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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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Security Reference Architecture Summary for Cloudera Data Platform

Cloudera

This blog will summarise the security architecture of a CDP Private Cloud Base cluster. The architecture reflects the four pillars of security engineering best practice, Perimeter, Data, Access and Visibility. Security Architecture Improvements. Logical Architecture. Logical Architecture.

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Host concurrent LLMs with LoRAX

AWS Machine Learning - AI

Furthermore, LoRAX supports quantization methods such as Activation-aware Weight Quantization (AWQ) and Half-Quadratic Quantization (HQQ) Solution overview The LoRAX inference container can be deployed on a single EC2 G6 instance, and models and adapters can be loaded in using Amazon Simple Storage Service (Amazon S3) or Hugging Face.

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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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A Reference Architecture for the Cloudera Private Cloud Base Data Platform

Cloudera

The release of Cloudera Data Platform (CDP) Private Cloud Base edition provides customers with a next generation hybrid cloud architecture. The storage layer for CDP Private Cloud, including object storage. Introduction and Rationale. Best of CDH & HDP, with added analytic and platform features .

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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

DeepSeek-R1 distilled variations From the foundation of DeepSeek-R1, DeepSeek AI has created a series of distilled models based on both Metas Llama and Qwen architectures, ranging from 1.570 billion parameters. Sufficient local storage space, at least 17 GB for the 8B model or 135 GB for the 70B model. 70B 128K model.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Software-as-a-service (SaaS) applications with tenant tiering SaaS applications are often architected to provide different pricing and experiences to a spectrum of customer profiles, referred to as tiers. The user prompt is then routed to the LLM associated with the task category of the reference prompt that has the closest match.