What is Configuration Drift?

In recent years, IT infrastructure and software development have evolved to adopt automated configuration management methods. Configuration management is a practice that involves tracking, maintaining, and controlling system changes.

As systems evolve, configurations can deviate from their intended state — a phenomenon known as configuration drift. Left unchecked, this drift can lead to severe issues, including system instability, security vulnerabilities, downtime, and data breaches.

In this blog post, we will explore the concept of configuration drift, the importance of maintaining consistent configurations, common causes of drift, tools to detect and remediate it, and best practices to minimize it.

What is configuration drift?

Configuration drift is when system configurations gradually deviate from their desired or documented state. This drift happens when changes are made to software or infrastructure settings over time without a proper change management process. We usually observe this situation in cases where system configuration is updated manually, often without governance.

This phenomenon can affect individual machines, software configurations, clusters, or entire IT systems. Configuration drift can have serious consequences, such as inconsistent configurations that cause unpredictable system behavior and increased difficulty in troubleshooting issues.

Common configuration drift causes

Now that we understand what configuration drift is, here are some of the most common causes:

1. Manual changes and human error

One of the primary causes of configuration drift is manual human intervention. Whether it's a system administrator making an ad-hoc change or a developer modifying settings in production, these human-introduced changes often need to be tracked or replicated across environments.

Even minor errors, such as mistyping a command, can lead to inconsistencies that are difficult to trace and correct.

2. Inconsistent and manual deployment processes

Deployment processes that are not fully automated or vary between environments can lead to drift.

For example, if software and configurations are deployed manually for different environments or processes are used, or if teams skip steps during deployment, the configurations in each environment can diverge over time.

3. Dependencies on external systems

Another drift source comes from your resources' reliance on external data sources.

For instance, if your application is configured only to accept traffic from specific tools and third-party software, you might restrict ingress to a particular range of IP addresses. However, because that range can be dynamic, you may need to update it automatically. Any changes to the externally provided system information will also be detected as drift that should be addressed with automation.

4. Differences in environments

Differences between environments, such as development, staging, and production, often contribute to drift. It's common to see testing and staging environments under-provisioned or simplified due to cost and complexity. If each environment is not standardized, subtle differences, such as network settings, operating system versions, or dataset differences, can lead to variations in systems' configurations.

5. Lack of version control

Version control is the golden standard for consistency in software and infrastructure codebases and deployments. Ensuring changes are tracked and applied consistently requires proper version control for configuration files.

Without version control and principles such as GitOps, changes may be made in isolation, creating situations where different versions of the configuration exist across environments, causing drift.

6. Insufficient or non-existent documentation

Poor or incomplete documentation can result in configuration drift. When the intended state of a system or a process isn't clearly defined, users are more likely to make unintended changes.

This lack of clarity can cause teams to overlook necessary configurations or introduce conflicting settings.

Configuration drift examples

A typical example of configuration drift is a system administrator bypassing infrastructure as code processes and pipelines and performing manual ad-hoc changes to cloud infrastructure.

In this example, because the user doesn't follow the formal procedures, they may make changes that deviate from the documented state of the system. This is sometimes necessary in extreme and urgent scenarios where action needs to be taken quickly. In such cases, the user must address the configuration drift after the emergency.

Another example is different configurations for production and testing environments due to the scale, cost, and complexity of maintaining multiple environments.

Different configurations across environments can lead to inconsistencies and unexpected behaviors on production and live systems.

Here's what could happen in practice:

Manual configuration changes - An administrator manually adjusts a server setting in production (e.g., changes a security group rule), but this change isn't updated in the code repository.
IAM role drift - New permissions are added to a user role in the production environment but aren't documented or implemented in other environments, leading to inconsistencies in permissions.
Environment variables - Application-level environment variables, such as API keys or database endpoints, are modified directly in the production environments without updating the configuration management system.
Container image drift - Different environments run different versions of container images because a new image version is manually updated only in production, leading to inconsistencies in code and dependencies.
Orchestration configuration drift - Kubernetes configurations (e.g., replica counts, resource limits) are updated directly on a running cluster and not in the configuration files, leading to divergence from the intended state.
Load balancer changes- Traffic routing rules on a load balancer are adjusted in production for performance, but these changes aren't propagated to backup or disaster recovery environments.

Risks associated with configuration drift

Configuration drift can seriously affect system reliability, security, and overall operational efficiency. When the configuration of a system drifts from its intended state, various risks emerge, threatening the stability and integrity of infrastructure and applications.

Here are the most critical risks associated with configuration drift:

1. Security vulnerabilities

One of the most significant risks of configuration drift is the introduction of security breaches and vulnerabilities. Configurations that are altered unintentionally or uncontrolled can expose systems to attacks.

For instance, firewall rules may be weakened by mistake, unnecessary services might be enabled, or critical security patches may not be applied consistently across all environments. This makes it easier for malicious actors to exploit gaps in the system's defenses.

2. Performance issues

Configuration drift can negatively impact system performance. Suboptimal or incorrect settings, especially in resource allocation, can lead to high latency, reduced throughput, and degraded application performance. These performance issues often arise due to changes that aren't uniformly applied across environments, resulting in unpredictable behavior in production systems.

3. Compliance violations

Many organizations are subject to regulatory requirements or industry standards, such as GDPR or HIPAA. Configuration drift can lead to non-compliance, especially if security and audit settings are not consistently enforced across all systems and environments. Failure to adhere to compliance standards may result in costly penalties, legal liabilities, and reputational damage.

4. Increased downtime and reduced reliability

Drift can introduce instability into an environment, increasing the likelihood of system outages or service disruptions. Changes made manually or outside a controlled process can cause systems to become unavailable, leading to increased downtime and a negative impact on business continuity.

5. Difficulty troubleshooting

Configuration drift makes it harder to troubleshoot and diagnose issues. When configurations differ between environments or systems, identifying the root cause of a problem becomes more complex and time-consuming. Drift creates uncertainty about the system's true state, leading to extended recovery times when failures occur.

6. Inconsistent user experience

Inconsistencies in configurations across different environments can lead to an unpredictable and inconsistent user experience.

For example, a feature that works correctly in a staging environment might behave differently or even fail when promoted to production due to differences in configuration. This inconsistency and potential failures can damage user trust and impact business reputation, especially for customer-facing applications.

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Tools to detect, prevent, and manage configuration drift

To minimize the impact of configuration drift, organizations can leverage various tools and practices to detect, prevent, and manage changes effectively. These are some of the most effective tools for combating configuration drift:

Version control systems, GitOps, and IaC tools

Version control systems, like Git, are essential for tracking changes to configurations. Using GitOps practices, where infrastructure and application configurations are stored in Git repositories, every change can be reviewed, approved, and tracked through a controlled workflow.

This ensures that configuration changes are versioned, auditable, and can be rolled back if necessary. GitOps promotes declarative infrastructure and enforces consistency across environments by treating code as the single source of truth for all configurations.

Continuous delivery tools

ArgoCD and Flux are examples of such tools for managing configurations for software deployments. Both tools provide GitOps controllers for Kubernetes and strong configuration drift controls that start by detecting drift and move up to automatic remediation options.

For example, Argo CD can automatically sync an application when it detects differences between the desired manifests in Git and the live state in the cluster.

Infrastructure as Code (IaC) and orchestration tools

Similarly, on the infrastructure provisioning side, IaC tools - which are usually declarative - are a great fit for observing and managing drifts. Tools such as OpenTofu, Hashicorp Terraform, or AWS CloudFormation use declarative templates to define the environment's state. This provides the option to detect drift by comparing the current state of resources to the defined infrastructure in the code.

IaC configuration languages, combined with robust IaC orchestration, collaboration, and automation tools such as Spacelift, can effectively detect, prevent, and manage drift. IaC tooling also facilitates automated provisioning and updates, reducing the risk of manual errors or inconsistencies that lead to drift.

Spacelift comes with a built-in mechanism to detect and --- optionally --- reconcile drift. It works by periodically executing proposed runs on your stable infrastructure (in Spacelift, it is generally represented it by the FINISHED stack state) and checking for any changes.

Configuration management tools

Configuration management tools like Ansible automate infrastructure provisioning and management, ensuring consistent configurations across environments. These tools allow you to define a set of instructions to run across your infrastructure and automatically enforce these changes across multiple systems.

By continuously applying the desired configuration, they help prevent drift by overwriting any unauthorized changes. If a system's configuration deviates, these tools can revert it back to the correct state.

Cloud configuration drift detection tools

Cloud providers offer services to detect, manage, and remediate configuration drift in their environments. Because cloud environments often become large and complex, services such as AWS Config, Azure Policy, and Workload Manager Evaluation can help continuously monitor and evaluate cloud resources and their configurations according to rules.

For example, AWS Config continuously evaluates cloud resources against desired settings and can trigger automatic notifications or corrective actions when drift is detected. Such tools are particularly useful for enforcing compliance in cloud environments, ensuring that resources stay aligned with best practices and security policies.

Best practices to minimize configuration drift

Configuration drift can lead to inconsistencies, security vulnerabilities, and operational inefficiencies in IT environments. To mitigate these risks, organizations should adopt the following best practices:

1. Use version control for all configurations

Treating configurations like code and storing them in a version control system such as Git is crucial for maintaining integrity and traceability. This practice allows teams to track changes over time, providing a clear history of modifications and the ability to roll back to previous versions if needed.

Version control also facilitates collaboration on configuration updates, enabling multiple team members to work on configurations simultaneously while maintaining a single source of truth.

2. Implement standardized deployments and automated configuration management

Developing repeatable, standardized processes for deployments is crucial in minimizing configuration drift. This can be achieved by adopting continuous integration/continuous deployment (CI/CD) pipelines for software deployment and IaC tools, like OpenTofu and Spacelift, which allow for the consistent provisioning of resources across different environments.

This ensures that all deployments follow the same validated procedures, reducing the risk of human error and inconsistencies.

Automation is the foundation for maintaining consistent configurations across systems. By leveraging configuration management tools such as Ansible, organizations can define their configurations as code, ensuring that changes are applied consistently across multiple systems. These tools allow for the systematic application of configurations and the automatic detection and correction of drift.

3. Regularly audit and monitor systems

Implementing a robust continuous monitoring system is essential for detecting drift early and preventing minor discrepancies from escalating into major issues. This involves using specialized tools to scan for unauthorized changes and setting up alerts that notify administrators of unexpected configuration modifications.

Periodic manual audits should complement regular automated checks to verify system states and ensure all configurations align with organizational standards and policies. This proactive approach allows teams to identify and address potential problems before they impact system performance or security.

4. Maintain comprehensive documentation

Keeping documentation up-to-date and easily accessible can help avoid configuration drift. This includes maintaining detailed records of all approved configurations, creating a comprehensive knowledge base of system architecture and dependencies, and regularly reviewing and updating this documentation to reflect current states.

Most importantly, well-maintained documentation serves as a reference point for understanding the intended state of systems, facilitating quicker identification and resolution of discrepancies. It also aids in onboarding new team members and ensures institutional knowledge is preserved even as team compositions change over time.

Key points

In this blog post, we explored the concept of managing configuration drift in software and IT systems and environments. We then examined common examples, causes of configuration drift, and risks associated with it. Finally, we analyzed best practices to minimize configuration drift and tools that can help us detect, prevent, and remediate configuration drift.

If you want to take your infrastructure automation to the next level, create a Spacelift account today or book a demo with one of our engineers.

Written by Ioannis Moustakis

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