What is immutable infrastructure?

Organizations can manage infrastructure through two approaches: mutable and immutable. Immutable infrastructure replaces servers entirely rather than modifying them. Mutable infrastructure modifies servers in place, applying updates, patches and configuration changes directly to production servers.

Because it’s primarily modifying existing servers, mutable infrastructure can seem more efficient. However, two factors often make immutable infrastructure more practical and preferable.

First, cloud computing and containerization have transformed deployment speed. Organizations can now replace virtual machines (VMs) and containers in minutes rather than the hours required for physical servers. Infrastructure automation tools can provision and configure new servers and IT resources and apply uniform changes at scale.

Second, immutable infrastructure can significantly cut down on configuration drift, a common feature of mutable infrastructure, wherein a system gradually diverges from its intended state as changes accumulate. Configuration drift is especially common when network issues interrupt the deployment process, causing partial or failed updates. This drift can lead to poor performance, security vulnerabilities and compliance violations. 

For example, when deploying a security update across 100 production servers, automation tools can create 100 new servers with the update preinstalled and validate them in isolation. Once validated, they redirect traffic and decommission the old servers—all within minutes with zero downtime.

Immutable infrastructure follows a three-phase workflow: provisioning new resources, deploying them and enabling instant recovery when needed.

This workflow applies to servers, containers, VMs, functions or any other infrastructure resource throughout its lifecycle.

Provisioning automatically creates new IT infrastructure components that use infrastructure as code (IaC)—a practice that uses declarative templates or code to define intended infrastructure states.

To update an immutable environment, teams create an entirely new resource with the defined configuration rather than using SSH (a network protocol for secure remote server access) to modify existing ones. 

All infrastructure changes are then documented in version control systems like Git, ensuring they’re tested and reproducible.

Common provisioning tools include: 

• Terraform: HashiCorp’s infrastructure-as-code platform provisions and manages infrastructure across AWS, Google Cloud, Azure and on-premises environments through their APIs, with declarative HCL syntax and state files to track changes.

• Docker: Builds lightweight container images based on layered file systems and OS-level virtualization, primarily on Linux systems but also Windows and macOS, enabling faster deployment than traditional VMs.

• Packer: HashiCorp’s tool that creates identical machine images simultaneously for multiple cloud providers and platforms (AMIs for AWS, VMware templates, Docker containers) from a single JSON or HCL configuration.

• AWS CloudFormation: AWS-native tool based on JSON/YAML templates to provision AWS resources with built-in rollback and drift detection. 

• Pulumi: IaC platform that uses familiar programming languages (Python, TypeScript, Go) instead of domain-specific languages, allowing developers to use standard programming constructs like loops and conditionals.

It’s worth mentioning that Puppet and Chef were originally designed for mutable infrastructure, where they update servers in place, though some teams now adapt them alongside immutable approaches.

Deployments in immutable infrastructure are atomic—they either succeed completely or don’t occur at all. This approach aligns with DevOps practices and continuous integration pipelines, which emphasize automated testing, rapid iteration and reliable deployments.

Automation tools deploy the new version of the resource, redirect traffic to it, then decommission the old one. If issues arise during deployment, the old resource remains untouched and operational, eliminating downtime and dependency risks.

Common deployment and orchestration tools include: 

• Kubernetes: Open source container orchestration platform that manages cloud-native containerized applications at scale through self-healing, automatic scaling and rolling updates across clusters of machines.

• Jenkins: Server-based CI/CD pipelines that automate building, testing and deployment with an extensive plug-in ecosystem (1,800+ plug-ins) for customizing build, test and deployment pipelines.

• GitHub actions: Event-driven CI/CD platform built into GitHub repositories, triggered by code commits, pull requests or schedules without requiring external servers.

• Ansible (Red Hat): Primarily a configuration management tool but also used for deployments. It uses YAML playbooks for agentless automation and requires no software installation on managed nodes, unlike Puppet or Chef. 

Because servers in immutable infrastructure are ephemeral—constantly being replaced—persistent data must be stored externally. Organizations use cloud databases, block storage or object storage services to maintain data separately from the servers being replaced. 

When a new server comes online, it reconnects to existing data through these external storage systems. Configuration and metadata frequently live in version control systems like Git. 

Each update creates a new instance, maintaining a clean image for rollback. The same automation tools that provision and deploy can restore previous versions in minutes. Teams redeploy the previous image rather than debugging and troubleshooting modified servers—greatly reducing the detective work traditionally required when configuration management changes fail.

The benefits of an immutable infrastructure are largely related to the deployment process, which immutability makes it simpler and more consistent.

Immutable infrastructure eliminates ambiguous server states through atomic deployments—updates either succeed completely or not at all.

Mutable infrastructures risk partial updates that lead to unpredictable “in-between” states, with characteristics that aren’t entirely known to administrators. This situation can make troubleshooting difficult and increase security risks.

An immutable infrastructure eliminates the possibility of such a state. If an update fails, the server remains in its well-documented state. If it succeeds, the new server arrives fully configured and tested.

Immutable infrastructure helps enable rapid horizontal scaling, the practice of meeting demand by adding a larger number of smaller machines to a network (as opposed to one large machine). A horizontally scaled system is more fault tolerant and can reduce processing bottlenecks by distributing its workload.

This approach is accomplished by using load balancers, which distribute network traffic across multiple servers to improve performance. Tools like Nginx and Amazon’s AWS Elastic Load Balancing (ELB) help support this practice by using an algorithm to assign user requests to the most efficient server at any particular moment.

This combination of load balancing and container orchestration makes immutable infrastructure, with its reproducible templates, essential for standing up multiple identical servers on short notice. This setup can be especially useful when networks expect massive traffic spikes, such as during a shopping holiday or ticket sale. It also helps when coordinating across global regions where traffic peaks at different and sometimes overlapping hours.

Immutable infrastructure strengthens security by eliminating unpredictable “snowflake states”—servers with unknown configurations after failed updates—and maintaining complete audit trails of all changes.

Each server conforms exactly to the source image file describing it, making it simpler to identify security vulnerabilities—such as unauthorized software installations or privilege escalations—and run security audits. Version control systems track each change made to the system, including who made it, when and why. This immutable history enables faster forensic analysis and incident response. Teams can immediately identify compromised configurations and roll back to known-good states if necessary.

An immutable infrastructure also eliminates the need to use Secure Shell (SSH) logins to edit servers in place, reducing the network’s overall attack surface.

Immutability also features tradeoffs compared to a more traditional, mutable infrastructure, mainly regarding data storage.

In a mutable infrastructure, a server might write critical application data to the local disk—making it dangerous or potentially system-breaking to delete and replace that server and disk. Therefore, in an immutable infrastructure data must be stored externally, adding an additional level of complexity to the system.

This method can be done by using external data storage such as cloud databases, block storage or object storage. When a new virtual machine comes online, it can then seamlessly reconnect with the existing data through this external storage. Organizations generally maintain configuration and metadata in version control systems such as Git.

However, the true “immutability” of an immutable infrastructure is sometimes disputed. This limitation is because externally stored network user data is in a constant state of flux and therefore cannot be compared to a known state.