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Improve Reliability Of Azure AI Search Solution

By Ashwin Venugopal -
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  Make Your Search Solution Highly Available One straightforward method to enhance the availability of your search solution is by increasing the quantity of replicas. The sole choice is to maintain more than one within the paid search service tiers. The Azure AI Search service has availability guarantees based on the number of replicas you have: Two replicas guarantee 99.9% availability for your queries Three or more replicas guarantee 99.9% availability for both queries and indexing The alternative method to incorporate redundancy into your search solution is by utilizing Availability Zones. This approach necessitates the use of at least a standard tier. When you create replicas, you have the option to place them in various Availability Zones. The advantage of spreading your replicas this way is that they are situated in separate data centers. Distribute Your Search Solution Globally A single resource group and region is the most economical method to design an Azure AI Search serv...
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Manage Costs of Azure AI Search Solution

By Ashwin Venugopal -
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  Manage Costs Of An Azure AI Search Solution The capacity and features you utilize determine how much an Azure AI Search solution will cost to operate. Estimate Your Search Solutions Baseline Costs An excellent tool for estimating the cost of utilizing any Azure service is the Azure pricing calculator. Make use of it to establish a baseline for your search service requirements. Browse to the Azure AI Search pricing calculator. Choose your region, currency, and hour or monthly pricing. Optimizing Azure AI Search's capacity, including the tier you require, the data you're searching, and the features you utilize, is a crucial part of maintaining an affordable Azure AI Search solution. Understand Billing Model Azure AI Search is invoiced similarly to other Azure resources. You are not charged for the number of search queries, responses, or documents ingested. Tips To Reduce Cost Of Your Search Solution These tips can help you reduce the cost of running your search solution: Minim...
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Azure AI Search Solution: Optimize Your Index Size And Schema

By Ashwin Venugopal -
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  Optimize Your Index Size and Schema The effectiveness of your search queries is closely linked to the size and intricacy of your indexes. The quicker Azure AI Search can answer queries, the more compact and streamlined your indexes are. If you don't pay attention, indexes can grow over time. You should review that all the documents in your index are still relevant and need to be searchable. Consider reviewing all the attributes you've enabled on each field. For example, adding support for filters, facets, and sorting can quadruple the storage needed to support your index. Improve Performance Of Your Queries If you're familiar with the workings of the search service, you can optimize your queries to significantly enhance performance. Use this checklist for writing better queries: Only specify the fields you need to search using the searchFields parameter. As more fields require extra processing. Return the smallest number of fields you need to render on your search results...
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Azure AI Search Solution: Optimize Performance of an Azure AI Search Solution

By Ashwin Venugopal -
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  Optimize Performance of an Azure AI Search Solution The size and complexity of your indexes may affect search solutions’ performance. Additionally, You also need to know how to write efficient queries to search it and choose the right service tier. Measure Your Current Search Performance If you don't know how well your search service works, you can't optimize. Establish a baseline performance benchmark so you can verify the advancements you achieve and monitor any decline in performance over time. To start with, enable diagnostic logging using Log Analytics: In the Azure portal, select Diagnostic settings. Give your diagnostic setting a name. Select allLogs and AllMetrics. Select Send to Log Analytics workspace. Choose, or create, your Log Analytics workspace. This diagnostic data must be recorded at the search service level. Your end users or apps may experience performance problems in a number of locations. If you can demonstrate that your search service is operating effici...
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Maintain an Azure AI Search Solution (Part 2)

By Ashwin Venugopal -
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  Authenticate Requests To Your Search Solution Your attention may go to how to verify search requests from your users and apps once you have the infrastructure in place to lessen the attack surface of your search solution. Key-based authentication is the default setting when you set up your ACS. There are two different kinds of keys: Admin Keys - grant write permissions and the right to query system information (maximum of 2 admin keys can be created per search service) Query Keys - grant read permissions and are used by your users or apps to query indexes (maximum of 50 query keys can be created per search service) Role-based access control (RBAC) is provided by the Azure platform as a global system to control access to resources. You can use RBAC in Azure AI Search in the following ways: Roles can be granted access to administer the service Define roles with access to create, load, and query indexes The built-in roles you can assign to manage the Azure AI Search serv...
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Maintain an Azure AI Search Solution (Part 1)

By Ashwin Venugopal -
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  Introduction Understanding how to manage Azure AI Search's two core workloads, indexing and querying, is essential to running a successful solution. The search solution must be as economical as feasible. Manage Security Of an Azure AI Search Solution Businesses must be able to rely on their search solutions' security. You have control over the security of the data you search for with Azure AI Search. Overview Of Security Approaches AI Search security builds on Azure's existing network security features. When you think about securing your search solution, you can focus on three areas: Inbound search requests made by users to your search solution Outbound requests from your search solution to other servers to index documents Restricting access at the document level per user search request Data Encryption Like all Azure services, the Azure AI Search service uses service controlled keys to encrypt the data it stores while it's at rest. Indexes, data sources, synonym maps,...
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Azure AI Search Push API

By Ashwin Venugopal -
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  Index Any Data Using Azure AI Search Push API The most adaptable method for adding data to an Azure AI Search index is the REST API. Any programming language or interactive application that can send JSON requests to an endpoint can be used. Supported REST API Operations There are two supported REST APIs provided by AI Search- Search and management APIs. How To Call Search REST API ? If you want to call any of the search APIs you need to: Use the HTTPS endpoint provided by your search service, you must include an api-version in the URI. The request header must include an api-key attribute. To find the endpoint, api-version, and api-key go to the Azure portal. In the portal, navigate to your search service, then select Search explorer. Choose Keys to locate the api-key on the left. If you're doing more than just accessing the index with the REST API, you can use either the primary or secondary admin key. You can make and use query keys if you only need to search an index. An a...
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