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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 214
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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 181
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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. These challenges stem from the distributed and often resource-constrained nature of edge computing.

Retail 258
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How digital experience monitoring helps deliver business observability

Dynatrace

Digital experience monitoring (DEM) allows an organization to optimize customer experiences by taking into account the context surrounding digital experience metrics. What is digital experience monitoring? Primary digital experience monitoring tools.

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

Dynatrace

What stands out as an imperative now is the urgent need for vendors to shift their focus back to customers and resist the temptation to capitalize on the growing demand for extensive data management and monitoring in complex IT environments. All data is readily accessible without storage tiers, such as costly solid-state drives (SSDs).

Retail 237
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Causal AI use cases for modern observability that can transform any business

Dynatrace

Traditional monitoring provides correlations between events, but causal AI goes further by inferring the probabilistic causal relationships between them. Retailers can analyze how factors such as demand, competition, and market trends affect pricing. That’s why many organizations turn to data lakehouses.

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Intelligent, context-aware AI analytics for all your custom metrics

Dynatrace

Non-topology metrics are not related to any Smartscape entity (for example, a retailer’s revenue numbers per store). Instead, the metric is related to the monitored environment as a whole. Choose your monitoring strategy (i.e., OneAgent comes with a new metric ingest channel already enabled.

Metrics 245