Anti-patterns for everything as code

• Checking in secrets: Storing sensitive data, such as API keys, passwords, or other secrets, directly in the code base or version control system is a critical security vulnerability. Checking in secrets exposes sensitive credentials to anyone with access to the repository and, if the repository is public, to the world. Instead, use management tools or services to store and retrieve secrets securely. These tools can integrate with deployment pipelines and systems during runtime to provide secrets only when necessary, ensuring they remain confidential and are not inadvertently exposed.

• Manual modifications to infrastructure: Making manual changes to infrastructure can be time consuming and error prone, leading to inconsistencies that can be difficult to troubleshoot and resolve. Actively prevent users from making manual changes to environments and workloads to ensure consistent and reliable deployments.

• Outdated or incomplete documentation: Ignoring documentation or treating it as an afterthought can lead to knowledge gaps, misunderstandings about system behavior, and misleading users. As the system changes over time, documentation needs to be continuously updated to align with the current system state.

• Ignoring configuration drift: Failing to track and manage changes to your system's configuration can result in configuration drift, where the actual configuration state deviates from the desired state. Overtime this can lead to system instability, security vulnerabilities, and operational inefficiencies. Use continuous configuration management practices and automated governance capabilities to keep configurations in a known and secure state.

• Bypassing code review and testing: Failing to review and test IaC changes, including data, documentation, configuration, and networking components is an anti-pattern that can lead to data inconsistencies, data loss, and system instability. It's important to apply the same quality assurance practices to IaC as you would to application code.

• Inefficient IaC development practices: Treating IaC differently from application code, especially by not using version control, diminishes developer experience and increases deployment risk. By not versioning IaC files, teams lose the ability to track changes over time, identify when specific changes were made, or correlate infrastructure changes with system behavior. Additionally, storing large, monolithic IaC files makes development and management of IaC more complex, as intertwining components make it challenging to identify specific sections and understand changes being made. Mitigate these challenges by segmenting IaC into modular units consistent with the system's architecture and maintain them within version control systems. Using general-purpose programming languages when developing IaC can further simplify managing IaC like other application code.

• Monolithic network architectures: Designing a network where different components are tightly coupled leads to reduced flexibility and increased complexity. This pattern can make troubleshooting and scaling particularly challenging, as changes in one component may inadvertently impact others. Instead, create a modular network design expressed through multiple, well-organized IaC files where components are loosely coupled and can be individually managed, maintained, and scaled.