Immutable or Mutable?

I have spoken several times with customer executives who have embraced #DevOps but wrestled with selecting an approach to updating or changing infrastructure and software. This article is based on those conversations.

Two keywords, #Immutable and #Mutable, can define how we may execute updates or changes to infrastructure and software. According to the Oxford Dictionary, the former means "unchanging over time or unable to be changed," and the latter means "liable to change."

?In the context of DevOps and IaC (infrastructure as Code), immutable and mutable infrastructures are two different approaches to managing resources, especially when making updates or changes.

?Immutable Infrastructure

?In immutable infrastructure, once a resource is created, it is never modified. Instead of updating an existing instance, you create a new one. This approach treats resources as disposable, making deployments more predictable, stable, and consistent.

Example: If you need to update an application on a server, you create a new server with the updated application, then switch traffic to this new instance and delete the old one.

?Pros: Eliminates configuration drift, easier rollbacks, reliable deployment, and consistency.

?Cons: May require more resources (time and compute), can be slower for deployments needing only small changes.

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Mutable Infrastructure

?In mutable infrastructure, resources are updated or modified in place. This means that an existing server or resource can be updated without needing to be recreated.

Example: If a patch or configuration change is required, it can be applied directly to the current server without spinning up a new instance.

?Pros: Faster for small, incremental changes and generally less resource-intensive.

??Cons: Risk of configuration drift, more complex to maintain consistency across instances, more challenging rollbacks.

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Use in IaC

?Immutable IaC: Often implemented with tools like Terraform and cloud templates that encourage “replace” over “update” policies. Containerization and serverless functions are good examples of immutable infrastructure.

?Mutable IaC: This approach is more traditional, involving direct updates to servers, commonly seen in managed environments with tools like Ansible, Chef, or Puppet, which configure and update live servers directly.

?Today's preferred approach for Infrastructure as Code (IaC) is generally immutable infrastructure, especially for applications requiring high reliability, consistency, and scalability. Here’s why:

Predictability and Consistency: Since resources are created anew with each deployment, they always start in a known, consistent state, eliminating the risks of configuration drift, where slight, unintended changes accumulate over time in mutable systems.

Ease of Rollback: With immutable infrastructure, if a new deployment has issues, you can simply revert to the previous version by redirecting traffic to the older instances. This is harder to achieve with mutable infrastructure since a rollback may require re-configuring the live system manually.

Simpler Testing and Debugging: Immutable resources ensure that the test environment and production environment remain the same, minimizing bugs and configuration errors that could arise due to differences between environments.

?Version Control and Auditing: Immutable infrastructure aligns with DevOps and CI/CD principles by treating infrastructure similarly to application code, where each deployment is versioned, traceable, and auditable. This leads to easier tracking of changes over time.

?Scalability: It’s easier to scale up resources with immutable infrastructure because new instances can be spun up in their final, tested state without additional configuration. This also aligns well with containerization and cloud-native architectures.

However, there are cases where mutable infrastructure still makes sense:

?Legacy Systems: When working with legacy systems or on-premises environments where resource replacement may not be feasible or efficient.

Quick Patches and Small Updates: Mutable infrastructure allows for rapid, small updates to resources without the overhead of replacing the instance, which can be helpful in environments with frequent, minor adjustments.

The immutable approach is generally preferred for modern, cloud-native applications because of its advantages in reliability, ease of management, and compatibility with CI/CD and DevOps practices. However, mutable infrastructure may still be suitable for environments where constraints make full replacements impractical.

While the immutable or mutable approach strongly applies to IaC, it also influences many other areas in modern software development and infrastructure management, as mentioned below.

Application Deployments

?Immutable Deployments: In modern application deployment, especially with containers and serverless, applications are often deployed as immutable units. For example, each new version of a Docker container is a complete, self-contained environment, and instead of updating a running container, new containers are deployed with the updated application code.

?Mutable Deployments: In traditional deployments (e.g., on virtual machines or bare-metal servers), updates are made directly to the running application. This might involve deploying new code to the same server, modifying dependencies, or making live configuration changes.

Configuration Management

?Immutable Configuration: Configuration-as-Code tools like Terraform or Pulumi support an immutable approach by encouraging full replacements of configurations rather than modifying them in place. This approach is preferred for consistency and easier rollbacks.

?Mutable Configuration: Tools like Ansible (supporting both mutable and immutable), Chef, and Puppet allow for changes to be made directly to the configurations of live systems. They update configurations in place, making them useful for environments where quick, direct updates are necessary.

Data Management

?Immutable Data: In data management, immutability is often used in logging, auditing, and certain database designs. For example, some databases use append-only logs or event sourcing, where instead of modifying records, new records are appended, preserving history.

Mutable Data: Traditional relational databases use mutable data, where records can be updated in place. This is common for transactional systems but can introduce complexity when tracking changes over time.

CI/CD Pipelines

?Immutable CI/CD Artifacts: In CI/CD, artifacts (e.g., builds, containers) are often treated as immutable. Each version is uniquely identified and stored, allowing for consistent, repeatable deployments.

?Mutable CI/CD Pipelines: While the artifacts themselves are often immutable, some parts of a CI/CD pipeline can be mutable, such as specific stages that are updated or reconfigured over time.

?Microservices and APIs

Immutable Microservices/Versions: In a microservices architecture, services are often treated as immutable. If a service changes, a new version is created rather than modifying the existing one. This is common with versioned APIs, where new versions are released rather than changing the existing API.

Mutable Microservices: In smaller or simpler applications, microservices may be updated in place without creating new versions. However, this can introduce backward compatibility issues and is generally avoided in large systems.

Conclusion:

I always prefer Immutability for its predictability, consistency, and ease of troubleshooting. Keeping versions and changes separate enables easier rollbacks, testing, and compliance, especially in complex, distributed systems. However, mutability may be more efficient or necessary in systems with limited resources or where rapid updates are critical.

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