July 2025 Summaries

New Relic has announced the general availability of its APM and OpenTelemetry (OTel) convergence, offering an observability platform for OTel data that allows users to obtain actionable insights from their telemetry data. The platform provides a seamless experience by normalizing OTel data to adhere to New Relic's APM standards without altering the original data, maintaining data fidelity. The blog post uses the Astroshop demo application, a microservices-based system, to demonstrate how New Relic's platform processes and visualizes OTel data. The Astroshop application is pre-configured to integrate with New Relic, allowing users to simulate software issues and explore the platform's capabilities, such as the Transaction 360 view, which offers in-depth analysis of application and infrastructure performance. This example highlights the convergence's ability to correlate performance data across various services and infrastructure entities, providing a comprehensive view of the system's health. As OTel evolves, New Relic plans to continue enhancing its platform to support OTel data, ensuring a robust observability solution for users.

New Relic has announced the general availability of its APM + OpenTelemetry Convergence, enhancing observability for OpenTelemetry (OTel) data by integrating it into a sophisticated platform that ingests, stores, correlates, and visualizes telemetry. The platform uses a fork of the OpenTelemetry Community's Astroshop demo application to demonstrate how New Relic transforms raw OTel data into actionable insights. The convergence process involves intelligent data normalization, making data conform to New Relic's APM semantic conventions while preserving original data for query purposes. This enables users to view and analyze telemetry data through New Relic's UI, which includes features like dynamic flow maps and Transaction 360 views, allowing for a comprehensive analysis of application and infrastructure performance. The Astroshop application is pre-configured to streamline setup, and by utilizing feature flags, users can simulate real-world software problems to evaluate the effectiveness of New Relic's observability tools. As OpenTelemetry continues to evolve, New Relic aims to advance alongside it, consistently updating their offerings to provide optimal support for OTel data.

The blog post by Dan Gomez Blanco, a Principal Observability Architect at New Relic, explores the complexities and importance of good telemetry in observability, emphasizing that it is a crucial aspect of understanding system performance in real-time. He introduces the "Instrumentation Score," a new open standard aimed at measuring how well applications are set up for observability by considering various signals like traces, metrics, and logs. The initiative, involving collaboration from engineers at New Relic and other organizations, seeks to establish standard measurements to enhance observability practices. The article discusses how different signals serve distinct purposes and highlights the significance of using the right data to troubleshoot and monitor performance effectively. By leveraging OpenTelemetry and employing smart sampling techniques, the Instrumentation Score aims to provide a comprehensive understanding of systems while avoiding excessive costs and operational challenges. The article encourages participation in developing this standard and emphasizes that observability maturity is a gradual process requiring strategic actions to improve system insights and drive business outcomes.

Telemetry is essential for real-time application performance understanding, but defining "good" telemetry is complex and context-dependent, varying by system, team, and organization. Observability is not an action but a system's inherent quality, like security or reliability, and requires agreed-upon standard measurements for improvement. A new project, Instrumentation Score, aims to measure how well applications are set up for observability, with collaboration from industry leaders like New Relic and Splunk. The project emphasizes the importance of using multiple signals like traces, metrics, and logs to gain holistic system insights, supported by OpenTelemetry's vendor-neutral generation of these signals. Instrumentation Score evaluates telemetry quality at the point of use, considering how well it helps understand and improve systems, promoting observability maturity through prioritized actions and gamification.

New Relic has introduced a new feature called Compute Budgets, designed to help organizations manage and control their spending by setting clear spending limits and monitoring real-time consumption. This capability complements the previously launched Compute Optimizer by allowing organizations to not only identify potential savings but also enforce budgetary controls to stay within monthly limits. Users can define and allocate flexible budgets at various organizational levels, monitor usage against these budgets without incurring additional costs, and receive proactive notifications to prevent overspending. Compute Budgets are easily set up through the New Relic platform by organization managers, enhancing budget management with visibility and alerting features. The initiative is part of New Relic's efforts to provide comprehensive solutions for managing compute investments efficiently.

New Relic has introduced Compute Budgets, a new feature designed to help organizations manage their computing costs proactively by setting and monitoring spending limits in real-time. This tool complements the previously launched Compute Optimizer by not only identifying potential savings but also allowing users to enforce budget constraints, thereby preventing overspending. Organization Managers can define and allocate budgets at different levels, track usage against these budgets without additional costs, and receive notifications when nearing their limits. The initiative aims to provide comprehensive control over compute expenses, enhancing user experience with visibility, alerting features, and ease of setup through the New Relic platform. The article highlights contributions from Jon Garside and Sanika Joshi, emphasizing their roles in making New Relic's solutions accessible and effective for customers.

Error analytics plays a crucial role in maintaining the reliability and user experience of modern applications, which are often complex systems built on microservices, APIs, and cloud infrastructure. When errors occur, they can quickly escalate into significant problems affecting user trust and causing financial losses. A structured approach to error analysis, supported by tools like New Relic, helps teams efficiently identify and resolve issues by providing full visibility into the system and reducing the time from detection to understanding. This involves aligning key signals such as errors, traces, and logs into a connected workflow, which aids in pinpointing root causes and prevents repeated failures. Proactive error management strategies, including setting service-level indicators, adding contextual information to error signals, adopting intelligent alerting, and automating responses to known error scenarios, are essential for transforming observability into a daily practice and ensuring system resilience. Ultimately, effective error analytics shifts teams from reactive debugging to proactive prevention, safeguarding business performance and user satisfaction.

Error analytics plays a crucial role in managing complex modern applications that rely on microservices, APIs, third-party integrations, and cloud infrastructure. These systems often face unexpected errors, which can lead to significant downtime costs and damage to user trust and brand reputation. By employing a structured approach to error analysis, teams can reduce downtime and enhance user experience. Tools like New Relic facilitate this process by aligning errors, traces, and logs into a cohesive workflow, enabling faster and more accurate root cause identification. Proactive error management strategies, such as defining reliability with service-level indicators (SLIs), adding context to errors, and automating responses to common failures, help teams prevent incidents and respond effectively when they occur. Observability and error analytics shift the focus from reactive debugging to proactive prevention, ultimately supporting business performance by ensuring more stable and reliable systems.

New Relic Predictions is an advanced tool that leverages AI and machine learning to shift IT teams from reactive incident response to proactive incident prevention, thereby enhancing operational efficiency and reducing downtime. By analyzing historical data, it identifies patterns and provides predictive alerts, allowing teams to address potential issues before they impact system performance. Key features include easy-to-use forecasting tools, causal analysis engines for understanding root causes, and seamless integration within the New Relic platform without the need for additional licenses. Predictive Alerts use the Holt-Winters algorithm for both seasonal and non-seasonal time series, automatically selecting the appropriate model based on historical data behavior. This functionality not only reduces alert fatigue but also maximizes system performance by efficiently allocating resources to critical areas, supporting various use cases such as infrastructure monitoring, application performance, and business strategy forecasting. The platform offers customization options for advanced users and is available under New Relic's Advanced Compute pricing, providing unlimited platform access with a usage-based pricing model.

Domain Naming System (DNS) resolution is a crucial process that converts human-readable domain names into machine-readable IP addresses, facilitating seamless internet navigation by serving as the internet's phone book. DNS resolution involves a sequence of lookups across a global network of servers, transforming domain names into IP addresses in milliseconds, and can be executed through recursive, iterative, or non-recursive methods. Challenges such as server unavailability, misconfigurations, and cache poisoning can impede DNS efficiency, while best practices like redundancy, appropriate TTL settings, and DNSSEC enhance performance and security. Monitoring tools, such as New Relic’s observability platform, offer comprehensive solutions for tracking DNS performance, ensuring reliability, and identifying potential security threats, thereby supporting a responsive digital experience.

New Relic has announced the General Availability of its enhanced Database Performance Monitoring, which provides deep query-level insights directly from database instances, improving the ability of DBA and infrastructure teams to diagnose and resolve performance issues without relying on application performance monitoring agents. This enhancement to the On-Host Integration (OHI) offers detailed visibility into slow queries, grouped query details, database wait types, and query execution plans for MySQL, Microsoft SQL Server, and PostgreSQL databases, including AWS Aurora/RDS compatibility. The tool allows for a comprehensive view of database performance across hybrid environments, supporting both self-hosted and cloud-based infrastructures. The installation process is designed to be user-friendly, with guided steps available in the New Relic One platform, and the integration helps standardize deep database monitoring, enhancing the reliability and performance of dependent services.

New Relic Predictions is an advanced AI-driven tool designed to shift IT operations from reactive incident response to proactive incident prevention by leveraging machine learning to analyze historical data and predict future trends and potential system issues. This capability allows IT teams to receive predictive alerts before issues impact users, thereby maintaining uptime and improving operational efficiency. Traditional alert systems notify teams only after problems occur, leading to prolonged downtime and potential revenue loss. New Relic Predictions addresses this by using algorithms like Holt-Winters to forecast and provide alerts for both seasonal and non-seasonal data trends, enabling resource allocation and preemptive action. The tool integrates seamlessly into the New Relic platform and offers customizable settings for advanced users, enhancing its adaptability to various IT requirements. Users can add forecasting to their alert conditions with ease, understand root causes with a causal analysis engine, and optimize system performance by visualizing trends, ensuring their systems remain optimized for peak performance.

DNS resolution is a crucial process that converts human-readable domain names into machine-readable IP addresses, allowing seamless internet navigation without the need for users to memorize complex numerical strings. This process involves several steps, including query initiation, contacting recursive and authoritative nameservers, and final connection establishment, typically completing in less than 100 milliseconds. Different resolution methods such as recursive, iterative, and non-recursive resolutions are used to balance efficiency and responsibility. Challenges like server unavailability, DNS record misconfigurations, cache poisoning attacks, and propagation delays can disrupt DNS resolution, but strategies like geographic redundancy, appropriate TTL settings, DNSSEC deployment, and regular monitoring can optimize performance and security. New Relic's observability platform offers comprehensive DNS performance monitoring, allowing users to track resolution times, error rates, and potential security threats, ensuring a reliable digital experience.

New Relic has announced the General Availability of its enhanced Database Performance Monitoring, which allows central infrastructure teams and DBAs to capture detailed query-level insights directly from MySQL, Microsoft SQL Server, and PostgreSQL database instances. This enhancement to the On-Host Integration (OHI) provides visibility into slow queries, wait types, and query execution plans, enabling faster identification and resolution of performance bottlenecks without needing access to application code or agents. The new functionality supports both on-premise and cloud environments, including AWS Aurora/RDS, allowing users to standardize database monitoring across hybrid infrastructures. The installation process is designed to be straightforward, with step-by-step guidance available through New Relic One, and users can view performance data via single-entity pages or multi-entity dashboards. This initiative aims to empower DBAs with the necessary tools to ensure database performance and reliability, enhancing the overall service quality for dependent applications.

New Relic has announced the general availability of its APM + OpenTelemetry Convergence, which aims to integrate OpenTelemetry (OTel) data into its existing application performance monitoring (APM) platform seamlessly. This convergence provides users with a unified observability experience by normalizing OTel data to conform with New Relic's APM semantic conventions, allowing for consistent monitoring, querying, and visualization across applications, whether instrumented with New Relic agents or OTel. The integration supports all major OTel languages and requires no additional configuration, enabling users to leverage New Relic's enterprise-grade analytics, AI-powered troubleshooting, and scalable backend. This approach seeks to eliminate data silos, offer flexibility, and future-proof instrumentation strategies without vendor lock-in, thus streamlining the transition between or combination of New Relic and OpenTelemetry tools.

A major upgrade to the Session Replay feature in New Relic's integrated Digital Experience Monitoring (DEM) solution enhances user experience analysis and troubleshooting with new functionalities. These updates introduce visual markers for JavaScript errors and Core Web Vitals indicators, allowing users to identify performance bottlenecks like Largest Contentful Paint (LCP) and Interaction to Next Paint (INP) more efficiently. The inclusion of smart issue aggregation and advanced filtering options streamlines the process of pinpointing critical issues by consolidating events and allowing targeted analysis. Additionally, the new Active Sessions indicator provides real-time insights into user behavior, and a full-screen replay mode offers improved clarity when monitoring complex workflows. These enhancements are designed to empower teams to address user experience issues more decisively, optimize collaboration, and make informed business decisions. The features are available immediately to all Session Replay users, with detailed guidance accessible through New Relic's documentation.

New Relic has announced the general availability of its APM + OpenTelemetry Convergence, offering a unified platform for monitoring and troubleshooting applications using OpenTelemetry (OTel) alongside traditional APM agents. This integration allows for the seamless normalization and visualization of OTel data, enabling consistent user experiences and standard querying across various data sources without the need for additional instrumentation or complex configurations. By supporting all major OpenTelemetry languages and offering out-of-the-box dashboards, New Relic aims to simplify migration efforts and reduce dependency on proprietary tools, providing enterprise-grade analytics, security, and AI-powered troubleshooting. The platform's strategic approach includes transparent consumption pricing, allowing users to pay only for what they use, while offering flexibility and scalability for different environments. This move is designed to future-proof instrumentation strategies, eliminate data silos, and streamline operations, with support available through New Relic's Explorers Hub for further guidance and integration options.

A major upgrade to the Session Replay feature within New Relic's Digital Experience Monitoring solution introduces several enhancements aimed at improving analysis and troubleshooting of user experience issues. The update includes new visual markers for key events like JavaScript errors and Core Web Vitals indicators, which help in quickly identifying performance bottlenecks. Features such as smart issue aggregation, advanced filtering options for targeted analysis, an "Active Sessions" indicator, and a full-screen replay mode are designed to streamline the process of resolving user issues. These enhancements empower teams to act more decisively, optimize collaboration, and gain real-time insights into user behavior, ultimately enabling smarter business decisions and more efficient management of high-demand enterprise applications. The updates are available immediately, with detailed guidance accessible in the New Relic Session Replay Documentation.

New Relic has introduced Compute Optimizer, a tool designed to help users optimize their compute usage and reduce costs by providing intelligent, data-driven recommendations for improving query efficiency. The tool identifies inefficient queries, particularly those related to compute-intensive products like Alerts, and offers clear optimization suggestions along with estimated cost savings. This feature aims to simplify the process of identifying and addressing costly queries for engineers and billing administrators, thus enabling organizations to maintain system performance while managing expenses effectively. Users can access Compute Optimizer through the New Relic platform, and new users are encouraged to sign up for a free account to start benefiting from the tool's capabilities. The article, authored by Jon Garside and Himanshu Gupta, emphasizes the importance of data-driven decision-making in optimizing compute resources and highlights their expertise in product marketing and management within the tech industry.

New Relic has launched Compute Optimizer, a tool designed to help organizations optimize their compute usage and reduce platform costs by identifying inefficient and costly queries. Compute Optimizer provides intelligent, data-driven recommendations for improving query efficiency, particularly in compute-intensive areas like Alerts, to maintain system observability while achieving cost savings. It offers clear guidance on optimization, estimates potential savings, and aggregates total savings potential, simplifying the process for engineers and billing administrators. Users can access the tool through the New Relic platform, and new customers are encouraged to sign up for a free account, which includes complimentary data ingest and user access. The blog post is authored by Jon Garside, Principal Product Marketing Manager, and Himanshu Gupta, Senior Product Manager at New Relic, both of whom emphasize the value of observability and data-driven decision-making in managing compute costs.

New Relic's Agentic AI Integrations for GitHub Copilot and ServiceNow are now generally available, marking a significant advancement in IT operations by incorporating real-time insights, automation, and decision-making capabilities. These integrations are designed to enhance observability and streamline workflows across Software Development Lifecycles (SDLC) and IT Service Management (ITSM) toolchains, allowing for more efficient and informed decision-making. By embedding intelligent insights and automation directly into platforms like GitHub and ServiceNow, New Relic aims to address issues of platform fragmentation, improve operational efficiency, and foster unified collaboration among stakeholders. The integrations leverage natural language processing to democratize access to observability data, enabling users to query system insights without complex query languages, thereby accelerating root cause analysis and reducing downtime. The introduction of features such as Role-Based Access Control and an expanded toolset further enhances their utility, supporting enterprises in achieving greater system resilience and operational excellence.

Agentic AI is revolutionizing enterprise IT operations by integrating with tools like GitHub Copilot and ServiceNow to provide real-time insights, automation, and decision-making capabilities, enhancing overall efficiency and reliability. New Relic's Agentic Integrations are now generally available, offering unique capabilities such as natural language-powered observability, which simplifies access to data by using natural language processing, allowing IT professionals to quickly obtain insights without complex queries. These integrations address common challenges like platform fragmentation and visibility gaps, enabling smarter decisions, improved efficiency, and unified collaboration by automating tasks and consolidating insights within familiar interfaces. By embedding intelligent insights and automation directly into platforms like GitHub, New Relic aims to eliminate deployment blind-spots and enhance system reliability, setting a new standard for observability and AI in IT operations.

Network performance monitoring (NPM) is crucial for maintaining optimal network operations by collecting, analyzing, and reporting on network metrics such as latency, jitter, packet loss, network errors, and bandwidth. This process enables IT teams to proactively identify and address potential issues, ensuring smooth application and service delivery, enhanced security, compliance with service level agreements, and cost optimization. Despite its importance, NPM faces challenges like complex network environments, alert fatigue, and security vulnerabilities. To overcome these, businesses should implement best practices such as establishing performance baselines, using real-time monitoring tools, automating routine tasks, and maintaining comprehensive documentation. Tools like New Relic offer features like AI-powered alerts and customizable dashboards to provide real-time visibility and ensure seamless monitoring as networks grow.

Kubernetes Monitoring with OpenTelemetry is introduced as a preview release aimed at enhancing observability in dynamic and complex Kubernetes environments by integrating OpenTelemetry Collector metrics, events, and logs with Kubernetes metadata into a single New Relic platform. This innovation facilitates rapid diagnosis of performance anomalies across pods, services, nodes, and namespaces without requiring additional agents or custom exporters. It offers zero-code, OpenTelemetry-native instrumentation, enabling automatic collection of pod, node, and container metrics/logs, and provides a unified observability experience that eliminates the need for multiple tools like Grafana, kubectl, or CloudWatch. Built on open standards like OpenTelemetry and Prometheus, it ensures flexibility, scalability, and vendor independence, making it suitable for large-scale clusters and modern CI/CD workflows. This initiative is led by Mikel Angulo, Product Manager at New Relic, who emphasizes the adoption of open standards and encourages engagement through the Explorers Hub for further discussion and support.

Network performance monitoring involves collecting, analyzing, and reporting on network metrics like latency, jitter, packet loss, and bandwidth to ensure optimal operation and support business objectives. It aids in proactive issue resolution, enhances security by detecting anomalies, assists in capacity planning, and optimizes costs by preventing downtime. This monitoring requires comprehensive data collection methods such as SNMP queries and deep packet capture, providing real-time visibility and traffic analysis to identify network anomalies and bottlenecks. Despite its benefits, network monitoring faces challenges due to complex environments and alert fatigue, necessitating tools that offer dynamic baselines and intelligent alert management to ensure effective performance management. New Relic’s network performance monitoring tool provides real-time visibility into network and application performance, AI-powered alerts to minimize alert fatigue, and customizable dashboards to tailor monitoring views, with integration capabilities for streamlined workflows.

Modern Kubernetes environments are characterized by their complexity and the presence of numerous ephemeral services and workloads, often posing challenges in obtaining the necessary contextual insights for effective service performance monitoring. To address this, a preview release of Kubernetes Monitoring with OpenTelemetry has been announced, offering an open, scalable, and efficient observability solution for cloud-native environments. This new capability integrates OpenTelemetry Collector metrics, events, and logs with Kubernetes metadata in a unified New Relic experience, allowing for seamless performance anomaly diagnosis across various Kubernetes components without requiring manual instrumentation. It enhances detection, troubleshooting, and collaboration among DevOps, SRE, and platform teams by eliminating the need for additional agents or custom exporters and consolidating disparate views from tools like Grafana, kubectl, and CloudWatch. With features such as Zero-Code OpenTelemetry-Native Instrumentation and curated dashboards, the solution ensures faster troubleshooting and future-proof observability investment, leveraging OpenTelemetry and Prometheus for flexibility and scalability in handling high-cardinality data. Users can easily get started by installing the OpenTelemetry Collector on their Kubernetes cluster, deploying the monitoring pipeline via the New Relic Helm chart, and configuring necessary details in the Helm values file, with further support available at the Explorers Hub community.

New Relic has been recognized for the 13th consecutive time as a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms, underscoring its commitment to innovation and customer satisfaction in the observability domain. The company's platform is praised for its AI and agentic orchestration capabilities, which integrate AI-powered observability into existing operations and workflows, with collaborations such as the integration with GitHub Copilot enhancing issue detection and resolution. Over the past year, New Relic has introduced over 25 platform innovations tailored to various industries, including healthcare and media, and has developed solutions like the intelligent streaming video observability tool. The platform's usage-based pricing model aligns costs with derived value, and it boasts native support for OpenTelemetry, facilitating easy data integration. Customer feedback on the Gartner Peer Insights platform further validates New Relic's reputation, with users highlighting its comprehensive monitoring features and user-friendly interface.

New Relic celebrates its 13th consecutive recognition as a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms, emphasizing its commitment to innovation and customer satisfaction. The company's CEO, Ashan Willy, highlights the significance of this achievement as a testament to New Relic's growth strategy and its integration of AI into observability tools, which are designed to enhance performance and reliability for critical projects. Over the past year, New Relic has expanded its partner ecosystem with AI integrations, including collaborations with industry leaders like GitHub Copilot, to streamline issue detection and resolution. The company has also introduced 25 platform innovations and industry-specific solutions, such as intelligent streaming video observability, to meet the evolving needs of enterprises. New Relic's usage-based pricing model aligns costs with value, and its platform has been adopted widely, as evidenced by a 30% quarterly growth in AI Monitoring usage. The company's customer-centric approach has resulted in high satisfaction ratings, with an overall score of 4.5 out of 5 on Gartner Peer Insights, underscoring its position as a trusted partner for observability solutions.

Distributed tracing in systems using Kafka is challenging due to Kafka's decoupled producers and consumers, which lack direct transactions to trace. However, monitoring Kafka clusters is possible with tools like OpenTelemetry, which offers two main approaches: zero-code and manual instrumentation. Zero-code instrumentation involves using an agent to automatically provide telemetry signals without changing the source code, offering quick setup but limited customization and visibility. Manual instrumentation, on the other hand, allows for more detailed and customized insights by adding dependencies and code, although it requires more effort. The blog demonstrates these concepts using a sample application with Kafka components, highlighting the differences in visibility between the two methods and encouraging exploration of OpenTelemetry's capabilities for enhanced application insights.

The blog post explains how to monitor Kafka clusters using distributed tracing and OpenTelemetry, highlighting the challenges due to Kafka's decoupled and asynchronous nature. It explores two approaches to instrumentation: zero-code and manual. Zero-code instrumentation, which uses an OpenTelemetry agent, allows for quick setup without modifying source code but offers limited customization and visibility. On the other hand, manual instrumentation involves adding dependencies and packages to the source code, providing more detailed and customizable telemetry at the cost of increased implementation effort. The author uses a sample application to demonstrate these techniques, showcasing how zero-code instrumentation provides a basic overview of service interactions while manual instrumentation offers deeper insights into specific code execution. The blog encourages exploring OpenTelemetry for better observability and invites readers to engage with the author for further discussion or questions.