diff --git a/en/applications/developer-guide.html b/en/applications/developer-guide.html
index 94f3f5ca69..581995897a 100644
--- a/en/applications/developer-guide.html
+++ b/en/applications/developer-guide.html
@@ -126,7 +126,7 @@ <h2 id="developing-components">Developing Components</h2>
         configuration is therefore accessed through generated config classes.
       </p><p>
       The Maven target <code>generate-sources</code> (invoked by <code>mvn install</code>) uses
-      <a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/src/main/resources/configdefinitions/metal-names.def">
+      <a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/app/src/main/resources/configdefinitions/metal-names.def">
         metal-names.def</a>
       to generate <code>target/generated-sources/vespa-configgen-plugin/com/mydomain/example/MetalNamesConfig.java</code>.
     </p><p>
@@ -140,7 +140,7 @@ <h2 id="developing-components">Developing Components</h2>
     <td>
       <p id="tests">
         Examples unit tests are found in
-        <a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/src/test/java/ai/vespa/example/album/MetalSearcherTest.java">
+        <a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/app/src/test/java/ai/vespa/example/album/MetalSearcherTest.java">
           MetalSearcherTest.java</a>.
         <code>testAddedOrTerm1</code> and <code>testAddedOrTerm2</code> illustrates two ways of doing the same test:
       </p>
@@ -250,7 +250,7 @@ <h3 id="running-java-tests">Running Java tests</h3>
 <p>
   The <code>apiKey</code> is used to fetch the <em>dev</em> instance's endpoints.
   The data plane key and certificate pair is used by
-  <a href="https://github.com/vespa-engine/vespa/blob/master/tenant-cd-api/src/main/java/ai/vespa/hosted/cd/Endpoint.java">ai.vespa.hosted.cd.Endpoint</a>
+  <a href="https://github.com/vespa-engine/vespa/blob/master/cloud/tenant-cd-api/src/main/java/ai/vespa/hosted/cd/Endpoint.java">ai.vespa.hosted.cd.Endpoint</a>
   to access the application endpoint.
   Note that the <code>-D vespa.test.config</code> argument is gone;
   this configuration is automatically fetched from the Vespa Cloud API—hence the need for the API key.
diff --git a/en/applications/unit-testing.html b/en/applications/unit-testing.html
index 94d73274e3..da11f30cad 100644
--- a/en/applications/unit-testing.html
+++ b/en/applications/unit-testing.html
@@ -20,7 +20,7 @@ <h2 id="unit-testing-using-application">Unit testing using Application</h2>
 the test through <a href="https://javadoc.io/page/com.yahoo.vespa/application/latest/com/yahoo/application/Application.html#getJDisc-java.lang.String-">app.getJDisc(clusterName)</a> -
 this class has methods for using all common <a href="../reference/applications/components.html">component types</a>.
 </p><p>
-Refer to <a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/src/test/java/ai/vespa/example/album/MetalSearcherTest.java">
+Refer to <a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/app/src/test/java/ai/vespa/example/album/MetalSearcherTest.java">
 MetalSearcherTest.java</a> for example use.
 Notice how the test disables the network layer in order to run tests in parallel.
 </p>
diff --git a/en/examples/billion-scale-image-search.md b/en/examples/billion-scale-image-search.md
index 99eac402ea..9af97c2738 100644
--- a/en/examples/billion-scale-image-search.md
+++ b/en/examples/billion-scale-image-search.md
@@ -88,14 +88,14 @@ or self-hosted on-premise.
 ## Stateless Components
 The app contains several [container components](../applications/components.html):
 
-- [RankingSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/java/ai/vespa/examples/searcher/RankingSearcher.java) implements the last stage ranking using
+- [RankingSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/java/ai/vespa/examples/searcher/RankingSearcher.java) implements the last stage ranking using
 full-precision vectors using an ONNX model for accelerated inference.
-- [DedupingSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/java/ai/vespa/examples/searcher/DeDupingSearcher.java) implements run-time de-duping after Ranking, using
+- [DedupingSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/java/ai/vespa/examples/searcher/DeDupingSearcher.java) implements run-time de-duping after Ranking, using
 document to document similarity matrix, using an ONNX model for accelerated inference.
-- [DimensionReducer](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/java/ai/vespa/examples/DimensionReducer.java) PCA dimension reducing vectors from 768-dims to 128-dims.
-- [AssignCentroidsDocProc](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/java/ai/vespa/examples/docproc/AssignCentroidsDocProc.java) searches the HNSW graph content cluster
+- [DimensionReducer](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/java/ai/vespa/examples/DimensionReducer.java) PCA dimension reducing vectors from 768-dims to 128-dims.
+- [AssignCentroidsDocProc](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/java/ai/vespa/examples/docproc/AssignCentroidsDocProc.java) searches the HNSW graph content cluster
 during ingestion to find the nearest centroids of the incoming vector.
-- [SPANNSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/java/ai/vespa/examples/searcher/SPANNSearcher.java)
+- [SPANNSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/java/ai/vespa/examples/searcher/SPANNSearcher.java)
 
 ## Deploying this app
 These reproducing steps, demonstrates the app using a smaller subset of the LAION-5B vector dataset, suitable
@@ -233,8 +233,8 @@ $ vespa deploy --wait 300 ./app
 It is possible to deploy this app to
 [Vespa Cloud](../basics/deploy-an-application-java.html).
 For Vespa cloud deployments to the [dev env](../operations/zones.html)
-replace the [src/main/application/services.xml](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/application/services.xml) with
-[src/main/application/services-cloud.xml](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/application/services-cloud.xml) -
+replace the [src/main/application/services.xml](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/qpp/src/main/application/services.xml) with
+[src/main/application/services-cloud.xml](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/application/services-cloud.xml) -
 the cloud deployment uses dedicated clusters for `feed` and `query`.
 
 Wait for the application endpoint to become available:
@@ -276,13 +276,13 @@ $ vespa document get \
 
 The response contains all fields, including the full vector representation and the
 reduced vector, plus all the metadata. Everything represented in the same
-[schema](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/application/schemas/image.sd).
+[schema](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/application/schemas/image.sd).
 
 
 ## Query the data
 The following provides a few query examples,
 `prompt` is a run-time query parameter which is used by the
-[CLIPEmbeddingSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/src/main/java/ai/vespa/examples/searcher/CLIPEmbeddingSearcher.java)
+[CLIPEmbeddingSearcher](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search/app/src/main/java/ai/vespa/examples/searcher/CLIPEmbeddingSearcher.java)
 which will encode the prompt text into a CLIP vector representation using the embedded CLIP model:
 
 <pre data-test="exec" data-test-assert-contains="documentid">
diff --git a/en/linguistics/query-rewriting.html b/en/linguistics/query-rewriting.html
index b07d52b1f3..cc6e7d7905 100644
--- a/en/linguistics/query-rewriting.html
+++ b/en/linguistics/query-rewriting.html
@@ -71,7 +71,7 @@ <h2 id="equiv">EQUIV</h2>
 The decision to use EQUIV must be taken by application-specific dictionary or linguistics use.
 This can be done using <a href="../reference/querying/yql.html#equiv">YQL</a>
 or from a container plugin (example
-<a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/src/main/java/ai/vespa/example/album/EquivSearcher.java">
+<a href="https://github.com/vespa-engine/sample-apps/blob/master/album-recommendation-java/app/src/main/java/ai/vespa/example/album/EquivSearcher.java">
 EquivSearcher.java</a>) where the query object is manipulated as follows:
 </p>
 <ol>
diff --git a/en/operations/enclave/aws-getting-started.md b/en/operations/enclave/aws-getting-started.md
index 1f113dddba..b16d239747 100644
--- a/en/operations/enclave/aws-getting-started.md
+++ b/en/operations/enclave/aws-getting-started.md
@@ -61,7 +61,7 @@ will let you know when a new release is available.
 #### Cloudformation
 
 Vespa also supports Cloudformation if you prefer the AWS-native solution.
-Download the Cloudformation stacks in our [github repository](https://github.com/vespa-cloud/cloudformation-aws-enclave) and
+Download the Cloudformation stacks in our [GitHub repository](https://github.com/vespa-cloud/cloudformation-aws-enclave) and
 refer to the README for stack-specific instructions.
 
 ### 4. Deploy a Vespa application
diff --git a/en/querying/nearest-neighbor-search.md b/en/querying/nearest-neighbor-search.md
index 5178835275..e2f75bd73a 100644
--- a/en/querying/nearest-neighbor-search.md
+++ b/en/querying/nearest-neighbor-search.md
@@ -407,7 +407,7 @@ In this case, it simply ranks documents based on how close they are in the CLIP
 As with all query operators in Vespa, one can build the query tree programmatically
 in a custom [searcher component](../applications/searchers.html).
 See
-[Centroids](https://github.com/vespa-engine/sample-apps/blob/master/billion-scale-image-search/src/main/java/ai/vespa/examples/Centroids.java)
+[Centroids](https://github.com/vespa-engine/sample-apps/blob/master/billion-scale-image-search/app/src/main/java/ai/vespa/examples/Centroids.java)
 in [Billion-Scale Image Search](https://github.com/vespa-engine/sample-apps/tree/master/billion-scale-image-search)
 for an example of how the `NearestNeighborItem` is used.