Dynatrace Cloud Automation Module uniquely combines automatic and intelligent observability with an enterprise-grade control plane to automate delivery and operations. The module helps organizations automate the entire software development lifecycle and orchestration process for faster innovation and less risk. It includes AI-powered quality checks against an organization’s service level objectives (SLOs) and automatic incident remediation. Extended by open-source components, it provides an enterprise-grade and scalable solution, increasing our openness and interoperability for the broader DevOps ecosystem.
The past 12 months have caused tectonic shifts in how businesses operate. Digital transformation plans, which were once stretched over years, suddenly had to be condensed to months or even weeks to ensure survival. Being proactive, and quickly reacting to changing markets and customer needs, became paramount for success. Think curbside delivery for groceries, video conferencing for work and school, and telemedicine for doctor visits.
Software companies who have already been following and adopting DevOps and site reliability engineering (SRE) practices alongside their shared ancestry in agile concepts came out on top – especially if they adopted those practices across the whole organization and customer value stream. Today, the speed of software development has become a key business differentiator, but collaboration, continuous improvement, and automation are even more critical to providing unprecedented customer value.
Critical success factors – velocity, resilience, and scalability
To sustain market leadership in this new normal, organizations must pay attention to key success factors, including:
- Velocity: Fast time to market and short release cycles, without an impact on quality.
- Resilience: Critical production business systems must not fail.
- Scale: Distributed teams managing a myriad of applications built on heterogeneous technology stacks across the globe need autonomy and closer collaboration.
These success factors bring challenges across the software development life cycle such as:
- Fragmented tool coverage, which increases complexity for your development, DevOps, and SRE teams as several tools are required to stitch together an end-to-end picture, which lacks a single point of truth.
- Stretched tools used outside of their key use-cases and beyond their core capabilities result in unreliable data leading to wrong decisions or a misplaced sense of safety.
- High maintenance of integration and configuration by stitching together proprietary and/or DIY solutions potentially sacrificing interoperability.
- Lots of data intended to help and aid, but instead results in too much noise and unnecessary alerts due to the lack of intelligent root-cause analysis and transparency.
- More-is-better attitude about measuring everything instead of a focus on measuring what matters; the services with the highest impact on customer experience.
To overcome these obstacles, it is crucial to implement a customer-focused, product-centric value stream. This requires observability across the whole software development lifecycle embedded with automation that allows safe and risk-free delivery. To cut through the noise of observability on such a scale, AI is a prerequisite. Broad-scale observability focused on using AI safely drives shorter release cycles, faster delivery, efficiency at scale, tighter collaboration, and higher service levels, resulting in seamless customer experiences.
Dynatrace launches Cloud Automation module for development, DevOps & SRE teams
Over the past few years, Dynatrace has been a keen voice in the field of DevOps and provided enterprise knowledge and expertise in the shape of Keptn, the open-source, cloud-native, lifecycle orchestration control plane developed as a CNCF sandbox project. Based on our findings gathered from the community, customers, partners, and our own R&D experience, we extended our Dynatrace Software Intelligence Platform to include capabilities supporting development, DevOps, and SRE teams. We are happy to announce Dynatrace® Cloud Automation, providing full lifecycle, AI-powered observability, and automation in a one-stop-shop.
All-in-one observability and enterprise-grade control plane
Dynatrace Cloud Automation leverages the AI and automation capabilities of the Dynatrace Software Intelligence Platform to enhance development, DevOps, and SRE teams’ processes with:
- Automated SLO validation and quality gates, to ensure high-quality code moves smoothly through the delivery pipeline and does not violate error budgets in production.
- Automated, closed-loop remediation of releases that fail in production, combining AI-powered root-cause analysis to pinpoint issues with the code, and orchestration by Keptn, to automatically execute remediation runbooks without manual intervention.
- Automated release inventory and version comparison, which allows teams to easily evaluate the performance of individual release versions, and as needed, roll back to a previous version.
In recent months, we have worked closely with customers and partners to gather their valuable feedback and insight.
Inetum-Realdolmen, one of our partners, is servicing a government agency, which has been able to quickly see the benefits provided by automation:
“Dynatrace Cloud Automation Quality Gates powered by Keptn helped us improve speed of delivery by 75% and reduce manual work to evaluate results by 80%.” – Wim Verhaeghe, KBI-Connect DevOps team lead at Inetum-Realdolmen
Automated release inventory and version comparison
The counterpart to IT support’s “Have you tried turning it off and on again?” is probably a developer’s “What version are you running?” when looking at a software issue ticket. Without this crucial information, it is almost impossible to provide timely support, remedy the issue, and make sure proper precautions are taken for future rollouts.
Dynatrace Cloud Automation allows easy analysis of the status and impact a release has on your business or on test results in any environment. This capability provides version information along with an additional insight into traffic and problems per version. This allows you to see the impact of any release and allows you to compare versions with AI-powered root-cause analysis in case of any release-related problems. Dynatrace highlights all your deployed instances and release events across all your environments and components, which can easily be extended with further context by integrating your ITSM platforms.
The move to Kubernetes enables even more rapid progressive delivery models such as canary deployments or feature flagging. Dynatrace’s version awareness allows you to stay in control despite speeding up application delivery.
For example, side-by-side with the deployed versions, Dynatrace also shows related release information. You can configure issue tracker queries with metadata of deployed versions to show known bugs or resolved issues related to your deployed software.
Automated SLO validation and quality gates
Dynatrace Cloud Automation provides guidance and templates for defining Service Level Objectives (SLOs) for production monitoring. This enables you to easily make use of the more than 2,000 out of the box metrics provided by Dynatrace as well as bringing in your custom metrics and data ingest. These metrics are then evaluated against business-level objectives (BLOs) and SLOs to ensure end-user Service Level Agreements (SLAs) are always in compliance.
Dynatrace takes this one step further by driving SLO evaluation earlier in the development lifecycle by bringing quality gates powered by Keptn into the testing process. This ensures only high-quality code automatically progresses through the delivery pipeline.
Automated, closed-loop remediation
Dynatrace Cloud Automation adds an enterprise-grade control plane for completely automated application lifecycle orchestration, with open integrations into your favorite DevOps tools for delivery, infrastructure, and operations automation such as Jenkins, Azure DevOps, Argo, Spinnaker, ServiceNow, Ansible, xMatters, Jira, Slack, and many others. Combined with AI-powered root-cause analysis, this allows for automatic remediation runbook execution, with no manual intervention required. By validating the effect of an executed action, Dynatrace Cloud Automation closes the loop and can make decisions whether the remediation workflow needs to continue, or if it already resolved the incident.
Get started with Dynatrace Cloud Automation and define your first SLO using our templates, enrich your dashboards with SLO tiles, or create dedicated SRE dashboards.
Stay tuned for another blog post demonstrating how Dynatrace Cloud Automation addresses velocity, resilience, and scalability from a practitioner’s point of view. Additionally, more product news is coming covering release advice and automation provided by Dynatrace Cloud Automation for release risk management, automated release decision making based on SLOs, orchestration, and auto-remediation.
To get insight into how to tackle and achieve autonomous cloud strategic visions, the Autonomous Cloud Enablement (ACE) practice can help you identify where to get started, provide hands-on expertise along the journey, and deliver rapid, meaningful automation services engagements to establish unbreakable delivery pipelines and NoOps cloud operations.