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How low-code/no-code AutomationEngine advances automated workflows

Dynatrace

But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. With the Dynatrace modern observability platform, teams can now use intuitive, low-code/no-code toolsets and causal AI to extend answer-driven automation for business, development and security workflows.

Code 214
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Unified observability delivers deeper insights with AI-driven analytics and automation

Dynatrace

Today’s organizations flock to multicloud environments for myriad reasons, including increased scalability, agility, and performance. With unified observability and security, organizations can protect their data and avoid tool sprawl with a single platform that delivers AI-driven analytics and intelligent automation.

Analytics 183
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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. Security Analytics and automation deal with unknown-unknowns With Security Analytics, analysts can explore the unknown-unknowns, facilitating queries manually in an ad hoc way, or continuously using automation.

Analytics 220
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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. focused on technology coverage, building on the flexibility of JMX for Java and Python-based coded extensions for everything else. Python code also carries limited scalability and the burden of governing its security in production environments and lifecycle management.

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Expanded Grail data lakehouse and new Dynatrace user experience unlock boundless analytics

Dynatrace

Grail – the foundation of exploratory analytics Grail can already store and process log and business events. Introducing Metrics on Grail Despite their many advantages, modern cloud-native architectures can result in scalability and fragmentation challenges. Grail solves this scalability issue!

Analytics 232
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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

The exponential growth of data volume—including observability, security, software lifecycle, and business data—forces organizations to deal with cost increases while providing flexible, robust, and scalable ingest. This “data in context” feeds Davis® AI, the Dynatrace hypermodal AI , and enables schema-less and index-free analytics.

Analytics 195
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Flexible, scalable, self-service Kubernetes native observability now in General Availability

Dynatrace

This file is automatically configured with working defaults, but it can be easily modified using a code editor such as VS Code. This gives us unified analytics views of node resources together with pod-level metrics such as container CPU throttling by node, which makes problem correlation much easier to analyze.