June 2023 Summaries

Optimizing strategies for open source contributions and usage is becoming crucial for organizations, as open source software (OSS) offers a faster, more collaborative, and flexible way of driving innovation compared to proprietary software. In 2022, 80% of organizations increased their use of OSS, particularly in critical infrastructure sectors like oil and gas, telecommunications, and energy. However, challenges such as governance, security, and balancing OSS contributions with commercial advantages persist. Organizations that engage in OSS benefit from diverse contributions, cost savings, and a culture of innovation, which can attract top talent and allow them to influence the technology's future. To maximize OSS contributions, organizations should define the scope of their involvement, contribute to open standards, and build robust security practices to manage vulnerabilities. As OSS becomes integral to long-term success, developing a strategic approach to using and contributing to OSS projects is essential for maintaining a competitive edge.

Dynatrace enhances enterprise observability, troubleshooting, security, and automation by streamlining the integration of log data from Amazon Web Services S3 into its Grail data lakehouse. This integration facilitates easy querying and analysis of log data without the complexities of storage management, addressing the growing need for comprehensive insight into cloud service activities across multiple AWS accounts and regions. The Dynatrace AWS S3 log forwarder, now offering enterprise-level support, simplifies the process of ingesting logs from AWS S3, supporting both text- and JSON-formatted logs from AWS services and third-party solutions. This solution maintains metadata, allowing for effective linking of logs to their source applications and infrastructure, thereby enhancing the unified observability on the Dynatrace platform. The log forwarder's scalable design handles large data volumes, enabling users to leverage exploratory analytics and visualization tools, such as Dashboards and Notebooks, to gain valuable insights from their log data.

In the digital era, software automation and analytics are crucial for optimizing business processes and enhancing efficiency. Software automation involves creating applications to automate repetitive IT tasks, helping digital supply chain stakeholders accelerate innovation and bring products to market more swiftly. Software analytics, on the other hand, provides insights from software-generated data, improving software quality and security through big data analytics and AI techniques. AIOps plays a pivotal role by applying advanced AI to automate cloud operations, enhancing infrastructure monitoring, application performance, and security. Implementing software automation varies by organization, but common goals include optimizing automation and observability across the software lifecycle. AIOps, integrated with cloud strategies, facilitates self-service observability and monitoring, enabling organizations to meet demand efficiently. The Dynatrace platform exemplifies how AI-driven insights can advance automation, offering a competitive edge by analyzing data in real time and driving innovation through a unified automation and analytics approach.

Dynatrace has launched its AI-powered SaaS platform on Microsoft Azure in Switzerland, marking the first observability solution available as a Switzerland-based SaaS deployment for Microsoft customers. This offering addresses the complex regulatory and data residency requirements of Swiss customers, ensuring that all data remains within a Swiss data center, in compliance with local regulations such as FINMA. By hosting the platform in the Azure Switzerland North region, Dynatrace provides Swiss customers with end-to-end observability and continuous runtime application security while benefiting from Azure's security and global reach. The integration allows customers to leverage the Azure Native Dynatrace Service, facilitating an automated setup and configuration directly from the Azure marketplace, and enabling purchases through the Microsoft Azure Consumption Commitment. The solution empowers developers and IT administrators to efficiently monitor their cloud applications while maintaining control over data location and security.

Government agencies face the challenge of building public trust while delivering seamless digital experiences, a task complicated by the necessity of cloud migration and the high expectations set by digital giants like Amazon. To meet these expectations, agencies must provide 24/7 online services, maintain robust cybersecurity, and ensure a competent digital reputation. While these goals are clear, agencies often struggle with a lack of skilled IT resources, difficulties in migrating legacy systems, and detecting security breaches. Leveraging technologies that offer real-time visibility and automation can help overcome these challenges, driving modernization and efficiency in government services. By adopting a unified observability and security platform, agencies can ensure uninterrupted digital transactions, thereby enhancing public trust and satisfaction.

Dynatrace has expanded its mobile app monitoring capabilities to include support for SwiftUI, .NET MAUI, and Jetpack Compose, addressing the growing adoption of these frameworks by development teams. These frameworks, known for their declarative syntax and streamlined development processes, present new challenges in monitoring user experience. Dynatrace, a leader in auto-instrumentation, now offers enhanced visibility and error identification for apps using these technologies, allowing developers to focus on innovation and user experience. With mobile Real User Monitoring (RUM), developers can quickly detect and resolve issues, meeting high consumer expectations for flawless mobile app experiences. Observability remains crucial, as it facilitates informed decision-making and performance optimization by collecting comprehensive data on user interactions and app performance. Dynatrace’s platform automates the capture of user interactions and app lifecycle data, minimizing the manual effort required from development teams, and providing insights that enhance user journeys and business outcomes.

Modern IT organizations face challenges in handling the massive and diverse data generated from various tools and technologies, leading to data silos that complicate the understanding and actionability of this information. An Italian bank encountered issues with inconsistent data and tracing across its custom applications managed by Apigee, which couldn't consistently export traces due to restrictions in its distributed tracing configuration. To ensure comprehensive monitoring and trace normalization, the bank partnered with Liquid Reply and adopted OpenTelemetry and Dynatrace. This collaboration enabled the bank to achieve 100% trace coverage by leveraging OpenTelemetry's open standards, converting data formats for easy ingestion into Dynatrace, and maintaining trace context throughout the process. The partnership highlights the benefits of integrating OpenTelemetry with Dynatrace, providing a seamless solution for end-to-end observability even in complex environments with custom APIs.

Dynatrace® AutomationEngine offers a low-code/no-code solution for workflow modeling, enabling seamless integration with various systems to support complex business logic and incident management. It empowers users by automating the response to security vulnerabilities and operational issues through predefined workflows that automatically create tickets and escalate incidents as needed. Leveraging Dynatrace observability, security monitoring, and Davis® causal AI, AutomationEngine can respond precisely to threats across hybrid and multicloud environments, with capabilities like blocking attacks or scaling resources. The system supports closed-loop functionality, integrating with tools like Jira and Slack for comprehensive incident lifecycle management, and offers custom extensions through HTTP calls, JavaScript, and custom apps to address specific business needs. With continuous enhancements and integrations, Dynatrace aims to streamline automation processes across AIOps, DevOps, and Security, encouraging users to explore its features through a free trial or demo.

Cloud application security has become increasingly crucial as cloud-based applications grow in popularity, driven by their flexibility and rapid deployment capabilities. However, these same features introduce security risks, requiring organizations to implement robust security measures, particularly within DevSecOps teams managing complex, microservices-based, cloud-native applications. Cloud application security encompasses a range of strategies, including authentication, data encryption, and vulnerability management, to mitigate exposure to threats. The shared security responsibility model between cloud service providers and organizations emphasizes the need for secure coding practices and monitoring. Challenges such as open-source vulnerabilities, siloed security tools, and rapid development cycles complicate the security landscape, while threats like misconfiguration, unauthorized access, and insecure APIs persist. Best practices involve strong authentication, regular updates, and proactive monitoring. The evolving nature of cloud applications necessitates advanced, automated solutions like Dynatrace, which integrates observability and security analytics to enhance real-time threat detection and streamline the software development lifecycle.

Dynatrace Managed version 1.268 introduces several enhancements and resolves numerous issues across various components. Key updates include the upgrade of the OpenSSL library to version 3.0 for increased resilience and security, now supporting FIPS 140-2 compliant cryptographic modules and TLS 1.3 communication in Nginx. The release also expands support for several Linux operating systems, such as Red Hat Enterprise Linux 8.8 and 9.2, Oracle Linux 8.8 and 9.2, and Rocky Linux 9.2, while deprecating older versions by December 2023. The update includes a cumulative series of resolved issues, such as improvements in Application Security monitoring, Autonomous Cloud references, Cluster log query stability, and Synthetic Monitoring on-demand results. Additionally, the new release resolves issues related to dashboard data display, tag encoding inconsistencies, metric suggestions errors, and introduces a skip path verification option for handling directory permissions during upgrades. The update cycle includes multiple builds that collectively address a wide array of bug fixes and enhancements, ensuring a more stable and secure Dynatrace Managed environment.

Dynatrace's inaugural partner enablement event, Amplify Sales Kickoff, highlighted its focus on enhancing end-to-end, full-stack observability through its unified intelligence platform, aiming to assist partners in driving customers' digital transformation. The event, themed "Observability Unleashed," declared 2023 as "The Year of the Partner," emphasizing the essential role of partners in extending Dynatrace's innovations, such as the Grail causal data lakehouse and the Dynatrace Platform Subscription (DPS), to more customers. Dynatrace is leaning heavily into SaaS, enhancing its cloud-native applications and infrastructure capabilities, and emphasizing application security. The event also introduced the Value Incentive Partner Program (VIPP) and a new Partner Services Endorsement Program, aiming to empower partners with certifications and skills to deliver Dynatrace's best practices effectively. Additionally, the launch of the new Partner Relationship Management (PRM) portal aims to streamline partners' access to resources, thus improving efficiency and customer value delivery. Dynatrace recognizes its partners as pivotal to customer retention and expansion, and the event underlined their commitment to supporting partners' growth and success through various initiatives and recognitions.

In a landscape marked by macroeconomic uncertainty, businesses increasingly rely on data-driven decision-making to maintain agility, with DevOps teams at the forefront leveraging cloud-based analytics to fuel sustainable growth. Despite their potential, cloud-based analytics present challenges due to the growing data volumes that complicate orchestration, processing, and analysis, creating burdens of cost and capacity that hinder DevOps maturity. The complexity of cloud-native environments, characterized by data silos and multicloud architecture, further complicates data management and analytics, often requiring costly and time-consuming data warehouse strategies. A data lakehouse approach, combining the capabilities of a data warehouse and a data lake, offers a solution by providing cost-effective, scalable, and rapid access to high-cardinality data, maintaining full data fidelity and context for accurate predictive analytics. This approach allows DevOps teams to unify observability data, including logs, metrics, and traces, to enhance their maturity and optimize digital services, while enabling DevSecOps practices by integrating security into the software delivery lifecycle. By utilizing platforms like Dynatrace's Grail data lakehouse, organizations can effectively manage data complexity and derive actionable insights, thereby enhancing their operational efficiencies and security measures in increasingly intricate digital environments.

Retailers are intensively preparing for Black Friday as the holiday season becomes more extended and complex, driven by shifts in consumer behavior that emphasize convenience and omnichannel experiences. The post-pandemic environment has accelerated these shifts, prompting retailers to enhance their last-mile services and invest in technologies like Buy Online Return In Store (BORIS) and Buy Online Pickup In Store (BOPIS). The increased digital touchpoints and the unpredictability of Black Friday demand place enormous pressure on retailers' digital infrastructures, exposing vulnerabilities to cyber threats and system downtimes that can damage consumer loyalty and profits. To address these challenges, retailers are turning to platforms like Dynatrace, which offers advanced observability, application security, and automation powered by AI to ensure robust performance and seamless customer experiences. Dynatrace aids retailers in managing complex digital ecosystems, optimizing supply chains, and maintaining infrastructure resilience, ultimately enabling them to meet changing consumer expectations and demands effectively.

The text discusses the differences and similarities between OpenShift and Kubernetes, two prominent container orchestration platforms used for managing containerized applications. Kubernetes, developed by Google and managed by the Cloud Native Computing Foundation, offers flexibility and is widely accessible across various platforms, while OpenShift, developed by Red Hat, provides a user-friendly interface with integrated development tools and security features but is limited to Red Hat distributions. Both platforms automate the administration of containerized workloads, though Kubernetes is known for its flexibility and complexity, which can pose challenges in observability. In contrast, OpenShift simplifies management with built-in CI/CD pipelines, security policies, and advanced networking solutions, making it suitable for industries with strict compliance requirements. Additionally, OpenShift's commercial model includes support and long-term updates, whereas Kubernetes relies on external tools for integrations. Both platforms can benefit from Dynatrace's observability solutions, which enhance monitoring and automate operations for efficient performance management.

Dynatrace has integrated advanced observability features to automatically monitor OpenAI/GPT model requests, providing critical insights into service behavior, latency, and token consumption. This capability is vital for businesses leveraging generative AI, as it helps identify and rectify slowdowns, ensuring efficient and reliable AI service performance. By using AI observability, companies can seamlessly track the cost, latency, and reliability of services using OpenAI models like GPT-3, GPT-4, and others. The platform's OneAgent automatically collects and visualizes metrics, including token usage and service interactions, without manual configuration, aiding in cost and performance optimization. Additionally, Dynatrace's Davis AI system can detect and analyze anomalies, automatically pinpointing issues to their root causes, thus enhancing operational efficiency and transparency. This observability is crucial as companies integrate AI into their infrastructure, offering peace of mind and aiding compliance with upcoming regulations for AI services.

The OneAgent release version 1.267, rolled out on June 7, 2023, introduces new technology support, enhancements, and numerous resolved issues. Notably, it supports Akka HTTP server versions 10.2, 10.4, and 10.5, and introduces Podman containers support for infrastructure monitoring, requiring Podman to use crun as its runtime. This release also enhances application security with improved attack and vulnerability detection, particularly for servlet-api-5.0, and offers secure zLocal-zRemote connections. Key resolved issues include the correction of host ID formats, improvements in OneAgent .NET stability, and a fix for high CPU usage on hosts with high network traffic. Additionally, the update addresses vulnerabilities, particularly in the Extensions Execution Controller for Python, and resolves various issues across modules such as Java, .NET, and JavaScript, enhancing overall system stability and security.

Kubernetes has emerged as the leading container orchestration platform, offering significant benefits such as automated scaling, self-healing, and a vast ecosystem of extensions, making it essential for managing, automating, and scaling containerized applications across diverse cloud environments. Despite its advantages, Kubernetes presents several challenges, including complexity, networking issues, observability, cluster stability, security concerns, logging difficulties, and storage management. These challenges require effective solutions to enhance observability, security, and resource management, such as the integration of comprehensive platforms like Dynatrace, which offers automated observability, AI-powered analytics, and robust security measures to address these issues. By overcoming these hurdles, organizations can optimize Kubernetes deployment, reduce risk, and accelerate innovation, ultimately enhancing their IT operations and business outcomes.

The text discusses the challenges and solutions related to managing modern application complexity in multicloud environments, emphasizing the limitations of manual processes and the benefits of automation. As organizations increasingly adopt multicloud strategies and microservices to improve efficiency and scalability, IT professionals face difficulties in monitoring, managing, and securing applications at scale without automated workflows. Dynatrace offers a solution with its automated workflows that utilize AI to provide a unified view of the full stack, enabling DevSecOps teams to efficiently manage multicloud environments. The text highlights the importance of automation for handling data proliferation, improving security, and optimizing operational efficiency, as manual processes are prone to errors, time-consuming, and resource-intensive. Through features like graphical workflows, targeted actions, specific event triggers, and customized schedules, Dynatrace's platform aims to streamline workflows and enhance speed, thus reducing engineering toil and improving the consistency of the DevSecOps cycle.

The F5 BIG-IP Local Traffic Manager (LTM) is a widely used application delivery controller that enhances network traffic performance, security, and availability across enterprise applications, web services, and cloud-based services. It offers features like application-layer load balancing, SSL/TLS acceleration, and traffic shaping, while also providing security measures such as DDoS protection and SSL VPN. Monitoring F5 BIG-IP instances is crucial for maintaining the smooth operation of business-critical applications, as it helps identify and resolve issues related to application delivery and security threats. The Dynatrace extension for F5 BIG-IP monitoring is popular due to its integration with AI-powered analytics that assist IT teams in quickly diagnosing root causes of problems. Dynatrace's capabilities include effectively modeling F5 instances, linking data from monitored hosts, and utilizing SNMP trap integration for real-time alerts. While the F5 BIG-IQ framework supports centralized management of application delivery infrastructure, it lacks detailed application performance insights, which Dynatrace provides, making it a recommended tool for deep performance analysis.

ChatOps is a DevOps practice that integrates chat platforms like Telegram and Google Chat with IT operations to enhance real-time communication and automation, thereby improving collaboration, efficiency, and incident management. Initially popularized by GitHub, ChatOps facilitates human-to-human and human-to-machine interactions, enabling teams to execute tasks such as code deployment, monitoring, and incident response directly from chat environments using plain-English commands. ChatBots serve as intermediaries, connecting various services and enabling automated responses, which accelerates issue resolution and streamlines workflows. The integration of Dynatrace with ChatOps tools provides further benefits, such as improved collaboration, faster incident resolution, increased automation, and greater operational efficiency. Setting up this integration involves creating custom notifications and webhooks in platforms like Telegram and Google Chat, allowing teams to receive real-time alerts and take immediate action, thus enhancing the stability and reliability of IT operations.

In the modern digital environment, maintaining high-quality software is essential for organizational success, and Service Level Objectives (SLOs) serve as a vital framework for assessing and enhancing software performance, reliability, and user satisfaction. SLOs provide measurable targets that help organizations avoid downtime, improve software quality, and foster automation within the DevOps lifecycle. As organizations accelerate software delivery, with many deploying updates frequently, the pressure to innovate often results in compromises on code quality, security, and reliability. Examples of SLOs, such as those related to availability, response time, user satisfaction, traffic, and success, are critical across industries, including e-commerce and fitness apps, to ensure seamless user experiences and operational efficiency. Implementing these SLOs can be supported by best practices like synthetic testing and optimal resource utilization, and tools like Dynatrace offer pre-configured templates and automation capabilities to streamline the SLO adoption process, ensuring applications meet speed and reliability goals effectively.