Deploy MongoDB Search and Vector Search

You can deploy MongoDB Search and Vector Search in your Kubernetes cluster to build powerful search experiences directly within your applications. Using MongoDB Search and Vector Search, you can build both traditional text search and AI-powered vector search capabilities that automatically sync with an on-premises MongoDB database. This eliminates the need to maintain separate systems in sync while providing advanced search features. To learn more, see:

To enable the search capabilities such as full-text and semantic search in on-prem deployments, you must deploy the MongoDB Search and Vector Search process (mongot) and connect it with your MongoDB database deployment (mongod). Deployment of mongot is optional and is needed only if you plan to leverage the search features it offers.

The MongoDB Database processes (mongod) acts as the proxy for all search queries for mongot. The mongod forwards the query to mongot, which processes the query. The mongot returns the query results to the mongod, which then forwards the results to you. You never interact directly with the mongot.

Each mongot process has its own persistent volume that is not shared with the database or other search nodes. Storage is used to maintain indexes that are built from the data continuously sourced from the database. The index definitions (metadata) are stored in the database itself.

The mongot performs the following actions:

Manages the index.

The mongot is responsible for updating the index definitions in the database.
Sources the data from the database.

The mongot nodes establish permanent connections to the database in order to update indexes from the database in real time.
Processes search queries.

When mongod receives a $search, $searchMeta, or $vectorSearch query, it directs the query to one of the mongot nodes. The mongot that receives the query processes the query, aggregates the data, and returns the results to mongod, which it forwards to the user.

The mongot components are tightly coupled with a single MongoDB replica set and cannot be shared across multiple databases or replica sets. That means a replica set deployment has its own dedicated search nodes.

Network connectivity between mongot and mongod goes in both directions:

mongot establishes connection to the replica set to source the data used to build indexes and run queries.
mongod connects to mongot to forward search related operations such as index management and querying the data.

MongoDB Search and Vector Search Deployment

There are not many differences between the search deployment architecture with or without the Kubernetes Operator. The Kubernetes Operator simplifies the steps required to deploy fully functioning search nodes, especially when the database is also managed by the Kubernetes Operator.

To deploy, you apply the MongoDBSearch Custom Resource (CR), which the Kubernetes Operator picks up and starts deploying mongot pods and requests persistent storage specified in the spec. The MongoDB Search and Vector Search deployed using the Kubernetes Operator can target MongoDB replica set deployed by the Kubernetes Operator inside the same Kubernetes cluster or a completely independent external MongoDB database. To learn how to deploy and configure mongot to use:

A MongoDB replica set in Kubernetes, see Install and Use Search With MongoDB Enterprise Edition
An external MongoDB replica set, see Install and Use MongoDB Search and Vector Search With External MongoDB Enterprise Edition.

Pre-Requisites

In order to leverage MongoDB Search and Vector Search in your MongoDB Enterprise deployment, you must have the following:

Fully functional MongoDB 8.0.10+ replica set deployed in one of the following ways:
- Inside a Kubernetes cluster using the Kubernetes Operator
- Outside a Kubernetes cluster
Cloud Manager or Ops Manager Instance

Configuration Tasks

The following table shows the configuration tasks that the Kubernetes Operator automatically performs and the actions that you must take to successfully deploy MongoDB Search and Vector Search in Kubernetes and connect to a MongoDB replica set in Kubernetes or an external MongoDB replica set.

Task	(Inside Kubernetes) Performed by	(External MongoDB) Performed by
Deploy Ops Manager inside Kubernetes	Kubernetes Operator	Kubernetes Operator
Deploy Cloud Manager or Ops Manager outside Kubernetes	You	You
Deploy MongoDB replica set	Kubernetes Operator	You
Create `MongoDBSearch` custom resource	You	You
Provide connection string to MongoDB replica set	Kubernetes Operator	You
Create `mongot` configuration YAML	Kubernetes Operator	Kubernetes Operator
Set necessary replica set parameters in each `mongod` process	Kubernetes Operator	You
Polyfill `searchCoordinator` role in MongoDB version less than 8.2	Kubernetes Operator	You
Create user for `mongot` with `searchCoordinator` role	Kubernetes Operator and you by applying MongoDBUser resource	You
Configure MongoDB replica set with a user that has necessary permissions to query search	You	You
Create MongoDB Search and Vector Search indexes	You	You
Expose search pods externally for connecting from each `mongod` node	Not necessary	You
Expose mongod pods externally for connecting from `mongot` nodes	Not necessary	You

The following diagram shows the deployment architecture of a single MongoDB Search and Vector Search instance with a MongoDB Enterprise replica set in a Kubernetes cluster.

Diagram showing the deployment architecture of MongoDB Search and Vector Search with MongoDB Enterprise in a Kubernetes cluster.

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The following diagram shows the components that the Kubernetes Operator deploys in a Kubernetes cluster for MongoDB Search and Vector Search with a MongoDB Enterprise Edition replica set.

Diagram showing the components included in the MongoDB Enterprise replica set with MongoDB Search and Vector Search deployment using the operator.

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When both the mongot and mongod processes are deployed inside the Kubernetes cluster, the Kubernetes Operator performs configuration for both processes automatically. Specifically, the Kubernetes Operator performs the following operations:

Finds the MongoDB CR referenced by MongoDBSearch using spec.source.mongodbResourceRef, or by a naming convention by looking for MongoDB CR with the same name as MongoDBSearch.
Generates mongot configuration in a YAML file and saves it to a config map named <MongoDBSearch.metadata.name>-search-config.

The Config map is mounted by the search pods and the YAML configuration is used by mongot's process on startup. The generated YAML contains all the information about how to connect to the replica set, TLS settings, and so on.
Deploys MongoDB Search and Vector Search stateful set named <MongoDBSearch.metadata.name>-search with storage and resource requirements configured according to the spec.persistence and spec.resourceRequirements settings in the CR.
Updates configuration of every mongod process by adding the necessary setParameter options, including the hostnames and port numbers of the mongot hosts. necessary setParameter options, including the hostnames and port numbers of the MongoDB replica set members.
For MongoDB version prior to v8.2, creates the searchCoordinator custom role with all the necessary permissions that the mongot process requires. Starting in MongoDB 8.2, the searchCoordinator is a built-in role.

You must perform the following actions:

Create a user in the replica set using a MongoDBUser custom resource. The mongot uses the credentials of this user to connect to the replica set to source the data:
- The user name is arbitrary (in the examples, we use search-sync-source-user), but it must have the searchCoordinator role set.
- The username and password of this user is passed in MongoDBSearch.spec.source.username and MongoDBSearch.spec.source.passwordSecretRef respectively.
  
  The password secret can refer to the same secret containing user password that was used to create MongoDBUser spec (in MongoDBUser.spec.source.passwordSecretKeyRef).
Configure and apply the MongoDBSearch custom resource.

To learn more about the CR settings for the mongot process, see MongoDB Search and Vector Search Settings.

The following diagram shows the deployment architecture of MongoDB Search and Vector Search in a Kubernetes cluster using an external MongoDB Enterprise Edition replica set.

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The following diagram shows the components that the Kubernetes Operator deploys in a Kubernetes cluster for MongoDB Search and Vector Search.

Diagram showing the components included in the deployment of MongoDB Enterprise Replica Set with MongoDB Search using the operator.

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In order to leverage MongoDB Search and Vector Search when you have your MongoDB deployment outside of Kubernetes, you deploy mongot using the Kubernetes Operator and you must perform some steps manually. The Kubernetes Operator handles configuration of the search pods. However, when the MongoDB replica set is outside of Kubernetes, you must reconfigure your MongoDB nodes and the networking.

You are responsible for the following manual configurations:

External MongoDB Configuration

Configure the following parameter using setParameter on every mongod process in your external replica set. When configuring, replace <search-service-hostname>:27027 with the actual resolvable hostname and port of your MongoDBSearch service.

setParameter:
  mongotHost: "<search-service-hostname>:27027"
  searchIndexManagementHostAndPort: "<search-service-hostname>:27027"
  skipAuthenticationToSearchIndexManagementServer: false
  searchTLSMode: "disabled"  # or "requireTLS" for TLS deployments

(Only for MongoDB version lesser than (<) 8.2) Create the searchCoordinator custom role with all the necessary permissions.

From MongoDB 8.2+, searchCoordinator is a built-in role and so, you can skip this step.
Create a user in the external replica set for the search synchronization process. This user must have the searchCoordinator role.
- userName: "search-sync-source" password: "<your-search-sync-password>" database: "admin" roles: - role: "searchCoordinator" db: "admin"

Kubernetes Configuration

Configure and apply the MongoDBSearch CR with spec.source.external pointing to your external MongoDB hosts.
Create a Kubernetes secret for the search synchronization user's password.
apiVersion: v1 kind: Secret metadata: name: search-sync-source-password stringData: password: "your-search-sync-password"
Create a keyfile secret containing the same keys specified in the keyfile used by your external MongoDB replica set.
Configure networking and DNS to ensure bi-directional connectivity between your external MongoDB and the search pods. Your external MongoDB environment must be able to resolve your search service hostname (<search-service-hostname>).

To learn more about the CR settings for the mongot process to connect to an external mongod process, see MongoDB Search and Vector Search Settings.

Security

The following image illustrates the security configuration for the mongot process. If the MongoDB server is inside of the Kubernetes cluster, the Kubernetes Operator automatically sets up keyfile authentication for MongoDB Search and Vector Search. If the MongoDB server is external, you must create a Kubernetes Secret containing the replica set's keyfile credential and reference it in the MongoDBSearch CR.

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Authentication

When connecting to mongod, mongot authenticates itself as a database user. When deploying MongoDB Search and Vector Search, you must create the database user. You must pass the user credentials stored in a Kubernetes Secret to mongot by populating the spec.source.username and spec.source.passwordSecretRef fields in the MongoDBSearch CR.

When accepting a connection from mongod, the mongot authenticates the remote request using internal authentication with keyfiles, similar to the MongoDB replica set member internal authentication. When configured to index a MongoDB resource on the same Kubernetes cluster, the Kubernetes Operator automatically sets up keyfile authentication for MongoDBSearch. If the MongoDB replica set is deployed outside Kubernetes, you must create a Kubernetes Secret containing the replica set's keyfile credential and reference it in the MongoDBSearch.spec.source.external.keyfileSecretRef field.

Transport Layer Security

MongoDBSearch can protect data and credentials in transit using TLS. For index management commands and search queries, specify (even an empty object, {}) spec.security.tls field and provide a TLS certificate in a Kubernetes Secret in the spec.security.tls.certificateKeySecretRef field. This TLS certificate must be issued and signed by the same CA that issued the CA certificate that the MongoDB replica set uses.

When both MongoDBSearch and MongoDB are deployed by the Kubernetes Operator, the underlying mongot and mongod configuration is largely handled by the Kubernetes Operator itself. When the MongoDB replica set is deployed outside of Kubernetes, the .spec.source.external.tls field must be populated with a Kubernetes Secret containing the same CA certificate mongod is configured with, and mongod configuration itself must have the searchTLSMode parameter set to requireTLS.

Deploy MongoDB Search and Vector Search

MongoDB Search and Vector Search Deployment

Pre-Requisites

Configuration Tasks

Both mongod and mongot Deployed in KubernetesArchitecture of mongod and mongot processes running in a Kubernetes cluster.

mongot Deployed in Kubernetes with mongod Running Outside KubernetesArchitecture of mongot processes deployed in a Kubernetes cluster to use mongod processes running outside the Kubernetes cluster.

Security

Authentication

Transport Layer Security