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Dynatrace OpenPipeline: Stream processing data ingestion converges observability, security, and business data at massive scale for analytics and automation in context

Dynatrace

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. However, there are many obstacles and limitations along the way to becoming a data-driven organization.

Analytics 194
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Business Flow: Why IT operations teams should monitor business processes

Dynatrace

The business process observability challenge Increasingly dynamic business conditions demand business agility; reacting to a supply chain disruption and optimizing order fulfillment are simple but illustrative examples. Most business processes are not monitored. First and foremost, it’s a data problem.

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Enhance data collection with Dynatrace OpenTelemetry Collector distribution

Dynatrace

As organizations strive for observability and data democratization, OpenTelemetry emerges as a key technology to create and transfer observability data. Understanding OpenTelemetry OpenTelemetry is an open, vendor-neutral standard for creating, collecting, and transferring telemetry data, like traces, metrics, and logs.

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Practical business process monitoring for real-time business observability

Dynatrace

Recent platform enhancements in the latest Dynatrace, including business events powered by Grailâ„¢, make accessing the goldmine of business data flowing through your IT systems easier than ever. The Business Flow app Business Flow, built with AppEngine, simplifies the configuration, monitoring, and analysis of business processes.

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Unlock the observability value of log data with processing at scale

Dynatrace

The data locked in your log files can be a goldmine for your application developers, operations teams, and your enterprise as a whole. However, it can be complicated , expensive , or even impossible to set up robust observability that makes use of this data. Log format inconsistency makes it a challenge to access critical data.

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AI techniques enhance and accelerate exploratory data analytics

Dynatrace

In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices.

Analytics 209
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Observability engineering: Getting Prometheus metrics right for Kubernetes with Dynatrace and Kepler

Dynatrace

This challenge has given rise to the discipline of observability engineering, which concentrates on the details of telemetry data to fine-tune observability use cases. To get a more granular look into telemetry data, many analysts rely on custom metrics using Prometheus.

Metrics 177