The emergence of infrastructure as code tools has significantly enhanced our ability to efficiently manage infrastructure in large-scale environments. I outline the top 10 solutions that warrant consideration based on key selection criteria. In evaluating top Infrastructure as Code offerings, DBAs need to review capabilities against crucial factors such as platform support, existing tool knowledge, single vs multi-cloud tradeoffs, reusability options, code testing needs, agent vs agentless architectures, reporting, and change controls. As infrastructure size has exploded across my client base over recent years, automation has transitioned from nice to have to an essential pillar in ensuring infrastructure resilience and rapid recoverability across test cycles. Beyond efficiencies, IAC capabilities that abstract provisioning also yield improved consistency and enable easier enforcement of configurations. As part of regular reporting, I map the relative positioning of the tools on factors like multi-cloud portability, Python customizability, cost, DSC openness, and more.
1. Terraform
Terraform has emerged as particularly well-suited for operators seeking a flexible infrastructure as a code solution to standardize and automate deployments with testing across hybrid environments. I select Terraform most often because its openness avoids vendor lock-in while still delivering out-of-the-box multi-cloud portability, including solid GCP and Azure support. But beyond the multi-cloud capabilities, Terraform shines on the customization front through both its own HCL syntax and integration options with Python that many competing options lack. The tool also incorporates change management safeguards and applies infrastructure changes incrementally to minimize disruption risks relative to the alternatives.
2. Ansible
In contrast to some of the more specialized IaC options focused purely on provisioning, Ansible delivers a simple yet powerful automation framework with agentless architecture that also spans configuration management, app deployment, intra-service orchestration, and more – helping unify many infrastructure automation needs under one roof while avoiding infrastructure agent overhead. Agentless provisioning similarly yields security advantages over options dependent on agents. Ansible warrants strong consideration where the simplicity of initial setup and learning curve is key or where agentless and Python programmability is crucial – with the tradeoffs centering around lack of state management, potential code drift risks, and more limited cloud support.
3. Chef
The prominence of Chef stems largely from its reliability, significant partner integrations, and customizable automation capabilities catered more to engineers. Chef incorporates sturdy DSL foundations allowing infrastructure teams to codify manual processes into reusable definitions while limiting drift via “infrastructure converge”. But beyond reliability, Chef also shines in both Windows automation support and compliance enforcement capabilities helping assure configurations match security guidelines – proving a versatile option suitable across on-prem and cloud deployments where assurance is essential. The strengths do come with the tradeoff of a steeper initial learning curve relative to alternatives and challenges arising in change tracking.
4. Puppet
Offering expansive cross-platform support, Puppet delivers consistency through “infrastructure as code” style automation coupled with its robust declarative language to help codify and propagate configurations while restricting manual changes. The robust partner community enables rich integrations with existing DevOps pipelines. As Puppet builds on the reliable foundations of its declarative approach, the latest versions have focused significantly on areas like simplified debugging, expanded testing tools, and improved scaling. The result is a battle-tested automation solution warranting strong consideration for Windows-centric shops seeking advanced capabilities like automated remediation and hierarchical data modeling that competitors often lack.
5. SaltStack
SaltStack takes a remote execution approach based on a lightweight publish-subscribe messaging bus. The architecture facilitates high-speed communication and scalability across infrastructure. Salt uses Python for formulating declarative states and imperative operations. The tool delivers versatility through a modular framework, extensible formulas, and integration capabilities. Teams can create state files to configure endpoints or execute one-off tasks with great flexibility. Salt also offers built-in multi-cloud support and Python API access.
6. AWS CloudFormation
CloudFormation allows engineers to model templates and provision AWS resources in a repeatable fashion. The service implements IaC capabilities natively through the AWS Management Console, Command Line Interface, or SDKs. CloudFormation templates can reference parameters, mappings, conditions, and dynamic references to streamline development. Teams can orchestrate fully integrated stacks across EC2, VPC, IAM, RDS, and most other AWS services. The native integration with the AWS ecosystem allows for the provisioning of scalable and secure architectures. CloudFormation simplifies infrastructure changes through integrated version control and tailored update policies.
7. Google Cloud Deployment Manager
Google Cloud Deployment Manager allows you to specify all infrastructure resources in YAML format and integrate with Stackdriver monitoring. Infrastructure templates integrate with the proprietary Google resource specification system. The Deployment Manager API enables full lifecycle management of Google Cloud Platform environments. The tool provisions and manages resources natively across GCP services like Compute Engine, VPN, load balancing, and BigQuery. Teams can configure deployment workflows including preview, rollback, and cancelation. The Deployment Manager also facilitates reuse through templatization and integration with Cloud Source Repositories.
8. Octopus Deploy
Octopus Deploy automates release management for web apps, cloud services, and custom solutions. The platform goes beyond infrastructure provisioning to facilitate the deployment of revised code. Octopus integrates with CI servers and can orchestrate upgrades, rollback, and app retirements. The tool allows centralized visibility across environments with built-in approvals and scheduling. Teams can define granular role-based access and leverage runbooks to standardize deployments. Octopus also offers options to integrate deployment data with monitoring and service desks. The tool focuses squarely on the universal automation needs of DevOps teams.
9. Pulumi
As a developer-first IaC tool, Pulumi takes a unique approach by leveraging mainstream programming languages like JavaScript, TypeScript, Python, Go, and .NET to create, deploy, and manage cloud infrastructure. Pulumi components map to cloud resources for modern infrastructure as code. Teams realize the added benefits of an IDE, package manager, code reuse, and testing frameworks when building cloud architectures.
10. AWS Serverless Application Model (SAM)
The AWS Serverless Application Model (SAM) extends AWS CloudFormation to provide a simplified way of defining serverless applications on AWS. SAM uses YAML syntax to model serverless functions, APIs, databases, event source mappings, and other components. These serverless templates integrate with CI/CD pipelines for automating the deployment and delivery of serverless applications built across various languages. SAM aims to accelerate and optimize building serverless applications across AWS.
