Enterprise Architecture artifacts [policies, principles, positions, practices, standards, guidelines]
Patterns/ Reference Architecture
Access Management
AI reference architecture
Digital Tech Stack
Application/ API integration
Containers and container orchestration: Microservices are packaged into containers (e.g., Docker) to ensure a consistent execution environment. Orchestration tools like Kubernetes automate the deployment, scaling, and management of these containers across the cloud infrastructure
Infrastructure as Code (IaC)
GitOps: A modern evolution of IaC, GitOps uses Git repositories as the single source of truth for both application code and infrastructure configurations. Automated agents then continuously monitor and reconcile the live cloud environment to match the state declared in the Git repository.
Continuous Integration/Continuous Delivery (CI/CD)
Observability (Monitoring and Logging): Teams implement comprehensive monitoring and logging across their cloud systems to gain deep visibility into application performance and infrastructure health. This provides fast feedback loops, allowing teams to quickly detect, diagnose, and resolve issues.
Shift-left security (DevSecOps)
Architecture governance typically includes some foundational agreed upon:
Architecture Policies: Compliance is mandatory and is non-negotiable. This will be reserved for very few items.
Architecture Principles: Simple statements of values and beliefs. Enterprise architecture principles are intended to guide the development, operations and maintenance of capabilities, the associated decision-making processes, and serve as a base for architectures, development, policies, and standards. These principles provide the guideposts for architects and engineers to make judgements toward their designs for their solutions.
Architecture Positions: A point of view on a topic that requires some common understanding.
Architecture Practices - Standards and Guidelines: Articulation of how we do our work.
These architectural principles are foundational to implementing DevOps on the cloud and address how software and infrastructure should be designed.
API architecture: This involves breaking down a monolithic application into a suite of smaller, independently deployable services. This design improves agility, fault isolation, and scalability, with each service responsible for a specific business function and communicating with others via APIs.
Containers and container orchestration: Microservices are packaged into containers (e.g., Docker) to ensure a consistent execution environment. Orchestration tools like Kubernetes automate the deployment, scaling, and management of these containers across the cloud infrastructure.
Cloud-native design: Cloud-native applications are designed to fully leverage the scalability, elasticity, and resilience of cloud platforms. This approach is vendor-neutral, allowing applications to be portable across different cloud environments.
Immutable infrastructure: This practice involves creating new infrastructure for every deployment, rather than updating existing servers. Infrastructure is treated as disposable; it is built and deployed, and when a new version is ready, the old infrastructure is replaced. This improves consistency and reliability by preventing configuration drift.
Complementing architectural patterns, these practices focus on the methodologies and tools used in the development and operational phases of the software lifecycle.
Infrastructure as Code (IaC): All infrastructure, including networks, virtual machines, and databases, is managed and provisioned using code and configuration files. Tools like Terraform and AWS CloudFormation allow for repeatable, version-controlled, and automated infrastructure deployments.
GitOps: A modern evolution of IaC, GitOps uses Git repositories as the single source of truth for both application code and infrastructure configurations. Automated agents then continuously monitor and reconcile the live cloud environment to match the state declared in the Git repository.
Continuous Integration/Continuous Delivery (CI/CD): A core practice that automates the building, testing, and deployment of code changes. A CI/CD pipeline enables developers to frequently merge code, test it, and deploy it to production or staging environments with minimal human intervention.
Observability (Monitoring and Logging): Teams implement comprehensive monitoring and logging across their cloud systems to gain deep visibility into application performance and infrastructure health. This provides fast feedback loops, allowing teams to quickly detect, diagnose, and resolve issues.
Shift-left security (DevSecOps): Instead of treating security as a final step, DevSecOps integrates security practices throughout the entire CI/CD pipeline and software development lifecycle. This involves automated security testing, threat modeling, and code analysis to identify and address vulnerabilities early.
Continuous improvement: A foundational DevOps principle that promotes a culture of ongoing learning, experimentation, and optimization. By analyzing metrics, gathering feedback, and running retrospectives, teams refine their processes and tools to enhance efficiency and reliability.