April 2021 Summaries

New Relic One is a leading observability platform that has achieved FedRAMP-certification at the FIPS 199 “Moderate” impact level in 2020, providing trusted security technologies for highly regulated environments. The addition of Logs and Metrics to its supported services allows U.S. government customers and leaders to get real-time insights comparable to commercial organizations. This certification is seen as a benchmark of a company's commitment to security and privacy controls. New Relic's experience has shown that FedRAMP certification can help minimize costs and risk associated with cloud migrations, improve user experience, and accelerate government IT modernization.

New Relic emphasizes the importance of data protection and security for its customers, particularly those operating in highly regulated federal environments, by achieving FedRAMP certification at the FIPS 199 “Moderate” impact level for its observability platform, New Relic One, in 2020. This certification, along with the recent addition of Logs and Metrics to its services, allows U.S. government customers to gain real-time insights comparable to commercial organizations. The company highlights the significance of FedRAMP certification as a benchmark for security and privacy controls, noting that both governmental and non-governmental clients value this accreditation. In a recent Nerdlog episode, New Relic's Greg Poirier and James Stibbards discuss the benefits of compliance, including reduced costs and risks in cloud migrations, improved user experiences, and the acceleration of government IT modernization. The company encourages customers to participate in discussions and updates through its Nerdlog events and documentation, while also providing a pathway for non-customers to sign up for a free account to explore its offerings.

In today's digital landscape, having a great mobile experience is crucial for businesses to avoid customer losses and revenue decline. According to App Annie's State of Mobile 2021, time spent in business apps grew 275% year-over-year, highlighting the importance of reliable mobile apps. Distributed tracing plays a vital role in running reliable mobile apps by tracking requests from mobile devices to backend services, providing visibility into issues and their source. With New Relic mobile monitoring, mobile app engineers can quickly discover which backend services impact customer experience, and both frontend and backend developers can see traces that originate from a mobile device. To incorporate distributed tracing with New Relic mobile monitoring, users need to deploy the latest mobile agent, review transition guides and documentation, and navigate to the distributed tracing navigation tab or Browse Data > Traces to view trace details and troubleshoot performance issues.

In the context of mobile apps, ensuring a smooth user experience is crucial for retaining customers and driving revenue, especially as time spent on business apps has significantly increased. Distributed tracing plays a vital role in maintaining reliable mobile applications by tracking requests from mobile devices through backend services, allowing for quicker error detection and resolution. New Relic offers a mobile monitoring solution that incorporates distributed tracing, enabling both frontend and backend engineers to identify how backend service issues affect customer experiences. Updating or deploying New Relic mobile agents allows app developers to access detailed trace data, facilitating effective troubleshooting of performance issues by providing insights into interactions between mobile requests and backend services. The blog emphasizes the importance of distributed tracing in mobile app performance monitoring and provides guidance on integrating New Relic’s mobile monitoring tools to enhance app reliability.

New Relic has partnered with Algorithmia to provide a seamless integration between their observability platform and Algorithmia's enterprise machine learning operations (MLOps) platform, allowing for real-time monitoring of model performance metrics in production systems. This partnership enables data scientists and DevOps engineers to track and detect model drift, data drift, and model bias, and relay that information efficiently to teams developing and operating these models. With New Relic's Insights feature, users can create dashboards, use alerts to analyze model performance metrics, and manage alert policies and conditions, all while leveraging Algorithmia's MLOps platform to streamline models into the observability platform. The integration allows for seamless collaboration between data science and DevOps teams, leading to innovative solutions and improved operation and monitoring of software.

Deploying a new machine learning (ML) model into production requires effective monitoring to track model drift, data drift, and model bias, ensuring that the model's performance continues to enhance business outcomes. This tutorial explains how data scientists and DevOps engineers can utilize New Relic's integration with Algorithmia to monitor ML model performance metrics seamlessly. Through this collaboration, teams can streamline models into an observability platform, create dashboards, and set up alerts to analyze model performance in real-time, promoting efficient collaboration between data science and DevOps teams. New Relic Alerts and Applied Intelligence provide a centralized notification system that helps detect anomalies and reduce alert noise, while Algorithmia Insights offers a metrics pipeline to monitor ML models. The integration process involves setting up an MLOps-focused dashboard, configuring data flow from Algorithmia to New Relic, and managing alert conditions based on ML metrics, ultimately leading to improved ML model performance and comprehensive observability into ML-powered applications.

When a company like myToys Group, which was born in an on-premises world, decided to move to Amazon Web Services (AWS), the primary motivation was scale and speed. The company chose to start with its highest-value application as a pilot project, but this approach may not be suitable for organizations without experienced team members. A generous buffer should be included in the timeline to account for unexpected delays. It's essential to measure customer impact by tracking conversion rates and using tools like New Relic to compare metrics between on-premises and AWS environments. Instrumenting everything early in the process can help identify issues, improve knowledge of services, and enhance planning. Finally, planning for post-migration product ownership is crucial to ensure operational excellence and knowledge retention within teams. By following these best practices, companies can successfully migrate to the cloud and achieve scalable infrastructure.

When Oleksii Svarychevskyi joined myToys Group as head of technology, the company was transitioning from on-premises infrastructure to Amazon Web Services (AWS) to enhance scalability and speed. The migration strategy involved choosing a high-value pilot project due to the existing AWS experience within the team, planning for potential delays, and ensuring customer impact was measurable through tools like New Relic. They faced challenges such as disparate observability tools and network latency, which were addressed by instrumenting systems early and using AWS Direct Connect. The company adopted a "You build it, you run it" approach for post-migration product ownership, which facilitated operational excellence and allowed for further migration of over 80% of their systems to AWS. This transition enabled rapid scaling and set the stage for automation in scalability, with the experience providing valuable insights for similar organizations considering cloud migration.

Ocado Group is a British online grocery technology company that utilizes cutting-edge automation technology in its warehouses, including machine learning for demand forecasting and custom robots to pick items. The company's business model relies on large, dedicated warehouses with no physical stores, and it has made the Ocado Smart Platform available to other retailers worldwide. Ocado uses Micrometer as part of its metrics and monitoring system, Flux, which provides complex, business-oriented metrics such as order abandonment rate and calculates these metrics using Amazon Kinesis and CloudWatch. The company tracks three main metrics for its event stream processing system: rate, loss, and delay, created using Micrometer and sent to both Prometheus and New Relic. Micrometer offers advantages such as close association with the Spring framework, vendor-neutrality, and support for four main metric types, including counters, gauges, timers, and distribution summaries, which provide flexibility in terms of investigations and creating alerts.

The Linux kernel has introduced eBPF (Extended Berkeley Packet Filter), a lightweight, sandbox virtual machine that allows developers to run BPF bytecode directly within the kernel. This technology eliminates the need to modify kernel source code and streamlines access to existing layers. eBPF offers several advantages, including speed, low intrusiveness, security, convenience, unified tracing, programmability, expressiveness, real-time data capture, and better performance compared to traditional tracers. However, it also has some limitations, such as being restricted to Linux and a recent kernel version, and potentially limited sandboxed programs. eBPF is widely used in various fields like system administration, cybersecurity, networking, and software development for real-time system monitoring, security, networking, application performance monitoring, and versatility. It provides unprecedented insights into system behavior and performance, revolutionizing the way engineers monitor systems, troubleshoot issues, and optimize performance.

Ocado Group, a British online grocery technology company, utilizes advanced automation technologies, including machine learning for demand forecasting and custom robots in its warehouses, to manage its online grocery operations and partnerships with international retailers such as M&S, Morrisons, and Kroger. The company's monitoring architecture, known as Flux, leverages Micrometer for metrics collection and analysis, integrating with platforms like Prometheus and New Relic for comprehensive monitoring and alerting. This system facilitates the generation of complex, business-oriented metrics, such as order abandonment rates, by processing business events through Amazon Kinesis and storing results in AWS CloudWatch. Micrometer's vendor-neutral framework supports various metric types and provides flexibility through a dimensional data model, enabling detailed aggregation and alert creation. This approach allows Ocado to maintain high-performance monitoring without being locked into specific vendor solutions, offering a scalable and reliable metrics system for their automation-heavy operations.

eBPF, or Extended Berkeley Packet Filter, is a transformative kernel technology that extends the capabilities of the original BPF, going beyond network packet filtering to provide extensive observability and performance monitoring within the Linux kernel. Introduced in Linux 4.x, eBPF allows developers to run sandboxed programs directly within the kernel without modifying its source code, enhancing efficiency, security, and granularity of control over system behavior. This innovation facilitates real-time data collection and analysis, making it invaluable for tasks like security monitoring, network management, and application performance monitoring. Despite its powerful capabilities, eBPF requires a deep understanding of kernel-level programming and has limitations, such as being restricted to newer Linux kernels and potential performance overhead. With its versatility and efficiency, eBPF is gaining traction in fields like system administration and cybersecurity, offering a unified framework for tracing processes and a more nuanced view into system operations.

As Nočnica Fee mentioned, logs are a fundamental component of observability, providing detailed information about an application's function. New Relic has continued to innovate in log management, introducing features like log patterns that use machine learning to cluster and detect patterns in log data automatically, allowing users to quickly troubleshoot and gain insights into their entire stack. The company also offers guided install to add log data to New Relic One within minutes, making it easy for developers to instrument their applications and infrastructure. Additionally, parsing and partitioning log data has been improved with built-in rulesets and custom rule creation options, enabling users to manage logs in a structured way. Overall, these features aim to simplify log management and provide users with more control over their log data.

Logs, a fundamental component of observability alongside metrics, events, and traces, contain detailed information about application functions. A recent discussion on Nerdlog Roundup highlighted innovations in log management, including machine learning capabilities for clustering, pattern detection, and outlier identification in log data, which facilitate quicker troubleshooting and insights. Log patterns can help users create queries, alerts, and dashboards, focusing on significant data changes. Additionally, parsing and partitioning log data into attribute/value pairs allow for better organization and insight, with New Relic offering both built-in and custom rules for parsing logs. The guided install feature simplifies adding log data to New Relic One, enabling users to instrument applications quickly and access insights within minutes. These advancements in log management were demonstrated by experts in a recent Nerdlog episode, showcasing the effectiveness and functionality of these new features.

The latest innovations in log management capabilities for New Relic One aim to provide end-to-end observability by breaking down silos between log data and other telemetry. The new features include the ability to detect patterns and outliers, simple analytics, partitioning of data for lightning-fast search performance, and easier onboarding processes. These enhancements will help users troubleshoot problems faster, reduce manual correlation efforts, and scale self-hosted logging tools more efficiently. With these updates, New Relic One offers a free log management solution with up to 100 GB/month, making it an affordable option for organizations of all sizes.

New Relic has significantly enhanced its log management capabilities within New Relic One, aiming to offer engineers and developers greater visibility and efficiency in managing log data. These improvements include advanced features such as pattern and outlier detection using machine learning, an updated user interface for more intuitive log analytics, and the ability to partition data for faster search performance. The platform also simplifies log onboarding through various methods, including native Heroku cloud support and agentless syslog support, allowing organizations to ingest up to 100 GB of data per month for free. These enhancements are designed to reduce troubleshooting time and improve the overall observability of software systems, providing a centralized view that helps streamline the process of correlating logs with application errors and traces.

The cloud has transformed the way businesses operate, but it also creates new challenges, including attaining observability into the cloud ecosystem to manage it correctly. A cloud center of excellence (CCOE) is crucial in developing and implementing cloud solutions, but operational efficiency starts with having tools that provide visibility into cloud infrastructure. An observability platform addresses problems such as bloat, errors, non-compliance, data quality, and automation challenges, enabling a CCOE to streamline infrastructure, identify issues before they cause disruption, achieve compliance, develop deeper operational insights, and leverage automation with confidence.

Cloud applications have largely replaced legacy systems like filing cabinets in modern business operations, with approximately 85% of businesses utilizing cloud technology for key functions, transforming business practices. However, while the cloud offers cost-effective solutions and increased computing power, it also introduces challenges, particularly in maintaining observability within cloud ecosystems. A Cloud Center of Excellence (CCOE) is crucial for implementing cloud strategies and achieving operational efficiency through enhanced observability, which allows businesses to streamline infrastructure, identify and resolve issues proactively, adhere to compliance regulations, gain deeper operational insights, and effectively leverage automation. Observability not only ensures efficient cloud management but also empowers teams to make informed decisions, optimize processes, and maintain a competitive edge.

Synthetic monitoring is a crucial aspect of ensuring website functionality and preventing IT downtime costs. To make synthetic monitoring more accessible, New Relic has introduced several updates, including a new step monitor type that allows users to set up monitors without code, a Quickstarts Synthetic Monitoring library with pre-built scripts, and enhanced visualization in Lookout. The step monitor provides a no-code way to create synthetic monitors by adding "steps" and entering actions, such as verifying text or elements on the page. Users can also utilize templates from the Quickstarts library to get started faster. Additionally, synthetics are now integrated with Lookout, allowing users to view performance changes across all monitors in a single view. To set up a step monitor, users follow a streamlined process that separates different monitor types into cards and guides them through the setup process. They can then configure the monitor, select locations for testing, enter steps, test the monitor before deployment, and troubleshoot any errors. The updated experience also includes a Selenium IDE script generator to facilitate more advanced tests.

New Relic has improved its log features with a clearer UI, making it easier to find functions and scan through logs quickly, thanks to a new log summary view that picks out key-value pairs and custom visualization feature that combines log messages with telemetry data. Additionally, New Relic now integrates with Heroku via a "logs drain" allowing users to view syslog entries within the platform and create custom dashboards based on log information.

Synthetic monitoring is crucial for maintaining the functionality of e-commerce websites, especially during critical updates or sales, by continuously testing business processes and alerting teams to issues before customers notice. New Relic has enhanced its synthetic monitoring tools to simplify setup and management, introducing the step monitor, which requires no coding, thus enabling more users to implement it. The Quickstarts Synthetic Monitoring library provides pre-built scripts, while integration with Lookout allows users to visualize performance and detect issues across their sites. The updated user interface separates monitor types into cards, guiding users through setup, and offers options like error detection, geographic testing, and advanced script editing. These improvements aim to streamline the monitoring process, ensuring website reliability and performance.

New Relic has enhanced its log management features within New Relic One, making it easier for users to send logs and visualize them alongside other telemetry data. A new user interface now presents log features such as parsing and drop filters more clearly, and a log summary view that highlights key-value pairs for quick scanning. Additionally, a custom visualization feature allows users to integrate log messages with existing telemetry data in dashboards. New Relic has also introduced integration with Heroku, enabling users to view syslog entries and create custom dashboards based on log information. This integration involves setting up a "logs drain" to send logs from Heroku to New Relic One, with detailed instructions provided for setup. New Relic encourages users to join the Nerdlog discussion on Twitch for weekly updates and insights into the latest features and releases.

New Relic has been recognized as a Leader in the 2021 Gartner Magic Quadrant for Application Performance Monitoring for the ninth time, showcasing its ability to execute and completeness of vision. The company's customers, including 50% of the Fortune 100, rely on New Relic daily to solve technology and business challenges. To improve customer satisfaction, New Relic has undergone a business transformation, augmenting its product, sales, and customer success functions, and simplifying its pricing model to include a perpetually free tier. The company continues to innovate with Full-Stack Observability, offering one front end for APM, Infrastructure, Logs, and more, on top of a single, unified data set. New Relic's commitment to customer feedback is evident in its high overall rating of 4.7 out of 5 among various vendors, recognized as the Customers' Choice in 2020. The company encourages customers to share their stories and join the Gartner Peer Insights crowd to weigh in on the latest developments.

Since its founding in 2008, New Relic has focused on providing software performance insights, with its flagship product, New Relic APM, launching in 2009. The company has been recognized as a leader in the 2021 Gartner Magic Quadrant for Application Performance Monitoring, marking the ninth time it has received this accolade for its execution and vision. More than 14,000 customers, including half of the Fortune 100, use New Relic to address various technology and business challenges, such as cloud adoption and enhancing digital customer experiences. The company has shifted from a subscription to a consumption pricing model, introduced a free tier, and continues to innovate by enhancing its Full-Stack Observability and expanding capabilities, such as through the acquisition of Pixie Labs. Customer feedback is highly valued, as evidenced by New Relic's high ratings in Gartner's customer surveys, and the company remains committed to improving usability, functionality, and innovation in its offerings.

New Relic has launched a new user management and access security model for existing customers, aiming to provide increased flexibility, security, and efficiency in managing observability access for teams. The new model allows administrators to manage users across their organization, assign access based on predetermined groups, and apply permissions and security settings with improved security posture. It also introduces flexible authentication options, including the ability to use different authentication methods for different teams and reduce logins required for SAML single sign-on organizations. Additionally, the new model enables more granular roles, automated user management, and reduces manual administration burden by integrating with identity and access management providers. Existing customers on AUM are already using the new model, and those interested in migrating can explore migration docs, talk to their account manager, or begin the guided migration process within their account settings page.

New Relic has introduced a new user management and access security model aimed at enhancing flexibility, security, and efficiency for engineering and IT organizations, which is now available to existing customers. This model, initially launched with New Relic One in July 2020, simplifies user management by reducing the steps required to manage users across multiple accounts, enabling organizations to manage users based on groups rather than individual accounts. It provides a unified view of all users, allows for the application of consistent permission settings, and supports various authentication methods, including SAML single sign-on, to accommodate diverse team needs. The model also introduces more granular roles, such as Billing User and Organization Manager, to distribute administrative responsibilities and reduce bottlenecks. Additionally, enterprises can leverage automated user management (AUM) for efficient user management via identity providers that support the SCIM standard, further reducing manual administrative efforts. Existing accounts already on AUM or created post-July 2020 are automatically using this new model, and resources are available for users interested in migrating to the updated system.

New Relic One synthetics monitoring capabilities help detect and resolve poor performance and outages before customers notice. With 10,000 synthetics checks per month included with free accounts, users can test complex user flows on their website without writing code. The new step builder feature allows users to easily create monitors that verify users can log in, perform actions like logging into a website or adding items to a shopping cart, and verify elements appear on the page. Users can locate elements by CSS class, HTML ID, link text, or XPath, and view performance metrics such as request/response times, error response codes, duration, and metadata and tags. Additionally, synthetics monitoring allows users to ping from multiple geographic locations, making it easier to localize problems and save time.

New Relic One offers advanced synthetics monitoring capabilities that allow users to detect and resolve website performance issues and outages proactively. The platform provides a new step builder feature that facilitates end-to-end testing of complex user flows on websites without the need for coding, simplifying the process of testing actions such as logging in or checking out. Users can create monitors using various methods to locate elements, such as CSS class, HTML ID, or XPath, and can edit the generated Selenium IDE scripts for more advanced testing. With the ability to monitor from multiple geographic locations, New Relic One enables precise identification of region-specific issues, which is crucial for replicating errors experienced by certain user subsets. Additionally, New Relic offers a free account option that includes 10,000 synthetic checks per month, making it accessible for users to set up comprehensive monitoring processes.

New Relic's observability platform is a FedRAMP-certified technology that enables US government agencies to instrument their digital environments and collect real-time telemetry data. The platform provides contextualized and curated data, allowing application owners, IT administrators, developers, security officers, and compliance officers to make informed decisions. New Relic mitigates the risks of cloud migrations by providing critical information about applications, tracking cloud preparedness, and monitoring real-time performance. It also improves user experience and loyalty by enabling real user monitoring across multiple interactions, channels, and products. The platform includes key security controls such as regular security scans, vulnerability management, and disaster recovery plans. With FedRAMP authority to operate, New Relic enables government IT leaders to get real-time insights while maintaining compliance with established security standards.

New Relic One is a FedRAMP-certified observability platform designed to support federal agencies by providing real-time insights into their IT environments, which include traditional on-premises systems and modern cloud-native applications. The platform offers a comprehensive view of application performance, facilitating secure cloud migrations and optimizing cloud usage and costs through tools like the New Relic One Cloud Optimization app. New Relic enhances user experience by offering stakeholders a unified view of citizen interactions across various channels while ensuring compliance with security standards through rigorous third-party assessments and continuous monitoring. It is available through Carahsoft Technology Corp.'s GSA Schedule, which simplifies procurement for federal, state, and local government agencies.

Monitoring and observability are often used interchangeably, but they serve distinct purposes in managing complex systems. Observability is about having the flexibility to ask why, providing a deeper understanding of issues beyond just identifying problems. High-cardinality data is essential for isolating root causes, allowing users to investigate individual transactions and analyze attribute distributions. Most monitoring tools struggle with high-cardinality data due to scalability limitations, leading to reduced storage duration, sampled or aggregated data, and punitive costs. New Relic's platform is designed to handle high-cardinality data, providing a powerful telemetry data platform that empowers users to ask any question of their data in real-time, combining metrics, events, logs, and traces in a unified platform.

New Relic is undergoing a transformation to align its growth and success more directly with its customers' adoption and consumption of its platform. This shift involves a consumption-based business model that focuses on delivering value to users, which requires changes in sales, marketing, and general and administrative expenses. The company will simplify roles in sales and customer adoption to focus on user success, decrease spend in these areas, and invest more in product and R&D to deliver transformational innovation. As part of this strategy, New Relic is reducing its workforce by nearly 120 employees in the US and up to 40 internationally, providing severance packages, extended benefits coverage, equity vesting, individual career outplacement support, and giving impacted employees their laptops and work equipment to keep for personal use. The company's new strategy aims to help customers realize the full value of its platform to solve business challenges, which will fuel the growth of its business.

The blog post discusses the importance of distinguishing between monitoring and observability in managing complex, distributed systems like websites, highlighting that while monitoring provides alerts for known issues, observability allows for deeper investigation into unknown problems. It emphasizes the need for high-cardinality data to effectively diagnose and resolve issues by offering detailed insights beyond aggregated metrics. The article explains that monitoring tools often struggle with scaling and data granularity, limiting their utility in real-time problem-solving. It advocates for platforms like New Relic, which are designed to handle high-cardinality data, enabling users to conduct detailed queries on their telemetry data across metrics, events, logs, and traces, thereby providing comprehensive insights into system performance. The post also mentions the capabilities of New Relic's platform, such as its ability to process petabytes of data quickly and offer affordable data ingestion pricing, and encourages interested readers to explore further through their free account offering.

New Relic has announced a strategic shift to a consumption-based business model, resulting in significant organizational changes aimed at enhancing customer engagement and platform value. This transition includes a reduction in workforce by nearly 120 employees in the US and up to 40 internationally, as part of an effort to realign company operations and reduce spending on Sales, Marketing, and G&A in favor of increased investment in Product and R&D. The move is designed to simplify roles in Sales and Customer Adoption, aligning them with user success and encouraging greater platform usage. CEO Lew Cirne expressed confidence in the new strategy despite the difficulty of the layoffs, emphasizing the company's commitment to supporting impacted employees through severance packages, extended benefits, and career support. The restructuring aims to fuel business growth by focusing on delivering value to users, which in turn is expected to increase platform adoption and customer success.

New Relic has introduced two new features to improve its NRQL query language: a regular expression filter and the ability to create smooth, accurate charts with sliding time windows. The new features aim to provide users with more flexibility in creating custom charts and data visualizations, allowing them to easily visualize their data and gain high-level insights. Additionally, New Relic has introduced nested queries, which enable users to simplify their data further by reducing cardinality by multiple degrees. These updates are designed to enhance the overall user experience of using NRQL, making it easier for users to get started with writing custom charts and visualizations. With these new features, users can now create more complex and customized dashboards, including multiple charts, and filter their queries with regular expressions. The introduction of sliding time windows also allows users to smooth out data points, resulting in clearer signaling and better visualization of trends.

New Relic offers powerful tools for custom data visualization and log management, featuring the New Relic Query Language (NRQL) and a query builder that enables users to create tailored charts and dashboards. Recent updates have introduced two enhancements to NRQL, including the ability to use regular expressions for more precise query filtering and sliding time windows for smoother charting. The platform also supports nested queries for data simplification, allowing for more comprehensive analysis. Users can engage with ongoing discussions and updates via the Nerdlog, a weekly event on Twitch, providing insights into the latest features and developments by New Relic's team.