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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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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. Augmenting LLM input in this way reduces apparent knowledge gaps in the training data and limits AI hallucinations. Failure to provide timely and accurate answers erodes user trust, hinders adoption, and harms retention.

Cache 201
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Why growing AI adoption requires an AI observability strategy

Dynatrace

As organizations turn to artificial intelligence for operational efficiency and product innovation in multicloud environments, they have to balance the benefits with skyrocketing costs associated with AI. An AI observability strategy—which monitors IT system performance and costs—may help organizations achieve that balance.

Strategy 218
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What the NIS2 Directive means for application security

Dynatrace

The Network and Information Systems 2 (NIS2) Directive, which goes into effect in Oct 2024, aims to enhance the security of network and information systems throughout the EU. NIS2 is an evolution of the Network and Information Systems (NIS) Security Directive, which has been in effect since 2016.

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Measuring the importance of data quality to causal AI success

Dynatrace

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. That’s where causal AI can help.

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Fueling the next wave of IT operations: Modernization with generative AI

Dynatrace

Teams require innovative approaches to manage vast amounts of data and complex infrastructure as well as the need for real-time decisions. As a result, organizations are turning to AI to automate tasks—from code development to incident response—to reduce manual effort and human error, and to boost workforce efficiency.

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Embrace enterprise-wide observability and security with Foundation & Discovery

Dynatrace

Still, a single unmonitored host can become a weak link , causing system failures and security breaches. This unified approach reduces the total cost of ownership (TCO), cutting down on the overhead costs associated with managing multiple standalone tools and training costs and simplifying procurement and vendor management.

Analytics 170