Open-source alternatives to Karpenter Provider Aws

Incus is a unified orchestration platform for managing system containers, OCI application containers, and virtual machines through a single control plane. It brings together cluster infrastructure management, secure multi-tenancy, software-defined networking, and pluggable storage backend orchestration into one cohesive system exposed via a full REST API and command-line interface. What distinguishes Incus is its ability to run multiple instance types side by side—full Linux system containers, OCI application containers, and QEMU virtual machines—all managed with consistent tooling. Networkin

KRR is an open-source tool for analyzing Kubernetes resource requests and recommendations. It evaluates how pods are currently configured and provides suggestions for optimizing CPU and memory allocations based on actual usage patterns. The project focuses on helping teams right-size their Kubernetes workloads by identifying over-provisioned and under-provisioned resources. It scans clusters and generates reports that highlight where adjustments can reduce costs or improve performance without compromising reliability. KRR is distributed as a Python command-line tool that can be run directly

This is an educational repository that teaches container orchestration fundamentals through hands-on guides and practical examples. It covers core Kubernetes concepts including Pods, Services, Deployments, and Namespaces, providing step-by-step exercises that demonstrate how to manage containerized applications across a cluster. The tutorials walk through essential Kubernetes capabilities such as decoupling configuration from application code using ConfigMaps and Secrets, exposing Pods with stable network endpoints via Services, and routing external traffic with Ingress controllers. The mater

This project provides a comprehensive guide and set of scripts for deploying and configuring a production-ready Kubernetes cluster from scratch. It centers on establishing a functional environment by installing core management components, storage, and networking across multiple nodes. The implementation emphasizes high availability for the control plane, utilizing layer-4 load balancing and leader election for the API server, scheduler, and controller manager. It further ensures reliability through the deployment of a distributed key-value store for persistent runtime data. The project cover

Boto3 is the AWS SDK for Python, providing a programmatic interface for managing and automating AWS cloud infrastructure and services. It serves as a cloud management API client and resource manager for provisioning, configuring, and scaling virtual servers, databases, and storage. The library enables the implementation of infrastructure-as-code through declarative templates and scripts, allowing for the deployment of identical resource stacks across multiple accounts and geographic regions. It also provides a framework for coordinating distributed workflows, serverless functions, and contain

Flux is a Kubernetes GitOps delivery tool used to automate application deployments by synchronizing cluster state with configurations stored in Git, OCI, or Helm repositories. It functions as a set of controllers that monitor desired state in external sources and continuously reconcile the live cluster to match those definitions. The system distinguishes itself through a multi-cluster management plane that coordinates application delivery across fleets of remote clusters from a central hub. It provides a dedicated mechanism for automated image updates, which scans container registries for new

The AWS Cloud Development Kit is an infrastructure-as-code framework that enables developers to define and provision cloud resources using familiar programming languages. By utilizing construct-based synthesis, it translates high-level, object-oriented code into declarative templates, allowing for the automated management of complex cloud environments through a centralized, code-driven control plane. The framework distinguishes itself through its ability to model infrastructure as a dependency-aware resource graph, ensuring that components are provisioned and updated in the correct order. It

Azure Docs is the official technical documentation repository for Microsoft Azure, the cloud computing platform. It provides comprehensive guidance on the full spectrum of Azure services, covering everything from core infrastructure components like virtual machines, Kubernetes clusters, and serverless computing to platform services for AI, machine learning, data analytics, and storage. The documentation details how to provision, manage, and govern cloud resources at scale, including policy enforcement, identity management, and cost optimization. The documentation distinguishes Azure through i

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

The Kubernetes Cluster Autoscaler is a mechanism that automatically adjusts the number of nodes in a cluster to match the resource demands of pending pods. It functions as a cloud infrastructure scaler that manages the desired capacity of scaling groups to ensure sufficient compute resources for workloads. The system manages cloud infrastructure automation by adjusting node counts when resources are insufficient or nodes are underutilized. It includes a manager for scaling groups using mixed instance policies to balance on-demand and spot instances for cost and availability. The project also

Agones is a Kubernetes game server orchestrator designed for hosting, scaling, and managing dedicated multiplayer game servers. It extends the Kubernetes control plane using custom resource definitions to define game server and fleet objects, utilizing a dedicated fleet manager to maintain pools of warm server instances. The system provides a game server SDK and language-specific client libraries that allow server processes to signal readiness, health, and shutdown states directly to the controller. It distinguishes itself through specialized scaling logic, including the use of WebAssembly mo

Talos is a minimal, immutable Linux distribution designed specifically for deploying and managing Kubernetes clusters. It functions as an API-driven infrastructure manager that replaces traditional shell access with a declarative gRPC interface to control operating system state and configuration. The system is distinguished by its use of a read-only root filesystem and a security-hardened kernel, which removes standard GNU utilities to reduce the attack surface. It ensures environment consistency by distributing the operating system as versioned, signed images and utilizes TPM-backed verified

This project is a local Kubernetes cluster manager and tool that runs control plane and worker nodes as containers on a host machine. It provides an environment for local development and automated testing by emulating a full Kubernetes cluster within a container runtime. The tool enables the creation of multi-node topologies and high-availability control planes through configuration files. It supports image sideloading to transfer container images directly from the host to nodes, bypassing remote registries, and allows for offline deployments using pre-built node images. Capabilities include

This repository provides a collection of reference implementations, toolkits, and orchestration tools for training and deploying large-scale AI models on Cloud TPU hardware. It serves as a framework for managing the lifecycle of accelerator clusters, including hardware orchestration and the provisioning of high-performance compute infrastructure for machine learning workloads. The project specifically enables the pre-training of foundation models, large language models, and complex reasoning architectures through distributed training toolkits and multi-host scaling recipes. It further provide

ClearML is a comprehensive MLOps platform designed to manage the end-to-end machine learning lifecycle, from initial experimentation to production deployment. It provides a suite of integrated tools including a pipeline orchestrator for automating workflows, an experiment tracking tool for logging hyperparameters and metrics, and a metadata-driven data versioning system for managing large-scale datasets and model artifacts. The platform is distinguished by its advanced compute management and serving capabilities. It features a GPU compute manager that supports fractional resource slicing and

Pulumi is an infrastructure-as-code framework that enables the definition, deployment, and management of cloud resources using general-purpose programming languages. It functions as a cloud resource orchestrator that coordinates the lifecycle of heterogeneous infrastructure by executing code to construct dependency graphs and reconciling the desired state against actual cloud environments. The platform distinguishes itself through a language-host runtime bridge that allows developers to use standard programming languages to define infrastructure, rather than relying solely on domain-specific

Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis

Cortex is an open-source, horizontally scalable metrics platform that ingests, stores, and queries Prometheus-compatible time-series data with multi-tenant isolation. It accepts metrics via Prometheus remote write and OpenTelemetry, executes PromQL queries against both recent and historical data, and provides a Prometheus-compatible alerting and recording rule engine with an integrated Alertmanager. The system is built as a set of independently scalable microservices that use hash-ring-based sharding, gossip-based cluster membership, and tenant-aware object storage to distribute workloads acro

Kill Bill is a subscription billing platform and usage-based billing engine designed to manage recurring invoicing and automated payment collection. It functions as a multi-tenant billing infrastructure, providing isolated environments for different organizational entities through a dedicated API. The system is distinguished by a plugin-based extension framework that allows for the integration of third-party payment gateways and custom business logic. It includes a payment gateway orchestrator to handle transactions and refunds, as well as a revenue recognition system to allocate contract rev

This project is a comprehensive educational resource and operational handbook for Kubernetes. It serves as a technical reference for installing, managing, and scaling container orchestration clusters across diverse environments, covering the core architectural principles and system components required to maintain containerized applications. The resource provides structured guides for cluster administration, including high availability setups, resource control, and data backup operations. It also functions as a security audit and troubleshooting manual, offering instructions for identifying no

Lens is a multi-cluster management platform and desktop application for administering Kubernetes environments. It provides a graphical interface for deploying Helm charts, editing YAML manifests, and managing the lifecycle of pods and deployments. The project features an AI-powered cluster assistant that enables users to query cluster state, perform autonomous troubleshooting, and translate natural language requests into system commands. It also supports collaborative team access through shared spaces, utilizing encrypted cluster sharing and role-based access control to manage credentials and

Sealos is a Kubernetes cloud operating system and orchestration engine that treats a Kubernetes cluster as a single unified operating system. It manages the full application lifecycle by acting as an application orchestrator, a cloud development environment provisioner, and a managed database orchestrator. The platform distinguishes itself through a multi-tenant Kubernetes architecture that provides workspace isolation, role-based access control, and resource quotas. It further differentiates its provisioning model by using natural language and AI to define and scale cloud resources, and by p

This project is a performance optimizer and resource benchmarker for AWS Lambda. It analyzes the trade-off between execution speed and cost by testing various memory configurations to identify the most cost-effective settings and minimize operational spending. The tool utilizes an AWS Step Functions orchestrator to automate the execution and data collection of multiple function test runs across different power levels. It simulates production workloads by injecting custom static or remote data and using weighted payload distribution to mimic real-world traffic patterns. The suite covers sever

The Kubernetes Python Client is a programmatic interface for cluster automation and resource management. It provides a REST-based API client that maps method calls to HTTP verbs and JSON payloads to create, update, delete, and monitor workloads and infrastructure components. The client features dynamic schema mapping and resource mapping, allowing it to control custom objects and unique resource definitions without requiring pre-defined classes or static schemas. It supports YAML manifest parsing to convert structured files into compatible objects for bulk resource deployment. The toolset co

Kuboard-press is a visual management interface for Kubernetes clusters that enables the orchestration of workloads and system objects without manual text file editing. It provides a centralized dashboard for importing and monitoring multiple clusters, using a visual interface to manage namespaces and containerized workloads. The project differentiates itself through hierarchical microservices visualization, which maps flat cluster workloads into a layered structure to represent architectural relationships. It also includes dedicated container operation tools for accessing logs, opening intera

Kubespray is an Ansible-based tool for deploying production-ready Kubernetes clusters on physical or virtual machines across various environments. It serves as an infrastructure provisioner and cluster deployer that automates the installation and configuration of cluster nodes. The project functions as a bare metal cluster orchestrator, allowing for the setup of Kubernetes on physical hardware without relying on a managed cloud provider. It includes specialized installers for configuring networking fabrics, pod communication plugins, and routing policies. The framework also manages the insta

This project is an infrastructure as code tool designed to automate the lifecycle management of Amazon Web Services resources. It functions as a cloud resource provisioner that enables users to define, version, and deploy infrastructure components through declarative configuration files. The system operates by reconciling the current state of a cloud environment against a desired configuration, calculating the necessary delta operations to achieve convergence. It utilizes a directed acyclic graph to resolve resource dependencies and determine the optimal execution order for changes, ensuring