Azure Management

Azure OpenAI Best Practices Insights from Customer Journeys

Introduction When integrating Azure OpenAI’s powerful models into your production environment, it’s essential to follow best practices to ensure security, reliability, and scalability. Azure provides a robust platform with enterprise capabilities that, when leveraged with OpenAI models like GPT-4, DALL-E 3, and various embedding models, can revolutionize how businesses interact with AI. This guidance document […]

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How to achieve cloud-native endpoint management with Microsoft Intune

This is the final blog post in our series highlighting the increasing benefits of becoming fully cloud-native in endpoint management with Microsoft Intune. In our first post, we talked about why more of our customers are migrating to cloud-native endpoint management. Our second post presented a three-phase model for how customers can go cloud-native with

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Best Practice Guidance for PTU

Co-authors: Luca Stamatescu, Alex Shen, Ming Gu, Michael Tremeer Contributors: Ranjani Mani In today’s rapidly evolving tech landscape, proficiency with Azure OpenAI is crucial for maintaining a competitive edge. Enhanced by the latest announcements at Build 2024, this guide from our Global Black Belt team focuses on the effective management of Provisioned Throughput Units (PTUs)

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Load Testing RAG based Generative AI Applications

When developing applications for Language Models (LLMs), we usually spend a lot of time on both the development and evaluation phases to ensure the app delivers high-quality responses that are not only accurate but also safe for users. However, a great user experience with an LLM application isn’t just about the quality of responses—it’s also about

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Leveraging Azure AI Services to Build, Deploy, and Monitor AI Applications with .NET

Azure AI services offer robust tools and platforms that enable developers to bring their AI solutions from concept to production seamlessly. Using .NET 8 alongside these services, developers can experiment, build, and scale their AI applications effectively. This post explores how you can harness the power of Azure AI and .NET to transform your ideas

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An Enterprise Design for Azure Machine Learning – An Architect’s Viewpoint

1. Problem Statement Many Organisations want to create enterprise data science capability. The goals can include unlocking value from their data assets, reducing cost, and driving customer engagement. While many organisations have an initial capability, challenges can arise while “scaling and industrialization” into an enterprise service. This Point-of-view provides an opinionated design for a “fit

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Unleashing the Power of Microsoft Defender for Cloud – Unique Capabilities for Robust Protection

Microsoft Defender for Cloud (MDC) is a cloud-native application protection platform (CNAPP) that is made up of security measures and practices that are designed to protect cloud-based applications from various cyber threats and vulnerabilities. In this article we make a case that the unique capabilities provided by MDC will be hard to replicate with a

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Native-First Cloud Security Approach

Customers migrating to Public Cloud (Azure, AWS, Google Cloud) are often lifting and shifting existing toolsets. Some customers have the misleading notion that a best of breed approach is better than using Cloud Native solutions. As a result, their cloud workloads suffer from security and efficiency gaps.  These 3rd party solutions rely on the visibility provided by CSPs APIs. However, each solution comes

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Prepare for upcoming transitions in Defender for Servers

Last summer, within the scope of the upcoming Log Analytics agent deprecation, we announced a new agent strategy for Defender for Servers with the goal to simplify the onboarding and reduce external dependencies in our offering while improving existing and adding new capabilities. As part of that new strategy, customers should enable, agentless scanning as

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How to Set Up Sentinel Data Connectors for Kubernetes and GitHub

A guide to configure and use Sentinel Connectors to collect logs and data from your Kubernetes clusters and GitHub CI/CD pipelines. Part 2 of 3 part series about security monitoring of your Kubernetes Clusters and CI/CD pipelines by @singhabhi and @Umesh_Nagdev Link to Part 1 Introduction In part 1 of this series, we discussed the type of log sources you

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