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Best Practices in Cloud Security Monitoring

Scalegrid

Cloud security monitoring is key—identifying threats in real-time and mitigating risks before they escalate. This article strips away the complexities, walking you through best practices, top tools, and strategies you’ll need for a well-defended cloud infrastructure. What does it take to secure your cloud assets effectively?

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Augmenting LLM input in this way reduces apparent knowledge gaps in the training data and limits AI hallucinations. The LLM then synthesizes the retrieved data with the augmented prompt and its internal training data to create a response that can be sent back to the user. million AI server units annually by 2027, consuming 75.4+

Cache 196
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226
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Why growing AI adoption requires an AI observability strategy

Dynatrace

An AI observability strategy—which monitors IT system performance and costs—may help organizations achieve that balance. Training AI data is resource-intensive and costly, again, because of increased computational and storage requirements. Continuously monitor AI models’ performance. AI requires more compute and storage.

Strategy 212
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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

already address SNMP, WMI, SQL databases, and Prometheus technologies, serving the monitoring needs of hundreds of Dynatrace customers. JMX monitoring extensions are currently being migrated. are technologically very different, Python and JMX extensions designed for Extension Framework 1.0 Extensions 2.0 Dynatrace Extensions 1.0

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Auto-adaptive thresholds for AI-driven quality gating

Dynatrace

While platform engineers can build and prepare the necessary infrastructure and templates for self-adoption, developers must still provide some customization. A series of models are continuously trained on Dynatrace tenants to effectively set objectives. Our data scientists utilize metrics and events to store these quality metrics.

Metrics 219
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What the NIS2 Directive means for application security

Dynatrace

The directive mandates operators of critical infrastructure and essential services to implement appropriate security measures and promptly report any incidents to the relevant authorities and affected parties. As the pace of digital transformation accelerates, the cloud applications supporting digital infrastructure become more complex.