March 2021 Summaries

Dynatrace has enhanced its integration with AWS services by partnering with Amazon CloudWatch Metric Streams, enabling faster and more efficient data ingestion for root-cause analysis using its Davis AI engine. Previously, CloudWatch metrics were periodically pulled into Dynatrace on a user-defined schedule, but the new integration with Metric Streams allows for immediate data push via Amazon Kinesis Data Firehose, facilitating near real-time analysis. This setup simplifies configuration requirements, needing only the execution of a CloudFormation script to create a Dynatrace configuration stack. Dynatrace aims to optimize the performance data distribution with this advancement and encourages user feedback to further enhance AWS cloud monitoring capabilities.

In an era of increasing data sharing, businesses are expected to safeguard sensitive information, but traditional application security measures often fall short in adapting to complex software environments and rapid release cycles. This gap has led to the evolution from DevOps to DevSecOps, which integrates security into the software development and operations workflow to enhance the entire software delivery life cycle. DevSecOps emphasizes a "shift left" approach, addressing security earlier in development, and a "shift right" focus on production environments to mitigate vulnerabilities. It promotes security by design, shared responsibility, and breaking down departmental silos through shared security intelligence and automation. Organizations transitioning to DevSecOps benefit from a cultural shift towards integrating security practices into every role, supported by tools like the Dynatrace Software Intelligence Platform, which offers real-time, automated vulnerability detection and remediation to improve speed and reliability in software delivery.

Dynatrace has introduced a new extension for monitoring SNMP protocols, providing enhanced observability for network infrastructure, particularly beneficial for on-premises environments where managing thousands of devices manually is challenging. SNMP, while not the newest protocol, is still widely used to gather device metrics, and the Dynatrace extension leverages this by integrating with their AI causation engine, Davis®, to automate monitoring. The extension framework allows for seamless integration and automation via an API-first approach, facilitating the ingestion of various custom data sources without web UI operations. This new setup includes dedicated dashboards for SNMP extensions, allowing users to monitor performance, configure alerts, and manage events efficiently. It also offers solutions for modeling topological relations and dependencies, crucial for accurate root cause analysis in complex infrastructures. Beyond SNMP extensions, Dynatrace aims to evolve its network-device monitoring solution to include additional functionalities like log monitoring and synthetic network monitoring, with plans to expand observability and improve user experience based on feedback from the initial release.

Mitchells & Butlers (M&B), one of the UK's largest restaurant and bar groups, is navigating digital transformation by adopting a BizDevOps approach to enhance customer experiences through digital channels. Spearheaded by Digital Readiness Manager Mark Forrester, M&B seeks to replicate the personal touch of in-person service in a digital environment, emphasizing the importance of seamless and satisfying customer journeys. By integrating DevOps metrics and collaborating across departments such as IT, marketing, and security, M&B leverages Dynatrace's platform to monitor and optimize digital experiences, ensuring each customer interaction is impactful and revenue-generating. The use of real-time data facilitates a two-way dialogue between departments, enabling informed decision-making and fostering collaboration beyond internal teams by involving suppliers. This strategy allows M&B to maintain a comprehensive view of the customer journey and continuously improve service delivery, ultimately achieving a more connected and efficient digital operation.

Dynatrace Extensions 2.0 offers an enhanced framework enabling users to extend the monitoring capabilities of the Dynatrace Software Intelligence Platform to incorporate custom data sources not initially covered by its OneAgent. This update emphasizes automated, zero-maintenance deployment, democratizing extensibility, and providing a more user-friendly experience through declarative extensions, allowing even those with limited technical knowledge to contribute to monitoring. The platform supports a wide range of entities and integrates seamlessly with various technologies, offering automated AI-driven alerting and root cause analysis at scale. With a centralized API and the Dynatrace Hub, users gain a unified interface to manage extensions, while the open API fosters greater customization and adaptability. As Dynatrace continues to evolve, it aims to phase out legacy extensions, with new capabilities being introduced to enhance the extensibility and monitoring functionalities, promising a more comprehensive and proactive approach to IT system management.

In today's dynamic IT environments, application security has become more complex due to the increasing reliance on cloud-native applications composed largely of open-source components. Traditional application security practices, which focused on post-development testing by security teams, are struggling to keep up with the accelerated software development life cycle (SDLC) and the intricate nature of modern applications. These conventional methods often result in numerous vulnerability alerts, many of which may not pose actual risks, leading to inefficiencies and potential oversights. To address these challenges, there is a shift towards integrating application security into the development process, with emphasis on using AI and automation to provide real-time detection and reduce false positives. Dynatrace's new Application Security Module aims to meet these needs by extending its Software Intelligence Platform, offering enhanced capabilities for cloud application security, particularly for Kubernetes and Node.js, thus enabling DevSecOps teams to maintain speed and security in software releases.

Dynatrace hosted an engaging event combining craft beer tasting with discussions on DevOps, featuring a panel of experts and customers who shared insights on the adoption and benefits of DevOps in their organizations. Notable speakers from companies like BT Consumer, PA Media Group, Kingfisher, and Willmott Dixon highlighted how DevOps has transformed their operations by fostering collaboration between development and operations, reducing incidents through tools like Dynatrace, and increasing agility and speed in responding to market needs. However, challenges such as standardizing across diverse technology stacks and re-architecting monolithic applications were also discussed. The event emphasized the importance of a cultural shift and a unified approach in adopting DevOps, with solutions like Dynatrace offering a single source of truth to drive success and eliminate silos. Looking forward, the panelists expressed interest in evolving towards NoOps and integrating security into DevOps processes, reflecting the ongoing evolution and potential of DevOps practices.

AIOps, or Artificial Intelligence Operations, is emerging as a transformative force in IT operations by leveraging AI algorithms and data analytics to automate tasks and suggest solutions for common IT issues, thereby easing the workload on IT teams. Despite the promise of AIOps, its adoption faces challenges due to the complexity of modern cloud-native environments and the limitations of traditional machine learning approaches, which struggle with scaling and require significant human intervention. Deterministic AI, with its systematic fault-tree analysis, offers an alternative by providing immediate and precise root-cause analysis in real time, helping IT teams respond swiftly to anomalies and streamline operations. By enhancing alert management, automating processes, and reducing IT spend, AIOps solutions can drive efficiency and support digital transformation, yet their implementation is hindered by a lack of internal skills, a common data model, and effective frameworks for automation. As organizations seek to harness AIOps, platforms like Dynatrace are adopting deterministic AI to deliver comprehensive observability and automated insights, thereby enabling IT teams to focus on strategic priorities and innovation.

The Dynatrace Managed release version 1.214, published on March 12, 2021, brings several specific changes and enhancements. Key updates include the introduction of Open Identity Connect (SSO) using an Internet proxy for reaching Identity Provider authentication endpoints, a request throttling mechanism for the Dynatrace API, and the addition of rack name selection in the node installation wizard to facilitate cluster scaling. The release also enhances DNS load-balancing performance by default disabling web UI traffic for nodes beyond a certain number, with configuration options available through the Cluster REST API. Security improvements include the removal of EXEC:ALL entry from dtrun sudoers setup and updates to the JRE for Cassandra and Elasticsearch to version 8u282. The release supports various Linux distributions and resolves numerous issues across components, improving overall system stability, performance, and user experience. Notable fixes address inconsistencies in successful request percentage calculations, issues with the "Problems" page display, API token permissions, and various UI-related problems. Additionally, the update enhances the representation of metrics and addresses specific errors related to data queries and charting.

In the fourth installment of a blog series on managing Dynatrace Managed at scale, the author explores optimizing anomaly detection settings using Dynatrace's raw problem and event data. The author highlights the challenges of managing problem noise across thousands of environments and introduces strategies to reduce the number of support tickets by visualizing historical problem data with a "Swimlane Visualization" and conducting statistical analyses. The author defines an "unhealthy" environment by the presence of at least one open problem and discusses the benefits of consolidating overlapping problems into singular "unhealthy situations" to streamline ITSM processes. By adjusting notification times and tweaking anomaly detection parameters, the author successfully reduces alert noise and unnecessary notifications, particularly for short-duration problems. The process involves iteratively analyzing data and refining settings, which ultimately leads to a 50% reduction in detected problems without loss of visibility. The blog concludes with a teaser for the next part, which will address Dynatrace configuration as code, emphasizing its relevance for both large-scale and smaller setups.

Apache Spark is a cluster computing framework designed to handle large volumes of data efficiently by dividing queries into tasks distributed across different nodes in a cluster. A key strategy for optimizing query performance is reducing data transfer from storage to executors through techniques like filter pushdown, which executes certain filters at the data source before loading data into executors. This approach is particularly beneficial when executors are on different physical machines than the data, and Spark often applies it automatically, though users may need to implement it for custom data sources. The Spark SQL module, accessed via a SparkSession, facilitates such optimizations by leveraging schema information to enhance performance. The effectiveness of filter pushdown varies; for instance, operations requiring data casting may not be pushed down unless the schema is explicitly defined to avoid casting, thus allowing filters to be pushed down. Additionally, when developing a custom data source, implementing support for filter pushdown is crucial, as it can significantly improve query performance by minimizing unnecessary data loading, although not all filter operations are subject to this optimization.

Dynatrace has made enhancements to its OneAgent software, allowing users to customize the location where log files are stored, starting with version 1.213. Previously, logs were moved to the /var/log/dynatrace/oneagent directory, but users can now define their preferred path using the LOG_PATH installation parameter, ensuring flexibility for different system configurations. This change is part of Dynatrace's ongoing effort to cater to a diverse customer base and accommodate varied implementation standards. The company emphasizes its commitment to customer feedback, highlighting its agile development approach and dedication to evolving the product based on user input. For users preferring the original log location, options exist for both manual and automatic migration, with assistance available from Dynatrace support teams. Dynatrace encourages users to participate in continuous feedback through various channels to further refine its offerings. A 15-day free trial of Dynatrace is also available, allowing potential users to explore its features without commitment.

Dynatrace enhances observability for HashiCorp's Consul service mesh by providing out-of-the-box insights, leveraging features like the Davis AI causation engine and automated error detection. As applications increasingly transition from monolithic to microservice-based architectures, Consul offers a robust solution for managing service connectivity and security across diverse environments, including legacy systems and Kubernetes. Dynatrace simplifies the process of importing telemetry data from Consul by supporting various custom metrics and enabling easy integration with its platform. Users can configure Consul to send StatsD metrics to Dynatrace, allowing for visualization and alerting through dashboards. This setup benefits from auto-baselining for adaptive alert thresholds and can be further enhanced with prebuilt configurations available via the Dynatrace Hub. Monitoring external Consul clients and Kubernetes-based deployments is facilitated by deploying Dynatrace's OneAgent, and users are encouraged to provide feedback through the Dynatrace Community.

Dynatrace is transitioning its forums to a new Community platform to enhance user support and interaction, aiming to deliver an outstanding user experience beyond its product offerings. This revamped platform is designed to facilitate easier discussions, knowledge exchange, and personalized user experiences, supporting 24/7 self-service resources. It introduces features like personalized notifications, user ranks, and branded badges to recognize community contributions, while emphasizing quality content over quantity. Users can also contribute product ideas, engage in community challenges, and benefit from improved search capabilities and forum structure. Dynatrace encourages users to explore the new platform and participate actively, assuring ongoing improvements and addressing any post-launch issues swiftly.

The OneAgent release notes for version 1.211, published on March 8, 2021, provide detailed information on the changes, updates, and resolved issues associated with this release. Key updates include the end of Dynatrace Real User Monitoring (RUM) support for Microsoft Edge Legacy due to Microsoft's termination of support and new tracing support added for IBM Integration Bus nodes. Additionally, the notes outline future changes in technology and operating system support, with specific OneAgent versions being the last to support various OpenTelemetry versions for Go and Node.js, and the discontinuation of support for certain operating systems by specified dates. The release also details a range of resolved issues across different components like mainframe, Java, .NET, Go, IBM Integration Bus, AI causation engine, Node.js, mobile, and JavaScript, improving performance, fixing bugs, and enhancing monitoring capabilities.

In complex IT environments where the volume of data is too large for manual monitoring, Dynatrace Davis® AI offers a fully automated solution for problem analysis, particularly in dynamic, web-scale cloud environments. This AI system automatically analyzes and alerts on anomalies within IT environments, such as outages in hosts, processes, or services, and extends its capabilities to custom data streams using tools like StatsD, Telegraf, and Prometheus. It simplifies observability by integrating custom metrics into its Smartscape topology model and utilizing an auto-adaptive baseline engine, reducing the need for manual alert maintenance. Users can configure alerts for outages, missing measurements, and unhealthy metric states, ensuring continuous monitoring of third-party data sources. Additionally, the platform supports advanced metric queries for more complex monitoring needs and offers customizable alert messages using metric dimension placeholders. This functionality enhances Dynatrace's ability to detect availability issues across a range of third-party data sources, making the platform more robust and versatile for monitoring and alerting on various IT infrastructure components.