aws-cdk.aws-neptune-alpha 2.239.0a0
The CDK Construct Library for AWS::Neptune
License: Apache-2.0
Requires Python: ~=3.9

# Amazon Neptune Construct Library

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![cdk-constructs: Experimental](https://img.shields.io/badge/cdk--constructs-experimental-important.svg?style=for-the-badge)

> The APIs of higher level constructs in this module are experimental and under active development.
> They are subject to non-backward compatible changes or removal in any future version. These are
> not subject to the [Semantic Versioning](https://semver.org/) model and breaking changes will be
> announced in the release notes. This means that while you may use them, you may need to update
> your source code when upgrading to a newer version of this package.

---
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Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Neptune is a purpose-built, high-performance graph database engine. This engine is optimized for storing billions of relationships and querying the graph with milliseconds latency. Neptune supports the popular graph query languages Apache TinkerPop Gremlin and W3C’s SPARQL, enabling you to build queries that efficiently navigate highly connected datasets.

The `@aws-cdk/aws-neptune-alpha` package contains primitives for setting up Neptune database clusters and instances.

```python
import aws_cdk.aws_neptune_alpha as neptune
```

## Starting a Neptune Database

To set up a Neptune database, define a `DatabaseCluster`. You must always launch a database in a VPC.

```python
cluster = neptune.DatabaseCluster(self, "Database",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE
)
```

By default only writer instance is provisioned with this construct.

## Connecting

To control who can access the cluster, use the `.connections` attribute. Neptune databases have a default port, so
you don't need to specify the port:

```python
cluster.connections.allow_default_port_from_any_ipv4("Open to the world")
```

The endpoints to access your database cluster will be available as the `.clusterEndpoint` and `.clusterReadEndpoint`
attributes:

```python
write_address = cluster.cluster_endpoint.socket_address
```

## IAM Authentication

You can also authenticate to a database cluster using AWS Identity and Access Management (IAM) database authentication;
See [https://docs.aws.amazon.com/neptune/latest/userguide/iam-auth.html](https://docs.aws.amazon.com/neptune/latest/userguide/iam-auth.html) for more information and a list of supported
versions and limitations.

The following example shows enabling IAM authentication for a database cluster and granting connection access to an IAM role.

```python
cluster = neptune.DatabaseCluster(self, "Cluster",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE,
    iam_authentication=True
)
role = iam.Role(self, "DBRole", assumed_by=iam.AccountPrincipal(self.account))
# Use one of the following statements to grant the role the necessary permissions
cluster.grant_connect(role) # Grant the role neptune-db:* access to the DB
cluster.grant(role, "neptune-db:ReadDataViaQuery", "neptune-db:WriteDataViaQuery")
```

## Customizing parameters

Neptune allows configuring database behavior by supplying custom parameter groups.  For more details, refer to the
following link: [https://docs.aws.amazon.com/neptune/latest/userguide/parameters.html](https://docs.aws.amazon.com/neptune/latest/userguide/parameters.html)

```python
cluster_params = neptune.ClusterParameterGroup(self, "ClusterParams",
    description="Cluster parameter group",
    parameters={
        "neptune_enable_audit_log": "1"
    }
)

db_params = neptune.ParameterGroup(self, "DbParams",
    description="Db parameter group",
    parameters={
        "neptune_query_timeout": "120000"
    }
)

cluster = neptune.DatabaseCluster(self, "Database",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE,
    cluster_parameter_group=cluster_params,
    parameter_group=db_params
)
```

Note: To use the Neptune engine versions `1.2.0.0` or later, including the newly added `1.4` series, it's necessary to specify the appropriate `engineVersion` prop in `neptune.DatabaseCluster`. Additionally, for both 1.2,  1.3 and 1.4 series, the corresponding `family` prop must be set to `ParameterGroupFamily.NEPTUNE_1_2`, `ParameterGroupFamily.NEPTUNE_1_3` or `ParameterGroupFamily.NEPTUNE_1_4` respectively in `neptune.ClusterParameterGroup` and `neptune.ParameterGroup`.

## Adding replicas

`DatabaseCluster` allows launching replicas along with the writer instance. This can be specified using the `instanceCount`
attribute.

```python
cluster = neptune.DatabaseCluster(self, "Database",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE,
    instances=2
)
```

Additionally, it is also possible to add replicas using `DatabaseInstance` for an existing cluster.

```python
replica1 = neptune.DatabaseInstance(self, "Instance",
    cluster=cluster,
    instance_type=neptune.InstanceType.R5_LARGE
)
```

## Automatic minor version upgrades

By setting `autoMinorVersionUpgrade` to true, Neptune will automatically update
the engine of the entire cluster to the latest minor version after a stabilization
window of 2 to 3 weeks.

```python
neptune.DatabaseCluster(self, "Cluster",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE,
    auto_minor_version_upgrade=True
)
```

You can also specify `autoMinorVersionUpgrade` to a database instance.
Even within the same cluster, you can modify the `autoMinorVersionUpgrade` setting on a per-instance basis.

```python
neptune.DatabaseInstance(self, "Instance",
    cluster=cluster,
    instance_type=neptune.InstanceType.R5_LARGE,
    auto_minor_version_upgrade=True
)
```

## Port

By default, Neptune uses port `8182`. You can override the default port by specifying the `port` property:

```python
cluster = neptune.DatabaseCluster(self, "Database",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE,
    port=12345
)
```

## Logging

Neptune supports various methods for monitoring performance and usage. One of those methods is logging

1. Neptune provides logs e.g. audit logs which can be viewed or downloaded via the AWS Console. Audit logs can be enabled using the `neptune_enable_audit_log` parameter in `ClusterParameterGroup` or `ParameterGroup`
2. Neptune provides the ability to export those logs to CloudWatch Logs

```python
# Cluster parameter group with the neptune_enable_audit_log param set to 1
cluster_parameter_group = neptune.ClusterParameterGroup(self, "ClusterParams",
    description="Cluster parameter group",
    parameters={
        "neptune_enable_audit_log": "1"
    }
)

cluster = neptune.DatabaseCluster(self, "Database",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE,
    # Audit logs are enabled via the clusterParameterGroup
    cluster_parameter_group=cluster_parameter_group,
    # Optionally configuring audit logs to be exported to CloudWatch Logs
    cloudwatch_logs_exports=[neptune.LogType.AUDIT],
    # Optionally set a retention period on exported CloudWatch Logs
    cloudwatch_logs_retention=logs.RetentionDays.ONE_MONTH
)
```

For more information on monitoring, refer to https://docs.aws.amazon.com/neptune/latest/userguide/monitoring.html.
For more information on audit logs, refer to https://docs.aws.amazon.com/neptune/latest/userguide/auditing.html.
For more information on exporting logs to CloudWatch Logs, refer to https://docs.aws.amazon.com/neptune/latest/userguide/cloudwatch-logs.html.

## Metrics

Both `DatabaseCluster` and `DatabaseInstance` provide a `metric()` method to help with cluster-level and instance-level monitoring.

```python
# cluster: neptune.DatabaseCluster
# instance: neptune.DatabaseInstance


cluster.metric("SparqlRequestsPerSec") # cluster-level SparqlErrors metric
instance.metric("SparqlRequestsPerSec")
```

For more details on the available metrics, refer to https://docs.aws.amazon.com/neptune/latest/userguide/cw-metrics.html

## Copy tags to snapshot

By setting `copyTagsToSnapshot` to true, all tags of the cluster are copied to the snapshots when they are created.

```python
cluster = neptune.DatabaseCluster(self, "Database",
    vpc=vpc,
    instance_type=neptune.InstanceType.R5_LARGE,
    copy_tags_to_snapshot=True
)
```

## Neptune Serverless

You can configure a Neptune Serverless cluster using the dedicated instance type along with the
`serverlessScalingConfiguration` property.

> Visit [Using Amazon Neptune Serverless](https://docs.aws.amazon.com/neptune/latest/userguide/neptune-serverless-using.html) for more details.

```python
cluster = neptune.DatabaseCluster(self, "ServerlessDatabase",
    vpc=vpc,
    instance_type=neptune.InstanceType.SERVERLESS,
    serverless_scaling_configuration=neptune.ServerlessScalingConfiguration(
        min_capacity=1,
        max_capacity=5
    )
)
```