June 2020 Summaries

New Relic Applied Intelligence (AIOps) helps diagnose issues faster by eliminating noise from alerts and providing actionable insights. It correlates related alerts into one issue using machine learning and user-generated decisions, allowing for prioritization and focus on critical issues. By creating and fine-tuning decisions, users can tailor the correlation logic to their system, reducing unnecessary alerts and improving incident response processes. The AIOps platform provides real-time feedback, enabling users to refine their decision-making and achieve faster mean time to resolution (MTTR). With features like flapping detection and suppression, users can reduce alert fatigue and improve overall system performance. By leveraging machine-based decisions and user-generated suggestions, New Relic AI helps organizations optimize their incident response processes and gain greater visibility into their systems.

The concept of "more perfect software" has become essential for business competitiveness in today's digital age, with companies prioritizing development, performance optimization, and life cycle management to deliver outstanding customer experiences. A recent research survey of hundreds of software professionals found that top performers excel in five key areas: cloud maturity, observability mastery, end-to-end data visibility, digital resilience, and free-to-thrive teams. These organizations have a higher success rate against business metrics such as financial performance, growth, innovation, employee engagement, and brand perception compared to their peers. By strengthening these capabilities, companies can release their engineers from firefighting duties and push customer-facing experiences to new heights.

New Relic Applied Intelligence (AI) is designed to alleviate alert fatigue by correlating related alerts into single actionable issues through machine learning and user-generated decisions. This system helps prioritize and focus on the most critical issues by reducing the number of alerts received, offering visibility and context for related incidents. Users can create and preview decisions tailored to their data, allowing them to refine correlation logic and reduce unnecessary alerts further. New Relic AI utilizes features like flapping detection to minimize alert noise and offers tools to gauge the effectiveness of incident correlation, empowering users to optimize their incident response process. By understanding and leveraging New Relic AI's capabilities, users can achieve faster mean time to resolution (MTTR) and build trust in their incident response process.

In the era of digital transformation, developing and optimizing "more perfect software" is crucial for business success, as highlighted in New Relic's report, "Deeper Than Digital: Why and How More Perfect Software Drives Business Success." The report examines how companies are prioritizing and enhancing software development and identifies five critical pillars: cloud maturity, observability mastery, end-to-end data visibility, digital resilience, and empowered teams. These pillars distinguish industry leaders from laggards, with leaders experiencing stronger financial performance, innovation, and customer satisfaction. Leaders efficiently integrate cloud technology, implement observability solutions, and foster a DevOps culture that encourages innovation and resilience in software design. In contrast, laggards face barriers such as limited cloud adoption, poor observability practices, and cultural resistance, resulting in slower innovation and more frequent system outages. The report encourages organizations to assess their current practices against these pillars to enhance their digital excellence and improve business outcomes.

The New Relic Technical Support team provides 24/7 support from multiple offices in Portland, Dublin, and Tokyo, ensuring customers have access to experts at all times. The team answers common questions about New Relic APM 360, covering issues such as network problems, slow UI performance due to Metric Grouping Issues (MGIs) or hostname explosions, deleting applications, chart loading issues, and tailoring Apdex thresholds. To address these concerns, the support team recommends checking agent configuration files, using the New Relic Diagnostics tool, ensuring containers have common names, disabling browser extensions, setting appropriate Apdex thresholds, and automating threshold updates for individual apps. If customers still have questions or need further assistance, they can contact the Support team directly.

The New Relic Technical Support team provides round-the-clock assistance from Portland, Dublin, and Tokyo, addressing common queries about New Relic APM 360. Key issues covered in their blog include network connectivity problems with APM agents often caused by locked networks, slow APM UI due to Metric Grouping Issues (MGIs) and hostname explosions, and strategies for deleting APM applications. They also tackle chart loading issues, often linked to browser extensions, unsupported browser versions, or service interruptions. The blog advises on optimizing the Apdex threshold for user satisfaction, suggesting a target Apdex score of around 0.90-0.92 using percentiles, and offers guidance on automating threshold adjustments with NRQL queries. Readers are encouraged to engage with the New Relic community for further support and to explore additional resources for enhancing their APM experience.

Fostering a growth mindset in oneself and others has been crucial to my career advancement as a technologist, professional, and human being. Initially, I learned through self-taught means and later earned a computer science degree before joining a startup called Wealthfront, where I was surrounded by brilliant minds moving quickly. I found myself struggling to keep up with my mentors but eventually grew significantly under their guidance. I then transitioned into mentoring others, teaching at Dev Bootcamp, and now work at New Relic, where I've been blessed with the mentorship of incredible engineers across two continents. To improve mentorship culture, I've learned that reassurance is not enough; instead, we should focus on exploring questions rooted in the mentee's experience to help them gain agency and mastery over their growth process. Additionally, growth means feeling uncomfortable, but also safe; we need to create a sense of safety while allowing individuals to feel uncomfortable, which can be achieved by finding a balance between approaches A and B. I've developed a mentorship approach with scaffolds that provides a mix of psychological safety, independent struggle, structured opportunities for interaction, and flexibility.

Fostering a growth mindset and embracing mentorship have been pivotal in the author's career, particularly in their roles at Wealthfront, Dev Bootcamp, and currently at New Relic. The author emphasizes that effective mentorship involves focusing on the mentee's feelings and perceptions rather than simply offering reassurance. They advocate for creating a "growth edge," where mentees feel safe yet challenged, and propose a scaffolded mentoring approach that balances independence with support. This involves structured discussions, problem-solving, and periodic check-ins, allowing mentees to take ownership of their learning while mentors provide guidance. The approach aims to address the limitations of traditional mentoring models, encouraging adaptability and communication to cater to individual learning needs.

Most companies are adopting modern software development approaches like microservices architectures to accelerate time to market, gain agility, and deliver differentiated experiences. However, maintaining and improving these environments becomes increasingly difficult, leading to increased mean time to resolution (MTTR) due to complexity. Distributed tracing solutions can help teams understand the flow of requests in microservices environments and pinpoint failures or performance issues. However, not all distributed tracing solutions offer equal business value, with some requiring significant "heavy lifting" on the company's part to operate. Managed distributed tracing solutions, on the other hand, provide cost-effectiveness by automating tasks associated with tracing software management. These solutions also allow for democratized access to telemetry data, enabling teams to adopt and use the tool without additional complexity or effort. Ultimately, a managed distributed tracing solution can help companies protect their investment in modern software and deliver economic value through improved MTTR, better performance, and improved customer experience.

Companies are increasingly adopting modern software development approaches like microservices architectures to enhance agility, market responsiveness, and customer experience, though these come with challenges such as increased complexity and mean time to resolution (MTTR). Distributed tracing is essential for navigating these challenges, offering insights into request flows and pinpointing issues, thereby reducing MTTR and minimizing the impact on customer experience. Managed distributed tracing solutions, as opposed to self-managed ones, are cost-effective and less burdensome, providing comprehensive data analysis without the extensive operational demands. By automating tasks and democratizing access to telemetry data, managed solutions enable teams to efficiently monitor microservices and protect the economic value derived from modern software investments, leading to improved performance and customer satisfaction.

OpenTelemetry is an open standard for collecting and sending telemetry data to backend platforms, allowing developers to choose a vendor-neutral path to capturing and transmitting telemetry without altering existing instrumentation. It combines the OpenTracing and OpenCensus projects into a single specification, providing benefits such as simplified choice, cross-platform support, and streamlined observability. The project consists of specifications, APIs, SDKs, exporters, collectors, and a shared context layer that enables data to be transferred between services and backends. With its flexible and extensible architecture, OpenTelemetry supports various languages and backends, allowing developers to focus on building reliable software solutions rather than managing instrumentation.

OpenTelemetry, a Cloud Native Computing Foundation project, standardizes the collection and transmission of telemetry data, simplifying the choice for developers by merging OpenTracing and OpenCensus into a single open standard. This initiative offers a vendor-neutral path to capturing telemetry data across various languages and backends, enhancing observability with its APIs, SDKs, and components like Tracer and Meter pipelines, and a shared Context layer. OpenTelemetry's architecture includes a flexible and extensible Collector that facilitates exporting spans and metrics to numerous telemetry systems. The project aims to provide a consistent application performance monitoring experience by ensuring all instrumentation contains the same semantic information, thus freeing developers to focus on building reliable software solutions. Currently in beta, OpenTelemetry is supported by practical examples and documentation to help developers quickly integrate it into their applications.

There are numerous reasons why businesses are moving to the cloud, including cost reduction, agility, and productivity gains. However, navigating financials can be complicated, with 23% of businesses over budget on their cloud spend and 30% of that spending wasted due to difficulties in identifying optimization opportunities. A central source of data is needed to unify business units and facilitate alignment between application owners and central IT teams. New Relic's Cloud Optimize app provides this by unifying performance information from various sources, enabling real-time identification of optimization opportunities and reducing bill shock. By driving optimization efforts through a combination of telemetry data and pricing information, businesses can save significant amounts, as demonstrated by customers who have saved seven figures by identifying right-sizing opportunities. The ability to communicate back to the business with accurate real-time data enables faster decision-making and delivers functionality to customers, while also freeing up resources from admin fatigue.

Businesses transitioning to the cloud often face complexities in financial management, with cloud cost optimization emerging as a top priority, yet many still exceed their budgets, as highlighted by the Flexera 2020 State of the Cloud Report. New Relic's Cloud Optimize application addresses these challenges by using telemetry data to identify real-time optimization opportunities, facilitating cross-functional collaboration and enabling businesses to make informed decisions without compromising application performance. The app integrates real-time pricing and sizing information from cloud providers' APIs, helping organizations pinpoint optimization candidates and reduce costs, as demonstrated by significant savings in case studies. Beyond cost savings, Cloud Optimize aids in reducing business risk, enhancing customer experience, and shifting focus from budget constraints to delivering better service.

Observability is an approach to understanding complex software systems by collecting, visualizing, and analyzing telemetry data in real-time. It goes beyond traditional monitoring techniques by providing a fully connected view of all software telemetry data, allowing teams to master the performance of their digital architecture, accelerate innovation, and reduce operational costs. Observability requires integrating three essential components: collecting exhaustive and granular telemetry data, correlating and contextualizing the data, and visualizing the data and making it actionable. It also enables connection, contextualization, and curation, allowing teams to analyze telemetry data in real-time, visualize complex systems, and surface critical information and insights quickly. Modern observability collects four major complementary telemetry classes: metrics, events, logs, and traces (M.E.L.T.), ensuring exhaustive and open collection by complementing proprietary agents with open-source tools. It guarantees interoperability of all types of data and telemetry, automatically identifying, creating, and maintaining entities, and surfacing connections between them. Observability also enables visibility, actionability, and programmability, allowing teams to build applications that optimize software investments, measure efficiency in real-time, and make objective decisions to maximize performance. With the increasing demands of digital transformation, companies must adopt observability to achieve optimal speed and performance, differentiate themselves from competition, and meet customers' expectations.

Observability is a comprehensive approach that goes beyond traditional monitoring by providing a deeper understanding of complex software systems, allowing teams to not only detect anomalies but also understand their underlying causes and system behaviors. It leverages modern technologies such as microservices, cloud, and DevOps practices, which, while increasing deployment efficiency, add complexity and fragmentation to software architecture. Observability centralizes telemetry data from various sources, including infrastructure, applications, and user experiences, ensuring exhaustive data collection across metrics, events, logs, and traces (M.E.L.T.). This data is then contextualized and visualized to offer actionable insights, enabling teams to accelerate innovation, optimize performance, and reduce operational costs. Additionally, observability platforms incorporate artificial intelligence for proactive issue detection and diagnosis, enhancing DevOps teams' ability to anticipate and resolve issues swiftly. Through programmable dashboards and workflows, observability empowers organizations to tailor data representation and analytics to their specific business needs, ultimately improving decision-making and fostering an innovative corporate culture.

New Relic is expanding its open source presence with the launch of New Relic Open Source, a central resource for discovering and contributing to open source projects maintained by New Relic engineers. The site catalogs over 180 open source projects, including data exporters, instrumentation agents, and custom visualizations, each with a clear statement of purpose and code available on GitHub under the Apache 2 license. The platform is built using open tools and platforms like Gatsby, MDX, and the GitHub GraphQL API, inviting users to contribute through simple pull requests. New Relic Open Source aims to engage thousands of engineers in the pursuit of open standards and collaboration, providing free access to its platform and tools through the Developer Edition.

New Relic has launched New Relic Open Source, a platform designed to enhance its open-source presence by providing a centralized resource for discovering, using, and contributing to open-source projects maintained by New Relic. The site, which features over 180 projects including data exporters, instrumentation agents, and example code, is optimized for all devices and aims to foster community engagement through the New Relic Explorers Hub. As an open-source initiative itself, New Relic Open Source invites contributions and modifications from the global developer community, aligning with New Relic's commitment to open standards and collaboration. Director of Open Source and Developer Advocacy, Joel Worrall, emphasizes that this platform is an invitation to work collectively toward a better internet, encouraging engineers to engage with and contribute to the ongoing projects.

AWS Lambda has announced a new integration with Amazon Elastic File System (Amazon EFS), allowing developers to add persistent storage to their serverless functions, enabling stateful applications and improving performance for tasks like machine learning and virus scanning. AWS Lambda is designed as a stateless service, but the addition of EFS enables it to be used in conjunction with other tools like step functions or EC2 instances for more complex state machines. The new integration also includes security controls, such as IAM authorization and access points, to protect data access. Additionally, Amazon Cloudwatch will provide key metrics about the performance of the EFS-Lambda connection, and New Relic's Infrastructure monitoring tool will gather these metrics for further analysis.

Monitoring traditional monolithic applications is no longer sufficient for modern distributed systems built with microservices. Microservices introduce complexity and increase the mean time to resolution (MTTR) due to their constant changes, short container lifetimes, increased scale complexity, and potential misalignment of teams responsible for services they didn't develop. To address these challenges, a new approach called observability is required, which provides a connected view of performance data in real-time, enabling teams to pinpoint issues faster, understand what caused them, and deliver excellent customer experiences. Observability combines metrics, events, logs, and traces to provide actionable insight into how distributed applications work together and how dependencies impact the entire application. Distributed tracing is a critical component of observability, allowing teams to quickly understand what happens to requests as they transit through microservices and pinpoint where failures or performance issues occur and why. By implementing distributed tracing and following best practices such as defining clear objectives, using distributed tracing, collecting comprehensive metrics, setting up centralized logging, implementing health checks, and security monitoring, organizations can reduce MTTR and improve their overall software development and operations efficiency.

Amazon Web Services (AWS) has introduced a new integration between AWS Lambda and Amazon Elastic File System (Amazon EFS), which allows for persistent storage capabilities that can enhance the functionality of serverless computing. This integration provides Lambda functions with the ability to store and access data concurrently, leveraging EFS's distributed file storage system, which is beneficial for tasks such as machine learning, virus scanning, and other use cases requiring large data storage. However, despite this advancement, AWS Lambda remains a stateless service, and using it to create stateful applications could lead to challenges, including potential failures in function chaining and service fragility. Security and configuration are critical when using EFS with Lambda, as it involves setting up a Virtual Private Cloud (VPC), managing access controls, and ensuring network visibility. Tools like New Relic's Infrastructure monitoring and Amazon Cloudwatch offer metrics to monitor the performance and security of the EFS-Lambda setup, providing insights into IOPS consumption and connection stability.

Transitioning to a microservices architecture, while beneficial for enhancing security, development speed, technology integration, infrastructure flexibility, and team collaboration, presents significant challenges in monitoring and managing distributed systems. Traditional monitoring strategies are inadequate for addressing the complexity of microservices, as they cannot effectively connect dependencies or track performance across distributed applications, leading to increased mean time to resolution (MTTR). Observability, which provides real-time, connected views of performance data, is critical for understanding the root causes of issues. It leverages telemetry data, including metrics, events, logs, and particularly distributed traces, to effectively diagnose and resolve performance bottlenecks in microservices environments. Implementing best practices such as clear objective definition, distributed tracing, comprehensive metric collection, centralized logging, and proactive alert and security measures can significantly enhance the management and reliability of microservices architectures.

Serverless adoption is gaining momentum, but it still faces significant challenges in terms of organizational and technical hurdles. The industry is experiencing a competitive landscape with varying capabilities between cloud vendors, leading to inflated expectations and potential disillusionment. The biggest challenges include dealing with larger file sizes, SQL database support, network, compute, storage, and governance issues. Despite these challenges, serverless has the potential to revolutionize the way applications are built and deployed, with innovations like Deno, a new experimental JavaScript runtime, offering exciting possibilities for serverless web development. The key to success lies in overcoming the myths surrounding lock-in and finding ways to make onboarding easier.

Serverless technology is gaining traction but remains in its early stages, as highlighted by Brian LeRoux of Begin, who points out the challenges and opportunities in its adoption. While the concept of serverless computing—outsourcing commoditized workloads to focus on core business value—promises a future of reduced ownership costs, its current state is marked by varied capabilities across cloud vendors like AWS and Azure. AWS faces hurdles with file size limitations and SQL database support, whereas Azure needs to enhance network ease for frontend developers and improve its Infrastructure as Code capabilities. LeRoux is particularly excited about the potential of Deno, an experimental JavaScript runtime that could advance serverless web development. Despite the enthusiasm around serverless, the industry is navigating a phase of disillusionment, with expectations needing to be tempered and technical challenges still to be addressed.

The past few weeks have been difficult for the author and many of their teammates due to feelings of anger, sadness, hurt, frustration, and exhaustion. However, this challenging time has also led to an outpouring of support and solidarity from many people who want to make real change in the world. The company New Relic is committed to taking anti-racist actions across three key areas: supporting their Black employees, donating to anti-racist causes, and becoming allies by educating themselves and others on how to create a more inclusive environment. To actively be anti-racist, individuals can take various actions such as educating themselves, engaging in discussions with people of color, donating to relevant organizations, voting, voicing their opinion, attending ally skills training, and committing to being part of the solution.

Recent events have left many, including the author, feeling overwhelmed by emotions such as anger, sadness, and exhaustion, while also feeling hopeful about the potential for change driven by individual actions and organizational commitments. At New Relic, efforts are being made to support Black employees through resources and career development, donate to anti-racist causes, and educate employees on becoming effective allies. The company emphasizes the importance of moving beyond neutrality to actively combat systemic racism, encouraging personal education, open dialogue, and civic engagement. The author, Tracy Williams, underscores the necessity of being a consistent voice against racism and highlights New Relic's commitment to ally skills training to support systemic change.

New Relic's NerdGraph API allows developers to query and manipulate data in a flexible and efficient manner using GraphQL. This enables developers to minimize superfluous API operations and reduce manual toil in data analysis workflows. With NerdGraph, developers can query various entities associated with their account, update workloads, create and manage tags, and fetch data for building New Relic One applications. The API explorer provides an interactive interface for building and running GraphQL queries, allowing developers to easily retrieve and process telemetry data. Additionally, NerdGraph supports interfaces, which enable developers to specify common fields that can be used across multiple object types. By using NerdGraph, developers can update integration configurations with mutations, reducing the overhead of working with their New Relic data. The API also provides tools for transferring data to code, such as copying curl statements and generating command-line ready queries or mutations. Overall, NerdGraph enhances developer productivity and eases the path for building powerful applications using New Relic's data.

New Relic's NerdGraph API, built on GraphQL, offers developers a streamlined way to query and manage telemetry data without excessive API operations, enhancing efficiency in creating dashboards and applications. By using a single endpoint, GraphQL allows for complex queries that can retrieve comprehensive data in one request, as opposed to multiple calls required by REST APIs. New Relic's implementation of GraphQL includes multiple APIs like accounts and Infrastructure, facilitating seamless data access and management across services. The blog post illustrates how to use NerdGraph for querying and updating New Relic Infrastructure cloud integrations, demonstrating the utility of interfaces and mutations in GraphQL for both retrieving detailed information and modifying configuration settings. Mark Weitzel emphasizes the flexibility and lightweight nature of GraphQL in reducing overhead and encourages developers to explore further capabilities through resources available on New Relic's developer site and community forum.

Resistance, cost, and uncertainty are significant challenges associated with large-scale technical cloud migration strategies and execution. To overcome these obstacles, organizations need to unblock common challenges, understand app dependencies and assessing costs, leverage their cloud and tech providers, and adopt a strategic advisory partnership approach. A successful cloud migration involves three stages: planning, migration, and running, which require defining the work involved in moving applications to the cloud, leveraging real-time data and tracking resource usage, and optimizing work environments to reduce time and cost. The Nimbus app, built on New Relic One, provides an actionable, real-time user interface to track workloads through key stages of planning, migration, and running in the cloud, enabling organizations to accelerate and de-risk their cloud optimization journey.

Resistance, cost, and uncertainty are significant challenges in large-scale cloud migration strategies, requiring strong leadership, funding, and collaboration across organizations. New Relic, in partnership with Amazon Web Services, has developed Nimbus, a real-time migration planning and tracking application, to address these challenges by accelerating migration and reducing risk. A recent poll by New Relic revealed that upskilling and delayed progress reporting are major hurdles, yet engineers display cautious optimism about managing migration projects with current tools. Although cloud adoption offers benefits such as innovation and agility, many enterprise workloads remain on-premises due to the complexities of migrating applications, which include understanding dependencies and accurately assessing costs. Successful cloud migration necessitates comprehensive planning, executing iterative migrations, and optimizing real-time operations. Nimbus, integrated with New Relic's telemetry data platform, offers a real-time interface for tracking cloud migration stages, providing valuable insights and enhancing the migration process by reducing risk and optimizing costs.

During times of planned system disruptions, muting rules in New Relic Alerts can help filter out noisy notifications while maintaining observability and alerting on the rest of the system. Muting rules allow users to create conditions that match a large number of attributes and tags present in a violation event, overriding default life cycles to indicate that alerts should not send notifications. This enables users to minimize risks of overmuting by targeting specific subsets of their systems affected by planned disruptions, allowing them to observe when entities have recovered from maintenance and returned to a healthy state. Muting rules can be created and managed using either the New Relic Alerts UI or the NerdGraph API explorer, providing flexibility and automation for enterprise-scale issue detection and incident management.

During planned system disruptions, New Relic Alerts offers muting rules to manage and silence notifications, allowing users to maintain observability without being overwhelmed by unnecessary alerts. These rules are designed to target specific subsets of systems affected by maintenance, deployments, or testing by leveraging contextual metadata, ensuring that only relevant notifications are muted while still tracking the recovery of entities post-disruption. Users can create and manage these muting rules through the New Relic Alerts UI or the NerdGraph API explorer, with the flexibility to construct complex rule filters for precise alert management. By overriding the typical alert lifecycle, muting rules ensure that incidents are logged and health indicators are updated without sending notifications unless necessary, thereby reducing alert fatigue. These muting controls are part of a broader initiative to enhance issue detection and incident management, offering automation and flexibility at an enterprise scale.

Luces Huayhuaca, a software engineer at New Relic, shares her experiences and advice for success in her role, highlighting the importance of being passionate about the product, having empathy for customers, and exchanging knowledge with peers. She describes New Relic's company culture as one of sharing, where employees are encouraged to learn from each other and offer mentorship. Luces offers three tips for those interested in joining New Relic: be authentic and find your strengths, be proactive and reach out to colleagues, and be disciplined and study every day. The company is currently hiring, with various open roles available.

In the inaugural post of New Relic's "Life at New Relic" blog series, software engineer Luces Huayhuaca shares her journey from joining the company as an inexperienced support engineer to becoming a software engineer on the Support Tools team. Originally from Peru, Luces emphasizes the importance of passion, empathy, and collaboration in her role, highlighting how learning from talented colleagues in a supportive company culture has been pivotal to her success. She describes the culture at New Relic as one of sharing and mentorship, where employees are encouraged to be authentic and proactive, which helps foster both professional and social connections. Luces advises potential employees to be disciplined in their learning and to leverage their unique strengths, while also extending invitations to colleagues for personal interactions, as a way to integrate into the company and grow professionally.

New Relic One` provides a platform for building and deploying custom apps to gain unique insights into data generated by various applications and systems. The company shares some of its popular open-source apps, including `Observability Maps`, `Metric Aggregator`, and `Workload Geo Ops`, which can be accessed through the `New Relic One Catalog`. These apps allow users to create customized views of their environment, aggregate metrics, and link workloads to physical locations. To deploy these apps, users need access to `New Relic One`, the `CLI`, a personal API key, and Node v10 or higher. The company also offers resources for building custom applications, including documentation, a developer toolkit, and a GraphQL explorer. Additionally, New Relic welcomes open-source contributions to its projects.

New Relic One offers a customizable platform where companies can build and deploy open-source applications tailored to their specific data needs, utilizing applications like Observability Maps, Metric Aggregator, and Workload Geo Ops. These applications provide unique functionalities such as creating custom views of service maps, converting event data into dimensional metrics, and linking workloads to geographic locations for efficient incident resolution. Users can access and manage these applications through the New Relic One Catalog, and for further customization, they can use the CLI for deployment. The platform encourages community contribution to its open-source projects, offering resources like the New Relic Developer Toolkit and the NerdGraph GraphQL Explorer to facilitate the development of custom applications. Joel Worrall, the Director of Open Source and Developer Advocacy at New Relic, emphasizes the platform's potential to foster innovation through an inclusive developer community while highlighting that the views expressed are his own and not necessarily those of New Relic.

New Relic is enhancing its features to meet the evolving needs of software engineering teams, particularly in terms of user data compliance, endpoint monitoring, and mobile application performance optimization. The company has introduced new ways to handle user data, including enabling or disabling cookie collection, dropping noisy or sensitive data from the New Relic Browser agent, and providing more global locations for monitoring uptime and performance. Additionally, New Relic is expanding its capabilities in Kubernetes environments, deploying synthetic monitors, and optimizing React Native application performance through an open beta agent. These updates aim to improve efficiency, optimization, and performance for developers using New Relic's platform.

New Relic has introduced several updates to enhance user data handling, endpoint monitoring, and mobile application performance, responding to customer feedback and regulatory compliance needs. These updates include the ability to enable or disable cookie collection in New Relic Browser for GDPR compliance, the introduction of data dropping to manage costs and handle sensitive information, and the deployment of synthetic monitors from Kubernetes environments to automate and ensure critical endpoint availability. Additionally, New Relic Synthetics has expanded its monitoring locations to Cape Town and Milan, allowing users to simulate traffic from closer to their end-users. Developers using React Native can also utilize an open beta agent to optimize pre-production application performance. These enhancements aim to streamline the integration of New Relic's tools with existing technologies while maintaining data privacy and performance standards.

The text discusses the importance of observability in modern environments and how it can help teams improve their triage and incident response processes. It highlights the limitations of traditional monitoring tools and introduces SolarWinds Orion as a potential solution for integrating data from various sources. The article then focuses on two methods for sending Orion alerts data to New Relic: building an alert action with a PowerShell script and creating a custom integration using New Relic Flex. Both methods allow users to collect valuable insights from the Orion Alerting Engine and enable them to start asking questions they didn't know they needed to ask. The article concludes by emphasizing the need for a true platform that can consolidate all data into a single point of truth, where teams can work together to reduce response times and increase innovation.

Zack Mutchler, a seasoned monitoring practitioner, discusses the importance of observability over simple monitoring in modern IT environments in his blog series. Working with New Relic and drawing on his experience with SolarWinds, Mutchler emphasizes the value of integrating data from various monitoring tools to improve incident response and triage processes. He explains how to enhance observability by leveraging New Relic's platform to collect and analyze data from SolarWinds Orion, providing detailed steps and options for integrating alerts and network statistics. Mutchler shares practical methods like using PowerShell scripts and New Relic Flex for data integration, enabling teams to consolidate data into a single source of truth. This approach allows for more effective monitoring, reducing response times, and fostering innovation. He encourages collaboration and experimentation in observability practices, underscoring the need for a comprehensive platform that unifies diverse data sources.