Database audit logging
Amazon Redshift logs information about connections and user activities in your database. These logs help you to monitor the database for security and troubleshooting purposes, a process called database auditing. The logs are stored in Amazon S3 buckets. These provide convenient access with data-security features for users who are responsible for monitoring activities in the database.
Topics
- Amazon Redshift logs
- Enabling logging
- Managing log files
- Troubleshooting Amazon Redshift audit logging
- Logging Amazon Redshift API calls with AWS CloudTrail
- Amazon Redshift account IDs in AWS CloudTrail logs
- Configuring auditing using the console
- Configuring logging by using the AWS CLI and Amazon Redshift API
Amazon Redshift logs
Amazon Redshift logs information in the following log files:
-
Connection log – Logs authentication attempts, connections, and disconnections.
-
User log – Logs information about changes to database user definitions.
-
User activity log – Logs each query before it's run on the database.
The connection and user logs are useful primarily for security purposes. You can use the connection log to monitor information about users connecting to the database and related connection information. This information might be their IP address, when they made the request, what type of authentication they used, and so on. You can use the user log to monitor changes to the definitions of database users.
The user activity log is useful primarily for troubleshooting purposes. It tracks information about the types of queries that both the users and the system perform in the database.
The connection log and user log both correspond to information that is stored in the system tables in your database. You can use the system tables to obtain the same information, but the log files provide an easier mechanism for retrieval and review. The log files rely on Amazon S3 permissions rather than database permissions to perform queries against the tables. Additionally, by viewing the information in log files rather than querying the system tables, you reduce any impact of interacting with the database.
Log files are not as current as the base system log tables, STL_USERLOG and STL_CONNECTION_LOG. Records that are older than, but not including, the latest record are copied to log files.
Connection log
Logs authentication attempts, and connections and disconnections. The following table describes the information in the connection log. For more information about these fields, see STL_CONNECTION_LOG in the Amazon Redshift Database Developer Guide.
| Column name | Description |
|---|---|
| event | Connection or authentication event. |
| recordtime | Time the event occurred. |
| remotehost | Name or IP address of remote host. |
| remoteport | Port number for remote host. |
| pid | Process ID associated with the statement. |
| dbname | Database name. |
| username | User name. |
| authmethod | Authentication method. |
| duration | Duration of connection in microseconds. |
| sslversion | Secure Sockets Layer (SSL) version. |
| sslcipher | SSL cipher. |
| mtu | Maximum transmission unit (MTU). |
| sslcompression | SSL compression type. |
| sslexpansion | SSL expansion type. |
| iamauthguid | The AWS Identity and Access Management (IAM) authentication ID for the AWS CloudTrail request. |
| application_name | The initial or updated name of the application for a session. |
| driver_version | The version of ODBC or JDBC driver that connects to your Amazon Redshift cluster from your third-party SQL client tools. |
| os_version | The version of the operating system that is on the client machine that connects to your Amazon Redshift cluster. |
| plugin_name | The name of the plugin used to connect to your Amazon Redshift cluster. |
| protocol_version | The internal protocol version that the Amazon Redshift driver uses when establishing its connection with the server. |
| sessionid | The globally unique identifier for the current session. |
User log
Records details for the following changes to a database user:
-
Create user
-
Drop user
-
Alter user (rename)
-
Alter user (alter properties)
| Column name | Description |
|---|---|
| userid | ID of user affected by the change. |
| username | User name of the user affected by the change. |
| oldusername | For a rename action, the original user name. For any other action, this field is empty. |
| action | Action that occurred. Valid values:
|
| usecreatedb | If true (1), indicates that the user has create database privileges. |
| usesuper | If true (1), indicates that the user is a superuser. |
| usecatupd | If true (1), indicates that the user can update system catalogs. |
| valuntil | Password expiration date. |
| pid | Process ID. |
| xid | Transaction ID. |
| recordtime | Time in UTC that the query started. |
User activity log
Logs each query before it is run on the database.
| Column name | Description |
|---|---|
| recordtime | Time the event occurred. |
| db | Database name. |
| user | User name. |
| pid | Process ID associated with the statement. |
| userid | User ID. |
| xid | Transaction ID. |
| query | A prefix of LOG: followed by the text of the query, including newlines. |
Enabling logging
Audit logging is not turned on by default in Amazon Redshift. When you turn on logging on your cluster, Amazon Redshift creates and uploads logs to Amazon S3 that capture data from the time audit logging is enabled to the present time. Each logging update is a continuation of the information that was already logged.
Audit logging to Amazon S3 is an optional, manual process. When you enable logging on your cluster, you are enabling logging to Amazon S3 only. Logging to system tables is not optional and happens automatically for the cluster. For more information about logging to system tables, see System Tables Reference in the Amazon Redshift Database Developer Guide.
The connection log, user log, and user activity log are enabled together by using
the
AWS Management Console, the Amazon Redshift API Reference, or the AWS Command Line
Interface (AWS CLI). For the user activity
log, you must also enable the enable_user_activity_logging database
parameter. If you enable only the audit logging feature, but not the associated
parameter, the database audit logs log information for only the connection log and
user
log, but not for the user activity log. The enable_user_activity_logging
parameter is not enabled (false) by default. You can set it to
true to enable the user activity log. For more information, see Amazon Redshift parameter groups.
Currently, you can only use Amazon S3-managed keys (SSE-S3) encryption (AES-256) for audit logging.
Managing log files
The number and size of Amazon Redshift log files in Amazon S3 depends heavily on the activity in your cluster. If you have an active cluster that is generating a large number of logs, Amazon Redshift might generate the log files more frequently. You might have a series of log files for the same type of activity, such as having multiple connection logs within the same hour.
Because Amazon Redshift uses Amazon S3 to store logs, you incur charges for the storage
that
you use in Amazon S3. Before you configure logging, you should have a plan for how
long you
need to store the log files. As part of this, determine when the log files can either
be
deleted or archived based on your auditing needs. The plan that you create depends
heavily on the type of data that you store, such as data subject to compliance or
regulatory requirements. For more information about Amazon S3 pricing, go to Amazon Simple Storage Service (S3) Pricing
Bucket permissions for Amazon Redshift audit logging
When you turn on logging, Amazon Redshift collects logging information and uploads it to log files stored in Amazon S3. You can use an existing bucket or a new bucket. Amazon Redshift requires the following IAM permissions to the bucket:
-
s3:GetBucketAclThe service requires read permissions to the Amazon S3 bucket so it can identify the bucket owner. -
s3:PutObjectThe service requires put object permissions to upload the logs. Also, the IAM user or IAM role that enables logging must haves3:PutObjectpermission to the Amazon S3 bucket. Each time logs are uploaded, the service determines whether the current bucket owner matches the bucket owner at the time logging was enabled. If these owners don't match, you receive an error.
If, when you enable audit logging, you select the option to create a new bucket, correct
permissions are applied to it. However, if you create your own bucket in
Amazon S3, or use an existing bucket, make sure to add a bucket policy that includes
the
bucket name. Logs
are delivered using service-principal credentials. For most AWS Regions, you add
the Redshift service-principal name, redshift.amazonaws.com.
The bucket policy uses the following format. ServiceName and
BucketName
are placeholders for your own values.
Also specify the associated actions and resources in the bucket policy.
{ "Version": "2012-10-17", "Statement": [ { "Sid": "Put bucket policy needed for audit logging", "Effect": "Allow", "Principal": { "Service": "ServiceName" }, "Action": [ "s3:PutObject", "s3:GetBucketAcl" ], "Resource": [ "arn:aws:s3:::BucketName", "arn:aws:s3:::BucketName/*" ] } ] }
The following example is a bucket policy for the US East (N. Virginia) Region and
a bucket named
AuditLogs.
{ "Version": "2008-10-17", "Statement": [ { "Sid": "Put bucket policy needed for audit logging", "Effect": "Allow", "Principal": { "Service": "redshift.amazonaws.com" }, "Action": [ "s3:PutObject", "s3:GetBucketAcl" ], "Resource": [ "arn:aws:s3:::AuditLogs", "arn:aws:s3:::AuditLogs/*" ] } ] }
Regions that aren't enabled by default, also known as "opt-in" regions,
require a region-specific service principal name. For these, the service-principal
name includes the region, in the format
redshift..
For example, region.amazonaws.comredshift.ap-east-1.amazonaws.com for the
Asia Pacific (Hong Kong) Region. For a list of the regions that aren't enabled by
default,
see Managing AWS Regions in the
AWS General Reference.
The region-specific service-principal name corresponds with the region where the cluster is located.
Best practices for S3 bucket permissions
When you give a third party access to your Amazon S3 buckets, make sure to consider security best practices. You can provide optional information in the bucket policy to designate the bucket owner. This way, the account owner can permit the role to be assumed only under specific circumstances, and avoid the confused-deputy problem. For more information, see The confused deputy problem in the IAM User Guide.
We recommend that you configure your bucket policy in a way to specify access granted to a service principal specifically on behalf of the bucket owner's (or their partner's) resources. The following example illustrates how you can configure your bucket to grant Amazon Redshift permission to upload logs into the bucket, by specifying the SourceArn, while blocking any other account from uploading log files. You can use either the SourceArn or SourceAccount to specify access.
{ "Version": "2008-10-17", "Statement": [ { "Sid": "Put bucket policy needed for audit logging", "Effect": "Allow", "Principal": { "Service": "redshift.amazonaws.com" }, "Action": [ "s3:PutObject", "s3:GetBucketAcl" ], "Resource": [ "arn:aws:s3:::AuditLogs", "arn:aws:s3:::AuditLogs/*" ], "Condition": { "StringEquals": { "aws:SourceArn": "arn:aws:redshift:us-east-1:123456789012:cluster:my-cluster" } } } ] }
When Redshift uploads log files to Amazon S3, large files can be uploaded in parts. If a multipart upload isn't successful, it's possible for parts of a file to remain in the Amazon S3 bucket. This can result in additional storage costs, so it's important to understand what occurs when a multipart upload fails. For a detailed explanation about multipart upload for audit logs, see Uploading and copying objects using multipart upload and Aborting a multipart upload.
For more information about creating S3 buckets and adding bucket policies, see Creating a Bucket and Editing Bucket Permissions in the Amazon Simple Storage Service User Guide.
Bucket structure for Amazon Redshift audit logging
By default, Amazon Redshift organizes the log files in the Amazon S3 bucket by using
the
following bucket and object structure:
AWSLogs/
AccountID/ServiceName/Region/Year/Month/Day/AccountID_ServiceName_Region_ClusterName_LogType_Timestamp.gz
An example is:
AWSLogs/123456789012/redshift/us-east-1/2013/10/29/123456789012_redshift_us-east-1_mycluster_userlog_2013-10-29T18:01.gz
If you provide an Amazon S3 key prefix, put the prefix at the start of the key.
For example, if you specify a prefix of myprefix:
myprefix/AWSLogs/123456789012/redshift/us-east-1/2013/10/29/123456789012_redshift_us-east-1_mycluster_userlog_2013-10-29T18:01.gz
The Amazon S3 key prefix can't exceed 512 characters. It can't contain spaces ( ), double quotation marks (“), single quotation marks (‘), a backslash (\). There is also a number of special characters and control characters that aren't allowed. The hexadecimal codes for these characters are as follows:
-
x00 to x20
-
x22
-
x27
-
x5c
-
x7f or larger
Troubleshooting Amazon Redshift audit logging
Amazon Redshift audit logging can be interrupted for the following reasons:
-
Amazon Redshift does not have permission to upload logs to the Amazon S3 bucket. Verify that the bucket is configured with the correct IAM policy. For more information, see Bucket permissions for Amazon Redshift audit logging.
-
The bucket owner changed. When Amazon Redshift uploads logs, it verifies that the bucket owner is the same as when logging was enabled. If the bucket owner has changed, Amazon Redshift cannot upload logs until you configure another bucket to use for audit logging. For more information, see Modifying the bucket for audit logging.
-
The bucket cannot be found. If the bucket is deleted in Amazon S3, Amazon Redshift cannot upload logs. You either need to recreate the bucket or configure Amazon Redshift to upload logs to a different bucket. For more information, see Modifying the bucket for audit logging.
Logging Amazon Redshift API calls with AWS CloudTrail
Amazon Redshift is integrated with AWS CloudTrail, a service that provides a record of actions taken by a user, role, or an AWS service in Amazon Redshift. CloudTrail captures all API calls for Amazon Redshift as events. These include calls from the Amazon Redshift console and from code calls to the Amazon Redshift API operations. If you create a trail, you can enable continuous delivery of CloudTrail events to an Amazon S3 bucket, including events for Amazon Redshift. If you don't configure a trail, you can still view the most recent events in the CloudTrail console in Event history. Using the information collected by CloudTrail, you can determine certain details. These include the request that was made to Amazon Redshift, the IP address it was made from, who made it, when it was made, and other information.
You can use CloudTrail independently from or in addition to Amazon Redshift database audit logging.
To learn more about CloudTrail, see the AWS CloudTrail User Guide.
Amazon Redshift information in CloudTrail
CloudTrail is enabled on your AWS account when you create the account. When activity occurs in Amazon Redshift, that activity is recorded in a CloudTrail event along with other AWS service events in Event history. You can view, search, and download recent events in your AWS account. For more information, see Viewing Events with CloudTrail Event History.
For an ongoing record of events in your AWS account, including events for Amazon Redshift, create a trail. A trail enables CloudTrail to deliver log files to an Amazon S3 bucket. By default, when you create a trail in the console, the trail applies to all regions. The trail logs events from all regions in the AWS partition and delivers the log files to the Amazon S3 bucket that you specify. Additionally, you can configure other AWS services to further analyze and act upon the event data collected in CloudTrail logs. For more information, see:
All Amazon Redshift actions are logged by CloudTrail and are documented in the
Amazon Redshift API Reference. For example, calls to the
CreateCluster, DeleteCluster, and
DescribeCluster actions generate entries in the CloudTrail log
files.
Every event or log entry contains information about who generated the request. The identity information helps you determine the following:
-
Whether the request was made with root or IAM user credentials.
-
Whether the request was made with temporary security credentials for a role or federated user.
-
Whether the request was made by another AWS service.
For more information, see the CloudTrail userIdentity Element.
Understanding Amazon Redshift log file entries
A trail is a configuration that enables delivery of events as log files to an Amazon S3 bucket that you specify. CloudTrail log files contain one or more log entries. An event represents a single request from any source and includes information about the requested action, the date and time of the action, request parameters, and so on. CloudTrail log files are not an ordered stack trace of the public API calls, so they do not appear in any specific order.
The following example shows a CloudTrail log entry for a sample CreateCluster call.
{ "eventVersion": "1.04", "userIdentity": { "type": "IAMUser", "principalId": "AIDAMVNPBQA3EXAMPLE", "arn": "arn:aws:iam::123456789012:user/Admin", "accountId": "123456789012", "accessKeyId": "AKIAIOSFODNN7EXAMPLE", "userName": "Admin", "sessionContext": { "attributes": { "mfaAuthenticated": "false", "creationDate": "2017-03-03T16:51:56Z" } }, "invokedBy": "signin.amazonaws.com" }, "eventTime": "2017-03-03T16:56:09Z", "eventSource": "redshift.amazonaws.com", "eventName": "CreateCluster", "awsRegion": "us-east-2", "sourceIPAddress": "52.95.4.13", "userAgent": "signin.amazonaws.com", "requestParameters": { "clusterIdentifier": "my-dw-instance", "allowVersionUpgrade": true, "enhancedVpcRouting": false, "encrypted": false, "clusterVersion": "1.0", "masterUsername": "awsuser", "masterUserPassword": "****", "automatedSnapshotRetentionPeriod": 1, "port": 5439, "dBName": "mydbtest", "clusterType": "single-node", "nodeType": "dc1.large", "publiclyAccessible": true, "vpcSecurityGroupIds": [ "sg-95f606fc" ] }, "responseElements": { "nodeType": "dc1.large", "preferredMaintenanceWindow": "sat:05:30-sat:06:00", "clusterStatus": "creating", "vpcId": "vpc-84c22aed", "enhancedVpcRouting": false, "masterUsername": "awsuser", "clusterSecurityGroups": [], "pendingModifiedValues": { "masterUserPassword": "****" }, "dBName": "mydbtest", "clusterVersion": "1.0", "encrypted": false, "publiclyAccessible": true, "tags": [], "clusterParameterGroups": [ { "parameterGroupName": "default.redshift-1.0", "parameterApplyStatus": "in-sync" } ], "allowVersionUpgrade": true, "automatedSnapshotRetentionPeriod": 1, "numberOfNodes": 1, "vpcSecurityGroups": [ { "status": "active", "vpcSecurityGroupId": "sg-95f606fc" } ], "iamRoles": [], "clusterIdentifier": "my-dw-instance", "clusterSubnetGroupName": "default" }, "requestID": "4c506036-0032-11e7-b8bf-d7aa466e9920", "eventID": "13ba5550-56ac-405b-900a-8a42b0f43c45", "eventType": "AwsApiCall", "recipientAccountId": "123456789012" }
The following example shows a CloudTrail log entry for a sample DeleteCluster call.
{ "eventVersion": "1.04", "userIdentity": { "type": "IAMUser", "principalId": "AIDAMVNPBQA3EXAMPLE", "arn": "arn:aws:iam::123456789012:user/Admin", "accountId": "123456789012", "accessKeyId": "AKIAIOSFODNN7EXAMPLE", "userName": "Admin", "sessionContext": { "attributes": { "mfaAuthenticated": "false", "creationDate": "2017-03-03T16:58:23Z" } }, "invokedBy": "signin.amazonaws.com" }, "eventTime": "2017-03-03T17:02:34Z", "eventSource": "redshift.amazonaws.com", "eventName": "DeleteCluster", "awsRegion": "us-east-2", "sourceIPAddress": "52.95.4.13", "userAgent": "signin.amazonaws.com", "requestParameters": { "clusterIdentifier": "my-dw-instance", "skipFinalClusterSnapshot": true }, "responseElements": null, "requestID": "324cb76a-0033-11e7-809b-1bbbef7710bf", "eventID": "59bcc3ce-e635-4cce-b47f-3419a36b3fa5", "eventType": "AwsApiCall", "recipientAccountId": "123456789012" }
Working with data sharing information in CloudTrail
All Amazon Redshift data sharing API operations are logged by CloudTrail. For example,
calls to
the AuthorizeDataShare, DeauthorizeDataShare, and
DescribeDataShares operations generate entries in the CloudTrail log
files. For information about the data sharing API operations, see the Amazon Redshift API Reference.
Every event or log entry contains information about who generated the request. The identity information helps you determine the following:
-
Whether the request was made with root or IAM user credentials.
-
Whether the request was made with temporary security credentials for an IAM role or federated user.
-
Whether the request was made by another AWS service.
For more information about CloudTrail userIdentity element, see CloudTrail
userIdentity Element.
Understanding log file entries for data sharing
A trail in CloudTrail is a configuration that enables delivery of events as log files to an Amazon S3 bucket that you specify. CloudTrail log files contain one or more log entries. An event represents a single request from any source. An event includes information about the requested action, the date and time of the action, or request parameters. CloudTrail log files aren't an ordered stack trace of the public API calls; they don't appear in any specific order.
The following example shows a CloudTrail log entry that illustrates the
AuthorizeDataShare operation.
{ "eventVersion": "1.08", "userIdentity": { "type": "AssumedRole", "principalId": "AKIAIOSFODNN7EXAMPLE:janedoe", "arn": "arn:aws:sts::111122223333:user/janedoe", "accountId": "111122223333", "accessKeyId": "AKIAI44QH8DHBEXAMPLE", "sessionContext": { "sessionIssuer": { "type": "Role", "principalId": "AKIAIOSFODNN7EXAMPLE:janedoe", "arn": "arn:aws:sts::111122223333:user/janedoe", "accountId": "111122223333", "userName": "janedoe" }, "attributes": { "creationDate": "2021-08-02T23:40:45Z", "mfaAuthenticated": "false" } } }, "eventTime": "2021-08-02T23:40:58Z", "eventSource": "redshift.amazonaws.com", "eventName": "AuthorizeDataShare", "awsRegion": "us-east-1", "sourceIPAddress": "3.227.36.75", "userAgent":"aws-cli/1.18.118 Python/3.6.10 Linux/4.9.217-0.1.ac.205.84.332.metal1.x86_64 botocore/1.17.41", "requestParameters": { "dataShareArn": "arn:aws:redshift:us-east-1:111122223333:datashare:4c64c6ec-73d5-42be-869b-b7f7c43c7a53/testshare", "consumerIdentifier": "555555555555" }, "responseElements": { "dataShareArn": "arn:aws:redshift:us-east-1:111122223333:datashare:4c64c6ec-73d5-42be-869b-b7f7c43c7a53/testshare", "producerNamespaceArn": "arn:aws:redshift:us-east-1:123456789012:namespace:4c64c6ec-73d5-42be-869b-b7f7c43c7a53", "producerArn": "arn:aws:redshift:us-east-1:111122223333:namespace:4c64c6ec-73d5-42be-869b-b7f7c43c7a53", "allowPubliclyAccessibleConsumers": true, "dataShareAssociations": [ { "consumerIdentifier": "555555555555", "status": "AUTHORIZED", "createdDate": "Aug 2, 2021 11:40:56 PM", "statusChangeDate": "Aug 2, 2021 11:40:57 PM" } ] }, "requestID": "87ee1c99-9e41-42be-a5c4-00495f928422", "eventID": "03a3d818-37c8-46a6-aad5-0151803bdb09", "readOnly": false, "eventType": "AwsApiCall", "managementEvent": true, "recipientAccountId": "111122223333", "eventCategory": "Management" }
You can use Amazon S3 bucket notification and direct Amazon S3 to publish object-created events to AWS Lambda. When CloudTrail writes logs to your S3 bucket, Amazon S3 can then invoke your Lambda function by passing the Amazon S3 object-created event as a parameter. Your Lambda function can read this log object and process the access records logged by CloudTrail. For more information, see Using AWS Lambda with AWS CloudTrail.
Amazon Redshift account IDs in AWS CloudTrail logs
When Amazon Redshift calls another AWS service for you, the call is logged with an
account
ID that belongs to Amazon Redshift. It isn't logged with your account ID. For example,
suppose
that Amazon Redshift calls AWS Key Management Service (AWS KMS) operations such as
CreateGrant,
Decrypt, Encrypt, and RetireGrant to manage
encryption on your cluster. In this case, the calls are logged by AWS CloudTrail using
an
Amazon Redshift account ID.
Amazon Redshift uses the account IDs in the following table when calling other AWS services.
| Region | Region | Account ID |
|---|---|---|
| US East (N. Virginia) Region | us-east-1 | 368064434614 |
| US East (Ohio) Region | us-east-2 | 790247189693 |
| US West (N. California) Region | us-west-1 | 703715109447 |
| US West (Oregon) Region | us-west-2 | 473191095985 |
| Africa (Cape Town) Region | af-south-1 | 420376844563 |
| Asia Pacific (Hong Kong) Region | ap-east-1 | 651179539253 |
| Asia Pacific (Mumbai) Region | ap-south-1 | 408097707231 |
| Asia Pacific (Osaka) Region | ap-northeast-3 | 398671365691 |
| Asia Pacific (Seoul) Region | ap-northeast-2 | 713597048934 |
| Asia Pacific (Singapore) Region | ap-southeast-1 | 960118270566 |
| Asia Pacific (Sydney) Region | ap-southeast-2 | 485979073181 |
| Asia Pacific (Tokyo) Region | ap-northeast-1 | 615915377779 |
| Canada (Central) Region | ca-central-1 | 764870610256 |
| Europe (Frankfurt) Region | eu-central-1 | 434091160558 |
| Europe (Ireland) Region | eu-west-1 | 246478207311 |
| Europe (London) Region | eu-west-2 | 885798887673 |
| Europe (Milan) Region | eu-south-1 | 041313461515 |
| Europe (Paris) Region | eu-west-3 | 694668203235 |
| Europe (Stockholm) Region | eu-north-1 | 553461782468 |
| Middle East (Bahrain) Region | me-south-1 | 051362938876 |
| South America (São Paulo) Region | sa-east-1 | 392442076723 |
The following example shows a CloudTrail log entry for the AWS KMS Decrypt operation that was called by Amazon Redshift.
{ "eventVersion": "1.05", "userIdentity": { "type": "AssumedRole", "principalId": "AROAI5QPCMKLTL4VHFCYY:i-0f53e22dbe5df8a89", "arn": "arn:aws:sts::790247189693:assumed-role/prod-23264-role-wp/i-0f53e22dbe5df8a89", "accountId": "790247189693", "accessKeyId": "AKIAIOSFODNN7EXAMPLE", "sessionContext": { "attributes": { "mfaAuthenticated": "false", "creationDate": "2017-03-03T16:24:54Z" }, "sessionIssuer": { "type": "Role", "principalId": "AROAI5QPCMKLTL4VHFCYY", "arn": "arn:aws:iam::790247189693:role/prod-23264-role-wp", "accountId": "790247189693", "userName": "prod-23264-role-wp" } } }, "eventTime": "2017-03-03T17:16:51Z", "eventSource": "kms.amazonaws.com", "eventName": "Decrypt", "awsRegion": "us-east-2", "sourceIPAddress": "52.14.143.61", "userAgent": "aws-internal/3", "requestParameters": { "encryptionContext": { "aws:redshift:createtime": "20170303T1710Z", "aws:redshift:arn": "arn:aws:redshift:us-east-2:123456789012:cluster:my-dw-instance-2" } }, "responseElements": null, "requestID": "30d2fe51-0035-11e7-ab67-17595a8411c8", "eventID": "619bad54-1764-4de4-a786-8898b0a7f40c", "readOnly": true, "resources": [ { "ARN": "arn:aws:kms:us-east-2:123456789012:key/f8f4f94f-e588-4254-b7e8-078b99270be7", "accountId": "123456789012", "type": "AWS::KMS::Key" } ], "eventType": "AwsApiCall", "recipientAccountId": "123456789012", "sharedEventID": "c1daefea-a5c2-4fab-b6f4-d8eaa1e522dc" }

