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Extract metrics from business events to increase the value of business analytics

Dynatrace

Exploding volumes of business data promise great potential; real-time business insights and exploratory analytics can support agile investment decisions and automation driven by a shared view of measurable business goals. To close these critical gaps, Dynatrace has defined a new class of events called business events.

Analytics 199
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DevOps automation: From event-driven automation to answer-driven automation [with causal AI]

Dynatrace

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. Though the industry champions observability as a vital component, it’s become clear that teams need more than data on dashboards to overcome persistent DevOps challenges.

DevOps 218
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Unlock the power of contextual log analytics

Dynatrace

Dynatrace enables various teams, such as developers, threat hunters, business analysts, and DevOps, to effortlessly consume advanced log insights within a single platform. DevOps teams operating, maintaining, and troubleshooting Azure, AWS, GCP, or other cloud environments are provided with an app focused on their daily routines and tasks.

Analytics 235
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. A log is a detailed, timestamped record of an event generated by an operating system, computing environment, application, server, or network device.

Analytics 207
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What is log analytics? How a modern observability approach provides critical business insight

Dynatrace

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 213
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AI techniques enhance and accelerate exploratory data analytics

Dynatrace

Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices. The next challenge is harnessing additional AI techniques to make exploratory data analytics even easier. Discovery using global search.

Analytics 208
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New analytics capabilities for messaging system-related anomalies

Dynatrace

An example of a critical event-based messaging service for many businesses is adding a product to a shopping cart. To know which services are impacted, DevOps teams need to know what’s happening with their messaging systems. Seamless observability of messaging systems is critical for DevOps teams. This is great!

Analytics 185