July 2022 Summaries

The global supply chain faces significant challenges from the increasing prevalence of software supply chain attacks, which have surged dramatically in recent years, particularly with open-source vulnerabilities such as the Log4Shell incident. These attacks occur when malicious actors infiltrate a software vendor's network and compromise the software before distribution, potentially affecting entire supply chains due to the interconnectedness of modern business systems. The rapid pace of software development exacerbates this issue as vulnerabilities can be overlooked, leading to compromised applications. Organizations are urged to adopt strategies like "shifting left" to integrate security testing early in development and "shifting right" to monitor runtime vulnerabilities, supported by modern observability techniques. These approaches, enhanced by AI-driven data analysis and automation, enable organizations to quickly identify, prioritize, and address security vulnerabilities, extending their cybersecurity efforts beyond their own systems to include third-party software and code practices.

The Dynatrace SaaS release version 1.248 introduces several key features and enhancements aimed at improving monitoring capabilities and access control. Notably, cross-environment tracing allows for seamless monitoring across different environments, maintaining a comprehensive end-to-end view. The release also includes fine-grained access control for Dynatrace Cloud Automation, which is crucial for managing user roles and permissions in sensitive projects. Additional updates include enhancements to application security, Kubernetes monitoring, and management zone tagging. The release provides new security notifications via email, improvements to the Smartscape topology view, and adjustments to service-level objectives. The release monitoring has been enhanced with new event ingestion capabilities and validation indicators. Several resolved issues across various components, such as cloud automation and the user interface, improve overall system functionality and reliability. The update also addresses specific issues in mobile session replay, on-prem installations, and API functionalities, ensuring a smoother user experience and more accurate monitoring.

The Dynatrace Managed release notes for version 1.246, published on July 27, 2022, outline several key changes and enhancements, including the end of support for certain operating systems such as CentOS 6.x and Red Hat Enterprise Linux 6.x, while introducing support for Red Hat Enterprise Linux 9.0. The release addresses a variety of resolved issues across components like ActiveGate, Application Security, and Cluster, with improvements such as fixing memory leaks, enhancing security problem visibility, and correcting alerting configurations. The notes detail multiple updates, including significant cumulative updates, that fix issues like incorrect baseline calculations and cluster upgrade failures. Additionally, future support changes are announced, indicating the end of support for additional operating systems by December 2025 and January 2026.

The Forrester Total Economic Impact (TEI) Study, commissioned by Dynatrace, highlights the substantial return on investment (ROI) that organizations can achieve through the deployment of Dynatrace's solutions, estimating an impressive 274% ROI over three years. This study, discussed in a recent webinar hosted by Dynatrace, involved a diverse range of companies and revealed consistent benefits such as improved DevOps innovation and operational efficiency. Although some benefits like enhanced employee productivity are subjective to company size and circumstances, the study provides a comprehensive financial framework that partners can adapt for their prospects. The study also emphasizes the importance of using specific data points and examples from existing customers to illustrate benefits to potential clients, and Dynatrace offers resources like a "Campaign-in-a-Box" to help partners leverage the study's findings effectively. Additionally, the study underscores the advantages of a full-stack approach to observability in increasingly complex digital environments, offering insights into improved business vision and interdepartmental collaboration.

Dynatrace has launched a new Prometheus Extension for Apache Cassandra in collaboration with Microsoft, aiming to enhance performance monitoring for Azure Managed Instance for Apache Cassandra. Apache Cassandra, a widely trusted open-source, distributed NoSQL database, is crucial for cloud and hybrid workloads due to its scalability and high availability. The partnership makes Dynatrace a natural fit for Microsoft's Azure Managed Instance for Apache Cassandra Service, providing a comprehensive solution that simplifies hybrid cloud complexities. This extension allows users to ingest and analyze Cassandra metrics within the Dynatrace platform, offering preconfigured dashboards and detailed insights into infrastructure and data metrics. The Dynatrace Data Explorer facilitates in-depth analysis with various visualizations, enabling users to assess metrics like client read/write latency and disk space usage. Additionally, the extension integrates with Dynatrace's AI causation engine, Davis®, which provides precise, root-cause analysis to streamline troubleshooting and improve application performance. Users can begin monitoring their Azure Managed Cassandra instances with a 15-day free trial, gaining access to tools that visualize performance issues and prioritize problem resolution.

Dynatrace's SaaS release version 1.246, published on July 25, 2022, brings a range of new features and enhancements across its platform. Key improvements include upgrades to the Data Explorer for enhanced data visualization and analysis, expanded distributed traces capabilities that now display complete traces with service call highlights, and new policy and API support for custom service detection. The release also introduces enhancements in security notifications integration, such as test notifications for verification, and further development in Kubernetes metrics monitoring, marking some existing metrics as deprecated while maintaining compatibility through a transition period. Additionally, the Smartscape topology now highlights third-party vulnerabilities, and management-zone settings have been updated for better permission management. The release also resolves 30 issues across various components, improving reliability and user experience, while the Dynatrace API and other tools receive updates to align with these changes.

Dynatrace has introduced support for Amazon's new VPC Flow Logs for AWS Transit Gateway, enhancing users' visibility into network traffic by directing Flow Logs to Amazon S3 or CloudWatch Logs. AWS Transit Gateway facilitates the connection of network resources through a centralized hub, while VPC Flow Logs capture detailed IP traffic data within VPCs. This integration with Dynatrace allows for sophisticated analysis of network traffic using their AI-driven platform, Davis®, which detects and alerts on performance anomalies. Dynatrace's capabilities include automated log monitoring and problem detection, providing detailed network-specific insights that aid in troubleshooting and improving system performance. The introduction of VPC Flow Logs for Transit Gateway represents a significant advancement in application monitoring, offering users enhanced tools for managing network-related traffic within their digital environments.

Dynatrace Cloud Automation has introduced fine-grained access control through Role-Based Access Control (RBAC), allowing organizations to define user roles and permissions based on their specific needs within the Software Development Lifecycle (SDLC). This update builds on the existing single sign-on (SSO) capabilities, enabling detailed management of user permissions by roles such as Developer, Product Engineer, and Site Reliability Engineer, among others. The RBAC system allows for policy, group, and user management, providing administrators with the ability to control which team members have access to specific tools and functions within the Cloud Automation environment. The recent update includes default policy templates for various permission levels, facilitating the setup of customized access policies. This enhancement aims to streamline the management of permissions and improve compliance and operational efficiency in DevOps and cloud automation workflows.

Dynatrace has introduced a new feature allowing for seamless integration of its synthetic monitors with external secret vaults such as HashiCorp Vault and Azure Key Vault, enhancing security and efficiency in managing credentials for monitoring websites and API endpoints. This integration enables automatic synchronization of credentials stored in Dynatrace with those in external vaults, simplifying the management of authorization secrets and reducing redundancy and security risks associated with frequent credential rotations. Users can create entries in the Dynatrace credential vault, mark them for synchronization, and provide the necessary external vault details, enabling Dynatrace to automatically generate synthetic HTTP monitors that synchronize the credentials without further management intervention. This feature supports a variety of authentication methods and offers flexibility in adjusting monitor definitions to accommodate different authorization methods or vaults. The synchronization process is designed to protect sensitive information by not storing execution details such as headers and payloads. This enhancement is part of a broader effort to improve Dynatrace Synthetic Monitoring, with future plans including on-demand execution triggers and deployment of private synthetic locations within Kubernetes clusters.

As digital transformation accelerates, developers face increasing pressure to proactively optimize applications and improve user experiences by addressing unforeseen production issues. Logs play a crucial role in this process, and Dynatrace enhances their utility by integrating them with user sessions and Session Replay, providing both frontend and backend developers with detailed insights into user journeys. This integration allows developers to identify and fix issues more efficiently, improving application performance and customer satisfaction while addressing the challenges posed by the massive volume of generated logs, which are often noisy and irrelevant. Dynatrace's solution, supported by Davis AI, enables prioritization of meaningful log entries and provides comprehensive visibility into user interactions, helping developers not only resolve current issues but also prevent future ones. This proactive approach mitigates the risk of losing customers to competitors and supports long-term business success. Furthermore, Dynatrace distinguishes itself by offering a comprehensive package with automatic application instrumentation and advanced digital experience monitoring, with plans to expand log storage and retention capabilities to meet industry demands.

Artificial intelligence is increasingly viewed as essential by U.S. government leaders for achieving mission outcomes, yet its deployment is hampered by significant challenges, including a lack of staff knowledge and trust in the technology. Research highlights that over half of the federal IT managers see AI as a high investment priority, but barriers such as insufficient understanding of AI benefits and fears of job replacement persist. Experts recommend focusing on mission-aligned strategies, starting with small, manageable projects like chatbots to build trust and understanding, and addressing skill gaps through training and collaboration with industry experts. Additionally, it's emphasized that AI should be seen as a tool for enhancing efficiency by automating mundane tasks, thus allowing IT professionals to engage in more strategic work. Overcoming these obstacles is crucial for unlocking AI's potential, with initiatives aimed at demonstrating its practical benefits and ease of use to build confidence among decision-makers and stakeholders.

Dynatrace Davis AI and Cloud Automation work together to enhance production environment stability by automatically detecting problems, identifying root causes, and executing remediation actions to minimize downtime and maintain service level objectives (SLOs). This approach supports development teams who prioritize innovation and quick releases while ensuring operational reliability through automated validations and problem remediation. The solution addresses critical challenges such as manual processes and communication issues, thereby reducing the financial and reputational impact of downtime, which can be costly for large organizations. By utilizing feature flag settings, process restarts, Kubernetes resource adoption, deployment rollbacks, and targeted notifications, automated remediation swiftly resolves issues. The blog post introduces a series focused on various problem remediation use cases and encourages further exploration of integrating these capabilities into existing DevOps toolchains to improve software delivery and issue resolution.

OpenTelemetry is a project designed to meet the increasing demand for artificial intelligence-enabled IT operations (AIOps) as organizations expand their technological infrastructures into multiple cloud environments. It offers a standardized set of vendor-neutral APIs that facilitate data collection from applications across various programming languages and frameworks, allowing for easier instrumentation and monitoring. This initiative is gaining traction, with Gartner predicting that by 2025, 70% of new cloud-native application monitoring will rely on open source instrumentation. OpenTelemetry is not an analytics engine but complements existing tools, providing greater flexibility by not being tied to a specific back-end system. It can be deployed manually or through semi-automatic instrumentation, offering different levels of control and ease of implementation. Companies like Dynatrace and W.W. Grainger utilize OpenTelemetry to enhance observability and streamline operations, enabling faster incident response and improved DevOps practices. The adoption of OpenTelemetry involves strategic planning and coordination across development and operations teams, focusing on use cases that leverage its capabilities while ensuring data privacy and standardization throughout the organization.

As organizations increasingly adopt cloud-native technologies, containers, and microservices, effective log monitoring and management have become essential to navigate the growing complexity and volume of logs. The log management market is projected to expand significantly, driven by the widespread use of hyperscale cloud providers like AWS, Azure, and GCP. Logs, which are timestamped records of events from various systems, provide crucial insights into system performance and user interactions. Log monitoring involves continuously observing logs to detect and address issues across the software delivery lifecycle, while log analytics evaluates logs to understand their significance and improve system performance. Together, these processes ensure optimal operation of applications and infrastructure, enhance collaboration, and enable faster incident response. However, challenges such as lack of end-to-end observability, inadequate context, and high costs can hinder effective log monitoring. Dynatrace addresses these challenges by using AI to provide comprehensive insights and automate processes, helping organizations gain situational awareness and improve both IT operations and business outcomes.

As federal agencies work to implement zero trust (ZT) cybersecurity measures as mandated by a White House Executive Order, challenges arise in balancing robust security with user-friendly experiences. While ZT principles like "trust nothing, verify everything, and enforce least privilege" are essential for protecting against cyber threats, the implementation often complicates interactions for both citizens and federal employees, as illustrated by a cumbersome experience with multi-factor authentication (MFA). This tension was a focal point of a panel discussion at the Advanced Technology Academic Research Center, where experts emphasized the need to integrate user experience considerations from the start of ZT initiatives. The discussion highlighted best practices such as simplifying authentication processes and leveraging advancements in biometrics and behavioral biometrics to make security seamless and unobtrusive. Additionally, agencies are encouraged to employ full-stack observability to monitor performance and ensure ZT policies do not impede user experiences. The panelists, including representatives from Dynatrace, underscored the importance of marrying security with positive user experiences to prevent users from turning away due to overly complex security protocols, advocating for a holistic approach that enriches federal IT systems while maintaining robust cybersecurity.

Google has launched Tau T2A virtual machines on Compute Engine, optimized for cost-effective performance on Arm architecture, as well as GKE Arm to support scale-out workloads. As a launch partner, Dynatrace emphasizes the importance of maintaining observability in Kubernetes environments, particularly with GKE Arm clusters, to ensure performance and availability. By integrating infrastructure, application, and site reliability engineering teams using the same data, issues can be resolved more efficiently, facilitating digital transformations. Dynatrace offers real-time topology mapping and anomaly detection through its AI engine, Davis, to enhance Kubernetes monitoring, now extended to GKE Arm clusters. The company continues to expand its partnership with Google Cloud, providing advanced observability solutions for modern cloud infrastructures.

The Dynatrace report unveils significant challenges in vulnerability management within the financial services sector, as banks and insurers increasingly adopt multicloud environments and cloud-native architectures to accelerate digital transformation. Despite employing layered cybersecurity strategies, more than 75% of CISOs believe their current security measures are insufficient to prevent vulnerabilities from entering production. The rapid pace of software delivery and reliance on open-source code exacerbate these challenges, with many security alerts proving to be false positives. Only a small fraction of organizations have real-time visibility into runtime vulnerabilities, and the majority lack comprehensive insights into third-party code usage. The report emphasizes the importance of adopting a DevSecOps culture and leveraging AI and automation to enhance security measures, suggesting that security should be a shared responsibility across the software development lifecycle to effectively manage risks and protect sensitive financial data.

Park 'N Fly, an operator of 15 offsite airport parking lots in the U.S., leverages IT automation, AIOps, and observability to enhance infrastructure management and develop revenue-generating services, thereby improving customer experience. By utilizing these technologies, Park 'N Fly offers services like pet boarding, vehicle detailing, and customer kiosks, supported by robust software intelligence. The transition to cloud infrastructure with Microsoft Azure initially introduced visibility challenges, but the implementation of Dynatrace's observability platform allowed the company to automate troubleshooting and improve infrastructure transparency. This automation not only aids in efficient problem resolution but also accelerates code development without compromising quality, leading to increased productivity and innovation. The strategic use of IT automation has empowered Park 'N Fly's IT teams to move beyond reactive tasks to focus on more strategic, business-aligned goals, earning the department a reputation for competence and innovation within the company.

Dynatrace has been recognized as a Leader in the 2022 Gartner Magic Quadrant for Application Performance Monitoring (APM) and Observability, positioned furthest for Completeness of Vision, and scored highest in four out of six use cases in the Gartner Critical Capabilities report. This recognition highlights Dynatrace's ability to anticipate market trends and innovate within its platform, particularly with its early adoption of observability and AI-enhanced capabilities, which differentiates it from other vendors. For partners, this acknowledgment validates confidence in Dynatrace's solutions and offers opportunities for large-scale transformation projects, enhancing their ability to deliver precise, intelligent automation solutions from observability data in modern cloud environments. Dynatrace's leadership in the market is underscored by its platform's extensive capabilities, spanning applications, infrastructure, user experience, and security, aligning with the latest open-source standards and providing partners and customers a competitive edge.

The sense-think-act model, originally used in robotics and self-driving cars, is increasingly being applied to IT operations through AIOps and observability to manage the complexity of cloud-native technologies. This approach enables IT teams to automatically detect, analyze, and respond to issues within multicloud environments, addressing challenges such as system performance, security risks, and application problems. By leveraging observability to "sense" data from user experience and infrastructure health, artificial intelligence to "think" and analyze this data for actionable insights, and AIOps to "act" by automating responses to anomalies, organizations can enhance decision-making, streamline operations, and mitigate risks. Dynatrace exemplifies this model by providing end-to-end observability and AI-driven automation to manage complex multicloud workloads, thereby enabling self-driving IT operations and reducing the need for manual interventions in problem-solving and system maintenance.

Microservices architecture is increasingly favored by organizations for its benefits like enhanced testing, easier deployment, and improved performance compared to monolithic architecture. While microservices break down applications into modular services with specific functions, monolithic architecture structures software as a single, large unit, often leading to management challenges as applications grow. Organizations must carefully consider the transition from monolithic to microservices architecture due to potential challenges like increased complexity, resource consumption, and the need for comprehensive monitoring solutions. Service-oriented architecture (SOA) is another alternative, focusing on protocols and larger databases, but many developers view microservices as a more refined and agile form of SOA. The choice between microservices and monolithic approaches also involves deciding on containerization strategies, with containers offering resource efficiency and scalability. Effective microservices implementation requires tools such as container orchestration environments, API gateways, and service mesh platforms, alongside robust monitoring and alerting systems to ensure application health and performance.

Site Reliability Engineering (SRE) is increasingly being adopted by organizations to manage the complexities of hybrid and cloud-native environments, which include thousands of microservices and a multitude of solutions within the Cloud Native Computing Foundation. Despite being in the early stages of adoption, SRE helps organizations better align reliability metrics with business objectives and enhances customer experience. Challenges such as training difficulties and finding skilled professionals are common, suggesting that developing internal expertise and using automated tools can facilitate SRE adoption. Standardizing toolchains and adopting an "everything-as-code" approach can reduce labor costs and improve system reliability through self-healing capabilities. Automation and AI are crucial for scaling SRE practices, enabling organizations to link business objectives with service-level objectives (SLOs) and reduce manual labor, although defining effective SLOs remains challenging due to information silos and complex toolsets. AIOps is becoming popular as it automates processes, enhances monitoring, identifies security vulnerabilities quicker, and supports predictive monitoring. As SRE matures, these practices are expected to provide organizations with a competitive edge in managing their application portfolios effectively.

AIOps, or artificial intelligence for IT operations, leverages machine learning and AI to manage the increasing complexity and scale of IT environments through automation, offering numerous benefits beyond just reducing complexity. By automating key processes like anomaly detection and root-cause analysis, AIOps not only enhances operational efficiency but also reduces IT costs by minimizing false positives and preventing costly outages. It enables faster business innovation by freeing IT teams from routine tasks, thus allowing them to focus on strategic initiatives. Additionally, AIOps promotes expanded collaboration across departments through its data-agnostic approach and streamlines product improvements by providing actionable insights. Enhanced automation capabilities allow IT teams to prioritize outcomes over manual processes, accelerating digital transformation in multicloud environments. Ultimately, AIOps delivers significant business value by improving system reliability, user experiences, and return on investment in hybrid cloud technologies, while fostering greater IT staff efficiency through better decision-making and collaboration.