May 2023 Summaries

FastAPI is a Python web framework that allows developers to quickly spin up REST services, but it can experience slowdowns due to various reasons such as heavy request payloads, blocking I/O operations, insufficient hardware resources, and outdated operating systems. To troubleshoot performance issues, developers can use New Relic's observability platform, which provides metrics, events, logs, and traces to gain deeper insights into the application's performance. By using New Relic, developers can identify the root cause of slowdowns and apply solutions such as making functions asynchronous or resizing images to improve performance. Additionally, New Relic offers a quickstart guide for installing the Python agent in FastAPI apps, which provides pre-built tools and a dashboard to monitor application performance.

FastAPI, a Python web framework, enables developers to create REST services efficiently, but like any framework, it can encounter performance issues, which can be diagnosed and resolved with observability tools like New Relic. Common causes of slowdowns include heavy request payloads, blocking I/O operations, and insufficient hardware resources. An example in the text illustrates how a steganography application faced performance issues due to synchronous code in a function responsible for extracting image pixels, leading to timeouts. Attempts to resolve the issue with asynchronous programming surprisingly worsened the performance, but resizing the image before pixel extraction significantly improved response times. The blog emphasizes using New Relic's platform to monitor and troubleshoot such issues effectively, providing a comprehensive application performance monitoring dashboard. Additionally, the text offers guidance on installing the New Relic Python agent for FastAPI applications through a quickstart guide, aiming to enhance observability and performance management.

New Relic recognizes and celebrates Asian American and Pacific Islander (AAPI) contributions during AAPI Heritage Month, acknowledging the historical contributions of these communities since 1978. The month commemorates significant events in the history of Asian Americans and Pacific Islanders, including the arrival of Japanese immigrants in 1843 and the completion of the transcontinental railroad by Chinese immigrants in 1869. To honor this month, New Relic established an API affinity group and hosted various activities, such as cultural food gatherings and educational sessions on Japanese culture. The company is committed to fostering an inclusive workplace where all employees feel welcome and valued, with diversity and inclusion being essential to driving innovation and achieving its mission. The celebration highlights the importance of learning about and honoring the diverse cultures of AAPI communities.

New Relic celebrates Asian American and Pacific Islander (AAPI) Heritage Month by acknowledging the historical contributions of these communities, which are commemorated in May due to significant events like the arrival of the first Japanese immigrants and the completion of the transcontinental railroad. The company has established an Asian and Pacific Islander affinity group as part of its Relics of Color Employee Resource Group, hosting cultural activities such as food gatherings and origami workshops to foster connection and understanding. New Relic emphasizes its commitment to diversity, equity, and inclusion (DEI), aiming to create an inclusive workplace where employees feel valued and supported, which aligns with their mission of using data-driven decisions in software development. The blog highlights contributions from New Relic's DEI leaders, who advocate for inclusive practices and aim to inspire future generations in tech.

New Relic offers a seamless integration for monitoring OpenAI's GPT models like GPT-3, GPT-3.5, and GPT-4, emphasizing the importance of tracking metrics such as average request time, total requests, and costs. This integration, part of New Relic's MLOps tools, allows users to track the performance and cost-efficiency of OpenAI APIs with real-time insights displayed on a pre-built dashboard. By installing the OpenAI Observability quickstart, users can monitor token usage, model performance, and user engagement, enabling better optimization of GPT applications. The integration simplifies the process with just two lines of code, providing valuable data to help improve machine learning models and manage expenses effectively. The article also highlights the broader capabilities of New Relic and encourages users to explore further integrations and support through its platform.

Structured logging is a method of organizing log data in a standardized format, making it easier to analyze and interpret. It allows for more efficient troubleshooting and debugging, provides valuable insights into application performance, and supports seamless scaling. Structured logs include key-value pairs that provide context and additional information about the logged event, enhancing efficiency, saving processing power, and reducing costs. A consistent log format is crucial for improved searchability, consistency, automation, and security. The best practices for structured logging include deciding on a consistent log format, using standard data formats, including all necessary context and metadata, making sure the data is useful for all stakeholders, avoiding verbosity, following security best practices, and monitoring and analyzing logs. Structured logging has numerous benefits, including performance, improved searchability, consistency, automation, and security. It provides a standardized format for log data, making it easier to search, analyze, and extract meaningful insights from the logs. New Relic offers powerful tools for log management, adding value to structured logging, and can help with use cases such as debugging, performance monitoring, distributed tracing, security audits, business intelligence, and more.

Structured logging is a method of organizing log data in a consistent format, typically using key-value pairs, which enhances the ability to search, filter, and analyze log data for debugging, monitoring, and compliance purposes. This approach is particularly beneficial in complex systems, as it reduces processing power, supports scalability, facilitates automation, and improves security. Structured logs provide standardized data that aids in performance monitoring, distributed tracing, security audits, and business intelligence, ultimately enabling better collaboration among developers and stakeholders. Tools like New Relic enhance structured logging by offering capabilities such as custom attributes, powerful search and analysis features, centralized logging, and integration with popular logging frameworks, making it easier to manage and extract insights from large volumes of log data.

Distributed logging often involves sending application logs directly to a backend, but this can lead to issues such as backpressure, latencies, and network connectivity problems. To address these challenges, decoupling the log forwarder from the application can enhance system reliability. This approach allows for complex processing to occur separately, provides flexibility with buffering, and supports various network protocols and output formats. Five enterprise-ready patterns for log forwarding are discussed, emphasizing the use of tools like Fluentd and Fluent Bit for integration with logging backends like New Relic. The patterns range from co-located forwarders using file tailers or sockets to separately located forwarders with load balancing, each with its advantages and potential drawbacks. Additionally, log interpretation and routing patterns can be applied to enrich, filter, and route logs strategically. The article highlights the importance of a resilient logging infrastructure to handle anomalies and ensure observability, offering practical configurations and considerations for selecting and deploying log forwarders.

New Relic's general availability of its connected infrastructure and application performance monitoring solution offers a more integrated observability experience, allowing users to correlate performance across infrastructure, APM, and the rest of their stack to remediate problems faster. The solution eliminates screen swivels and data silos by providing an integrated infrastructure experience inside APM, at-a-glance estate and impact view, in-context application health, related entities automap, and embedded change tracking. It also eliminates peak billing and predatory pricing practices, offering consumption-based pricing with no additional charges for custom metrics, up to 1/3rd the cost of competitors, and consistent per-GB pricing. The solution is designed to help users solve problems faster by providing a new infrastructure experience with opinionated workflows, saved views, and quickstarts for easy setup.

New Relic has announced the general availability of its updated infrastructure and application performance monitoring (APM) solution, which integrates infrastructure monitoring within APM to enhance observability and problem remediation across entire tech stacks. The solution offers a unified platform for correlating performance data from infrastructure and applications, enabling users to address issues faster without switching between tools. It features consumption-based pricing, eliminating peak billing practices common among competitors like Datadog, thereby reducing costs significantly. Key updates include new user interfaces that provide dynamic charts and integrated views of CPU and memory usage for hosts, containers, and virtual machines, along with change tracking and automapping of related infrastructure components. This comprehensive monitoring solution allows real-time correlation of application and host health, enabling quicker detection and resolution of performance bottlenecks while reducing operational expenses.

The OpenTelemetry Collector is a powerful tool for log enrichment, allowing you to collect, process, and export telemetry data from various sources. By adding metadata, context information, or other data to logs, you can troubleshoot issues faster, have deeper insights into your system, and improve efficiency. The collector provides flexible options for collecting, enriching, and exporting logs, making it easy to implement log enrichment through its highly configurable processors. You can add Kubernetes metadata with the `k8sattributes` processor, filter unnecessary logs with the `filter` processor, extract environmental data as attributes with the `resourcedetection` processor, add resource attributes for correlation with other telemetry data with the `resource` processor, and modify log attributes based on conditions with the `transform` processor. With these processors, you can enrich your logs with OpenTelemetry Collector and gain valuable insights into your system.

The integration between New Relic and AWS Systems Manager Distributor allows for quick and easy installation of the New Relic infrastructure agent on multiple nodes directly through the AWS interface, eliminating the need to instrument each instance individually. This integration provides auto-instrumentation to bootstrap agent installation on new EC2 instances, as well as the ability to use AWS CLI or IaC tooling to install the agent. The Distributor enables centralized storage of software packages in a version-controlled location, simplifying package distribution and update processes. By integrating with AWS Systems Manager features, the Distributor allows users to deploy the New Relic agent across their fleet of nodes without instrumenting each one individually, taking into account different operating system types and autoscaling factors. The integration provides instant observability by monitoring services, querying incoming data, and building dashboards in New Relic, and can be managed right through the AWS console without any overheads.

New Relic's log management service offers log obfuscation options to enhance data privacy and comply with security guidelines by concealing sensitive information such as PII, PHI, and financial data. The service utilizes regular expressions to automate the masking or hashing of confidential data, ensuring efficient and scalable obfuscation without lengthy manual configurations. By implementing log obfuscation, organizations can protect data from breaches, adhere to data protection regulations, and maintain customer trust while enabling effective data analysis. Users can create obfuscation rules using either masking, which permanently replaces data with x's, or hashing, which uses SHA-256 for reversible obfuscation. Best practices include identifying sensitive data, developing a strategy, automating the process, testing and monitoring the obfuscation, and documenting the procedures to maintain compliance and effectiveness. Users can get started by accessing their New Relic accounts, benefiting from free data ingestion and user access.

Log enrichment, crucial for modern observability, involves enhancing logs with additional metadata and context to derive actionable insights from vast amounts of unstructured data. The OpenTelemetry Collector, an open-source, vendor-agnostic tool, facilitates log enrichment by collecting, processing, and exporting telemetry data like logs, traces, and metrics. It allows users to configure data pipelines with community-contributed processors, such as k8sattributes for Kubernetes metadata, filter for removing unnecessary logs, resourcedetection for environmental metadata, resource for correlating logs with other telemetry data, and transform for modifying log attributes based on conditions. These processors enable the creation of enriched logs that enhance system monitoring, troubleshooting, and compliance while optimizing resource usage. Log enrichment aids in performance monitoring by providing insights into system behavior, enabling IT teams to identify bottlenecks and optimize configurations, ultimately improving system performance.

An integration between New Relic and AWS Systems Manager Distributor has been announced, facilitating the installation of New Relic's infrastructure agent directly through the AWS interface, thus enabling efficient service monitoring and data querying without manually instrumenting each AWS instance. This integration allows management of up to 30,000 instances from the AWS console, providing auto-instrumentation to ensure new EC2 instances are equipped with the agent, and supports installation via AWS CLI or Infrastructure as Code tools. AWS Systems Manager Distributor centralizes and version-controls software packages, streamlining their distribution, installation, and updating across a fleet of managed nodes, accommodating different operating systems and autoscaling needs. The integration simplifies the deployment process by grouping nodes and allowing package installations based on tags, regions, or account numbers, with the option for scheduled updates. Detailed prerequisites and steps are outlined for setup, ensuring the New Relic agent can be automatically installed and updated on EC2 instances, enhancing observability through New Relic's interface.

In today's rapidly-evolving technological environment, mobile applications have revolutionized the way individuals and businesses live and work by providing convenient access to information and services on the go. However, without proper monitoring, application crashes can lead to frustrated customers and lost revenue, highlighting the importance of implementing a comprehensive and proactive monitoring system that can track app performance and detect issues before they become major problems. New Relic instant observability solutions offer pre-built solutions that work across the whole stack, providing mobile developers with real-time visibility into their app's performance and data-driven insights to optimize app performance and enhance customer experience, ultimately improving business outcomes. Specifically, the Mobile Crash Analytics dashboard provides in-depth analysis of crash trends, while the Mobile Network Performance dashboard offers an in-depth review of HTTP issues and network problems, enabling developers to identify and troubleshoot performance bottlenecks and improve their mobile application's overall quality.

Mobile applications have become essential tools for both individuals and businesses, transforming the way we access information and services. However, without proper monitoring, app crashes and network issues can lead to user frustration and revenue loss. New Relic offers pre-built observability solutions like the Mobile Crash Analytics and Mobile Network Performance dashboards, which provide real-time insights into app performance. These tools help developers track and troubleshoot issues, optimize app functionality, and enhance customer experience by offering data-driven insights. To use these solutions, developers need to integrate New Relic's mobile SDKs into their applications, allowing them to monitor performance across various platforms, including iOS, Android, and hybrid apps like React Native and Flutter. With these dashboards, businesses can ensure app reliability, leading to improved customer satisfaction and business outcomes.

In today's digital age, security is a major concern for individuals and organizations alike, with the increasing number of cyberattacks and data breaches making it crucial for developers to have a thorough understanding of security best practices. The growth and speed of cloud-native development have resulted in an expanding attack surface filled with vulnerabilities that can directly impact the safety and privacy of users' data if left unchecked. To raise the bar on security skill sets, developers can use the capabilities of the New Relic observability platform to detect and remediate issues in applications like Juice Shop, a deliberately insecure web application from OWASP. Application monitoring for identifying vulnerabilities in real-time can be achieved through APM, which provides real-time insights into performance and behavior, including response times, error rates, and transaction traces. High error rates can indicate security vulnerabilities or potential threats, such as hack bots trying to find open paths into an application. Error tracking is also crucial, allowing developers to quickly identify and resolve issues that could be exploited by adversaries. New Relic's Vulnerability Management capability helps overcome security blindspots within applications, identifying the most urgent vulnerabilities, calculating the vulnerability surface area, triaging and assigning vulnerabilities, and providing remediation steps. Synthetic monitoring can simulate user behavior and test the performance of applications, identifying potential security issues and vulnerabilities, such as testing access to sensitive information without proper authentication. With New Relic's capabilities, developers can enhance their security knowledge and skills, adopting a security mindset and upleveling their skills today by signing up for a free account.

In the current digital landscape, enhancing security practices is essential for developers to protect applications from cyberattacks and data breaches. The blog highlights the importance of understanding security vulnerabilities and presents the New Relic observability platform as a tool to detect and remediate issues using Juice Shop, a purposefully insecure web application developed by OWASP for educational purposes. New Relic's features, such as application performance monitoring (APM), error tracking, and synthetic monitoring, provide real-time insights into application performance and behavior, helping to identify potential security threats, such as SQL injection vulnerabilities and improper access to sensitive information. The platform also offers Security RX, which aids in addressing vulnerabilities in software components by identifying, triaging, and providing remediation steps for known issues. The blog concludes by emphasizing the growing need for developers to adopt a security mindset and suggests using New Relic to enhance security skills through its comprehensive monitoring and remediation capabilities.

Monitoring Red Hat Ansible Automation Controller is crucial for ensuring the smooth operation of automation workflows. The platform's rich set of features can lead to increased complexity, making it essential to monitor its performance. By using a monitoring tool like New Relic, organizations can gain valuable insights into their platform's performance and optimize processes for maximum efficiency. Monitoring key metrics such as job status, inventory health, resource usage, user activity, and logs is critical to achieving improved automation efficiency, reduced infrastructure downtime, and better system resource allocation. The New Relic integration provides pre-built dashboards that display critical query data in one place, making it easy to monitor and troubleshoot issues. By installing the New Relic infrastructure agent, configuring the Prometheus OpenMetrics integration, forwarding Ansible controller logs, restarting the infrastructure agent, using NRQL to view data, and seeing Ansible Automation Controller metrics in a dashboard, organizations can effectively monitor their platform and achieve better results.

This guide provides a step-by-step process for capturing logs from Azure using Azure Event Hubs and Azure Functions, and sending them to New Relic for analysis. To set up this solution, users need an active Microsoft Azure account and a New Relic ingest license key. They will use App Service for Diagnostic logs, Azure Event Hubs, and Azure Functions to forward logs to New Relic. The guide covers the pre-requisites, setting up Azure services, configuring log forwarding, creating an Azure Function app, adding code to the function, deploying the function, and troubleshooting common issues. By following this guide, users can monitor their logs easily and effectively, and gain visibility into their application's performance and issues.

Managing logs in Azure can be complex and costly, but integrating Azure with New Relic offers a streamlined solution for monitoring and analyzing logs efficiently. The process involves setting up Azure services like Azure Event Hubs, AppService for Diagnostic logs, and Azure Functions to capture logs and forward them to New Relic using the Logs API. This integration provides real-time log analysis and helps identify trends and patterns, which is particularly beneficial for large-scale applications. The guide emphasizes the importance of enabling Azure Diagnostic Logs and configuring log forwarding to New Relic to ensure effective log management across multiple Azure resources. By following the step-by-step instructions, users can achieve a seamless end-to-end integration that enhances application performance monitoring and troubleshooting.

Automation has become essential for organizations to manage their infrastructure, and Red Hat Ansible Automation Controller is a widely used platform for defining, operating, and scaling automation. Monitoring this platform is crucial as workflows become more complex, and the article discusses the benefits of monitoring Ansible Automation Controller, such as improved efficiency, reduced downtime, and better resource allocation. It emphasizes the importance of tracking various metrics like job status, inventory health, resource usage, user activity, and logs to ensure smooth operation. The integration with New Relic is highlighted as a means to gain valuable insights into the platform's performance, offering pre-built dashboards that provide a comprehensive view of critical metrics, helping optimize processes for maximum efficiency. The article provides a step-by-step guide to integrating Ansible Automation Controller with New Relic, explaining how to install the infrastructure agent, configure Prometheus OpenMetrics, and forward logs to New Relic to enhance visibility and management of automation workflows.

Fluent Bit can be used to improve the readability of multiline logs by consolidating them into a single log record. This can make it easier to understand and analyze logs, especially when dealing with complex or nested log messages. A custom Fluent Bit configuration can be created using a configurable multiline parser to identify the start and continuation lines of a multiline log message. The configuration uses regular expressions (regex) to match the start state and potential continuation lines, allowing for more accurate parsing and consolidation of multiline logs. With this configuration, multiline logs can be consolidated into a single log record in New Relic, making it easier to read and analyze them.

Managing logs is a significant challenge in today's complex systems, with individual log messages providing valuable context when issues arise. As infrastructure grows and applications become more complex, it can be overwhelming to navigate the constant influx of log data. To overcome this, it's essential to understand the reasons behind high log volume, such as growing application complexity, inadequate log rotation policies, and granular information in logs. By implementing best practices like forwarding logs to a centralized location, standardizing log levels, keeping a consistent log format, logging valuable information, and considering structured logging, organizations can manage their log volume effectively. Techniques like log throttling, sampling, dynamic log level adjustment, and log analysis can also help reduce the volume of logs while providing more helpful data. With New Relic's log management capability, users can monitor their logs, find signal within noise, and enjoy near-instant search and full contextual log information for any volume of queries, all with simple and transparent pricing.

Managing logs in modern IT environments is challenging due to the constant generation of log data by applications, servers, and network devices, which can become overwhelming as infrastructures grow. Effective log management is crucial for gaining visibility into performance data, reducing mean time to resolution (MTTR) and detection (MTTD), and involves techniques such as centralizing logs, standardizing log levels, employing structured logging, and ensuring logs are both parseable and valuable. Common issues contributing to high log volume include complex application architectures, lack of log rotation policies, and excessive granularity in logs, which can be mitigated through best practices like log throttling, sampling, and dynamic log level adjustment. New Relic provides tools for managing log volume efficiently, offering features like log analysis, cost-effective scalability, and integration capabilities, thereby helping organizations to save costs, enhance system performance, and ensure compliance with security and privacy standards.

Multiline logs can pose readability challenges when each line appears as a separate entry, making it difficult to interpret them among other intermixed logs. A solution involves consolidating multiline log messages into a single entry using Fluent Bit, an open-source logging processor, to enhance clarity and efficiency. The process involves creating a custom Fluent Bit configuration with a multiline parser that uses regular expressions to identify the start and continuation of log lines. This configuration can be applied across various platforms, including Kubernetes and New Relic, by setting up a parser and ensuring it matches the log format used, such as the CRI-Log format for Azure Kubernetes Service. By implementing this setup, users can improve the debugging experience, as logs appear as cohesive entries rather than fragmented lines, thus saving time and reducing complexity in log management.

Modern applications often utilize a complex architecture of microservices, serverless, and container technologies, which, while efficient, can become difficult to manage when issues arise, particularly during off-hours. To effectively troubleshoot and maintain performance, observability practices are essential, with log monitoring being a common method used by over 73% of DevOps teams to track application data and assess performance. However, relying solely on log monitoring can be limiting due to its time-consuming nature and the challenge of managing logs across multiple services. Instrumentation, which involves adding code to applications to monitor metrics, events, logs, and traces, provides a more comprehensive view of an application's performance. By fully instrumenting an application, developers can gain immediate visibility and insights, allowing for quicker issue resolution and a better understanding of complex environments. This approach is recommended for a holistic monitoring strategy that goes beyond log management, offering a more effective way to analyze and optimize distributed systems.

Contextual logging refers to seeing logs together with the issues in your applications and infrastructure. This approach simplifies log management by providing a centralized location where teams can retrieve, visualize, and analyze log data in context with other services and data sources. Contextual logging tools address challenges such as collecting logs, managing alerts, and reducing alert fatigue. By using contextual logging, teams can improve incident response times, collaboration, and the efficiency of their team, while also creating more accurate alerts and reducing false positives. Implementing contextual logging involves setting up a solution that forwards log data to a central location, exploring the available logging data, reviewing other places where logs are accessed, setting up alerts, and querying data to create dashboards.

Log management involves the entire process of handling logs, from their generation to eventual disposal, with a focus on aggregating them for effective troubleshooting. Contextual logging plays a crucial role by providing insights into applications and infrastructure, helping to identify patterns and trends within systems. This approach addresses challenges such as collecting and locating specific logs, managing alerts, and minimizing alert noise. Tools like New Relic enhance log management by correlating application performance monitoring data with logs, allowing teams to visualize, analyze, and create better alerts through contextual log data. This enriched logging method improves incident response times, facilitates team collaboration, reduces alert fatigue, and enhances the accuracy of alerts. Implementing contextual logging involves setting up systems to forward log data and utilizing specific agents for different application languages, ultimately making log management more efficient and insightful.

The article introduces New Relic AI, a generative AI assistant that combines large language models with the unified telemetry data platform to provide deep insights into a system's state through straightforward questions. This solution empowers all teams, from developers to non-technical users, to fix issues faster, reduce outages, and increase development velocity and innovation. New Relic AI unifies data, context, tools, and teams under one roof, generating higher-quality AI responses by accessing 30+ correlated capabilities. It accelerates onboarding, instrumentation, error resolution, and code-level debugging, making observability more accessible to everyone. The solution is part of New Relic's journey to transform observability into an essential practice in software development.

New Relic has launched the first generative AI assistant for observability, which integrates large language models with its unified telemetry data platform to provide insights and suggested fixes through a simple chat interface. This tool aims to democratize observability by enabling users, regardless of their technical expertise, to ask questions and receive detailed analysis and solutions to system anomalies, thereby reducing outages and enhancing development velocity. By unifying data, context, tools, and teams, New Relic AI turns complex data into actionable insights and supports a range of functions from debugging code-level errors to optimizing alerts. The platform marks a significant milestone in New Relic's journey to make observability more accessible and integrate AI capabilities for predictive analytics and AI optimization, thereby transforming it into an essential practice for software development.