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The top four log analytics and log management best practices

Dynatrace

The growing challenge in modern IT environments is the exponential increase in log telemetry data, driven by the expansion of cloud-native, geographically distributed, container- and microservice-based architectures. By following key log analytics and log management best practices, teams can get more business value from their data.

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Dynatrace simplifies OpenTelemetry metric collection for context-aware AI analytics

Dynatrace

Kubernetes teams lack simple, consistent, vendor-agnostic architectures for analyzing observability signals across teams. Second, embracing the complexity of OpenTelemetry signal collection must come with a guaranteed payoff: gaining analytical insights and causal relationships that improve business performance.

Analytics 289
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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 218
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How unified data and analytics offers a new approach to software intelligence

Dynatrace

However, cloud infrastructure has become increasingly complex. Further, the delivery infrastructure that makes this happen has also become complex. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. The next frontier: Data and analytics-centric software intelligence.

Analytics 200
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Extending modern observability for exploratory analytics

Dynatrace

A modern observability and analytics platform brings data silos together and facilitates collaboration and better decision-making among teams. Here are some examples: IT infrastructure and operations. To tame this complexity and optimize cloud operations, teams across the organization need to manage and explore their data effectively.

Analytics 130
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Dynatrace extends contextual analytics and AIOps for open observability

Dynatrace

Today’s digital businesses run on heterogeneous and highly dynamic architectures with interconnected applications and microservices deployed via Kubernetes and other cloud-native platforms. Common questions include: Where do bottlenecks occur in our architecture? Dynatrace extends its unique topology-based analytics and AIOps approach.

Analytics 246
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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says. Logs on Grail Log data is foundational for any IT analytics. Open source solutions are also making tracing harder.

Analytics 195