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Dynatrace OTel Collector distribution amplifies OpenTelemetry integration for scalable, production-ready observability

Dynatrace

But rigorous requirements for security, production readiness, scalability, and reliability can make adopting OpenTelemetry challenging for teams to maintain at enterprise scale. With deep analytics of traces from Dynatrace, developers have data in full context, which helps them easily debug instrumentation issues.

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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.

Analytics 196
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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Current analytics tools are fragmented and lack context for meaningful analysis. Effective analytics with the Dynatrace Query Language.

Analytics 242
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Google Cloud Next 2024: AI innovation for Google Cloud

Dynatrace

As organizations continue to expand within cloud-native environments using Google Cloud, ensuring scalability becomes a top priority. Dynatrace offers essential analytics and automation to keep applications optimized and businesses flourishing. Learn to boost system reliability through proactive issue detection.

Google 269
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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

that offers security, scalability, and simplicity of use. Python code also carries limited scalability and the burden of governing its security in production environments and lifecycle management. address these limitations and brings new monitoring and analytical capabilities that weren’t available to Extensions 1.0:

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

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Dynatrace extends contextual analytics and AIOps for open observability

Dynatrace

With extended contextual analytics and AIOps for open observability, Dynatrace now provides you with deep insights into every entity in your IT landscape, enabling you to seamlessly integrate metrics, logs, and traces—the three pillars of observability. How can we optimize for performance and scalability?

Analytics 246