How to Use Azure Go SDK to Manage Azure Data Explorer Clusters

Getting started with Azure Data Explorer using the Go SDK covered how to use the Azure Data Explorer Go SDK to ingest and query data from azure data explorer to ingest and query data. In this blog you will the Azure Go SDK to manage Azure Data Explorer clusters and databases.

Azure Data Explorer (also known as Kusto) is a fast and scalable data exploration service for analyzing large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more. This data can then be used for diagnostics, monitoring, reporting, machine learning, and additional analytics capabilities.

Packages for Store Routines in MariaDB 11.4
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MariaDB 11.4 introduced many advanced features. One that grabbed my attention is the general support of packages for stored routines. Although this was previously available by activating the Oracle compatibility mode, now the feature is available gener... […]
Maintain Chat History in Generative AI Apps With Valkey
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A while back I wrote up a blog post on how to use Redis as a chat history component with LangChain. Since LangChain already had Redis chat history available as a component, it was quite convenient to write a client application. But, that's not the same... […]
Knowledge Graph Enlightenment, AI, and RAG
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In the previous edition of the YotG newsletter, the wave of Generative AI hype was probably at its all-time high. Today, while Generative AI is still talked about and trialed, the hype is subsiding. Skepticism is settling in, and for good reason. Repor... […]
Building an Effective Zero Trust Security Strategy for End-To-End Cyber Risk Management
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You've probably heard a lot about zero-trust security lately, and for good reason. As we move more of our applications and data to the cloud, the traditional castle-and-moat approach to security just doesn't cut it anymore. This makes me come... […]
Phased Approach to Data Warehouse Modernization
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A modernized database will help you focus on building innovative solutions rather than investing your time and effort in managing these legacy systems. Based on the scale of your existing data warehouse processes or jobs, it can be an enormous task to ... […]