April 2022 Summaries

As e-commerce continues its rapid expansion, retailers face increasing complexity in their digital infrastructures, prompting a shift towards multicloud strategies to maintain agility and competitiveness. This complexity pushes IT teams to their limits, necessitating automation in incident management to minimize downtime and manual interventions. SAP, in collaboration with Dynatrace and ServiceNow, has embraced this approach to support its Commerce Cloud, which serves over 3,500 customers across multiple industries and countries, promising 99.95% availability and rapid storefront loading times. By integrating Dynatrace's observability platform with ServiceNow, SAP can maintain a real-time configuration management database, efficiently manage about 50,000 alerts monthly, and prioritize incident responses based on business impact. This integration not only enhances resolution speed by reducing the need for solution-switching but also aims to automate more of the incident management process, moving towards a proactive service model where customers are informed of issues and their resolutions in real-time.

Kubernetes enhances software development speed and reliability through effective management of containerized workloads, but its complexity at scale presents challenges that organizations must address. Dynatrace offers a solution by integrating cloud-native observability with AIOps, which intelligently manages Kubernetes environments and provides continuous operational insights across the Kubernetes value stream. This approach helps to address key DevOps challenges, such as resource overprovisioning and safe resource resizing, by using the Davis AI engine to pinpoint root causes of performance issues and their broader impacts on the system. By dynamically evaluating workloads and identifying specific issues, Dynatrace helps organizations maintain optimal performance and user experience. The company’s platform not only highlights the interconnections between services but also ensures that Kubernetes deployments are efficient and responsive to changing business conditions.

The Dynatrace SaaS release version 1.241, announced on April 22, 2022, introduces several enhancements and features aimed at improving user experience and system functionality. Among the notable changes is the deprecation of the classic User sessions page, which will be replaced with a more advanced session segmentation page. New features include Application Security Remediation tracking, enhanced Davis AI capabilities for message queues, and updated visualization options like pie charts and single values on unified analysis pages. The release also offers a new interface for automatic tagging and improved Kubernetes monitoring with detailed pod state information. Several updates address resolved issues across different system components, including fixing broken links in Markdown tiles, enhancing API documentation, and optimizing filter operators' efficiency. Overall, the release aims to enhance the platform's usability, security, and performance through various updates and fixes.

Many companies face the challenge of data silos when implementing observability tools like OpenTelemetry, Prometheus, and Grafana, which hinders their ability to achieve comprehensive situational awareness in complex cloud-native environments. Despite the usefulness of these open-source tools for specific observability tasks, they often generate siloed data, leading to inconsistent views and increased operational overhead. To address this, companies are encouraged to integrate various data sources into a single platform, applying AI to provide consistent insights and understand root causes of issues. The Dynatrace Software Intelligence Hub exemplifies this approach by integrating with open-source tools and providing a unified view of data, as demonstrated by SAP's use of Dynatrace to streamline telemetry data collection and analysis. This integration allows organizations to overcome data silos, enabling a more cohesive and effective observability strategy.

As organizations transition to microservices and cloud-native architectures, such as those offered by Microsoft Azure, they face increased operational complexity, prompting a need for enhanced observability and migration strategies. The Azure Well-Architected Framework, developed by Microsoft, provides a set of guiding principles across five pillars—cost optimization, operational excellence, performance efficiency, reliability, and security—to help organizations design scalable and aligned architecture. Dynatrace complements this framework by offering integration and AI-driven tools that enhance monitoring, automate root-cause analysis, and improve performance management, thereby assisting organizations in optimizing costs, enhancing operational processes, ensuring application reliability, and strengthening security measures. By leveraging Dynatrace's capabilities alongside the Azure framework, organizations can achieve more effective cloud migrations and operations, with an emphasis on proactive monitoring and automated problem resolution.

Dynatrace has introduced AI-powered database extensions to enhance its AIOps capabilities, providing real-time insights into Oracle and Microsoft SQL Server databases. These extensions aim to improve database performance monitoring and management, allowing DevOps and SRE teams to optimize applications and enhance user experiences by offering precise data on performance impacts. The complexity of managing modern, cloud-native applications with a variety of databases is addressed by these tools, which offer automatic insights into performance metrics and business KPIs, facilitating cross-team collaboration. Dynatrace's Davis® AI reduces alert storms by enabling custom alerting and auto-adaptive baselining, ensuring alerts are raised only for significant events. The extensions also allow for custom configurations to track and alert on data from databases, further integrating intelligent observability into their Application Performance Management (APM) suite. Future enhancements include query-level visibility and additional database monitoring extensions for technologies like Oracle RAC and SAP HanaDB, aiming to offer comprehensive observability and automated root cause analysis.

Dynatrace has officially launched its Software Intelligence Platform as a Software as a Service (SaaS) solution on Google Cloud Platform, marking a significant step in its strategic partnership with Google. This move provides Google Cloud customers with enhanced flexibility in choosing cloud services while benefiting from Dynatrace’s comprehensive application and infrastructure monitoring, digital experience management, and security features. The platform integrates unified AIOps to simplify cloud operations and automate DevSecOps across major cloud technologies, enabling organizations to manage complexity and reduce manual efforts. Additional benefits include consolidated billing through the Google Cloud Marketplace, easy deployment of Dynatrace OneAgent, and extensive support for over 50 Google Cloud services. This enhanced level of observability helps teams accelerate root-cause analysis, improve security, and enhance user experiences, aligning with ongoing digital transformation goals.

Kitopi, a cloud kitchen network, has experienced significant growth over the past two years, necessitating enhanced observability of its end-to-end kitchen delivery workflow. The company transitioned from a DIY approach to using the Dynatrace Software Intelligence Platform to monitor infrastructure, application, and business process metrics efficiently. This shift enabled faster and more accurate problem detection and resolution, reducing Mean Time to Resolution (MTTR) for various issues while improving visibility. Kitopi's architecture, relying on Apache Kafka, allows for an event-driven system that tracks order and kitchen status, with improvements made to extract and visualize business metrics effectively. By integrating Dynatrace, Kitopi has automated anomaly detection and alerting, enhancing operational efficiency and ensuring customer satisfaction. The company plans to further leverage Dynatrace's capabilities for unified data analysis and automated problem remediation, optimizing its operations and maintaining its commitment to satisfying customer demands.

Dynatrace has been acknowledged as a launch partner for Amazon Web Services' new offering, Amazon EKS Blueprints, a framework designed to simplify the deployment of shared services to Amazon EKS clusters. This service aims to enhance user experience by automating Kubernetes EKS and integrating the Dynatrace Intelligent Observability Platform. Kubernetes serves as an orchestration engine for containerized applications, aiding in automation processes, while Amazon EKS provides a managed infrastructure service for executing Kubernetes applications in the AWS cloud. EKS Blueprints provides best practices for deploying these services, easing the complexity and facilitating tool integration, continuous delivery, automation, and management from a single GIT repository. By integrating the Dynatrace OneAgent Operator via EKS Blueprints, users gain enhanced observability and automatic root-cause analysis, enabling agile and efficient application management. This collaboration underscores Dynatrace's commitment to innovation and leadership in cloud computing, offering users the tools to modernize their application infrastructure efficiently.

Site Reliability Engineering (SRE) using DevOps highly relies on automation to facilitate rapid testing and release schedules, with observability being key to balancing the needs of developers and operations teams. The open-source project Keptn, developed by Dynatrace, serves as a control plane that automates cloud-native continuous delivery and operations by configuring observability tools, dashboards, and alerts based on service-level objectives (SLOs). By reducing the complexity associated with traditional scripting and allowing the integration of preferred tools, Keptn streamlines the orchestration of multi-stage application delivery and enables developers to focus on SREs. Its adoption is growing among companies for its ability to automate production releases and validation processes, ensuring that applications meet high availability standards like "the five nines." Keptn uses a declarative approach to define automation sequences, retains tool configurations under version control, and provides SLO-based release validation, making it a valuable asset for developers who want to maintain production sequences without extensive manual customization. Additionally, Dynatrace offers an enterprise version through its cloud SaaS, which includes features like self-management and automatic upgrades, and Keptn's future roadmap includes improvements in high availability, role-based access controls, and GitOps.

Dynatrace has played a pivotal role in assisting the U.S. Department of Veterans Affairs (VA) in modernizing its cloud operations by transitioning from reactive to proactive strategies, addressing the growing complexity of cloud environments. As organizations, including the VA, expand their cloud infrastructures to include public, private, and on-premises systems, they encounter challenges such as cloud observability walls, which arise when moving from static virtual machines to dynamic container orchestration and multicloud environments. Dynatrace provided the VA with advanced monitoring capabilities that enabled the agency to manage over 150 cloud instances effectively, especially during the COVID-19 pandemic, when remote work demands surged. By leveraging Dynatrace’s AI, Davis, the VA could detect potential issues before they impacted operations, ensuring consistent service delivery. The agency also utilized Dynatrace to optimize its mission-critical applications, such as the Consolidated Mail Outpatient Pharmacy Application, by addressing performance bottlenecks and preparing for cloud migration. Dynatrace’s comprehensive observability tools, like Smartscape topology and AI-driven insights, have empowered organizations to innovate rapidly and maintain operational efficiency, with companies like SAP and Kroger already benefiting from proactive cloud operations.

The #BreakTheBias campaign theme for International Women's Day 2022 aimed to promote a gender-equal world free of bias and discrimination, encouraging diverse and inclusive environments. Dynatrace's Women Employee Resource Group (ERG) supports this initiative by increasing women's participation in tech and highlighting their achievements. The company hosted a virtual panel during Women’s History Month, featuring board members Jill Ward, Kirsten Wolberg, and Ambika Kapur, moderated by Denise Mitchell. The discussion focused on overcoming bias in workplaces, with Wolberg referencing a Stanford study on gender-biased language in performance evaluations. The panelists shared personal stories and professional motivations, emphasizing the importance of subjective measures such as meaningful work and life events. The event concluded with a reflection on personal and professional balance, inspiring participants to consider their own "crystal moments" and encouraging further engagement with International Women's Day themes.

Dynatrace Labs has developed an innovative approach to enhance functional test result analysis by integrating Selenium with Dynatrace Real User Monitoring (RUM), allowing for a seamless connection between test outcomes and detailed performance data. This integration provides testers and developers with a direct link to a Dynatrace RUM dashboard whenever a test fails or runs slower than expected, streamlining the triage process and eliminating the need for manual data searches. As part of their Acceptance Test Environment, Dietmar Strasser's team uses this integration to monitor various test environments and ensure that any potential issues with virtual machines (VMs) running Selenium tests are detected early, promoting efficient and reliable test cycles. By passing test context to Dynatrace user sessions and leveraging its APIs, teams can enhance their test results with additional metrics and make informed decisions about test execution based on the health of the application environment. This methodology underscores the importance of accessible metrics within continuous delivery and feedback processes, encouraging other teams to adopt similar strategies for improved software testing.

The blog post emphasizes the importance of Role-Based Access Control (RBAC) in enhancing the security of Kubernetes clusters, particularly within the context of managing almost 400 clusters at Dynatrace. It outlines the basic steps of RBAC, which include defining roles or ClusterRoles, creating service accounts or managing users/groups, and binding these roles to appropriate subjects. Key best practices highlighted include ensuring the principle of least privilege by granting only necessary permissions, avoiding the use of default service accounts, and instead creating dedicated service accounts for pods that need to access the kube-apiserver. The post also advises disabling the automounting of service account tokens for pods that do not require kube-apiserver access and stresses the importance of naming roles clearly and defining roles based on permissions rather than on service accounts. The piece concludes by pointing out that adhering to these practices is an essential step towards securing a Kubernetes cluster, with future posts promising to address NetworkPolicies.

Dynatrace's CEO expresses enthusiasm for the company's potential, driven by an expansive market for digital transformation, differentiated technology, strong company performance, and talented employees. Through engagement with stakeholders, the company has refined its mission, purpose, and vision to better articulate its goals and differentiate itself in the market. Dynatrace's mission is to provide intelligent automation and insights from data through its platform, which enhances cloud ecosystem situational awareness. The company's purpose is to enable secure and flawless digital interactions amidst the complexity of digital transformation. Their vision is to create a world where software operates perfectly, driving investments in advanced software intelligence. The CEO is inspired by these guiding principles and optimistic about the company's future impact on customers and stakeholders, asserting that Dynatrace uniquely offers the comprehensive observability, precision, and automation necessary for modern cloud environments.

Dynatrace has integrated its PurePath® technology with Fluentd to enhance log and trace analysis in Kubernetes environments, offering a comprehensive observability solution. By combining Fluentd logs with distributed traces, Dynatrace provides a transaction-centric view of data that facilitates more actionable insights for DevOps and platform teams, helping to pinpoint root causes of anomalies using the AI engine, Davis. Fluentd, an open-source data collector, supports a wide array of plugins for log collection, processing, and output, and can be run as a DaemonSet in Kubernetes clusters. Dynatrace's approach enriches logs with metadata, providing a detailed context that aids in fast ad-hoc problem debugging and precise anomaly detection. The platform's ability to model causal relationships between observability data enhances performance analysis and resource allocation, offering users the flexibility of custom metrics and alerting for specific log events. While Fluentd offers a robust plugin ecosystem, Dynatrace's OneAgent DaemonSet provides ease of deployment and automation, making it a compelling choice for organizations looking to streamline log monitoring in Kubernetes environments.

Dynatrace Managed version 1.240 introduces several updates and enhancements aimed at improving security, cluster management, and Kubernetes event monitoring. Notable changes include the update of the OpenSSL library for enhanced security, the addition of a cluster REST API for managing notifications related to disk space and hardware insufficiencies, and the transition of Kubernetes event monitoring from Early Adopter to General Availability, affecting how tenants receive event notifications. The release also addresses multiple resolved issues across various components, such as Autonomous Cloud, cloud automation, and cluster management, improving functionalities like user interface efficiency, error handling, and performance. Additionally, updates and changes in operating systems support are outlined, with some systems no longer being supported after specified dates, prompting users to adjust accordingly. The release notes highlight ongoing improvements and fixes, including enhanced alerting precision, resolved vulnerabilities, and better user experience through interface and process adjustments.

Dynatrace's version 1.240 release introduces several enhancements and changes designed to improve production resiliency and observability. Key updates include automated problem remediation through Dynatrace Davis® AI, which detects issues and triggers remediation actions. There are notable changes such as the end-of-life for Session Replay masking v1 and the classic User sessions page, replaced by more advanced alternatives. New features include burn rate visualization for service-level objectives, expanded application security monitoring, and enhanced Kubernetes monitoring now available in General Availability, subject to DDU consumption. The OS service monitoring now supports both Windows and Linux services, while dashboards can be filtered by custom dimensions. Various resolved issues across clusters and user interfaces highlight improvements in alerting, network zones, JVM memory charts, and support for ServiceNow notifications. The release notes also detail updates to the Dynatrace API and other settings, ensuring users have access to the latest functionalities and security measures.

Dynatrace Davis AI now offers automated analysis of Spring Boot application metrics through Micrometer, requiring no configuration effort from users. This integration, enhanced by OneAgent, facilitates real-time topology discovery across various platforms and technologies. While some companies adopt open-source solutions like Micrometer for vendor neutrality and broad data collection, Dynatrace provides advanced tools for managing the complexity of analyzing extensive data sets. With its AI engine, Davis AI, Dynatrace delivers topology-aware anomaly detection, auto-adaptive baselines, and seamless metric exportation via the Dynatrace Metrics API v2. The integration supports automatic and secure metric collection without complex configurations, enhancing the ability to perform in-depth analyses and generate actionable insights. Users can easily integrate Micrometer metrics into their monitoring systems with minimal setup, leveraging Dynatrace's capabilities to handle a wide range of pre-instrumented and custom metrics from Spring Boot applications.

Dynatrace has been recognized as a launch partner for AWS's new Lambda Function URLs, a feature that enhances the accessibility and configuration efficiency of AWS Lambda functions by allowing developers to invoke functions over HTTPS without needing to provision APIs or gateways. This feature introduces a new Lambda resource type with APIs for creating and managing URLs, which can be monitored with CloudWatch metrics, offering increased efficiency, streamlined configuration, and improved observability with tools like Postman, Cloud Formation, and Terraform. The integration aims to provide seamless end-to-end distributed tracing, automatic root cause analysis, and insights into serverless functions' impact on user experience, while also offering opportunities for optimization through response time and error analytics. Dynatrace guides users on setting up AWS Lambda monitoring within its environment, offering configuration options through environment variables, config files, or code snippets, and encourages users to explore its capabilities with a free trial to optimize Lambda architectures and improve infrastructure monitoring and management.

The OneAgent version 1.237 release introduces several enhancements and support changes across various platforms and features. Key updates include monitoring capabilities for process availability and resource-intensive processes on hosts, support for OpenTelemetry Java agent auto-instrumentation, and the addition of PHP code module support on Linux ARM64. Notable changes also involve the expanded support for web servers like Apache and NGINX on Linux ARM64, and the introduction of new features for Java and z/OS. The release notes detail future support discontinuations for certain operating systems, such as Amazon Linux 2 and Windows Server 2012 R2, and highlight resolved issues across components like the AI causation engine, infrastructure monitoring, and logging modules. Additionally, improvements in input validation for Real User Monitoring and the stability of OneAgent modules for .NET, PHP, and mobile platforms are addressed, along with fixes for vulnerabilities and bugs affecting various areas, including JavaScript and mobile agents.