January 2023 Summaries

The Department of Defense has launched the Joint Warfighter Cloud Capability (JWCC), a groundbreaking series of contracts aimed at establishing enterprise cloud services across the department while enhancing cloud performance and security. Awarding $9 billion to Microsoft, Amazon Web Services, Google, and Oracle for a five-year period, JWCC replaces the now-defunct Joint Enterprise Defense Infrastructure (JEDI) initiative, which was scrapped due to its inability to meet evolving demands and security needs. JWCC's multicloud approach aims to mitigate risks inherent in a single-provider model by distributing resources across multiple vendors, thereby reducing the vulnerability of military operations to cyberattacks. This initiative underscores the critical role of cloud technology in military strategy, enabling real-time data updates and informed decision-making. The program capitalizes on partnerships with companies like Dynatrace to provide advanced observability and security, ensuring robust cloud performance and operational awareness.

Dynatrace has introduced cross-environment tracing, which allows enterprises to track distributed traces across different monitoring environments while maintaining a comprehensive end-to-end view. This development is particularly significant as many large companies have adopted microservices-based architectures that span multiple clouds and geographies, driven by the need for increased agility, performance, and compliance with regional data regulations. The new feature simplifies the complexity of monitoring distributed applications, especially those requiring data separation across global locations, by providing seamless integration and visibility across multiple Dynatrace environments. An example provided illustrates the ease of identifying performance issues in a hybrid cloud setup, with the front end on a hyperscaler and the back end managed on-premises, showcasing the capability to quickly pinpoint problems through direct links between environments. The setup for this feature is straightforward, requiring minimal configuration, and is available in recent versions of Dynatrace SaaS, Dynatrace Managed, and OneAgent.

The Dynatrace Managed release 1.258, rolled out starting January 30, 2023, introduced several enhancements and fixes specific to its platform. Key updates include improvements to the Mission Control connection status, automation of node replication procedures for Premium High Availability deployments, and new alerting mechanisms for cluster nodes unable to receive OneAgent traffic. The release also upgraded technical components such as Cassandra and the Java Runtime Environment (JRE) to enhance performance and security. A crucial reminder was issued regarding the end-of-life support for several operating systems in future releases. Numerous resolved issues addressed application security, autonomous cloud operations, and cluster management, with particular emphasis on fixing errors related to API interactions and metric event handling. The release also highlighted updates and resolutions across various builds, including fixes for RUM settings, Kubernetes alerts, and synthetic monitoring challenges.

Site Reliability Engineering (SRE) is a discipline that applies software engineering principles to operations in order to create reliable and scalable software systems, with a focus on improving system reliability in areas such as availability, performance, and incident response. Coined by Google in 2003, SRE aims to automate and optimize operations, bridging the gap between development and operations teams to ensure seamless and reliable software deployment. The key benefits of implementing SRE practices include increased system reliability, improved scalability and user experience, cost savings through automation, and enhanced collaboration across teams. SREs are responsible for tasks such as monitoring infrastructure, responding to incidents, automating processes, and planning for capacity, often acting as first-line defenders during system alerts. The approach requires cultural changes within organizations, emphasizing a collaborative environment that integrates DevOps practices and fosters continuous learning. SRE and DevOps are complementary, with DevOps focusing on speeding up changes and SRE ensuring these changes are reliable. Ultimately, SRE is an evolving field that continually adapts to the demands of digital infrastructure, requiring openness and a willingness to learn from both successes and failures.

The OneAgent release version 1.257 introduces a range of new features, enhancements, and resolved issues across various platforms and technologies. Key updates include support for Apache HttpClient 5.2, Node.js 19, and new functionalities for IBM App Connect Enterprise and z/OS. Infrastructure monitoring has been improved with alerts for non-installed OS services and separate reporting for OS service events, while tracing support has been expanded for AWS Lambda and Google Cloud Run environments. Mobile Digital Experience updates include support for Android's Configuration cache Gradle feature and enhanced iOS 16 compatibility. Several operating systems will lose support in future updates, including specific versions of Amazon Linux, Debian, and Windows. The release addresses 16 resolved issues, including vulnerabilities and performance improvements across components like Go, NGINX, and Java. Additionally, JavaScript, iOS, and Android platforms have seen specific bug fixes, enhancing action information retention, API functionality, and crash prevention mechanisms.

Following an SSO service disruption in early January that affected many Dynatrace customers, the company has outlined several measures to prevent future incidents. These include improvements in architectural design, deployment automation, traffic management, and service dependencies, all aimed at enhancing security, access, and system resilience. While some enhancements, such as additional compute resources and improved deployment automation, have been completed, others like optimizing database queries and increasing load testing are in progress with a completion target by the end of Q1. Dynatrace is also working on accelerating status updates and improving customer support accessibility through various communication channels. The company emphasizes transparency and a commitment to continuous learning from mistakes to achieve seamless software functionality.

DevSecOps represents the integration of security into every phase of the software development and deployment lifecycle, emphasizing a cultural shift where development, security, and operations work collaboratively. Unlike traditional waterfall approaches that handle security post-development, DevSecOps embeds security testing and monitoring into the continuous integration and delivery pipeline, facilitating faster detection and remediation of vulnerabilities. This methodology promotes automated security testing, continuous monitoring, and real-time feedback to enhance software quality and compliance with security regulations while ensuring faster time-to-market and reducing costs associated with security breaches. Despite its advantages, implementing DevSecOps poses challenges such as the need for cultural change, retraining teams on security best practices, and integrating modern security tools that can handle the complexities of contemporary software environments, like open-source components and cloud-native applications. By fostering a culture of collaboration and utilizing platforms like Dynatrace for comprehensive monitoring and automation, organizations can effectively align security with development goals, delivering secure, reliable software efficiently.

Microservices and microservices architecture have become the standard in modern software development due to their ability to meet the demands for fast, flexible, and scalable digital services. These small, modular units of software enable developers to build applications in smaller, manageable pieces rather than maintaining a cumbersome monolithic codebase. A 2020 survey highlighted that 61% of organizations have adopted microservices with 92% reporting success. This architecture allows developers to independently update, scale, and secure each service, reducing the risk of single points of failure. Microservices architecture integrates well with DevOps practices, facilitating continuous integration and delivery, and is supported by container-based orchestration platforms like Kubernetes and Docker, as well as cloud-native services such as AWS Lambda and Azure Functions. While the architecture offers benefits like flexibility, resource efficiency, and reliability, challenges such as complexity, observability, and cultural shifts need to be addressed. Effective management involves automation and observability solutions like those provided by Dynatrace, which uses AI for enhanced microservices monitoring and management.

DevOps observability is crucial for organizations aiming to enhance software delivery speed, quality, reliability, and security amid the pressures of digital transformation. This approach not only aids DevOps and DevSecOps teams in automating processes, but also helps in overcoming challenges posed by siloed data and manual tasks. As organizations aim to release software more frequently, DevOps practices, often complemented by Site Reliability Engineering (SRE), are essential for achieving digital transformation and optimizing the software development lifecycle (SDLC). Continuous integration and delivery (CI/CD) practices streamline development and deployment, while service-level objectives (SLOs) ensure service quality. Integrating security into DevOps through DevSecOps helps address security concerns early in the process, offering protection against vulnerabilities like Log4Shell. Observability tools play a vital role in implementing these methodologies, facilitating proactive testing through chaos engineering and automating lifecycle orchestration to support application security and efficiency in cloud environments.

Dynatrace provides real-time business observability to support data-driven decision-making by leveraging business events and its data lakehouse, Grail. Business events, prioritized over metric events for lossless precision, enable organizations to capture and analyze critical business data from various sources, such as OneAgent, real-user monitoring sessions, log files, or external tools. These events facilitate advanced analytics and automation to enhance business outcomes without the constraints of traditional business intelligence tools, which are often backward-looking and inflexible. Grail and the Dynatrace Query Language (DQL) offer features such as cost-effective long-term storage, unaggregated granularity, instant indexless storage, and Smartscape context to support comprehensive analytics and collaboration. Through use cases such as real-time business intelligence and enhancing customer experience post-digital conversion, Dynatrace demonstrates how business events can provide actionable insights that drive performance improvements. The platform's capabilities include configuring business events with OneAgent, processing rules to transform data, and retaining data with predefined periods, all while automatically enriching events with topology and application information for deeper analysis and troubleshooting.

Dynatrace enhances OpenTelemetry's capabilities by simplifying the acquisition and analysis of OpenTelemetry metrics through its support for the OpenTelemetry Protocol (OTLP), enabling organizations to discover contextual relationships between various Kubernetes elements like pods, services, nodes, and clusters. This integration addresses the challenges organizations face with OpenTelemetry's complexity and lack of context by delivering context-aware insights and reducing the need for manual efforts like applying labels or building crosslinks between dashboards. The Dynatrace approach facilitates exploratory analysis and root-cause detection using its Davis AI-powered insights, which automatically correlate OpenTelemetry metrics with relevant context such as workload information and deployment events. By using an example of order fulfillment in a Kubernetes workload, Dynatrace demonstrates how its capabilities can quickly identify performance issues linked to specific deployment changes, thus underscoring the efficiency and effectiveness of its solution in providing comprehensive observability in cloud-native environments. As Dynatrace continues to invest in cloud-native observability, it plans to expand its support for OpenTelemetry logs alongside metrics and traces in 2023, aiming to offer scalable and hassle-free signal collection without the need for extensive infrastructure maintenance.

Kubernetes has rapidly become a foundational technology for cloud-native computing, serving as the "operating system" of the cloud due to its orchestration capabilities for microservice applications. A survey report analyzing production data from thousands of organizations using the Dynatrace platform reveals the widespread adoption of Kubernetes, driven by the need for advanced platform features such as security, observability, and CI/CD technologies. The report highlights a significant shift towards cloud-hosted Kubernetes clusters, which grew at an annual rate of 127% in 2022, outpacing on-premises deployments, with most being managed by major cloud providers like AWS, Azure, and Google Cloud. It also notes the rising importance of auxiliary workloads, reflecting the diverse use cases organizations find for Kubernetes, including security and messaging systems, and emphasizes the role of open-source software in enriching the Kubernetes ecosystem. Java, Go, and Node.js are identified as the top programming languages for Kubernetes workloads, highlighting the platform's support for polyglot programming. The study, based on data from January 2021 to September 2022, underlines the growing complexity and capabilities of Kubernetes as it becomes integral to modern enterprise infrastructure.

In a complex digital infrastructure environment, Park 'N Fly faced challenges with fragmented cloud monitoring tools and siloed teams, leading to inefficiencies and a blame culture when issues arose. By adopting Dynatrace as a unified cloud monitoring platform, the company was able to integrate front-end and back-end performance data, providing a single source of truth that enhanced their ability to predict and address potential problems before they impacted customers. This integration not only improved their customer experience by ensuring seamless transactions across mobile apps, websites, and kiosks but also strengthened collaboration with third-party partners through shared performance insights. As a result, Park 'N Fly shifted from reactive problem-solving to a more proactive approach, fostering a culture of innovation and continuous improvement.

As organizations increasingly adopt cloud-native technologies, infrastructure monitoring has become crucial to align business objectives with IT performance. Infrastructure monitoring involves collecting and analyzing data from IT systems to enhance availability, performance, and resource efficiency, ensuring mission-critical applications remain operational. Modern infrastructure monitoring includes agent-based and agentless methods, utilizing data from various sources like operating systems, databases, and network devices to detect, alert, and remediate issues proactively. With the rise of multicloud environments, challenges such as limited visibility and managing multiple monitoring solutions have emerged, making comprehensive monitoring and root-cause analysis essential for maintaining optimal performance and minimizing downtime. Key practices include leveraging automation, prioritizing alerts, creating role-specific dashboards, and regularly reviewing metrics. Advanced monitoring solutions offer AI-driven insights and end-to-end observability, aiding organizations in achieving their business goals efficiently.

Organizations striving for improved customer service face challenges in managing the vast amounts of business analytics and observability data generated by their systems, leading to issues like data silos, fragile integrations, and high storage costs. Traditional methods of monitoring struggle to extract real-time insights due to the overwhelming volume and variety of data, resulting in constraints on deriving actionable intelligence. To address these challenges, a modern approach using a data lakehouse, such as Dynatrace's Grail, is proposed. This approach integrates business analytics and observability data, providing a unified platform that eliminates the need for complex integrations and allows for real-time, contextual analysis. By centralizing data and leveraging real-time insights, organizations can enhance collaboration between business and IT teams, optimize processes like customer service, and make more informed, agile business decisions. The data lakehouse model promises to unlock the potential of disparate data sources, providing immediate, actionable insights while reducing costs and increasing efficiency.

On January 3, 2023, Dynatrace experienced a disruption in its Single Sign On (SSO) service, preventing customer access to its SaaS environments, although monitoring data collection remained largely unaffected except for some customers with significant SSO dependency. The disruption was caused by an inefficient use of the SSO API, resulting in excessive load and compounded by an unintended dependency issue between two SSO services, which hindered the auto-remediation mechanisms. The resolution required a complete redeployment of the SSO services, during which communication delays on the Dynatrace Status portal were noted. In response, Dynatrace is implementing improvements in architectural design, deployment automation, and load testing, alongside enhancing communication processes to prevent future occurrences. The company acknowledges the reliance of its users on their platform and is committed to delivering high-quality observability solutions.

AIOps, or Artificial Intelligence for IT Operations, is a transformative approach that leverages AI to enhance IT operations by automating routine tasks such as event correlation, anomaly detection, and root-cause analysis. As organizations face increasing complexity in multicloud environments, AIOps provides the tools necessary to maintain efficiency, reduce costs, and foster innovation by allowing IT teams to focus on higher-value work rather than manual processes. With the ability to preemptively identify and remediate performance and security issues, AIOps offers organizations improved visibility and reliability in their IT environments. This approach is gaining traction, with the AIOps market valued at $17 billion annually and its adoption expected to rise significantly. The integration of AIOps with digital transformation initiatives can lead to enhanced operational efficiencies, innovation, and customer satisfaction, as evidenced by companies like Park ‘N Fly, which have successfully applied AIOps to improve customer experiences and streamline processes.