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Dynatrace Releases AI Observability

Dynatrace released Dynatrace® AI Observability, extending its analytics and automation platform to provide holistic observability and security for large language models (LLMs) and generative AI-powered applications.

This enhancement to the Dynatrace® platform enables organizations worldwide to embrace generative AI confidently and cost-effectively as part of their focus on increasing innovation, productivity, and revenue.

Dynatrace® AI Observability is a comprehensive solution. It covers the end-to-end AI stack, including infrastructure, such as Nvidia® GPUs, foundational models, such as GPT4, semantic caches and vector databases, such as Weaviate, and orchestration frameworks, such as LangChain. It also supports the major platforms for building, training, and delivering AI models, including Microsoft® Azure OpenAI Service, Amazon® SageMaker, and Google® AI Platform.

Dynatrace AI Observability leverages the platform’s Davis® AI and other core technologies to deliver a precise and complete view of AI-powered applications. As a result, organizations can provide great user experiences while identifying performance bottlenecks and root causes automatically. Dynatrace AI Observability with Davis AI also helps them comply with privacy and security regulations and governance standards by tracing the origins of the output created by their apps with precision. Additionally, it helps them forecast and control costs by monitoring their consumption of tokens, which are the basic units that generative AI models use to process queries.

“Generative AI is the new frontier of digital transformation,” said Bernd Greifeneder, CTO at Dynatrace. “This technology enables organizations to create innovative solutions that boost productivity, profitability, and competitiveness. While transformational, it also poses new challenges for security, transparency, reliability, experience, and cost management. Organizations need AI observability that covers every aspect of their generative AI solutions to overcome these challenges. Dynatrace is extending its observability and AI leadership to meet this need, helping customers to embrace AI confidently and securely with unparalleled insights into their generative AI-driven applications.”

Dynatrace AI Observability is available now for all Dynatrace customers.

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Dynatrace Releases AI Observability

Dynatrace released Dynatrace® AI Observability, extending its analytics and automation platform to provide holistic observability and security for large language models (LLMs) and generative AI-powered applications.

This enhancement to the Dynatrace® platform enables organizations worldwide to embrace generative AI confidently and cost-effectively as part of their focus on increasing innovation, productivity, and revenue.

Dynatrace® AI Observability is a comprehensive solution. It covers the end-to-end AI stack, including infrastructure, such as Nvidia® GPUs, foundational models, such as GPT4, semantic caches and vector databases, such as Weaviate, and orchestration frameworks, such as LangChain. It also supports the major platforms for building, training, and delivering AI models, including Microsoft® Azure OpenAI Service, Amazon® SageMaker, and Google® AI Platform.

Dynatrace AI Observability leverages the platform’s Davis® AI and other core technologies to deliver a precise and complete view of AI-powered applications. As a result, organizations can provide great user experiences while identifying performance bottlenecks and root causes automatically. Dynatrace AI Observability with Davis AI also helps them comply with privacy and security regulations and governance standards by tracing the origins of the output created by their apps with precision. Additionally, it helps them forecast and control costs by monitoring their consumption of tokens, which are the basic units that generative AI models use to process queries.

“Generative AI is the new frontier of digital transformation,” said Bernd Greifeneder, CTO at Dynatrace. “This technology enables organizations to create innovative solutions that boost productivity, profitability, and competitiveness. While transformational, it also poses new challenges for security, transparency, reliability, experience, and cost management. Organizations need AI observability that covers every aspect of their generative AI solutions to overcome these challenges. Dynatrace is extending its observability and AI leadership to meet this need, helping customers to embrace AI confidently and securely with unparalleled insights into their generative AI-driven applications.”

Dynatrace AI Observability is available now for all Dynatrace customers.

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In APMdigest's 2026 Observability Predictions Series, industry experts offer predictions on how Observability and related technologies will evolve and impact business in 2025. Part 5 covers APM and infrastructure monitoring ...

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In APMdigest's 2026 Observability Predictions Series, industry experts offer predictions on how Observability and related technologies will evolve and impact business in 2025. Part 4 covers user experience, digital performance, website performance and ITSM ...

In APMdigest's 2026 Observability Predictions Series, industry experts offer predictions on how Observability and related technologies will evolve and impact business in 2025. Part 3 covers more predictions about Observability ...

In APMdigest's 2026 Observability Predictions Series, industry experts offer predictions on how Observability and related technologies will evolve and impact business in 2025. Part 2 covers predictions about Observability and AIOps ...

The Holiday Season means it is time for APMdigest's annual list of predictions, covering Observability and other IT performance topics. Industry experts — from analysts and consultants to the top vendors — offer thoughtful, insightful, and often controversial predictions on how Observability, AIOps, APM and related technologies will evolve and impact business in 2026 ...

IT organizations are preparing for 2026 with increased expectations around modernization, cloud maturity, and data readiness. At the same time, many teams continue to operate with limited staffing and are trying to maintain complex environments with small internal groups. These conditions are creating a distinct set of priorities for the year ahead. The DataStrike 2026 Data Infrastructure Survey Report, based on responses from nearly 280 IT leaders across industries, points to five trends that are shaping data infrastructure planning for 2026 ...

Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...