This guide will run through the custom integration that was created for Azure Citadel to use the Azure Search service to index the site and provide search results to users. Although the solution was specific to this site and Jekyll, the working principals and approach could be reused for integrating any static website with Azure Search

Azure Search is a search-as-a-service cloud solution that gives developers APIs and tools for adding a rich search experience over heterogenous content in a range of applications

Using Azure Search with a static site like Jekyll presented several challenges

  • Generating site content (Markdown and HTML pages) in generalised a data format Azure Search can consume and index
  • Getting said data into Azure Search
  • Allowing users to query the search from the site, i.e. creating the frontend

Solution Components

The solution consists of four main elements:

  • Jekyll page (Liquid template) that outputs site as JSON
  • Azure Pipeline for pushing data into Azure Search index
  • Azure Search service
  • Search page ‘client’ written in jQuery & HTML5
  • App Insights for analytics and gathering telemetry

End to End Data Flow

The data flow and interaction between the components is as follows

Overall solution flow

Site JSON Generation

A Liquid template page was created to output the site as a single JSON document, this page resides in _pages/site.json with a permalink set to /site.json so it outputs to the root of the site. It loops over all pages in the site when the Jekyll build is run. The resulting JSON object is an array of documents in a format ready for Azure Search index to consume. See Azure Search documentation on the required format of the data

  • Only pages with .md extension are processed, this stops us processing many of the static/special .html pages on the site
  • The id field is created from the page URL. This will be used as the key field (as it is unique), Base64 encoding ensures the key is “safe” for Azure Search (no strange characters)
  • The other fields are mostly copied from the page object directly
  • The content is placed in a field called content
  • @search.action field is an instruction to Azure Search

The source of _pages/site.json



---
layout: null
permalink: /site.json
---
{% assign content_pages = site.pages | where_exp: "p", "p.path contains '.md'" %}
{ 
  "value": [
    {% for page in content_pages %}
    {
      "@search.action": "mergeOrUpload",
      "id":      "{{ page.url | base64_encode }}",
      "author":  "{{ page.author | join: ', ' }}",
      "tags":    "{{ page.tags | join: ', ' }}",
      "title":   "{{ page.title }}",
      "teaser":  "{{ page.header.teaser }}",
      "url":     "{{ page.url }}",
      "excerpt": "{{ page.excerpt }}",
      "date":    "{{ page.date | date: "%Y-%m-%d" }}",
      "content":  {{ page.content | jsonify }}
    }{% if forloop.last %}{% else %},{% endif %}
    {% endfor %}
    ]
}

Here’s an example of one element (page) in the array:

    {
      "@search.action": "mergeOrUpload",
      "id":      "L2F1dG9tYXRpb24vdGVycmFmb3JtL1RlcnJhZm9ybUVudGVycHJpc2Uv",
      "author":  "Fred Blogs",
      "tags":    "tag1, tag2",
      "title":   "Just An Example",
      "teaser":  "images/teaser/example.png",
      "url":     "/stuff/example/",
      "excerpt": "Short overview of a very boring thing that doesn't exist",
      "date":    "2018-10-29",
      "content": "<< REMOVED TO SAVE SPACE >>"
    },

Azure Pipelines - Build & Re-index

To keep the index up to date and fresh, some sort of scheduled automation process was required. Azure Pipelines was used for this as it has the ability to run the Jekyll build tasks and is flexible enough to automate the other steps required.

The automation is done as a single ‘Build Pipeline’ in Azure Pipelines. The pipeline was defined in YAML and is shown in full below

trigger: none 
pr: none

queue:
  name: Hosted Ubuntu 1604

variables:
  - group: citadel-shared-vars

steps:
- task: UseRubyVersion@0
  displayName: 'Use latest Ruby version'

- script: 'gem install bundler -v 1.17.3'
  displayName: 'Install bundler at version 1.17.3'

- script: 'bundle install'
  displayName: 'Run bundle install'

- script: 'bundle exec jekyll build'
  displayName: 'Run jekyll and build site'

- script: 'curl -v -H "api-key: $(search-admin-key)" -H "Content-Type: application/json" --data-binary "@_site/site.json" -X POST "https://$(search-account).search.windows.net/indexes/$(search-index)/docs/index?api-version=2017-11-11"'
  displayName: 'Push site.json to Azure Search'

A summary of pipeline:

  • Environmental setup (Ruby and bundler)
  • Run bundle exec jekyll build to build the site, to default output directory _site
  • Using curl, call the Azure Search REST API and push the JSON results (site.json) as a single POST

Secrets and other variables are held in Azure Pipelines as a variable group called citadel-shared-vars. This variable group was created and pre-populated using the Azure DevOps Portal, so that no secrets or other variable settings needed to be hardcoded into the pipeline.

The pipeline runs on a schedule every 24 hours (and not not on repo pushes/commits as many build pipelines would) and the definition YAML stored in the Git repo that contains the site

Azure Search Configuration

Azure Search is a powerful search as a service capability available as PaaS within Azure. For this integration the set up was fairly simple, an Azure Search instance (i.e. account) was created on the Free tier using the Azure Portal. This was a one time task so was not automated.

As the Azure Portal experience for managing and fully configuring Azure Search is quite limited, the REST API was used to setup and configure the service. Postman was used to provide a nice interface to work with the API.

To assist using the API with Postman, the following can be used:

To use simply download & import into Postman, then configure the variables in ‘Azure Search’ environment to match your setup.

As the documents to be indexed are pushed directly to the API, certain featured of Azure Search such as data source and indexer are not required. The only aspect that needs to be setup & configured is an index

Azure Search - Index

The Azure Search index determines which fields will be searchable and returned when querying, and holds the actual data (at least in index form)

Notes on index fields:

  • Custom id field used as a key, created by the site.json generation template page
  • Main searchable fields are content, title, tags and excerpt
  • Other fields marked as retrievable are: url, date, author and teaser
  • All fields are strings

Example index JSON:

{  
  "name": "citadel-index",
  "fields": [  
    {  
      "name": "id",
      "key": true,
      "retrievable": true,
      "type": "Edm.String"
    },
    {  
      "name": "content",
      "retrievable": false,
      "searchable": true,
      "type": "Edm.String"      
    },
    {  
      "name": "title",
      "retrievable": true,
      "searchable": true,
      "type": "Edm.String"      
    },
    {  
      "name": "tags",
      "retrievable": true,
      "searchable": true,
      "type": "Edm.String"      
    },  
    {  
      "name": "excerpt",
      "retrievable": true,
      "searchable": true,
      "type": "Edm.String"        
    },
    {  
      "name": "url",
      "retrievable": true,
      "searchable": false,
      "type": "Edm.String"        
    },
    {  
      "name": "author",
      "retrievable": true,
      "searchable": false,
      "type": "Edm.String"        
    },
    {  
      "name": "date",
      "retrievable": true,
      "searchable": false,
      "type": "Edm.String"        
    }, 
    {  
      "name": "teaser",
      "retrievable": true,
      "searchable": false,
      "type": "Edm.String"        
    }
  ]
}

Search Page

To consume or use the search index and actually find results, a client page was created using jQuery. As the site in question is static HTML more modern JavaScript frameworks were deemed to complex to integrate with the site. The search experience is a single query field, and results are fetched & shown in real time as they are typed

The page is very simple, mostly self contained & consists of:

  • Search input field bound with keyup events (using jQuery)
  • Area for results to dynamically be displayed
  • Function to call Azure Search query API (using jQuery AJAX), parse results & update the page
  • Delay callback function
  • Simple spinner to give user feedback on activity

The basic form is the Azure Search query API is used as follows

GET https://${AZURE_SEARCH_ACCOUNT}.search.windows.net/indexes/${AZURE_SEARCH_INDEX}/docs?api-version=2017-11-11&api-key=${AZURE_SEARCH_KEY}&search={QUERY}

The delay function prevents us overloading the API with requests, so API calls are only made after the user has stopped typing for 500 milliseconds. The API call is made with jQuery, however something like Fetch could have been used.

The API results are parsed as JSON, and certain fields such as header run through JSON.parse() as they contain embedded JSON strings for nested objects. The url can be used to form a link to the relevant page, and fields such as header.teaser, title, excerpt, date & author allow for display of meaningful results on the page. The parsed results are pushed back to the page with a dynamic element and jQuery append.

There’s one other task the search page performs, and that’s to track search events in Azure Application Insights for analytics & reporting. For Azure Citadel, App Insights had already been setup and all pages instrumented with the standard JavaScript code snippet. The search page sends two types of custom event to App Insights using appInsights.trackEvent, one called “Search” for a completed search (where results > 0) and another called “Click”. The two events can be correlated together with the id parameters provided in the events

This is fully documented in the Azure Search Docs:
Search Traffic Analytics ⇒

The source of the page created can be found in the Citadel GitHub repo

For a working demonstration simply click the search link on this site’s toolbar!

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