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Environment Creation

In this lab, you will create an Azure Search service and a storage account. We recommend keeping both in a new and unique resource group, to make it easier to delete at the end of the workshop (if you want to). We will also upload the data to a blob storage within the storage account.

Step 1 - Create the Azure Search service

  1. Go to the Azure portal and sign in with your Azure account.

  2. Click Create a resource, search for Azure Search, and click Create. See Create an Azure Search service in the portal if you are setting up a search service for the first time, and use the bullet point list below for the details you will use to fill out the details for the Azure Search service.

Dashboard portal

  1. For the URL, that is the service name, choose a name that you can easily remember. We will use it dozens of times in the next labs. The name of the service in the screenshots of this lab won't be available, you must create your own service name.

  2. For Resource group, create a resource group named kmb to contain all the resources you will create in this Knowledge Mining Bbootcamp. In addition to facilitating organization and visualization in the portal, using a single resource group helps you, if necessary at the end of the training, remove all services created. If you want to keep this solution up and running, for demos and POCs in minutes with your own data, this resources cleaning isn't necessary.

  3. For Location, choose one of the regions below, Cognitive Search is not available in all Azure regions.

  • West Central US
  • South Central US
  • East US
  • East US 2
  • West US 2
  • Canada Central
  • West Europe
  • UK South
  • North Europe
  • Brazil South
  • Southeast Asia
  • Central India
  • Australia East

  1. For Pricing tier, create a Basic service to complete tutorials and quickstarts. For deeper information on Azure Search pricing and limits, click here and here.

  2. Pin the service to the dashboard for fast access to service information.

Service definition page in the portal

  1. After the service is created, collect the following information: URL from the Overview page, and api-key (either primary or secondary) from the Keys page. You will need them in the following labs.

Endpoint and key information in the portal

Note! Azure Search must have 2 replicas for read-only SLA and 3 replicas for read/write SLA. This is not addressed in this training. For more information, click here

Step 2 - Clone the Repo

Cloning the repo will download all the training materials to your computer, including the dataset, the slides and the code for the Bot project. The cloning of the repository will use close to 110 MB in total.

  1. In the Cortana search bar, type "git bash" and select "Git Bash Desktop App", or type "cmd" and select "Command Prompt".

  2. Next, type cd c:\ then enter. Now, you will be in the root directory of your computer. If you don't have permission to create folders and files here, navigate to a folder where you can download the Bootcamp materials.

  3. Type and enter git clone https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp.git

  4. Validation step: Go to C:\LearnAI-KnowledgeMiningBootcamp and confirm it exists, including the dataset in the resources folder

Git process

Note! The image above has a smaller number of files downloaded than expected, the training is under constant development.

Step 3 - Create the Azure Blob service and upload the dataset

The enrichment pipeline pulls from Azure data sources. Source data must originate from a supported data source type of an Azure Search indexer. For this exercise, we use blob storage to showcase multiple content types.

  1. Create a storage account in the same region of your Azure Search service created in the step above, to avoid latency between the search service and the files. Use a general purpose account and LRS replication. For production environments, you may need to use another replication type.

  2. From the storage account Overview tab, click the link to Blobs and create a container named basicdemo:

    • Enter a name for the container.
    • Select Container for Access Type.

  3. Upload all files from the \resources\dataset cloned github folder to the basicdemo blob storage container. You can do it using Azure Portal or Azure Storage Explorer. There are other methods to upload data to Azure, but we don't suggest them for this training.

Tip! If you are using Azure Storage Explorer, in the basicdemo container you created, click Upload to upload the sample files.

Be careful! don't create another folder level. This training is created with the assumption that all of the data is located in the root folder of the container.

Use the portal to confirm that all of the 21 files are uploaded to the root directory of the basicdemo container.

Also in the portal, find the storage account tab called Access keys, it has information you will use in the next lab. Get familiar with the blue icons to copy the information for storage account name, key and connection string. They prevent partial copy of the codes. Extra care with the connection string, it is long and finished with core.windows.net.

Step 4 - Create the Cognitive Services Account

As explained in the introduction and in the Solution Architecture: Starting December 21, 2018, you will need to associate a Cognitive Services resource to your Azure Cognitive Search solution, in order to enrich more than 20 documents per day. This is the case of this training.

Follow this process to create a Cognitive Account in the same region and resource group you choose in the previous steps. Name your resource as my-cog-serv and use the S0 pricing tier. It will give you access to Vision, Language and Search capabilities, exactly what is required for this training.

Next Step

Azure Search Lab or Back to Read Me