Latest news

You can build a list of the latest news articles in several ways. This page shows two of them: full schemas with references, and an index schema.

Using full schemas

The frontPage schema below lists the 3 latest news articles that match the front page’s culture.

/** @type {Enterspeed.FullSchema} */
export default {
  triggers: function(context) {
    context.triggers("cms", ["frontPage"]);
  },
  routes: function(sourceEntity, context) {
    context.url(sourceEntity.url);
  },
  properties: function (sourceEntity, context) {
    return {
      title: sourceEntity.properties.name,
      description: sourceEntity.properties.description,
      latestNews: context
                .reference("news")
                .filter(`type eq 'news' and properties.culture eq '${sourceEntity.properties.culture}'`)
                .orderBy({propertyName: "properties.date", direction: "desc"})
                .limit(3)
    };
  }
}

To keep the list up to date, you need to reprocess the frontPage schema whenever a news article is created, updated or deleted. See more about when reprocessing is needed. Below is an example of the news schema including the reprocess action.

Always make your reprocess actions as precise as possible to avoid overprocessing. Typically, you want to reprocess by id, as this is the fastest and most precise option.In this case, you don’t have the id of the front page. But you only have one front page per culture, so you can target that single front page source entity with a filter expression matching the culture.

/** @type {Enterspeed.FullSchema} */
export default {
  triggers: function(context) {
    context.triggers("cms", ["news"]);
  },
  routes: function(sourceEntity, context) {
    context.url(sourceEntity.url);
  },
  actions: function(sourceEntity, context) {
    context.reprocess('frontPage')
            .filter(`type eq 'frontPage' and properties.culture eq '${sourceEntity.properties.culture}'`);
  },
  properties: function (sourceEntity, context) {
    return {
      title: sourceEntity.properties.name,
      date: sourceEntity.properties.date,
      category: sourceEntity.properties.category,
      text: sourceEntity.properties.text
    };
  }
}

Using index schemas

Index schemas are a paid add-on. They don’t need reprocessing, and they let you query the index using the Query API for the news articles you want to return, for example based on culture and category.

/** @type {Enterspeed.IndexSchema} */
export default {
  triggers: function(context) {
    context.triggers('cms', ['news']);
  },
  index: {
    fields: {
      title: { type: "text" },
      date: { type: "date" },
      culture: { type: "keyword" },
      category: { type: "keyword" },
      text: { type: "text" }
    }
  },
  properties: function (sourceEntity) {
    return {
      title: sourceEntity.properties.name,
      date: sourceEntity.properties.date,
      culture: sourceEntity.properties.culture,
      category: sourceEntity.properties.category,
      text: sourceEntity.properties.text
    };
  }
}

Here’s a request to the Query API for the newsIndex and the response.

curl -L -X POST 'https://query.enterspeed.com/v1/newsIndex' \
-H 'X-Api-Key: [your_environment_key]' \
-H 'Content-Type: application/json' \
-d '{
    "filters": {
      "and": [
        {
          "field": "culture",
          "operator": "equals",
          "value": "en-us"
        }
      ]
    },
    "sort": [
      {
        "field": "date",
        "order": "desc"
      }
    ],
    "pagination": {
      "page": 0,
      "pageSize": 3
    }
  }'

{
  "totalResults": 100,
  "results": [
      {
        "_sourceGuid": "6f544251-40ca-474b-9c00-5d44bc891799",
        "_updatedAt": "2025-10-17T12:08:43.5022645Z",
        "_originId": "f269a7fc-2a96-4246-b8d6-6e91e6bfa390",
        "title": "Management MCP now supports schema dry runs against single entities",
        "date": "2025-10-17",
        "culture": "en-us",
        "category": "Product update",
        "text": "..."
      },
      {
        "_sourceGuid": "6f544251-40ca-474b-9c00-5d44bc891799",
        "_updatedAt": "2025-10-16T09:15:44.9083304Z",
        "_originId": "bb27cc54-3e72-4191-a096-081038e3fde9",
        "title": "Speedtrain: A/B output comparison in review sessions",
        "date": "2025-10-16",
        "culture": "en-us",
        "category": "Feature release",
        "text": "..."
      },
      {
        "_sourceGuid": "6f544251-40ca-474b-9c00-5d44bc891799",
        "_updatedAt": "2025-10-14T13:50:24.9083304Z",
        "_originId": "5012de39-4739-4c37-84d0-321f8e859f5c",
        "title": "New documentation for the Query API and index setup",
        "date": "2025-10-14",
        "culture": "en-us",
        "category": "Documentation",
        "text": "..."
      }
  ],
  "facets": [],
  "nextPageToken": "eyJhbGlhcyI6InF1ZXJ5LWMwNzA1MzAxLWIxMDYtNDkwZi05MjQwLTE3MjQ2NTYzMTRkZS1wcm9kdWN0aW5kZXgiLCJzb3J0IjpbMTc2MDcwMjkyMTMxNCwyXX0=",
  "status": 0
}

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Using full schemas

Using index schemas

​Using full schemas

​Using index schemas

Using full schemas

Using index schemas