Update automating_json_log_loading_with_vector.md

Author: soyeric128

docs/en/tutorials/load/automating_json_log_loading_with_vector.md

@@ -8,6 +8,92 @@ In this tutorial, we'll simulate generating logs locally, collect them using [Ve
 
 Before you start, ensure you have the following prerequisites in place:
 
-- **Amazon S3 Bucket**: An S3 bucket where logs collected by Vector will be stored. [Learn how to create an S3 bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/create-bucket-overview.html). In this tutorial, we use `s3://databend-doc/` as the location for staging the collected logs.
-- **AWS Credentials**: AWS Access Key ID and Secret Access Key with sufficient permissions for accessing the S3 bucket. [Manage your AWS credentials](https://docs.aws.amazon.com/general/latest/gr/aws-sec-cred-types.html#access-keys-and-secret-access-keys).
-- **Docker**: Ensure that [Docker](https://www.docker.com/) is installed on your local machine, as it will be used to set up Vector.
+- **Amazon S3 Bucket**: An S3 bucket where logs collected by Vector will be stored. [Learn how to create an S3 bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/create-bucket-overview.html).
+- **AWS Credentials**: AWS Access Key ID and Secret Access Key with sufficient permissions for accessing your S3 bucket. [Manage your AWS credentials](https://docs.aws.amazon.com/general/latest/gr/aws-sec-cred-types.html#access-keys-and-secret-access-keys).
+- **AWS CLI**: Ensure that the [AWS CLI](https://aws.amazon.com/cli/) is installed and configured with the necessary permissions to access your S3 bucket.
+- **Docker**: Ensure that [Docker](https://www.docker.com/) is installed on your local machine, as it will be used to set up Vector.
+
+## Step 1: Create Target Folder in S3 Bucket
+
+To store the logs collected by Vector, create a folder named logs in your S3 bucket. In this tutorial, we use `s3://databend-doc/logs/` as the target location. 
+
+This command creates an empty folder named `logs` in the `databend-doc` bucket:
+
+```bash
+aws s3api put-object --bucket databend-doc --key logs/
+```
+
+## Step 2: Create Local Log File
+
+Simulate log generation by creating a local log file. In this tutorial, we use `/Users/eric/Documents/logs/app.log` as the file path.
+
+Add the following JSON lines to the file to represent sample log events:
+
+```json title='app.log'
+{"user_id": 1, "event": "login", "timestamp": "2024-12-08T10:00:00Z"}
+{"user_id": 2, "event": "purchase", "timestamp": "2024-12-08T10:05:00Z"}
+```
+
+## Step 3: Configure & Run Vector
+
+1. Create a Vector configuration file named `vector.yaml` on your local machine. In this tutorial, we create it at `/Users/eric/Documents/vector.yaml` with the following content:
+
+```yaml title='vector.yaml'
+sources:
+  logs:
+    type: file
+    include:
+      - "/logs/app.log"
+    read_from: beginning
+
+transforms:
+  extract_message:
+    type: remap
+    inputs:
+      - "logs"
+    source: |
+      . = parse_json(.message) ?? {}
+
+sinks:
+  s3:
+    type: aws_s3
+    inputs:
+      - "extract_message"
+    bucket: databend-doc
+    region: us-east-2
+    key_prefix: "logs/" 
+    content_type: "text/plain" 
+    encoding:
+      codec: "native_json" 
+    auth:
+      access_key_id: "<your-access-key-id>"
+      secret_access_key: "<your-secret-access-key>"
+```
+
+2. Start Vector using Docker, mapping the configuration file and local logs directory:
+
+```bash
+docker run \
+  -d \
+  -v /Users/eric/Documents/vector.yaml:/etc/vector/vector.yaml:ro \
+  -v /Users/eric/Documents/logs:/logs \
+  -p 8686:8686 \
+  --name vector \
+  timberio/vector:nightly-alpine
+```
+
+3. Wait for a moment, then check if any logs have been synced to the `logs` folder on S3:
+
+```bash
+aws s3 ls s3://databend-doc/logs/
+```
+
+If the log file has been successfully synced to S3, you should see output similar to this:
+
+```bash
+
+```
+
+
+
+