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Causal AI use cases for modern observability that can transform any business

Dynatrace

Software project managers can optimize development processes by analyzing workflow data, such as development time, code commits, and testing phases. Retailers can analyze how factors such as demand, competition, and market trends affect pricing. Government.

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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

As an example, many retailers already leverage containerized workloads in-store to enhance customer experiences using video analytics or streamline inventory management using RFID tracking for improved security. Application observability also helps to improve end-user experiences when combined with Dynatrace Digital Experience monitoring.

Retail 263
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Dynatrace Named a Leader and Positioned Furthest for Vision and Highest in Execution in the 2023 Gartner® Magic Quadrant™ for Application Performance Monitoring and Observability

Dynatrace

Director of infrastructure, software sector “ Strong technology and stronger people. Additionally, we’ve been able to unify dev teams and business teams to set and monitor metrics around user interaction with our sites.”

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RSA Guide 2023: Cloud application security remains core challenge for organizations

Dynatrace

For example, the open source Java library at the heart of the Log4Shell crisis in 2021 was patched within days given the pervasiveness of the code. How vulnerabilities are evaluated – platform module Learn the mechanism that Dynatrace Application Security uses to generate third-party vulnerabilities and code-level vulnerabilities.

Cloud 191
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LATAM COVID-19 readiness

Dynatrace

With the increasing consumption of infrastructure and core applications coupled with sustaining a fast and error-free user experience, Dynatrace is helping customers meet expectations of their customers. And more importantly, can organizations’ infrastructure cope with the increasing demand? What are the changes?

Retail 179
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Pioneering customer-centric pricing models: Decoding ingest-centric vs. answer-centric pricing

Dynatrace

retail giant, initially tied to an ingest-centric pricing vendor, found itself manually curbing costs by limiting daily log ingestion to 3 TB and reducing retention periods. Consequently, the company’s mean time to identify (MTTI) and mean time to resolve (MTTR) during peak retail seasons was too slow. Enhanced code-level visibility.

Retail 241
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Enhancing Azure data analytics and Azure observability with Dynatrace Grail

Dynatrace

As we stand on the cusp of a new era of digital transformation, aptly termed as “2.0,” this paradigm shift is evident in groundbreaking advancements such as cashless retail environments, AI-powered customer service chatbots, front-office robotic process automation, and the burgeoning edge economy.

Azure 184