Open-source alternatives to Terraform Best Practices

This project is a set of git pre-commit hooks designed to automate the formatting, linting, and validation of Terraform configurations. It functions as an infrastructure as code linter, security scanner, cost estimator, and documentation generator to ensure code quality before commits are finalized. The tool distinguishes itself by providing specialized capabilities for infrastructure workflows, such as scanning templates for security vulnerabilities and hardcoded secrets, calculating projected cloud spending against budgets, and automatically extracting module definitions to populate readme

Terragrunt is an infrastructure as code orchestrator and a thin wrapper for Terraform. It serves as a configuration manager designed to reduce code duplication and manage the execution and deployment order of infrastructure across complex cloud architectures. The tool facilitates scaling cloud deployments across multiple environments, such as development, staging, and production, while keeping configurations consistent. It focuses on organizing large-scale deployments into manageable components to avoid monolithic state files and limit the blast radius of changes. Its capabilities cover infr

This is a Terraform infrastructure as code module designed for provisioning and managing Amazon Elastic Kubernetes Service clusters and worker nodes. It functions as a Kubernetes cluster provisioner that handles the deployment of managed container orchestration environments, including the control plane and associated node groups. The project provides a cloud node security manager to apply network rules and security groups to both managed and self-managed node clusters. It further automates the setup of these environments through custom bootstrap scripts and configuration files injected during

Terraform is a declarative infrastructure-as-code tool designed to manage the lifecycle of cloud and on-premises resources. It functions as a workflow engine that reconciles a defined desired state against real-world infrastructure, using a persistent state-tracking layer to maintain consistency and visibility across distributed environments. By mapping infrastructure components into a directed acyclic graph, the system calculates the optimal order for provisioning, updating, or destroying resources. The platform is distinguished by its extensible plugin-based architecture, which decouples co

Test Kitchen is an infrastructure testing framework designed to automate the lifecycle of infrastructure code and system configurations. It provides a modular orchestration system that manages the creation, configuration, and teardown of isolated virtual or containerized environments, enabling developers to validate infrastructure changes across multiple platforms and cloud providers before deployment. The project utilizes a plugin-oriented architecture that decouples core orchestration logic from platform-specific implementations. This allows for the integration of diverse drivers for enviro

This project provides a comprehensive collection of standardized conventions and architectural patterns designed to maintain consistent code quality, secure workflows, and project stability. It serves as a structured guide for implementing engineering processes, including automated testing, dependency management, and environment configuration across diverse software development lifecycles. The framework distinguishes itself by offering a unified approach to version control and interface design. It enforces linear development practices through standardized commit messages and branch protection

This repository is a comprehensive educational resource covering the full spectrum of DevOps practices, including continuous integration and delivery, containerization, orchestration, configuration management, and infrastructure as code. It provides structured content that walks through automating the build, test, and deployment lifecycle using multi-stage pipelines with Jenkins and Azure DevOps. The material covers declarative server configuration and state management through automated Ansible playbooks, enabling consistent system environments across machines. It also addresses container lif

The Serverless Framework is a declarative infrastructure-as-code tool designed to automate the deployment, scaling, and lifecycle management of cloud-native applications. It provides a unified command-line interface that translates high-level configuration files into provider-specific resource templates, enabling developers to orchestrate complex architectures, event-driven functions, and cloud resources within a single project structure. What distinguishes this framework is its focus on developer experience and multi-environment parity. It supports local function invocation and event proxyin

OpenTofu is a declarative infrastructure orchestrator that automates the provisioning and management of cloud resources. It functions as a platform-agnostic interface, allowing users to define their desired environment state in configuration files, which the system then reconciles against live infrastructure to calculate and execute necessary updates. The project utilizes a graph-based execution engine to determine the optimal sequence for resource operations, enabling the parallel processing of independent components to reduce deployment times. To support complex, multi-platform environments

This repository is a curated collection of reusable AWS CloudFormation templates that automate the provisioning of AWS resources using infrastructure as code. The templates serve as ready‑to‑deploy blueprints for common AWS components—such as VPCs, EC2 instances, databases, and security groups—and include serverless application templates that combine API Gateway with Lambda to create endpoints triggered by HTTP requests without manual configuration. The templates are written in declarative YAML or JSON and support nested stack composition, allowing related resources to be grouped into reusabl

Goss is a declarative system validation framework that verifies server state by comparing live system attributes against YAML specifications. It checks the state of packages, ports, services, files, users, processes, DNS records, kernel parameters, mounts, network interfaces, and HTTP endpoints, reporting pass or fail for each condition. The tool distinguishes itself through several automation capabilities. It can scan a running system to automatically generate YAML baseline files that capture current resource configurations, eliminating the need to write tests from scratch. A retry-with-time

ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning pipelines and agentic workflows. It provides a unified framework that manages the entire lifecycle of machine learning assets, from data processing and model training to the deployment of persistent inference services. By decoupling pipeline logic from underlying compute and storage, the platform enables teams to transition workflows seamlessly from local development environments to production-grade cloud infrastructure. The platform distinguishes itself through a service-oriented

This project serves as an educational resource for mastering automated infrastructure provisioning, configuration management, and container orchestration. It provides structured learning paths and hands-on exercises designed to teach the principles of defining and managing server environments through version-controlled configuration files. The repository distinguishes itself by offering specific, practical tutorials for industry-standard automation tools. It covers the deployment of cloud resources through declarative configuration files, the automation of server setup and software maintenanc

Unstructured is an enterprise-grade data orchestration engine designed to transform raw, unstructured files into structured, machine-readable formats. It functions as a comprehensive platform for document ingestion, partitioning, and enrichment, specifically engineered to prepare complex data for retrieval-augmented generation and agentic AI workflows. The platform distinguishes itself through its sophisticated document processing strategies, which combine rule-based extraction with vision-language models to handle diverse file layouts, tables, and images. It provides a modular architecture t

NATS Server is a high-performance, lightweight messaging system designed for cloud-native applications, edge computing, and distributed microservices. It functions as a distributed publish-subscribe broker that routes messages using hierarchical, dot-separated subject strings, enabling decoupled communication between services without requiring centralized broker lookups. The system supports core messaging patterns including asynchronous publish-subscribe, request-reply, and load-balanced queue processing. The platform distinguishes itself through a decentralized architecture that eliminates t

dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control. It functions as a data transformation engine that enables users to define data structures and business logic through declarative configuration files, which the system then compiles into executable code. By managing complex data dependencies through a directed acyclic graph, it ensures that transformation tasks execute in the correct order while maintaining a manifest-driven state to track lineage and execution history. The project distinguishes itself through an adapter-based d

Ory Keto is an open-source authorization server that implements Google Zanzibar’s relationship-based access control model. It stores every access relationship as a tuple in a SQL database and exposes a declarative TypeScript-like namespace language for defining object types, relations, and permissions. The service provides bidirectional permission resolution, configurable consistency levels for checks, and dual gRPC and REST APIs for broad integration. Keto extends the Zanzibar model with edge enforcement of access policies, structured compliance auditing of permission decisions, and infrastr

This project is a standardized machine learning experiment boilerplate and project template that combines PyTorch Lightning with the Hydra configuration framework. It provides a structured codebase for organizing deep learning workflows, specifically designed to integrate hierarchical configuration management with distributed training. The template features a specialized workflow for hyperparameter optimization and batch experiment execution, allowing for automated parameter sweeps without modifying source code. It employs a hierarchical system for managing settings via YAML files and command

This project is a serverless infrastructure orchestrator and deployment tool designed to host Next.js applications on AWS. It functions as an edge computing deployment framework and cloud infrastructure-as-code wrapper that automates the provisioning of AWS Lambda functions, S3 buckets, and CloudFront distributions. The system distinguishes itself by distributing server-side rendering and API routes across global edge locations to reduce latency. It integrates directly with content delivery networks to optimize the delivery of static assets and rendered pages, while providing a layer to wrap

Meshery is a service mesh management plane and cloud native infrastructure orchestrator. It provides a visual design-as-code environment for modeling microservices and infrastructure components through declarative blueprints, functioning as a centralized platform for designing, deploying, and managing service mesh infrastructure. The platform is distinguished by its ability to translate visual designs into active deployments and its use of gRPC-based adapters to integrate with diverse infrastructure providers. It features a multi-tenant architecture that manages shared workspaces and role-bas

Coder is a self-hosted platform for provisioning and managing isolated, containerized development environments. It provides a centralized infrastructure for teams to deploy ephemeral workspaces on private cloud or on-premises hardware, ensuring consistent toolchains and dependencies across distributed development environments. The platform distinguishes itself through its focus on secure, infrastructure-as-code governance and autonomous agent integration. It allows organizations to define reusable, versioned environment templates that integrate with existing identity providers and role-based

This project is a centralized library of community-contributed, declarative configuration files designed for automating the deployment of cloud infrastructure and services. It serves as a repository of machine-readable templates that define the desired state of cloud environments, enabling consistent and repeatable resource provisioning. The collection provides pre-configured scripts that streamline the setup of virtual machines, databases, and networking components. By utilizing these templates, users can standardize the deployment of cloud services and automate the creation of development,

pyinfra is an agentless infrastructure automation framework that turns declarative Python code into idempotent shell commands to manage servers, containers, and local machines over SSH without requiring any pre-installed software on target hosts. It operates by comparing the desired state of a system against its current state, using a dry-run simulation mode to preview changes and a fact-based conditional execution engine to gather host attributes at runtime and control which operations run. The tool compiles Python operations into optimized shell commands and executes them in parallel across

The project is a Kubernetes operator that automates the deployment, configuration, and management of ClickHouse database clusters using native custom resources and declarative manifests. It functions as a distributed database controller and stateful workload manager, handling infrastructure provisioning and scaling routines across containerized environments. The operator provides comprehensive database lifecycle management capabilities, controlling operational states, safe software version upgrades, and dynamic cluster scaling while automatically propagating schema changes. It includes custom

Angular-chart.js is a frontend charting library that provides a set of reusable directives for integrating the Chart.js visualization engine into AngularJS applications. It functions as a wrapper that encapsulates complex rendering logic within declarative components, enabling the creation of interactive and responsive graphical data representations. The library distinguishes itself by providing reactive data synchronization, which automatically triggers canvas re-renders whenever underlying data or configuration models change. It also utilizes a provider-based configuration system, allowing

kube-no-trouble is a Kubernetes deprecated API scanner and cluster auditor designed to detect outdated API versions. It identifies resources that may cause failures during cluster upgrades by checking them against predefined rulesets of deprecated or removed versions. The tool operates across multiple environments, providing both live cluster auditing and static analysis of local YAML manifests. It further extends its detection capabilities to Helm releases, extracting metadata from deployed charts to pinpoint deprecated APIs within installations. Its broader capabilities include infrastruct

This project is a comprehensive educational resource and curriculum focused on site reliability engineering, distributed systems, and infrastructure operations. It provides technical guides, a systems engineering course, and instructional manuals designed to teach the principles of managing large-scale computing environments. The curriculum covers high-level architectural design for scalability and resilience, including fault-tolerant infrastructure, high-availability patterns, and microservices decomposition. It emphasizes the practical application of site reliability engineering through the