February 2021 Summaries

The shift towards cloud-native technologies in 2020 accelerated the adoption of DevOps and Site Reliability Engineering (SRE) practices to meet the increased demand for online services. DevOps focuses on closing the gap between software development and IT operations through agile processes and automation, aiming to deliver better software faster by aligning service-oriented teams. On the other hand, SRE applies DevOps principles to improve the operational side by enhancing availability, performance, and scalability, using software engineering to design operations functions. While both practices share common philosophies such as "everything as code" and valuing measurability, they operate in different scopes: DevOps emphasizes development and delivery, whereas SRE concentrates on operational processes, including efficient change management and robust emergency responses. Organizations are increasingly integrating both practices to automate tasks, improve software delivery, and build resilience into cloud-native applications, with platforms like Dynatrace offering tools to support these efforts.

The Dynatrace Managed release version 1.212 introduces several enhancements and resolved issues to improve system performance and user experience. Key updates include the ability to install the Dynatrace Managed cluster in a Rack-aware deployment for increased availability and resilience, ensuring data consistency even if one rack fails. The Cluster Management Console now features an automated self-service support system to streamline issue resolution by providing diagnostic data and potential solutions. The release also extends the Cluster REST API to include license consumption data and introduces new cluster token scopes for managing settings resources. Additionally, the update brings support for Ubuntu 20.10 while phasing out older operating systems like Amazon Linux AMI 2017.x and openSUSE versions. Numerous resolved issues across various components bolster the system's reliability, including enhancements to the Autonomous Cloud, synthetic monitoring, and cluster management functionalities.

Dynatrace has enhanced its Application Security Module to provide comprehensive protection for Kubernetes platforms and Node.js workloads, offering automatic vulnerability detection and AI-powered risk assessment. This development allows BizDevSecOps teams to mitigate risks more efficiently by connecting vulnerabilities to specific pods and containers within Kubernetes clusters. The extension of automatic vulnerability detection to Kubernetes ensures that even the platform's underlying complexities are secured, while the addition of Node.js support complements existing Java workload security. Leveraging Snyk’s vulnerability database and the Dynatrace Davis AI-engine, the platform offers real-time insights and accurate risk evaluations, reducing false positives and facilitating faster remediation. New collaboration features enable seamless vulnerability management and remediation across teams, with role-based permissions and management zones enhancing secure access control. These enhancements aim to address the evolving needs of cloud-native application stacks, ensuring continuous and robust security for critical applications and services.

Dynatrace Cloud Automation Module combines intelligent observability with an enterprise-grade control plane to enhance automation in the software development lifecycle, offering capabilities like AI-driven quality checks, automated incident remediation, and seamless integration with DevOps tools. This module is designed to address the challenges faced by organizations in rapidly evolving digital landscapes, where speed, resilience, and scalability are crucial for maintaining market leadership. The module aids in overcoming issues such as fragmented tool coverage and data noise by providing an integrated solution that ensures high-quality code and efficient release cycles. By leveraging AI and automation, Dynatrace enables development, DevOps, and SRE teams to achieve faster software delivery, improved collaboration, and enhanced service levels, ultimately leading to better customer experiences.

Dynatrace's blog series explores the integration of its observability platform with open-source frameworks like StatsD, Telegraf, and Prometheus, focusing on the use of its AI-driven Davis engine for automatic alerting and root cause analysis of metrics. The final part of the series highlights how Dynatrace enhances the analysis of metrics collected by Telegraf, a plugin-based system from Influxdata, by providing intelligent observability and root cause analysis across over 200 technologies. This integration allows users to analyze metrics in real-time by contextualizing data within the Dynatrace platform, revealing relationships and interdependencies in application environments. Users can enable this functionality by installing Telegraf with Dynatrace OneAgent and configuring the output plugin, simplifying the process of gaining actionable insights from their data.