August 2024 Summaries

The text discusses the challenges of debugging complex issues in distributed systems and how to use New Relic to understand and observe these systems at scale. It highlights the importance of adding relevant data to transactions, such as upstream application information and trace IDs, to improve debuggability. The article provides examples of how to instrument Ruby on Rails and Java Spring applications with custom attributes using New Relic's Agent, and demonstrates how distributed tracing can be used to track complex issues across multiple services. It also showcases the benefits of using New Relic for debugging complex issues in distributed systems, including improved visibility into system calls and individual transactions, and provides resources for further guidance and support.

Over the past two decades, the transition of distributed systems from specialized fields to everyday enterprise operations has necessitated enhanced observability and understanding of these systems at scale. New Relic offers tools to address the challenges of tracking errors and latency issues in distributed architectures by enabling instrumentation and distributed tracing. Key performance metrics such as payload size, request duration, and success rates can be enhanced with additional attributes like "traceId" and "upstreamApplication" for effective debugging. Implementing these attributes can be easily achieved in applications developed with frameworks like Ruby on Rails and Java Spring, facilitating the tracing of requests across microservices and identifying the root causes of errors. New Relic's distributed tracing capabilities allow for seamless tracking of individual transactions and provide insights into application dependencies and performance through a user-friendly interface, ultimately simplifying the debugging process in complex distributed infrastructures.

Observability is a key component in accelerating the adoption of Artificial Intelligence (AI) by enabling CIOs and CTOs to monitor, analyze, and manage complex systems and data in real-time. This allows for faster time-to-insight and better decision-making, ultimately driving business value. By leveraging observability tools, organizations can identify issues before they become major problems, reduce downtime, and improve overall system performance. Additionally, observability provides a single source of truth for understanding AI model behavior, enabling data-driven decision making and reducing the risk of model drift or bias.

Observability is a critical component in accelerating the adoption of Artificial Intelligence (AI) by CIOs and CTOs, as it enables them to monitor, analyze, and improve the performance of complex systems and applications. By gaining visibility into system behavior, organizations can identify issues before they become major problems, optimize AI models for better results, and develop more effective strategies for managing risk and uncertainty. Observability also helps organizations to provide better support for their users by identifying areas where AI is not meeting expectations and making data-driven decisions about how to improve it. This enables CIOs and CTOs to make informed decisions about the adoption of AI technologies and ensure that they are aligned with business goals and objectives.

Observability is a critical aspect of modern application and infrastructure management, encompassing metrics, logs, events, and traces to provide actionable insights into system performance and behavior. It extends this concept to the complex world of AI-powered applications, enabling organizations to optimize for accuracy, efficiency, and reliability, while mitigating risks such as bias and drift, and addressing security and compliance concerns. The challenges of AI adoption include complexity, operational efficiency, scalability and performance, cost management, data quality and fairness, security and compliance, culture and skill set. Observability can simplify AI application deployment, maintain operational efficiency, ensure scalability and performance, manage costs, ensure data quality and fairness, enhance security and compliance, and foster a cultural transformation. By integrating observability into AI adoption strategies, organizations can navigate the complexities of AI implementation more effectively, ensuring sustained success and a competitive edge in the AI-driven landscape.

AI is poised to significantly impact global economies, potentially adding trillions of dollars annually, as highlighted by a McKinsey report. The successful adoption of AI involves overcoming challenges related to deployment complexity, operational efficiency, scalability, cost management, data quality, security, compliance, and cultural adaptation, with observability playing a vital role in addressing these issues. Observability, defined as the ability to infer a system's internal states through its outputs, is crucial for managing AI applications, offering insights into performance, data quality, and system behavior. It aids in streamlining AI deployments, maintaining operational efficiency, optimizing resource use, and ensuring data accuracy and fairness, while also enhancing security and compliance. By fostering transparency and collaboration, observability supports cultural and skill transformations necessary for AI readiness, enabling organizations to navigate AI adoption complexities effectively and achieve sustained success in an AI-driven world.

New Relic Change Tracking is a solution that helps developers and operations teams identify the root cause of issues after updates by providing a clear picture of how modifications impact software systems, including "who, what, when, and why" behind changes. This solution integrates with existing development workflows and offers features such as correlating changes to performance impact, simplifying troubleshooting, and boosting collaboration. It also empowers users to proactively reduce the risk of negative impacts from changes by introducing controlled deployment strategies, such as canary deployments, blue-green deployments, feature flag deployments, and rolling updates. Additionally, New Relic Change Tracking offers advanced capabilities like capturing environment variables and build versions, providing a richer context for change history, and transforming change tracking into a strategic tool for informed decision-making.

Change tracking is a vital tool for developers and operations teams, helping manage and understand the impact of modifications within software systems. New Relic offers a comprehensive change tracking solution that integrates seamlessly with existing workflows, allowing teams to record all deployments, code updates, and infrastructure changes. This system helps correlate changes with performance impacts, simplifies troubleshooting, and boosts team collaboration by offering a centralized view of all changes. New Relic's change tracking also supports deployment strategies such as canary, blue-green, feature flag, and rolling updates, which minimize risks and ensure controlled rollouts. Advanced features like capturing environment variables and build versions enrich the change history, enabling deeper insights and data-driven decision-making. By leveraging these capabilities, teams can transform change tracking into a strategic tool, ensuring a smooth and efficient development process.

At Car IQ, a real-time financial transactions company, they aimed to monitor and resolve issues quickly to maintain customer satisfaction. To achieve this, they implemented dashboards with distributed tracing agents, alerts, and synthetic monitoring. The dashboards provided a high-level view of infrastructure performance, allowing them to identify issues instantly. They fine-tuned their alert thresholds to ensure only critical errors reached their teams, enabling swift action and minimizing alert fatigue. Synthetic monitoring enabled regular checks on their systems, validating data integrity and performance. By automating their DevOps processes, Car IQ reduced costs, increased engineering team delivery rates, and shifted focus towards product development and strategic partnerships.

Car IQ has implemented a robust monitoring system using New Relic to enhance the reliability of its real-time financial transactions at petrol pumps, aiming to address issues before customers report them. The company employs dashboards for infrastructure oversight, finely-tuned alerts to avoid alert fatigue, and synthetic monitoring for regular system checks. This integration has significantly improved their mean time to recovery (MTTR), reduced infrastructure issues, and enhanced developer workflow by automating problem detection and resolution. As a result, the company has seen a 50% improvement in engineering team delivery rates, allowing them to focus on innovation and strategic growth rather than constant firefighting. The views expressed in the blog are personal to the author, Christian Gerrard, and do not necessarily represent those of New Relic.

The New Relic user flows app is a tool that helps businesses understand their users' journeys and experiences by analyzing every action and page visited on their website. By consolidating user flow details and performance impacts into one screen, it provides insights to product and engineering teams to spend resources on the right set of features, improve user adoption, and drive business outcomes. The app is designed for single-page application architecture and requires specific setup and configuration before use. It offers various features such as flow analysis, funnel conversion, and stepwise performance tracking, enabling businesses to make data-driven decisions to enhance user satisfaction and achieve their objectives.

A user flow, or user journey, is the path an end user takes through a website to complete specific tasks, and understanding these flows is essential for enhancing user interactions, business outcomes, and revenue growth. Analyzing user flows allows businesses to better understand customer personas, improve user adoption, and optimize product features. However, many tools require complex integrations and do not provide performance insights for DevOps teams. The New Relic user flows app offers a streamlined solution by consolidating user flow details and performance impacts into a single platform with a simple setup. This app captures real user interactions, provides funnel conversion insights, and visualizes user flows through flow diagrams, while also offering query tools for performance analysis and troubleshooting. It enables businesses to make data-driven decisions to enhance user satisfaction, drive conversions, and achieve business objectives.

New Relic has been named a Leader in the 2024 Gartner Magic Quadrant for Observability Platforms, marking its 12th consecutive year as a Leader. This recognition demonstrates New Relic's commitment to helping businesses like Domino's and Mercado Libre stay ahead in their respective markets. The proliferation of monitoring tools is driving operational complexities, but New Relic addresses these challenges with its unified observability platform, providing a holistic view of technology landscapes and deep context for troubleshooting. Innovation is at the core of New Relic's success, with recent collaborations like NVIDIA and launches of AI-driven solutions such as DEM and Pathpoint. Customers have consistently rated New Relic highly, with 90% willingness to recommend the platform and an overall rating of 4.5 stars out of 5.0 on Gartner Peer Insights.

New Relic has been recognized as a Leader in the 2024 Gartner Magic Quadrant for Observability Platforms, marking its 12th consecutive year receiving this accolade. This recognition highlights New Relic's commitment to helping clients like Domino's and Forbes Media manage the growing technological complexities and improve operational efficiency with their unified observability platform. The company emphasizes innovation through partnerships, such as with NVIDIA, and advancements in AI-driven solutions and OpenTelemetry support. New Relic offers a flexible consumption pricing model and is highly rated by customers for enhancing system resilience, providing insightful data analytics, and delivering superior customer experiences. The company's ongoing mission is to make observability accessible to all businesses, maintaining consistent high ratings and recommendations from its users.

The New Relic browser agent provides a way to capture raw log data from web applications for more thorough debugging and analysis. The agent has two API methods, `log` and `wrapLogger`, which allow developers to manually capture browser logs emitted by their web applications. This feature is useful for spotting errors or inconsistencies that may not be visible through traditional error tracking, obtaining verbose log messages with finer granularity, gaining insight into user behaviors, and easily organizing and triaging logs. The process of installing and configuring the browser agent involves selecting a deployment method, choosing an existing app monitored in APM, or naming a new app and enabling it. The `log` API captures data as a single log event, while the `wrapLogger` API instruments methods to capture log events on every call, simplifying the process of capturing logs across entire application ecosystems. Captured browser logs can be viewed, sorted, and customized within the logging view to help break down issues and improve understanding of the application's impact on customer experience.

The New Relic browser agent allows users to monitor the performance, errors, and user interactions of web applications by collecting data on page load times, Ajax requests, JavaScript errors, and custom events, which are then analyzed and visualized in New Relic. To enhance debugging, it now offers API methods for capturing raw browser logs manually, which can help identify issues not caught by traditional error tracking and provide detailed insights into user behavior and application processes. Users can manually capture log events with the "log" API for specific cases or use the "wrapLogger" API to automatically capture logs from existing methods, facilitating comprehensive logging across the application. The collected logs can be viewed, sorted, and customized within the application's logging view to assist in troubleshooting and improving customer experience, and the functionality is available from browser agent version 1.261.0 and higher.