AWS Aurora

Scanner supports AWS Aurora logs, which is log data related to serverless databases in AWS. In order for Scanner to see them, you can publish these logs to CloudWatch, forward to Kinesis Data Firehose, and then write them into an S3 bucket that Scanner is linked to.

Step 1: Configure Aurora to publish logs to CloudWatch

Follow the AWS documentation to configure your Aurora database to export some or all of its log types to CloudWatch. This will create one or more new CloudWatch log groups. See: .

Step 2: Set up CloudWatch to push to Kinesis Data Firehose

You can follow the AWS documentation to configure your new CloudWatch log groups to push their logs to a Kinesis Data Firehose. See: .

Step 3: Configure the Kinesis Data Firehose to write logs to S3

A Kinesis Data Firehose can push logs to various destinations. We want to push to an S3 bucket that Scanner is linked to. You can follow the AWS documentation to configure the Firehose to write to an S3 bucket. See: .

Step 4: Link the S3 bucket to Scanner

If you haven't done so already, link the S3 bucket containing your Aurora logs to Scanner using the Linking AWS Accounts guide.

Step 5: Set up an S3 Import Rule in Scanner

Within Scanner, navigate to Settings > S3 Import Rules.
Click Create Rule.
For Rule name, type a name like my_team_name_aws_aurora_logs.
For Destination Index, choose the index where you want these logs to be searchable in Scanner.
For Status, set to Active if you want to start indexing the data immediately.
For Source Type, we recommend aws:aurora, but you are free to choose any name. However, out-of-the-box detection rules will expect aws:aurora.
For AWS Account, choose the account that contains the S3 bucket containing Aurora logs.
For S3 Bucket, choose the S3 bucket containing Aurora logs.
For S3 Key Prefix, type the prefix (i.e. directory path) of the S3 objects that your Firehose is writing.
For File type, choose CloudWatchLogStream with Gzip compression.
For Timestamp extractors, under Column name, type timestamp. This is the field in each log event that contains the timestamp information.
Click Preview rule to try it out. Check that the S3 keys you expect are appearing, and check that the log events inside are being parsed properly with the timestamp detected properly.
When you're ready, click Create.

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Step 5: Set up an S3 Import Rule in Scanner

Within Scanner, navigate to Settings > S3 Import Rules.

Click Create Rule.

For Rule name, type a name like my_team_name_aws_aurora_logs.

For Destination Index, choose the index where you want these logs to be searchable in Scanner.

For Status, set to Active if you want to start indexing the data immediately.

For Source Type, we recommend aws:aurora, but you are free to choose any name. However, out-of-the-box detection rules will expect aws:aurora.

For AWS Account, choose the account that contains the S3 bucket containing Aurora logs.

For S3 Bucket, choose the S3 bucket containing Aurora logs.

For S3 Key Prefix, type the prefix (i.e. directory path) of the S3 objects that your Firehose is writing.

For File type, choose CloudWatchLogStream with Gzip compression.

For Timestamp extractors, under Column name, type timestamp. This is the field in each log event that contains the timestamp information.

Click Preview rule to try it out. Check that the S3 keys you expect are appearing, and check that the log events inside are being parsed properly with the timestamp detected properly.

When you're ready, click Create.