradients, and customizable line interpolations to improve data clarity and comprehension, while upgrades to the Needle component reduce jitter and support a horizontal orientation for better data tracking. This update is part of a broader effort to ensure platform consistency, offering a seamless and cohesive experience across the entire platform. Users have the flexibility to opt-in to the new design at their own pace and can revert to the classic view if desired, as New Relic continues to refine and add new features to the platform.

Application performance monitoring (APM) has evolved to address the complexities of modern architectures like microservices and serverless functions, necessitating tools that provide comprehensive, full-stack visibility. The guide reviews five APM tools—New Relic, Datadog, Dynatrace, AppDynamics, and Elastic APM—highlighting features such as distributed tracing, correlation of logs and metrics, and ease of integration with cloud services. It emphasizes the importance of choosing an APM tool that aligns with a team's specific needs and workflows, suggesting that a platform-based approach can reduce tool sprawl and improve efficiency by consolidating metrics, logs, and user experience data. New Relic is noted for its unified observability, developer-friendly workflows, and flexible adoption, making it a strong contender for teams seeking to enhance their system reliability and user experience. The article also discusses criteria for evaluating APM tools, such as support for distributed systems, alerting capabilities, and pricing scalability, advising on incremental adoption to optimize performance monitoring across an organization's stack.

Achieving operational excellence involves more than just setting up alerts; it requires ensuring their reliability to prevent dangerous "false silences," which occur when alert conditions fail to recognize data outages. Organizations often face challenges in managing hundreds of NRQL alert conditions without the vital Signal Loss and Gap Filling settings as they scale their observability environments. Signal Loss ensures that any halt in telemetry data is quickly flagged, thus preventing the mean time to detect (MTTD) from increasing indefinitely, while Gap Filling addresses data stream instability by preventing minor reporting gaps from causing alert fatigue. The solution involves an automated approach using NerdGraph, New Relic's GraphQL API, to manage and update alert conditions at scale. Through a two-step automation process—first collecting condition IDs and then applying updated configurations—teams can efficiently standardize alert settings across numerous conditions, thus reducing manual efforts and improving system reliability. This approach not only enhances the operational efficiency of engineering teams but also mitigates business risks by reducing incident MTTD and improving customer experience.

The New Relic Databricks Integration offers a comprehensive solution for enhancing the performance, reliability, and cost-efficiency of Databricks workloads by providing a unified observability platform that collects and analyzes telemetry data across various Databricks components. This open-source integration simplifies troubleshooting and optimization by offering a "single pane of glass" view, allowing users to correlate performance metrics directly to costs, thereby maximizing their Databricks investment. It includes capabilities such as Spark and query optimization, resource tuning, and job-level cost analysis, and facilitates effortless setup with immediate insights through sample dashboards, enabling businesses to transform their data operations into fully observable systems.

The journey through network monitoring reveals a transformative shift from traditional tools like SNMP to a unified platform approach that breaks down data silos and enhances observability. This evolution, highlighted by the transition from isolated monitoring tools to a comprehensive platform, enables rapid, collaborative problem-solving by providing a single-pane-of-glass view of the entire system, from application code to network packet. The article contrasts the old method, characterized by siloed tools and prolonged troubleshooting, with the new method where a unified platform quickly identifies root causes, such as a faulty service deployment affecting a database, by correlating data across application performance, infrastructure monitoring, and network observability. The narrative underscores the importance of engineers evolving from specialists to system thinkers, who can navigate and correlate diverse data sets to solve complex performance issues, thereby elevating their role from infrastructure guardians to indispensable problem solvers. This transformation is framed as both a challenge and an opportunity, encouraging engineers to embrace API fluency, data analysis, and collaboration.