AWS, Cloud Computing

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A Guide to Drift Management in AWS CloudFormation

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As organizations embrace the benefits of cloud computing and infrastructure as code, AWS CloudFormation emerges as a cornerstone for streamlining resource management and provisioning in the AWS environment. Defining infrastructure using declarative templates allows for reproducibility, scalability, and consistency. However, in the dynamic landscape of IT operations, where changes are inevitable, ensuring that your deployed resources align with your intended configuration becomes paramount.


AWS CloudFormation Drift Management addresses maintaining configuration consistency in evolving infrastructure. In the context of AWS CloudFormation, Drift refers to the nuanced disparities between the specified infrastructure configuration in your templates and the actual state of deployed resources.

These discrepancies can result from intentional modifications made outside the AWS CloudFormation orchestration process and unforeseen adjustments occurring within the AWS environment.

In the subsequent sections of this blog post, we will embark on a comprehensive exploration of AWS CloudFormation Drift Management. From understanding the intricacies of Drift to implementing proactive strategies for detection and remediation, we will equip you with the knowledge and tools needed to maintain control and consistency in your AWS environment. Let’s delve into the nuances of Drift, why it matters, and how AWS CloudFormation offers robust capabilities for effective drift management.

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Understanding Drift in AWS CloudFormation

Drift in AWS CloudFormation refers to the misalignment between the desired and actual states of resources defined in AWS CloudFormation templates. There are two primary types of drift: resource drift and stack drift. Resource drift occurs when individual resources deviate from their specified configurations in the template due to manual changes made outside AWS CloudFormation. For instance, alterations to security group rules or modifications to instance types can result in resource drift. Stack drift, on the other hand, involves changes at the stack level, impacting parameters, tags, or the configuration of multiple resources within the stack. Recognizing and comprehending these types of drift is vital for maintaining the integrity and consistency of your AWS infrastructure. Regular drift detection and resolution are essential to ensure that resources and stacks align with their intended configurations, minimizing operational challenges and enhancing security.

In practical terms, Drift can have significant implications for day-to-day operations. Resource drift may introduce inconsistencies that lead to unexpected behavior, while stack drift can result in systemic changes affecting multiple resources. Detecting and understanding drift is not only about identifying deviations but also about maintaining operational control and security. By addressing drift promptly and integrating preventative measures, organizations can uphold the reliability and stability of their AWS environments, ensuring that infrastructure configurations align with established best practices and compliance standards.

Detecting Drift

Detecting drift in AWS CloudFormation is a critical step in maintaining the integrity of your infrastructure. When you initiate a drift detection operation, AWS CloudFormation meticulously compares the current state of your deployed resources against the specifications outlined in your CloudFormation templates. This process meticulously scrutinizes each resource for any deviations in configuration, identifying instances of resource drift and stack drift. The results provide a clear snapshot of any disparities, enabling you to take corrective actions promptly.

This proactive drift detection approach empowers you to avoid potential operational challenges and security risks. Incorporating regular drift detection into your workflow ensures that your AWS resources align with your intended configurations, fostering a more stable and secure environment.

Types of Drift

Understanding the types of drift is essential for effective management. There are two main types:

  1. Resource Drift:

Resource drift occurs when individual resources within an AWS CloudFormation stack deviate from their specified configurations in the associated template. This deviation is typically the result of manual interventions, wherein changes are made directly to the resource properties outside the purview of AWS CloudFormation.

Consider a scenario where the template dictates a specific Amazon EC2 instance type, security group rules, or an Amazon S3 bucket policy. Resource drift would manifest if an administrator manually modifies any of these properties outside the orchestrated processes of AWS CloudFormation.

The significance of understanding resource drift lies in its potential to introduce inconsistencies and misconfigurations, which can, in turn, compromise the operational integrity and security of the AWS infrastructure. Detecting resource drift becomes pivotal for maintaining a reliable and secure environment, ensuring each resource aligns with the expected state defined within the AWS CloudFormation template.

  1. Stack Drift:

In contrast, stack drift pertains to changes occurring at the holistic level of an AWS CloudFormation stack. This encompasses alterations to stack-wide settings, such as parameter values, tags, or even drift in one or more constituent resources.

For instance, if a stack is configured to deploy instances in a specific Amazon VPC, a change to the VPC outside the orchestration of AWS CloudFormation would constitute stack drift. Understanding and addressing stack drift are paramount for preserving the overall coherence of the infrastructure, as modifications at the stack level can have cascading effects on associated resources.

Both resource and stack drift collectively underscore the need for vigilant monitoring and management. Regularly inspecting and remediating drift ensures that the actual state of the AWS environment aligns harmoniously with the intended configurations specified in CloudFormation templates. This theoretical exploration is the foundation for practical strategies to mitigate drift effectively in real-world AWS deployments.

Strategies for Managing Drift

  • Addressing Drift Manually: Evaluate whether the drift aligns with your desired state for intentional changes. You can update your AWS CloudFormation template to reflect these changes. Alternatively, if the drift is unintentional, corrective action may involve updating the resource manually or through automation.
  • Automating Drift Remediation: Leverage automation tools and scripts to programmatically address drift. This could involve updating the AWS CloudFormation template to include the drifted configuration or implementing custom scripts to bring the resource back into alignment.
  • Setting Drift Alarms: To proactively manage drift, set up Amazon CloudWatch Alarms to notify you when drift is detected. This allows you to take immediate action and prevents unnoticed drift from causing issues over time.


Managing drift in AWS CloudFormation is critical to maintaining a secure, compliant, and consistent infrastructure. By understanding the concept of drift, regularly detecting and addressing it, and implementing preventative measures, you can ensure that your AWS resources align with your desired configuration, enhancing the reliability and stability of your infrastructure.

Incorporate these strategies into your AWS CloudFormation workflows to maintain control and visibility over changes, ultimately contributing to a more robust and manageable AWS environment.

Drop a query if you have any questions regarding AWS CloudFormation and we will get back to you quickly.

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1. What is drift in AWS CloudFormation?

ANS: – Drift in AWS CloudFormation occurs when there are discrepancies between the expected and actual configurations of resources, potentially impacting operational stability and security.

2. How can I detect drift in AWS CloudFormation?

ANS: – Drift in AWS CloudFormation can be detected using the Drift Detection feature, comparing current and expected resource states.

3. How does YUM contribute to package management in Red Hat-based systems?

ANS: – YUM, or Yellowdog Updater, Modified, is a package manager used in Red Hat-based systems. It simplifies managing software packages, handling dependencies, and accessing centralized repositories for software installation and updates.

WRITTEN BY Karan Malpure



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