How to Audit Amazon DocumentDB

Auditing is a critical component of database security and compliance. Organizations using Amazon DocumentDB often need to track database activity, monitor administrative actions, investigate security incidents, and demonstrate compliance with regulatory frameworks such as GDPR, HIPAA, PCI DSS, and SOX.

As cloud adoption accelerates, maintaining visibility into database operations becomes increasingly important. Industry research consistently shows that unauthorized access, misconfigurations, and insider threats remain among the most common causes of data exposure. A well-designed audit strategy helps organizations detect suspicious behavior, simplify investigations, and maintain accountability. Organizations implementing data compliance programs and following modern regulatory compliance requirements increasingly rely on comprehensive database auditing to strengthen governance and reduce risk.

Amazon DocumentDB provides several native auditing and monitoring capabilities through AWS services. However, organizations with complex compliance requirements frequently require centralized monitoring, advanced analytics, automated reporting, and unified governance. According to the AWS DocumentDB documentation, the service integrates with multiple AWS monitoring and logging tools to help organizations maintain operational visibility. Additionally, the Cybersecurity and Infrastructure Security Agency (CISA) identifies audit logging and continuous monitoring as fundamental cybersecurity best practices.

This guide explains how to audit Amazon DocumentDB using native AWS capabilities and how DataSunrise can enhance audit visibility and compliance management.

Importance of Auditing Amazon DocumentDB

Amazon DocumentDB environments often support customer-facing applications, analytics platforms, and business-critical services where database availability and operational integrity are just as important as security. Auditing provides a reliable record of database activity that helps organizations understand how their environments are being used and managed over time.

One of the primary benefits of auditing is operational transparency. Database teams can track configuration changes, identify the source of unexpected behavior, and verify whether application deployments or administrative actions contributed to performance issues. This historical visibility significantly reduces troubleshooting time during incidents.

Auditing also strengthens change management processes. In dynamic cloud environments, multiple administrators, DevOps engineers, and automated systems may interact with Amazon DocumentDB clusters. Audit records help organizations verify that changes follow internal procedures and provide a clear history of who performed specific actions.

For organizations adopting cloud-native architectures, auditing supports governance initiatives by establishing accountability across teams. Detailed activity records help ensure that database resources are used according to organizational policies and enable managers to review operational practices over time.

From a risk management perspective, audit data provides valuable information for identifying unusual trends and long-term usage patterns. Security teams can analyze historical activity to establish normal behavior baselines, making it easier to recognize anomalies and potential threats before they become significant incidents.

Modern organizations also use audit information to support capacity planning and resource optimization. By understanding how applications interact with Amazon DocumentDB, teams can make better decisions regarding infrastructure scaling, workload distribution, and future architecture investments.

To further strengthen visibility and governance, organizations frequently combine native Amazon DocumentDB monitoring with solutions such as Database Activity Monitoring and Data Audit, creating a more comprehensive view of database operations across cloud environments.

Native Amazon DocumentDB Auditing Capabilities

Amazon DocumentDB does not include a dedicated native audit log mechanism comparable to those available in some enterprise database platforms. Instead, auditing and monitoring are achieved through a combination of AWS services that collectively provide visibility into administrative actions, operational events, database performance, and network activity.

Audit Data Sources in Amazon DocumentDB

Amazon DocumentDB auditing primarily relies on AWS CloudTrail, Amazon CloudWatch, Amazon EventBridge, database profiling, and VPC Flow Logs. Each service captures different aspects of database operations.

AWS CloudTrail records administrative API activity, allowing organizations to monitor infrastructure changes and management operations. Amazon CloudWatch provides performance metrics, operational monitoring, and alerting capabilities. EventBridge enables automated responses to database events, while database profiling captures query execution details and performance information. VPC Flow Logs add network-level visibility by recording traffic associated with DocumentDB resources.

When combined, these services create a foundational auditing framework that helps organizations monitor database environments and investigate operational or security-related events.

Step 1: Enable AWS CloudTrail

CloudTrail serves as the primary source for tracking administrative actions performed against Amazon DocumentDB resources. It records API calls made through the AWS Management Console, AWS CLI, SDKs, and automated services.

Typical events captured by CloudTrail include cluster creation and deletion, instance modifications, parameter group updates, snapshot operations, security group changes, and IAM permission modifications.

Example CloudTrail event:

{
  "eventVersion": "1.08",
  "userIdentity": {
    "type": "IAMUser",
    "principalId": "AIDAEXAMPLE123456789",
    "arn": "arn:aws:iam::123456789012:user/admin-user",
    "accountId": "123456789012",
    "userName": "admin-user"
  },
  "eventTime": "2026-06-17T10:15:32Z",
  "eventSource": "rds.amazonaws.com",
  "eventName": "ModifyDBCluster",
  "awsRegion": "us-east-1",
  "sourceIPAddress": "192.168.1.100",
  "userAgent": "AWS Console",
  "requestParameters": {
    "dbClusterIdentifier": "production-docdb-cluster",
    "backupRetentionPeriod": 14
  },
  "responseElements": {
    "dbClusterIdentifier": "production-docdb-cluster",
    "status": "available"
  }
}

These records allow administrators and security teams to determine who performed specific actions, when changes occurred, and which resources were affected. This level of visibility is particularly valuable during incident investigations and change management reviews.

Step 2: Monitor DocumentDB Metrics with CloudWatch

Amazon CloudWatch provides continuous monitoring of operational metrics generated by Amazon DocumentDB clusters.

Organizations commonly monitor metrics such as CPU utilization, memory consumption, active connections, read and write latency, disk queue depth, and network throughput. These metrics help identify performance bottlenecks, resource constraints, and unusual activity patterns.

CloudWatch alarms can be configured to notify administrators when predefined thresholds are exceeded. Common use cases include detecting abnormal connection spikes, performance degradation, resource exhaustion, or service availability issues.

Example CloudWatch alarm:

aws cloudwatch put-metric-alarm \
  --alarm-name "DocumentDB-HighConnections" \
  --alarm-description "Alert when database connections exceed threshold" \
  --metric-name DatabaseConnections \
  --namespace AWS/DocDB \
  --statistic Average \
  --period 300 \
  --threshold 100 \
  --comparison-operator GreaterThanThreshold \
  --evaluation-periods 2 \
  --dimensions Name=DBClusterIdentifier,Value=production-docdb-cluster \
  --alarm-actions arn:aws:sns:us-east-1:123456789012:DocDBAlerts \
  --treat-missing-data notBreaching

By continuously monitoring these indicators, organizations gain better visibility into database health and operational behavior.

Step 3: Use EventBridge for Audit Event Automation

Amazon EventBridge enables automated processing of Amazon DocumentDB events.

The service can monitor events such as cluster restarts, snapshot creation, instance failures, configuration changes, and scheduled maintenance activities. When a specific event occurs, EventBridge can automatically trigger notifications, workflows, serverless functions, or incident response procedures.

Example EventBridge rule:

{
  "source": [
    "aws.docdb"
  ],
  "detail-type": [
    "DocumentDB DB Cluster Event"
  ],
  "detail": {
    "EventCategories": [
      "configuration change",
      "failure",
      "maintenance",
      "notification"
    ]
  },
  "resources": [
    "arn:aws:rds:us-east-1:123456789012:cluster:production-docdb-cluster"
  ]
}

Example target configuration:

aws events put-targets \
  --rule DocumentDBAuditEvents \
  --targets Id=1,\
Arn=arn:aws:sns:us-east-1:123456789012:SecurityNotifications

This automation reduces response times and helps security and operations teams react quickly to important infrastructure events without requiring constant manual monitoring.

Step 4: Enable Database Profiling

Amazon DocumentDB supports database profiling, which provides visibility into query execution and database operations.

To enable profiling:

use admin

db.setProfilingLevel(
  1,
  {
    slowms: 100
  }
)

db.getProfilingStatus()

To review collected profiling data:

db.system.profile.find(
  {
    millis: {
      $gt: 100
    }
  }
)
.sort(
  {
    ts: -1
  }
)
.limit(10)
.pretty()

Profiling records information about executed queries, execution times, and resource consumption. This information helps administrators identify slow queries, inefficient workloads, application performance issues, and unusual database activity.

Beyond performance optimization, profiling can also assist security teams by revealing unexpected access patterns or abnormal application behavior that may require further investigation.

Step 5: Review Audit Information

A complete Amazon DocumentDB auditing strategy typically involves consolidating information from multiple AWS services.

Security and operations teams often review CloudTrail administrative events alongside CloudWatch metrics, EventBridge notifications, and profiling records to gain a broader understanding of database activity.

For example, administrators may correlate a configuration change recorded in CloudTrail with a performance spike detected by CloudWatch and a series of slow queries captured by the profiler.

Example profiling query for slow operations:

db.system.profile.find(
  {
    millis: {
      $gt: 100
    },
    op: {
      $in: [
        "query",
        "update",
        "insert",
        "remove"
      ]
    }
  }
)
.sort(
  {
    ts: -1
  }
)
.limit(20)

Example aggregation for identifying frequently executed operations:

db.system.profile.aggregate([
  {
    $group: {
      _id: "$op",
      totalOperations: {
        $sum: 1
      },
      averageExecutionTime: {
        $avg: "$millis"
      },
      maxExecutionTime: {
        $max: "$millis"
      }
    }
  },
  {
    $sort: {
      totalOperations: -1
    }
  }
])

Combining these sources provides context that would be difficult to obtain from a single monitoring service alone.

While this approach requires coordination across several AWS services, it establishes a practical baseline for auditing Amazon DocumentDB environments and supports both operational oversight and security monitoring.

How to Audit Amazon DocumentDB with DataSunrise

DataSunrise enhances Amazon DocumentDB auditing by providing a centralized platform for monitoring database activity, security events, and compliance controls. Unlike native AWS auditing, which requires organizations to aggregate information from multiple services, DataSunrise consolidates audit data into a single interface and delivers real-time visibility across database environments.

The platform supports a variety of non-intrusive deployment modes, allowing organizations to implement auditing with minimal impact on existing infrastructure. Combined with intelligent monitoring, automated compliance features, and behavioral analytics, DataSunrise simplifies the process of auditing Amazon DocumentDB at scale.

Step 1: Connect Amazon DocumentDB

The first step is connecting the Amazon DocumentDB instance to DataSunrise. After defining the connection parameters, administrators can begin monitoring database activity through the DataSunrise management console.

DataSunrise supports several deployment approaches, including Proxy Mode, Native Trail Mode, and Sniffer Mode. These deployment options provide flexibility for cloud, on-premises, and hybrid environments while allowing organizations to select the architecture that best aligns with operational requirements.

Once the connection is established, DataSunrise begins collecting database activity information and preparing the environment for audit policy configuration.

Step 2: Create Audit Rules

After connecting the database, administrators can define audit policies that determine which activities should be monitored.

Audit rules can be configured based on users, collections, database operations, client applications, IP addresses, or specific database objects. This level of granularity allows organizations to focus monitoring efforts on critical assets, privileged accounts, or sensitive business data.

DataSunrise also supports Machine Learning Audit Rules, which help identify significant activity patterns automatically. These capabilities reduce manual configuration requirements and improve audit coverage by recognizing potentially important events that might otherwise be overlooked.

Step 3: Capture Database Activity

Once audit rules are active, DataSunrise continuously records database activity and stores audit information in a centralized repository.

Captured events typically include user login activity, administrative actions, data access operations, query execution details, schema modifications, and privilege changes. This information provides a comprehensive audit trail that can be used for investigations, operational analysis, and regulatory reporting.

Because audit records are collected in a single platform, security teams can analyze historical activity without manually correlating information from multiple monitoring tools.

Step 4: Monitor Activity in Real Time

DataSunrise provides real-time visibility into database activity through dashboards, alerts, and behavioral analysis capabilities.

Security teams can quickly identify suspicious behavior, unusual access patterns, privilege misuse, and unauthorized activities. Instead of relying solely on traditional log reviews, DataSunrise continuously analyzes activity as it occurs.

User Behavior Analytics and Suspicious Behavior Detection capabilities help identify anomalies that may indicate compromised accounts, insider threats, or policy violations. This proactive monitoring approach enables faster response to potential security incidents and improves overall situational awareness.

Compliance Benefits of Auditing Amazon DocumentDB

Auditing plays an important role in helping organizations satisfy regulatory and governance requirements. Many regulations require organizations to maintain records of data access, monitor administrative activity, and demonstrate accountability for sensitive information.

For example, GDPR requires organizations to maintain visibility into personal data access, HIPAA focuses on monitoring healthcare information, PCI DSS requires audit trails for payment-related data, SOX emphasizes accountability for administrative actions, and CCPA requires organizations to track consumer data access activities.

Meeting these requirements manually can create significant operational overhead, particularly in large-scale cloud environments where audit data is distributed across multiple systems.

DataSunrise simplifies compliance management through automation and centralized governance capabilities. Features such as Compliance Autopilot, Continuous Regulatory Calibration, Automatic Compliance Policy Generation, Audit-Ready Reporting, and Compliance Drift Detection help organizations maintain alignment with evolving regulatory requirements.

By automating policy management and reporting processes, DataSunrise reduces administrative effort, improves audit readiness, and helps maintain continuous compliance across Amazon DocumentDB environments.

Amazon DocumentDB Native Auditing vs DataSunrise

A comparison of native AWS auditing capabilities and DataSunrise demonstrates how centralized visibility, automated compliance controls, and advanced analytics can simplify security operations while improving audit effectiveness across Amazon DocumentDB environments.

Conclusion

Amazon DocumentDB auditing typically combines AWS CloudTrail, CloudWatch, EventBridge, and database profiling capabilities. These native services provide valuable visibility into administrative activity, operational events, and performance-related database actions.

However, modern compliance programs often require broader visibility, centralized management, advanced analytics, and automated governance.

DataSunrise enhances Amazon DocumentDB auditing through centralized Database Activity Monitoring, Compliance Manager, Machine Learning Audit Rules, Continuous Regulatory Calibration, Suspicious Behavior Detection, and comprehensive Audit Logs. The platform supports structured, semi-structured, and unstructured data environments while providing flexible deployment options across cloud, on-premises, and hybrid infrastructures.

The result is a unified, enterprise-ready auditing platform that improves visibility, accelerates investigations, strengthens compliance programs, and reduces administrative effort across Amazon DocumentDB environments.

Learn more about DataSunrise's Data Audit capabilities, centralized Database Activity History management, and advanced compliance solutions, or schedule a live demo to see Amazon DocumentDB auditing in action.