diff --git a/use-timescale/page-index/page-index.js b/use-timescale/page-index/page-index.js
index 56dd340835..9dadc204e3 100644
--- a/use-timescale/page-index/page-index.js
+++ b/use-timescale/page-index/page-index.js
@@ -753,6 +753,11 @@ module.exports = [
         href: "limitations",
         excerpt: "Current limitations of TigerData product features",
       },
+      {
+        title: "Integrate data lakes with Tiger Cloud",
+        href: "tigerlake",
+        excerpt: "Unifies the Tiger Cloud operational architecture with the data lake (S3 + Iceberg) architectures",
+      },
       {
         title: "Troubleshoot TigerData products",
         href: "troubleshoot-timescaledb",
diff --git a/use-timescale/tigerlake.md b/use-timescale/tigerlake.md
new file mode 100644
index 0000000000..8e7096fabb
--- /dev/null
+++ b/use-timescale/tigerlake.md
@@ -0,0 +1,257 @@
+---
+title: Integrate data lakes with Tiger Cloud
+excerpt: Unifies the Tiger Cloud operational architecture with data lake architectures. This enables real-time application building alongside efficient data pipeline management within a single system.
+products: [cloud]
+price_plans: [scale, enterprise]
+keywords: [data lake, lakehouse, s3, iceberg]
+---
+
+import IntegrationPrereqsCloud from "versionContent/_partials/_integration-prereqs-cloud-only.mdx";
+
+# Integrate data lakes with $CLOUD_LONG
+
+$LAKE_LONG unifies the $CLOUD_LONG operational architecture with data lake architectures. $LAKE_LONG enables you to build 
+real-time applications alongside efficient data pipeline management within a single system.
+
+This experimental release is a native integration enabling continuous replication between managed Iceberg and catalog 
+running in AWS [S3 Tables][s3-tables] in your AWS account and relational tables and $HYPERTABLEs in $CLOUD_LONG. 
+
+## Prerequisites
+
+<IntegrationPrereqsCloud/>
+
+## Integrate a data lake with your $SERVICE_LONG
+
+To connect a $SERVICE_LONG to the AWS S3 Tables that make up your data lake, you need the following:
+
+- The ARN of the data lake table bucket
+- The ARN of a role with permissions to write to the table bucket
+
+You set up the data lake table bucket and role ARNs, using one of the following methods:
+
+<Tabs label="Install TimescaleDB">
+
+<Tab title="AWS Management Console">
+
+<Procedure >
+
+1. **Set the AWS Region to host your table bucket**
+   1. In [AWS CloudFormation][cmc], select the current AWS Region at the top-right of the page.
+   2. Set it to the Region to create your table bucket in. 
+
+   **This must match the region your $SERVICE_LONG is running in**: if the regions do not match AWS charges you for 
+   cross-region data transfer.
+
+1. **Create your CloudFormation stack**
+   1. Click `Create stack`, then select `With new resources (standard)`.
+   1. In `Amazon S3 URL`, paste the following URL, then click `Next`.
+   
+      ```http request
+      https://tigerlake.s3.us-east-1.amazonaws.com/tigerlake-connect-cloudformation.yaml
+      ```
+   
+   1. In `Specify stack details`, enter the following details, then click `Next`:
+      * `Stack Name`: a name for this CloudFormation stack
+      * `BucketName`: a name for this S3 table bucket
+      * `ProjectID` and `ServiceID`: enter the [connection details][get-project-id] for your $LAKE_LONG $SERVICE_SHORT.
+   1. In `Configure stack options` check `I acknowledge that AWS CloudFormation might create IAM resources`, then 
+      click `Next`.
+   1. In `Review and create`, click `Submit`. and wait for the deployment to complete. 
+       AWS deploys your stack and creates the S3 table bucket and IAM role.
+   1. Click `Outputs`, then copy all four outputs.
+
+  Provide $COMPANY with the ARN of this role, the ARN of the S3 table bucket.
+  $COMPANY uses the outputs to spin up your $LAKE_LONG services, then let you know when the $SERVICE_SHORT is 
+  ready to use. Provisioning takes a couple of minutes, during this time the $SERVICE_SHORT is restarted.
+
+</Procedure>
+
+</Tab>
+
+<Tab title="AWS CloudFormation CLI">
+
+<Procedure >
+
+1. **Create your CloudFormation stack** 
+   Replace the following values in the command, then run it from the terminal:
+   
+      * `StackName`: the name for this CloudFormation stack
+      * `BucketName`: The name of the S3 table bucket to crate
+      * `ProjectID`: enter your $SERVICE_LONG [connection details][get-project-id] 
+      * `ServiceID`: enter your $SERVICE_LONG [connection details][get-project-id]
+   
+   ```shell
+   aws cloudformation create-stack \
+     --capabilities <CapabilityIAM> \
+     --template-url https://tigerlake.s3.us-east-1.amazonaws.com/tigerlake-connect-cloudformation.yaml \
+     --stack-name <StackName> \
+     --parameters \
+       ParameterKey=BucketName,ParameterValue="<BucketName>" \
+       ParameterKey=ProjectID,ParameterValue="<ProjectID>" \
+       ParameterKey=ServiceID,ParameterValue="<ServiceID>"
+   ```
+
+  Provide $COMPANY with the ARN of this role, the ARN of the S3 table bucket.
+  $COMPANY uses the outputs to spin up your $LAKE_LONG services, then let you know when the $SERVICE_SHORT is 
+  ready to use. Provisioning takes a couple of minutes, during this time the $SERVICE_SHORT is restarted.
+
+</Procedure>
+
+</Tab>
+
+<Tab title="Manual configuration">
+
+<Procedure >
+
+1. **Create a S3 Bucket** 
+
+   1. Set the AWS Region to host your table bucket
+      1. In [Amazon S3 console][s3-console], select the current AWS Region at the top-right of the page.
+      2. Set it to the Region to create your table bucket in.
+
+      **This must match the region your $SERVICE_LONG is running in**: if the regions do not match AWS charges you for
+      cross-region data transfer.
+   1. In the left navigation pane, click `Table buckets`, then click `Create table bucket`.
+   1. Enter `Table bucket name`, then click `Create table bucket`. 
+   1. Copy the `Amazon Resource Name (ARN)` for your table bucket.
+
+1. **Create an ARN role**
+   1. In [IAM Dashboard][iam-dashboard], click `Roles` then click `Create role`
+   1. In `Select trusted entity`, click `Custom trust policy`, replace the **Custom trust policy** code block with the 
+      following: 
+   
+      ```json
+      {
+          "Version": "2012-10-17",
+          "Statement": [
+              {
+                  "Effect": "Allow",
+                  "Principal": {
+                      "AWS": "arn:aws:iam::142548018081:root"
+                  },
+                  "Action": "sts:AssumeRole",
+                  "Condition": {
+                      "StringEquals": {
+                          "sts:ExternalId": "<ProjectID>/<ServiceID>"
+                      }
+                  }
+              }
+          ]
+      }
+      ```
+      
+      `"Principal": { "AWS": "arn:aws:iam::123456789012:root" }` does not mean `root` access. This delegates 
+        permissions to the entire AWS account, not just the root user.
+
+   1. Replace `<ProjectID>` and `<ServiceID>` with the the [connection details][get-project-id] for your $LAKE_LONG 
+         $SERVICE_SHORT, then click `Next`.  
+
+   1. In `Permissions policies`. click `Next`.
+   1. In `Role details`, enter `Role name`, then click `Create role`.
+   1. In `Roles`, select the role you just created, then click `Add Permissions` > `Create inline policy`.
+   1. Select `JSON` then replace the `Policy editor` code block with the following:
+   
+         ```json
+         {
+           "Version": "2012-10-17",
+           "Statement": [
+             {
+               "Sid": "BucketOps",
+               "Effect": "Allow",
+               "Action": [
+                 "s3tables:*"
+               ],
+               "Resource": "<S3TABLE_BUCKET_ARN>"
+             },
+             {
+               "Sid": "BucketTableOps",
+               "Effect": "Allow",
+               "Action": [
+                 "s3tables:*"
+               ],
+               "Resource": "<S3TABLE_BUCKET_ARN>/table/*"
+             }
+           ]
+         }
+         ```
+   1. Replace `<S3TABLE_BUCKET_ARN>` with the `Amazon Resource Name (ARN)` for the table bucket you just created.
+   1. Click `Next`, then give the inline policy a name and click `Create policy`.
+
+   Provide $COMPANY with the ARN of this role, the ARN of the S3 table bucket.
+  $COMPANY uses the outputs to spin up your $LAKE_LONG services, then let you know when the $SERVICE_SHORT is 
+  ready to use. Provisioning takes a couple of minutes, during this time the $SERVICE_SHORT is restarted.
+
+</Procedure>
+
+</Tab>
+
+</Tabs>
+
+## Stream data from your $SERVICE_LONG to your data lake
+
+To stream data from a $PG relational table, or a $HYPERTABLE in your $SERVICE_LONG to your data lake, run the following 
+statement:
+
+```sql
+ALTER TABLE <table_name> SET (
+   tigerlake.iceberg_sync = true | false,
+   tigerlake.iceberg_partitionby = '<partition_specification>'
+)
+```
+
+* `tigerlake.iceberg_sync`: `boolean`, set to `true` to start streaming, or `false` to stop the stream. A stream 
+  **cannot** resume after being stopped. 
+* `tigerlake.iceberg_partitionby`: optional property to define a partition specification in Iceberg. By default the 
+  partitioning specification of the $HYPERTABLE is used. Streamed $PG tables can have a partition specification 
+  for the Iceberg table, if intentially defined. Please refer to [partitioning](#partitioning) for more details.
+
+Only tables or $HYPERTABLEs with primary keys are supported, this includes composite primary keys as well. 
+A primary key is necessary for Iceberg to perform update or delete statements.
+
+When a stream is started, the full table is synchronized to Iceberg, this means that all prior records are imported first.
+The write throughput is ranging at approximately 40.000 records / second, for larger tables a full import can take some time.
+
+### Partitioning
+
+By default, the partition interval for an Iceberg table is the same as the one from a $HYPERTABLE.
+The sync of a Postgres table does not enable any partitioning in Iceberg, but can be set through the [API](#api) with `tigerlake.iceberg_partitionby`.
+
+The following partition intervals and specifications are supported, and the define behavior of [Iceberg partition specification][iceberg-partition-spec].
+
+| Interval      | Description | Source types | Result type |
+| ------------- | --- | --- | --- |
+| `hour`        | Extract a date or timestamp day, as days from 1970-01-01 | `date`, `timestamp`, `timestamptz` | `int` |
+| `day`         | Extract a date or timestamp day, as days from 1970-01-01 | `date`, `timestamp`, `timestamptz` | `int` |
+| `month`       | Extract a date or timestamp day, as days from 1970-01-01 | `date`, `timestamp`, `timestamptz` | `int` |
+| `year`        | Extract a date or timestamp day, as days from 1970-01-01 | `date`, `timestamp`, `timestamptz` | `int` |
+| `truncate[W]` | Value truncated to width W, see [options][iceberg-truncate-options] | `int`, `long`, `decimal`, `string`, `binary` | `int` |
+
+## Limitations
+
+* Only Postgres 17 is supported.
+* Only the S3 Tables REST Iceberg catalog is supported.
+* Certain columnstore optimizations must be disabled in $HYPERTABLEs in order to collect correlating WAL events.
+* The `TRUNCATE` statement is not supported, and will not truncate data in the corresponding Iceberg table.
+* The [tiered data](/use-timescale/latest/data-tiering/) of a $HYPERTABLE will not be synched.
+* Renaming a table in Postgres is not reflected in Iceberg table and can lead sync issues.
+
+## Replicas
+
+**TODO**
+What happens on fail over?
+
+
+[cmc]: https://console.aws.amazon.com/cloudformation/
+[aws-athena]: https://aws.amazon.com/athena/
+[duckdb]: https://duckdb.org/docs/stable/extensions/iceberg/amazon_s3_tables
+[apache-spark]: https://spark.apache.org/
+[s3-tables]: https://aws.amazon.com/s3/features/tables/
+[aws-console]: https://console.aws.amazon.com/
+[s3-console]: https://console.aws.amazon.com/s3/
+[iam-dashboard]: https://console.aws.amazon.com/iamv2/home
+[iceberg-partition-spec]: https://iceberg.apache.org/spec/#partition-transforms
+[iceberg-truncate-options]: https://iceberg.apache.org/spec/#truncate-transform-details
+[get-project-id]: /integrations/:currentVersion:/find-connection-details/#find-your-project-and-service-id
+[setup-console]: /use-timescale/:currentVersion:/tigerlake/#setup-tiger-lake-using-aws-management-console
+[setup-cli]: /use-timescale/:currentVersion:/tigerlake/#setup-tiger-lake-using-the-aws-cloudformation-cli
+[setup-manual]: /use-timescale/:currentVersion:/tigerlake/#setup-tiger-lake-manually