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Enhancing Azure data analytics and Azure observability with Dynatrace Grail

Dynatrace

Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. As digital transformation accelerates and more organizations are migrating workloads to Azure and other cloud environments, they need observability and data analytics capabilities that can keep pace.

Azure 179
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Dynatrace unveils Security Analytics to elevate threat detection, forensics, and incident response

Dynatrace

A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. Additionally, Runtime Application Protection provides the ability to protect from attacks while giving development teams much-needed time to remediate these vulnerabilities.

Analytics 217
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Dynatrace simplifies OpenTelemetry metric collection for context-aware AI analytics

Dynatrace

Code changes are often required to refine observability data. This results in site reliability engineers nudging development teams to add resource attributes, endpoints, and tokens to their source code. Thus, measuring application performance becomes an unnecessarily frustrating coordination effort between teams.

Analytics 279
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Unmatched scalability and security of Dynatrace extensions now available for all supported technologies: 7 reasons to migrate your JMX and Python plugins

Dynatrace

focused on technology coverage, building on the flexibility of JMX for Java and Python-based coded extensions for everything else. While Python code can address most data acquisition and ingest requirements, it comes at the cost of complexity in implementation and use-case modeling. available, and more are in the pipeline.

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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 180
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Mitigating risk with AI observability: Dynatrace empowers organizations to embrace AI for all use cases

Dynatrace

From generating new code and boosting developer productivity to finding the root cause of performance issues with ease, the benefits of AI are numerous. By packaging [these capabilities] into hypermodal AI, we are able to run deep custom analytics use cases in sixty seconds or less.”