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What is data architecture? A framework to manage data

CIO

Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Cloud storage.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.

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How MCP can revolutionize the way DevOps teams use AI

CIO

Traditionally, the main benefit that generative AI technology offered DevOps teams was the ability to produce things, such as code, quickly and automatically. MCP makes it possible to integrate AI into a wide variety of common DevOps workflows that extend beyond familiar use cases like code generation.

DevOps 196
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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Through advanced data analytics, software, scientific research, and deep industry knowledge, Verisk helps build global resilience across individuals, communities, and businesses. In this post, we describe the development journey of the generative AI companion for Mozart, the data, the architecture, and the evaluation of the pipeline.

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IT leaders brace for the AI agent management challenge

CIO

Agentic AI systems require more sophisticated monitoring, security, and governance mechanisms due to their autonomous nature and complex decision-making processes. Durvasula also notes that the real-time workloads of agentic AI might also suffer from delays due to cloud network latency. IT employees? Not so much.

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Navigating the cloud maze: A 5-phase approach to optimizing cloud strategies

CIO

It prevents vendor lock-in, gives a lever for strong negotiation, enables business flexibility in strategy execution owing to complicated architecture or regional limitations in terms of security and legal compliance if and when they rise and promotes portability from an application architecture perspective.

Cloud 147
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There Is Only One Key Difference Between Observability 1.0 and 2.0

Honeycomb

Under the hood, these are stored in various metrics formats: unstructured logs (strings), structured logs, time-series databases, columnar databases , and other proprietary storage systems. is how you operate your code; observability 2.0 is about how you develop your code Observability 1.0 Observability 1.0