At Perform, its flagship annual user conference, Dynatrace showcased how customers are using Dynatrace AI Observability to scale AI applications safely, reliably, and cost-effectively.
Gartner® predicts that “40% of enterprise apps will be integrated with task-specific agents, up from less than 5% now” – making the shift from experimentation to production a business priority. Organizations need observability solutions that can not only monitor AI, but actively optimize, govern, and secure it at scale.
With the Dynatrace platform as a control plane for AI in production, enterprises gain the visibility, automation, and governance required to adopt agentic AI with confidence. This evolution is helping customers manage complexity and compliance while optimizing performance across emerging technologies.
Customers in Action
Canadian technology giant, TELUS, has been using Dynatrace AI Observability to transform incident response and drive measurable operational ROI. By consolidating multiple monitoring tools into a single observability platform, TELUS has lowered tooling costs and achieved a 30% reduction in onboarding time for new teams. Automation and monitoring as code capabilities reduced the effort to deploy end-to-end observability from 600 minutes to just 20 minutes, delivering substantial time savings for the business.
New Advancements
Despite AI enthusiasm, according to recent findings, the majority (95%) of AI initiatives deliver zero return on investment due to failures before reaching production. Dynatrace has introduced major advancements designed to close this gap, helping enterprises scale AI initiatives with confidence while mitigating security and compliance risks such as data leakage, prompt injection, and policy violations.
Recent innovations include:
- Unified observability across the agentic AI stack. Support for a broad ecosystem of agentic frameworks and services, including Amazon Bedrock AgentCore, Amazon Bedrock Strands, Google Agent Development Kit, OpenAI Agent, Anthropic Model Context Protocol (MCP), LangChain Agents and Azure AI Factory agents. This gives organizations a single, unified view across internal and external models, services, and orchestration layers.
- Model versioning & A/B testing. Built-in comparison across models such as GPT-5, Claude, Vertex AI, Azure AI Foundry using metrics including response time, token consumption, cost, and relevancy – enabling data-driven selection and continuous optimization.
- Intelligent alerting and forecasting. AI-driven cost and performance forecasting helps teams anticipate risk early and maintain predictable, efficient AI operations.
“By combining our Agentic AI initiatives with Dynatrace’s AI Observability capabilities, we’ve successfully optimized our development and operations workflows. This collaboration has enabled us to streamline incident resolution to minutes, from detection to pull requests. Through this integration of AI technologies, we’re driving innovation and delivering measurable business impact while reducing downtime.” states Kulvir Gahunia at TELUS. This partnership has delivered clear, measurable ROI for TELUS by accelerating innovation, reducing operational effort, and enabling us to proactively ensure the reliability and performance of our most important digital services.”
“Across industries, our customers are leading the shift from AI experimentation to AI at enterprise scale,” said Steve Tack, Chief Product Officer at Dynatrace. “Their work demonstrates how deep observability of modern AI workloads – using LLMs, agentic AI workflows, and generative AI applications – enables organizations to move faster and more confidently. By combining visibility with automation and intelligent analytics, our customers are turning AI into measurable business outcomes – faster innovation, improved reliability, higher customer satisfaction, and stronger operational efficiency.”
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