What Is Cloud Detection and Response (CDR)?

Cloud Detection and Response (CDR) is a security solution that uses endpoint security techniques, big data analysis and machine learning to detect, investigate, and respond to threats in the cloud environment. It's a service that continually monitors and analyzes activities across cloud workloads to detect suspicious activity.

Amit Sheps
January 23, 2024

CDR is an evolution of Endpoint Detection and Response (EDR) solutions that have been widely adopted in recent years in on-premises environments. While EDR primarily focuses on detecting and responding to threats to traditional endpoints, like employee workstations or servers, CDR extends this capability to the cloud. It provides a holistic view of cloud workloads, enabling security teams to detect threats earlier, investigate them more effectively, and rapidly respond.

In this article:

Importance of Cloud Detection and Response 

A CDR solution provides the following key benefits:

Protects Sensitive Data and Supports Compliance

As businesses migrate more and more of their operations to the cloud, the need to protect sensitive data becomes increasingly important. With regulations such as GDPR and CCPA, businesses are under increasing pressure to ensure that their data is secure.

CDR helps to meet this challenge by providing real-time detection and response to threats. With CDR, security teams can monitor all activities in the cloud environment and quickly respond to any suspicious activity, with a special focus on cloud assets or resources that manage sensitive data. This can help prevent data breaches and comply with data protection regulations.

Increases Visibility

CDR increases visibility into the cloud environment. Traditional security solutions often struggle to provide complete visibility into the cloud, as they are not designed to handle the scale and complexity of cloud environments.

CDR solutions have been specifically designed for the cloud. They provide security teams with a holistic view of activities in cloud workloads, enabling them to detect and respond to threats more effectively. CDR also helps to improve accountability, allowing security teams to track activities in the cloud, identify who is responsible for a particular action, and more easily investigate and respond to security incidents.

Improves Response Times

CDR can significantly improve response times to cloud-based security incidents. Traditional security solutions often struggle to keep up with the dynamic nature and scale of cloud environments. This can result in delayed responses, which can increase the potential damage caused by a security incident.

CDR solutions are designed to respond to threats in real-time. They use machine learning algorithms to detect threats as they occur and can automatically respond and contain the threat. In addition, they provide security teams with the forensic data they need to rapidly investigate and respond to threats across the cloud environment.

Tips from the Expert

here are tips that can help you use CDR solutions more effectively in your cloud environment:

  • Custom script integration for automated workflows: Enhance your CDR solution by integrating custom scripts that automate workflows based on specific, common threats in your environment.
  • Integrate with DevOps pipelines: Integrate CDR into your CI/CD pipelines for continuous security assessment of staging and production environments.
  • Cross-platform incident playbooks: Develop incident response playbooks that can apply to multiple cloud platforms, with procedures for containment, eradication, and recovery in each cloud provider.
  • AI-enhanced threat hunting: Prefer CDR solutions that enable AI-enhanced threat hunting, analyzing patterns over time and predicting potential future attack vectors.
  • Compliance driven security posture: Use your compliance requirements as a baseline for your security posture and ensure they are covered by the CDR solution.

How Does CDR Work? 

The CDR process involves the following steps:

Threat Detection

Unlike traditional security measures that rely on predefined rules and signatures to identify threats, CDR uses advanced machine learning algorithms to detect anomalies and suspicious activities.

These algorithms analyze large volumes of data in real time and identify patterns that deviate from the norm. This could be an unusual login activity, suspicious network traffic, or abnormal data access, among others. Once a potential threat is detected, it is flagged for further investigation. In some cases, the CDR can automatically perform actions to block and contain the threat.

CDR solutions can monitor both structured and unstructured data across multiple cloud platforms. This wide coverage enhances the system’s ability to detect threats that could otherwise go unnoticed in a single-platform environment.


Once alerted to the presence of threats, security analysts must look deeper into the flagged anomalies. They can then determine whether these events pose a real threat or are false positives. CDR can provide additional context about security events to assist the investigation process. The system gathers all relevant information about the anomaly, like the user involved, the time of occurrence, the affected resources, and the nature of the unusual activity.

To make this process more efficient, CDR solutions offer data visualization tools. These tools present the data in a clear and digestible format, making it easier for analysts to understand the situation better and make informed decisions.


Once a threat is confirmed, the response phase kicks in. The primary goal here is to contain the threat and mitigate its potential damage. This could involve blocking an IP address, isolating a network, or even taking a system offline. These actions might be carried out automatically by the CDR system, or triggered manually by security analysts following their investigation.

Data Sources for CDR 

CDR’s effectiveness as a security solution depends on the data it analyzes. This data comes from two primary sources: agents and cloud logs.


Agents are software installed on resources, such as virtual machines or containers, within the cloud environment. They monitor user activities, system events, and network traffic, sending this data back to the CDR system for analysis.

These agents are designed to operate with minimal impact on the performance of cloud assets, and are often equipped with self-protection mechanisms to prevent attackers from disabling or manipulating them. Through these agents, CDR can obtain detailed information about suspicious activity on cloud resources.

Cloud Logs

Cloud logs provide another rich source of data for CDR. These logs record all activities within the cloud environment, from user access to system changes and network connections.

By analyzing these logs, CDR can gain valuable insights into the operational patterns of the cloud environment. Any deviation from these patterns could indicate a potential threat.

Cloud logs are comprehensive in that they cover all aspects of the cloud environment and its security state. However, they often provide less information about specific cloud workloads. CDR combines log data with the deeper real-time data from agents to gain a comprehensive view of the cloud environment.

Considerations When Choosing a Cloud Detection and Response Tool 

When selecting a CDR solution, it is important to consider the following:

Integration with Existing Tools

The tool you select should seamlessly integrate with your existing security infrastructure, including your cloud provider security tooling, virtual private clouds (VPC), and intrusion detection systems. Integration with existing tools can ensure CDR receives pertinent security data from your existing security infrastructure and complements existing security capabilities.

Automated Threat Detection and Response

Evaluate the ability of the cloud detection and response tool to automatically identify and neutralize threats before they can cause significant damage. This can significantly reduce workload for security teams and ensure faster response times.

Multi-Cloud Support

With the rise of multi-cloud environments, it’s crucial to choose a cloud detection and response tool that supports multiple cloud platforms. This will ensure that your tool can provide comprehensive security coverage regardless of the cloud platform you are using. Multi-cloud support will allow you to manage security across all your cloud environments from a single, centralized platform and ensure consistent protection across clouds.

Learn more in our detailed guide to multi cloud strategy 

Threat Intelligence

Threat intelligence refers to the tool’s ability to gather information about potential threats, analyze this information, and use it to enhance its threat detection and response capabilities. A good cloud detection and response tool should be able to gather information from various sources, including vulnerability databases, open-source intelligence, threat intelligence feeds, and cloud provider security advisories.

The CDR tool should also be able to analyze this information quickly and accurately, using AI and other advanced technologies to identify potential threats and implement effective countermeasures.

Amit Sheps
Amit is the Director of Technical Product Marketing at Aqua. With an illustrious career spanning renowned companies such as CyberX (acquired by Microsoft) and F5, he has played an instrumental role in fortifying manufacturing floors and telecom networks. Focused on product management and marketing, Amit's expertise lies in the art of transforming applications into cloud-native powerhouses. Amit is an avid runner who relishes the tranquility of early morning runs. You may very well spot him traversing the urban landscape, reveling in the quietude of the city streets before the world awakes.