Readme

lsierant · lsierant · commit 63cc861b9df0 · 2025-05-12T09:02:39.000+02:00
diff --git a/docs/community-search/quick-start/README.md b/docs/community-search/quick-start/README.md
@@ -130,7 +130,7 @@ This command checks the `mongodb-kubernetes-database-pods` service account to co
 
 With the prerequisites and initial setup complete, you can now deploy MongoDB Community Edition and enable Search.
 
-### 1. Create MongoDB User Secrets
+### 6. Create MongoDB User Secrets
 
 MongoDB requires authentication for secure access. This step creates two Kubernetes secrets: `admin-user-password` and `search-user-password`. These secrets store the credentials for the MongoDB administrative user and a dedicated search user, respectively. These secrets will be mounted into the MongoDB pods.
 
@@ -146,7 +146,7 @@ kubectl --context "${K8S_CLUSTER_0_CONTEXT_NAME}" --namespace "${MDB_NAMESPACE}"
 ```
 Ensure these secrets are created in the same namespace where you plan to deploy MongoDB.
 
-### 2. Create MongoDB Community Resource
+### 7. Create MongoDB Community Resource
 
 Now, deploy MongoDB Community by creating a `MongoDBCommunity` custom resource named `mdbc-rs`. This resource definition instructs the MongoDB Kubernetes Operator to configure a MongoDB replica set with 3 members, running version 8.0.6. MongoDB Community Search is supported only from MongoDB Community Server version 8.0. It also defines CPU and memory resources for the `mongod` and `mongodb-agent` containers, and sets up two users (`admin-user` and `search-user`) with their respective roles and password secrets. User `search-user` will be used to restore, connect and perform search queries on the `sample_mflix` database.
 
@@ -209,7 +209,7 @@ spec:
 EOF
 ```
 
-### 3. Wait for MongoDB Community Resource to be Ready
+### 8. Wait for MongoDB Community Resource to be Ready
 
 After applying the `MongoDBCommunity` custom resource, the operator begins deploying the MongoDB nodes (pods). This step uses `kubectl wait` to pause execution until the `mdbc-rs` resource's status phase becomes `Running`, indicating that the MongoDB Community replica set is operational.
 
@@ -223,7 +223,7 @@ echo; echo "Pods running in cluster ${K8S_CLUSTER_0_CONTEXT_NAME}"
 kubectl --context "${K8S_CLUSTER_0_CONTEXT_NAME}" -n "${MDB_NAMESPACE}" get pods
 ```
 
-### 4. Create MongoDB Search Resource
+### 9. Create MongoDB Search Resource
 
 Once your MongoDB deployment is ready, enable Search capabilities by creating a `MongoDBSearch` custom resource, also named `mdbc-rs` to associate it with the MongoDB instance. This resource specifies the CPU and memory resource requirements for the search nodes.
 
@@ -261,7 +261,7 @@ requests:
     memory: 2G
 ```
 
-### 5. Wait for Search Resource to be Ready
+### 10. Wait for Search Resource to be Ready
 
 Similar to the MongoDB deployment, the Search deployment needs time to initialize. This step uses `kubectl wait` to pause until the `MongoDBSearch` resource `mdbc-rs` reports a `Running` status in its `.status.phase` field, indicating that the search nodes are operational and integrated.
 
@@ -272,7 +272,7 @@ kubectl --context "${K8S_CLUSTER_0_CONTEXT_NAME}" -n "${MDB_NAMESPACE}" wait --f
 ```
 This command polls the status of the `MongoDBSearch` resource `mdbc-rs`.
 
-### 6. Verify MongoDB Community Resource Status
+### 11. Verify MongoDB Community Resource Status
 
 Double-check the status of your `MongoDBCommunity` resource to ensure it remains healthy and that the integration with the Search resource is reflected if applicable.
 
@@ -283,7 +283,7 @@ kubectl --context "${K8S_CLUSTER_0_CONTEXT_NAME}" -n "${MDB_NAMESPACE}" wait --f
 ```
 This provides a final confirmation that the core database is operational.
 
-### 7. List Running Pods
+### 12. List Running Pods
 
 View all the running pods in your namespace. You should see pods for the MongoDB replica set members, the MongoDB Kubernetes Operator, and the MongoDB Search nodes.
 
@@ -301,7 +301,7 @@ kubectl --context "${K8S_CLUSTER_0_CONTEXT_NAME}" -n "${MDB_NAMESPACE}" get pods
 
 Now that your MongoDB Community database with Search is deployed, you can start using its search capabilities.
 
-### 1. Deploy MongoDB Tools Pod
+### 13. Deploy MongoDB Tools Pod
 
 To interact with your MongoDB deployment, this step deploys a utility pod named `mongodb-tools-pod`. This pod runs a MongoDB Community Server image and is kept running with a `sleep infinity` command, allowing you to use `kubectl exec` to run MongoDB client tools like `mongosh` and `mongorestore` from within the Kubernetes cluster. Running steps in a pod inside the cluster simplifies connectivity to mongodb without neeeding to expose the database externally (provided steps directly connect to the *.cluster.local hostnames).
 
@@ -329,7 +329,7 @@ echo "Waiting for the mongodb-tools to be ready..."
 kubectl wait --for=condition=Ready pod/mongodb-tools-pod -n "${MDB_NAMESPACE}" --context "${K8S_CLUSTER_0_CONTEXT_NAME}" --timeout=60s
 ```
 
-### 2. Import Sample Data
+### 14. Import Sample Data
 
 To test the search functionality, this step imports the `sample_mflix.movies` collection. It downloads the sample dataset and uses `mongorestore` to load the data into the `sample_mflix` database in your MongoDB deployment, connecting as the `search-user`.
 
@@ -347,7 +347,7 @@ EOF
 ```
 This command uses `mongoimport` from the `mongodb-tools-pod` to load data from the downloaded `sample_mflix.archive` file.
 
-### 3. Create Search Index
+### 15. Create Search Index
 
 Before performing search queries, create a search index. This step uses `kubectl exec` to run `mongosh` in the `mongodb-tools-pod`. It connects to the `sample_mflix` database as `search-user` and calls `db.movies.createSearchIndex()` to create a search index named "default" with dynamic mappings on the `movies` collection. Dynamic mapping automatically indexes all fields with supported types. MongoDB Search offers flexible index definitions, allowing for dynamic and static field mappings, various analyzer types (standard, language-specific, custom), and features like synonyms and faceted search.
 
@@ -361,7 +361,7 @@ kubectl exec --context "${K8S_CLUSTER_0_CONTEXT_NAME}" -n "${MDB_NAMESPACE}" mon
     --eval 'db.movies.createSearchIndex("default", { mappings: { dynamic: true } });'
 ```
 
-### 4. Wait for Search Index to be Ready
+### 16. Wait for Search Index to be Ready
 
 Creating a search index is an asynchronous operation. This script polls periodically the status by executing `db.movies.getSearchIndexes("default")`.
 
@@ -389,7 +389,7 @@ if [[ "${search_index_status}" != "READY" ]]; then
 fi
 ```
 
-### 5. Execute a Search Query
+### 17. Execute a Search Query
 
 Once the search index is ready, execute search queries using the `$search` aggregation pipeline stage. MongoDB Search supports a query language, allowing for various types of queries such as text search, autocomplete, faceting, and more. You can combine `$search` with other aggregation stages to further refine and process your results.
 
diff --git a/docs/community-search/quick-start/README.md.j2 b/docs/community-search/quick-start/README.md.j2
@@ -76,7 +76,7 @@ This command checks the `mongodb-kubernetes-database-pods` service account to co
 
 With the prerequisites and initial setup complete, you can now deploy MongoDB Community Edition and enable Search.
 
-### 1. Create MongoDB User Secrets
+### 6. Create MongoDB User Secrets
 
 MongoDB requires authentication for secure access. This step creates two Kubernetes secrets: `admin-user-password` and `search-user-password`. These secrets store the credentials for the MongoDB administrative user and a dedicated search user, respectively. These secrets will be mounted into the MongoDB pods.
 
@@ -86,7 +86,7 @@ MongoDB requires authentication for secure access. This step creates two Kuberne
 ```
 Ensure these secrets are created in the same namespace where you plan to deploy MongoDB.
 
-### 2. Create MongoDB Community Resource
+### 7. Create MongoDB Community Resource
 
 Now, deploy MongoDB Community by creating a `MongoDBCommunity` custom resource named `mdbc-rs`. This resource definition instructs the MongoDB Kubernetes Operator to configure a MongoDB replica set with 3 members, running version 8.0.6. MongoDB Community Search is supported only from MongoDB Community Server version 8.0. It also defines CPU and memory resources for the `mongod` and `mongodb-agent` containers, and sets up two users (`admin-user` and `search-user`) with their respective roles and password secrets. User `search-user` will be used to restore, connect and perform search queries on the `sample_mflix` database.
 
@@ -95,7 +95,7 @@ Now, deploy MongoDB Community by creating a `MongoDBCommunity` custom resource n
 {% include "code_snippets/0310_create_mongodb_community_resource.sh" %}
 ```
 
-### 3. Wait for MongoDB Community Resource to be Ready
+### 8. Wait for MongoDB Community Resource to be Ready
 
 After applying the `MongoDBCommunity` custom resource, the operator begins deploying the MongoDB nodes (pods). This step uses `kubectl wait` to pause execution until the `mdbc-rs` resource's status phase becomes `Running`, indicating that the MongoDB Community replica set is operational.
 
@@ -104,7 +104,7 @@ After applying the `MongoDBCommunity` custom resource, the operator begins deplo
 {% include "code_snippets/0315_wait_for_community_resource.sh" %}
 ```
 
-### 4. Create MongoDB Search Resource
+### 9. Create MongoDB Search Resource
 
 Once your MongoDB deployment is ready, enable Search capabilities by creating a `MongoDBSearch` custom resource, also named `mdbc-rs` to associate it with the MongoDB instance. This resource specifies the CPU and memory resource requirements for the search nodes.
 
@@ -129,7 +129,7 @@ requests:
     memory: 2G
 ```
 
-### 5. Wait for Search Resource to be Ready
+### 10. Wait for Search Resource to be Ready
 
 Similar to the MongoDB deployment, the Search deployment needs time to initialize. This step uses `kubectl wait` to pause until the `MongoDBSearch` resource `mdbc-rs` reports a `Running` status in its `.status.phase` field, indicating that the search nodes are operational and integrated.
 
@@ -139,7 +139,7 @@ Similar to the MongoDB deployment, the Search deployment needs time to initializ
 ```
 This command polls the status of the `MongoDBSearch` resource `mdbc-rs`.
 
-### 6. Verify MongoDB Community Resource Status
+### 11. Verify MongoDB Community Resource Status
 
 Double-check the status of your `MongoDBCommunity` resource to ensure it remains healthy and that the integration with the Search resource is reflected if applicable.
 
@@ -149,7 +149,7 @@ Double-check the status of your `MongoDBCommunity` resource to ensure it remains
 ```
 This provides a final confirmation that the core database is operational.
 
-### 7. List Running Pods
+### 12. List Running Pods
 
 View all the running pods in your namespace. You should see pods for the MongoDB replica set members, the MongoDB Kubernetes Operator, and the MongoDB Search nodes.
 
@@ -162,7 +162,7 @@ View all the running pods in your namespace. You should see pods for the MongoDB
 
 Now that your MongoDB Community database with Search is deployed, you can start using its search capabilities.
 
-### 1. Deploy MongoDB Tools Pod
+### 13. Deploy MongoDB Tools Pod
 
 To interact with your MongoDB deployment, this step deploys a utility pod named `mongodb-tools-pod`. This pod runs a MongoDB Community Server image and is kept running with a `sleep infinity` command, allowing you to use `kubectl exec` to run MongoDB client tools like `mongosh` and `mongorestore` from within the Kubernetes cluster. Running steps in a pod inside the cluster simplifies connectivity to mongodb without neeeding to expose the database externally (provided steps directly connect to the *.cluster.local hostnames).
 
@@ -171,7 +171,7 @@ To interact with your MongoDB deployment, this step deploys a utility pod named
 {% include "code_snippets/0410_run_mongodb_tools_pod.sh" %}
 ```
 
-### 2. Import Sample Data
+### 14. Import Sample Data
 
 To test the search functionality, this step imports the `sample_mflix.movies` collection. It downloads the sample dataset and uses `mongorestore` to load the data into the `sample_mflix` database in your MongoDB deployment, connecting as the `search-user`.
 
@@ -181,7 +181,7 @@ To test the search functionality, this step imports the `sample_mflix.movies` co
 ```
 This command uses `mongoimport` from the `mongodb-tools-pod` to load data from the downloaded `sample_mflix.archive` file.
 
-### 3. Create Search Index
+### 15. Create Search Index
 
 Before performing search queries, create a search index. This step uses `kubectl exec` to run `mongosh` in the `mongodb-tools-pod`. It connects to the `sample_mflix` database as `search-user` and calls `db.movies.createSearchIndex()` to create a search index named "default" with dynamic mappings on the `movies` collection. Dynamic mapping automatically indexes all fields with supported types. MongoDB Search offers flexible index definitions, allowing for dynamic and static field mappings, various analyzer types (standard, language-specific, custom), and features like synonyms and faceted search.
 
@@ -190,7 +190,7 @@ Before performing search queries, create a search index. This step uses `kubectl
 {% include "code_snippets/0430_create_search_index.sh" %}
 ```
 
-### 4. Wait for Search Index to be Ready
+### 16. Wait for Search Index to be Ready
 
 Creating a search index is an asynchronous operation. This script polls periodically the status by executing `db.movies.getSearchIndexes("default")`.
 
@@ -199,7 +199,7 @@ Creating a search index is an asynchronous operation. This script polls periodic
 {% include "code_snippets/0440_wait_for_search_index_ready.sh" %}
 ```
 
-### 5. Execute a Search Query
+### 17. Execute a Search Query
 
 Once the search index is ready, execute search queries using the `$search` aggregation pipeline stage. MongoDB Search supports a query language, allowing for various types of queries such as text search, autocomplete, faceting, and more. You can combine `$search` with other aggregation stages to further refine and process your results.
 
