Open Source Linux Container Management Software
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Container Management Software for Linux
View 44 business solutionsBrowse free open source Container Management software and projects for Linux below. Use the toggles on the left to filter open source Container Management software by OS, license, language, programming language, and project status.
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1
Reloader
A Kubernetes controller to watch changes in ConfigMap and Secrets
A Kubernetes controller to watch changes in ConfigMap and Secrets and do rolling upgrades on Pods with their associated Deployment, StatefulSet, DaemonSet, and DeploymentConfig – [✩Star] if you're using it. We would like to watch if some change happens in ConfigMap and/or Secret; then perform a rolling upgrade on relevant DeploymentConfig, Deployment, Daemonset, Statefulset, and Rollout. Reloader can watch changes in ConfigMap and Secret and do rolling upgrades on Pods with their associated DeploymentConfigs, Deployments, Daemonsets Statefulsets, and Rollouts. -
2
containerd
An open and reliable container runtime
An industry-standard container runtime with an emphasis on simplicity, robustness and portability. As of February 28, 2019, containerd is officially a graduated project within the Cloud Native Computing Foundation, following Kubernetes, Prometheus, Envoy, and CoreDNS. We'd like to thank the amazing containerd community for making this all possible and we're excited for the future of the project. containerd is available as a daemon for Linux and Windows. It manages the complete container lifecycle of its host system, from image transfer and storage to container execution and supervision to low-level storage to network attachments and beyond. Management of network namespaces containers to join existing namespaces. Network primitives for creation, modification, and deletion of interfaces. Multi-tenant supported with CAS storage for global images. -
3
Argo Rollouts
Progressive Delivery for Kubernetes
Argo Rollouts is a Kubernetes controller and set of CRDs that provide advanced deployment capabilities such as blue-green, canary, canary analysis, experimentation, and progressive delivery features to Kubernetes. Argo Rollouts (optionally) integrates with ingress controllers and service meshes, leveraging their traffic shaping abilities to gradually shift traffic to the new version during an update. Additionally, Rollouts can query and interpret metrics from various providers to verify key KPIs and drive automated promotion or rollback during an update. -
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Kubernetes Gateway API
Repository for the next iteration of composite service
Gateway API is an official Kubernetes project focused on L4 and L7 routing in Kubernetes. This project represents the next generation of Kubernetes Ingress, Load Balancing, and Service Mesh APIs. From the outset, it has been designed to be generic, expressive, and role-oriented. Most of the configuration in this API is contained in the Routing layer. These protocol-specific resources (HTTPRoute, GRPCRoute, etc) enable advanced routing capabilities for both Ingress and Mesh. When using Gateway API to manage ingress traffic, the Gateway resource defines a point of access at which traffic can be routed across multiple contexts -- for example, from outside the cluster to inside the cluster (north/south traffic). Each Gateway is associated with a GatewayClass, which describes the actual kind of gateway controller that will handle traffic for the Gateway; individual routing resources (such as HTTPRoute) are then associated with the Gateway resources. -
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5
K3s
Lightweight Kubernetes
Lightweight Kubernetes. Production-ready, easy to install, half the memory, all in a binary less than 100 MB. K3s is a highly available, certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. K3s is packaged as a single <70MB binary that reduces the dependencies and steps needed to install, run and auto-update a production Kubernetes cluster. Both ARM64 and ARMv7 are supported with binaries and multiarch images available for both. K3s works great on something as small as a Raspberry Pi to an AWS a1.4xlarge 32GiB server. -
6
Kueue
Kubernetes-native Job Queueing
Kueue is a set of APIs and controllers for job queueing. It is a job-level manager that decides when a job should be admitted to start (as in pods can be created) and when it should stop (as in active pods should be deleted). Use Kueue to build a multi-tenant batch service with quotas and a hierarchy for sharing resources among teams in your organization. Based on the available quotas, Kueue decides when jobs should wait and when and where they should run. Kueue works in combination with standard kube-scheduler, cluster-autoscaler, and the rest of the Kubernetes ecosystem. This combination allows Kueue to run both on-prem and in the cloud, where resources can be heterogeneous, fungible, and dynamically provisioned. -
7
Kuma
The multi-zone service mesh for containers, Kubernetes and VMs
Kuma is a modern Envoy-based service mesh that can run on every cloud, in a single or multi-zone capacity, across both Kubernetes and VMs. Thanks to its broad universal workload support, combined with native support for Envoy as its data plane proxy technology (but with no Envoy expertise required), Kuma provides modern L4-L7 service connectivity, discovery, security, observability, routing, and more across any service on any platform, databases included. Easy to use, with built-in service mesh policies for security, traffic control, discovery, observability, and more, Kuma ships with advanced multi-zone and multi-mesh support that automatically enables cross-zone communication across different clusters and clouds, and automatically propagates service mesh policies across the infrastructure. Kuma is currently being adopted by enterprise organizations around the world to support distributed service meshes across the application teams, on both Kubernetes and VMs. -
8
NVIDIA AI Cluster Runtime (AICR)
Tooling for optimized and reproducible GPU-accelerated AI runtime
NVIDIA AI Cluster Runtime (AICR) is an emerging project within NVIDIA’s AI infrastructure ecosystem focused on enabling advanced AI compute and runtime workflows, though publicly available documentation remains limited. Based on its positioning within NVIDIA’s repositories, it is designed to support scalable AI runtime environments, potentially addressing challenges related to orchestration, resource management, or reproducible AI execution. The project likely aligns with NVIDIA’s broader strategy of building modular infrastructure layers that integrate with GPU-accelerated workloads and cloud-native systems. It appears to emphasize automation, consistency, and performance optimization across AI pipelines, potentially targeting enterprise and research use cases. Given NVIDIA’s ecosystem, it may also integrate with containerized environments, Kubernetes, or other orchestration frameworks. -
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ChaosBlade
An easy to use and powerful chaos engineering experiment toolkit
ChaosBlade is an Alibaba open source experimental injection tool that follows the principles of chaos engineering and chaos experimental models to help enterprises improve the fault tolerance of distributed systems and ensure business continuity during the process of enterprises going to cloud or moving to cloud-native systems. Chaosblade is an internal open-source project of MonkeyKing. It is based on Alibaba's nearly ten years of failure testing and drill practice and combines the best ideas and practices of the Group's businesses. -
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10
Volcano
A Cloud Native Batch System (Project under CNCF)
Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with. Volcano builds upon a decade and a half of experience running a wide variety of high-performance workloads at scale using several systems and platforms, combined with best-of-breed ideas and practices from the open-source community. Until June 2021, Volcano has been widely used around the world at a variety of industries such as Internet/Cloud/Finance/ Manufacturing/Medical. More than 20 companies or institutions are not only end users but also active contributors. -
11
Strimzi
Apache Kafka® running on Kubernetes
Strimzi provides a way to run an Apache Kafka cluster on Kubernetes in various deployment configurations. Strimzi provides a way to run an Apache Kafka cluster on Kubernetes in various deployment configurations. For development, it’s easy to set up a cluster in Minikube in a few minutes. For production you can tailor the cluster to your needs, using features such as rack awareness to spread brokers across availability zones, and Kubernetes taints and tolerations to run Kafka on dedicated nodes. You can expose Kafka outside Kubernetes using NodePort, Load balancer, Ingress and OpenShift Routes, depending on your needs, and these are easily secured using TLS. The Kube-native management of Kafka is not limited to the broker. You can also manage Kafka topics, users, Kafka MirrorMaker and Kafka Connect using Custom Resources. This means you can use your familiar Kubernetes processes and tooling to manage complete Kafka applications. -
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cri-dockerd
dockerd as a compliant Container Runtime Interface for Kubernetes
This adapter provides a shim for Docker Engine that lets you control Docker via the Kubernetes Container Runtime Interface. Mirantis and Docker have agreed to partner to maintain the shim code standalone outside Kubernetes, as a conformant CRI interface for the Docker Engine API. For Mirantis customers, that means that Docker Engine’s commercially supported version, Mirantis Container Runtime (MCR), will be CRI compliant. This means that you can continue to build Kubernetes based on the Docker Engine as before, just switching from the built-in docker shim to the external one. Mirantis and Docker intend to work together to make sure it continues to work as well as before and that it passes all the conformance tests and continues to work just like the built-in version did. Mirantis will be using this in Mirantis Kubernetes Engine, and Docker will continue to ship this shim in Docker Desktop. -
13
KServe
Standardized Serverless ML Inference Platform on Kubernetes
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and Canary Rollouts to your ML deployments. It enables a simple, pluggable, and complete story for Production ML Serving including prediction, pre-processing, post-processing and explainability. KServe is being used across various organizations. -
14
GoDoxy
High-performance reverse proxy and container orchestrator
GoDoxy is a high-performance reverse proxy and container orchestrator tailored for self-hosting environments, blending automated routing with a user-friendly web interface and advanced traffic control. Written in Go, it automatically discovers services (like Docker containers) and generates routes based on configuration or container labels, letting you expose and secure apps with minimal manual routing. GoDoxy includes features like ACL control, automatic SSL certificate management with Let’s Encrypt, support for HTTP, TCP/UDP forwarding, and integration points for OpenID Connect authentication and forward auth, making it highly versatile for modern home labs and self-hosted stacks. Its WebUI provides dashboard views of routes, container stats, and real-time logs, while optional idle-sleep controls let you conserve resources by pausing inactive services. It fills the gap between simple reverse proxies and full-featured orchestrators with a focus on automation and live management. -
15
Harbor
An open source trusted cloud native registry project that stores
Harbor is an open-source trusted cloud native registry project that stores, signs, and scans content. Harbor extends the open-source Docker Distribution by adding the functionalities usually required by users such as security, identity and management. Having a registry closer to the build-and-run environment can improve the image transfer efficiency. Harbor supports replication of images between registries, and also offers advanced security features such as user management, access control and activity auditing. Harbor is hosted by the Cloud Native Computing Foundation (CNCF). If you are an organization that wants to help shape the evolution of cloud native technologies, consider joining the CNCF. Cloud native registry: With support for both container images and Helm charts, Harbor serves as registry for cloud native environments like container runtimes and orchestration platforms. -
16
Podman Desktop
A graphical tool for developing on containers and Kubernetes
Podman Desktop is an open source graphical tool enabling you to seamlessly work with containers and Kubernetes from your local environment. Podman Desktop installs, configures, and keeps Podman up to date on your local environment. It provides a system tray, to check status and interact with your container engine without losing focus from other tasks. The desktop application provides a dashboard to interact with containers, images, pods, and volumes but also configures your environment with your OCI registries and network settings. Podman Desktop also provides capabilities to connect and deploy pods to Kubernetes environments. -
17
Ceph CSI
CSI driver for Ceph
Ceph CSI plugins implement an interface between a CSI-enabled Container Orchestrator (CO) and Ceph clusters. They enable dynamically provisioning Ceph volumes and attaching them to workloads. For details about the configuration and deployment of the RBD plugin, please refer rbd doc and for the CephFS plugin configuration and deployment please refer cephFS doc. -
18
Moby
Project for the container ecosystem to assemble containe-based systems
An open framework to assemble specialized container systems without reinventing the wheel. Moby is an open framework created by Docker to assemble specialized container systems without reinventing the wheel. It provides a “lego set” of dozens of standard components and a framework for assembling them into custom platforms. At the core of Moby is a framework to assemble specialized container systems which provides a library of containerized components for all vital aspects of a container system, OS, container runtime, orchestration, infrastructure management, networking, storage, security, build, image distribution, etc. Tools to assemble the components into runnable artifacts for a variety of platforms and architectures: bare metal (both x86 and Arm); executables for Linux, Mac and Windows; VM images for popular cloud and virtualization providers. -
19
PaaSTA
An open, distributed platform as a service
PaaSTA is a highly-available, distributed system for building, deploying, and running services using containers and Kubernetes. PaaSTA has been running production services at Yelp since 2016. It was originally designed to run on top of Apache Mesos but has subsequently been updated to use Kubernetes. Over time the features and functionality that PaaSTA provides have increased but the principal design remains the same. PaaSTA aims to take a declarative description of the services that teams need to run and then ensures that those services are deployed safely, efficiently, and in a manner that is easy for the teams to maintain. Rather than managing Kubernetes YAML files, PaaSTA provides a simplified schema to describe your service and in addition to configuring Kubernetes it can also configure other infrastructure tools to provide monitoring, logging, cost management etc. -
20
Robusta
Kubernetes observability and automation
Keep your Kubernetes microservices up and running. Connect your existing Prometheus, gain 360° observability. Robusta is both an automation engine for Kubernetes and a multi-cluster observability platform. Robusta is commonly used alongside Prometheus, but other tools are supported too. By listening to all the events in your cluster, Robusta can tell you why alerts fired, what happened at the same time, and what you can do about it. Robusta can either improve your existing alerts or be used to define new alerts triggered by APIServer changes. -
21
Robusta KRR
Prometheus-based Kubernetes Resource Recommendations
Robusta KRR (Kubernetes Resource Recommender) is a CLI tool for optimizing resource allocation in Kubernetes clusters. It gathers pod usage data from Prometheus and recommends requests and limits for CPU and memory. This reduces costs and improves performance. -
22
DockStation
Application to managing projects based on Docker
DockStation is a developer-centric application to managing projects based on Docker. Instead of lots of CLI commands you can monitor, configure, and manage services and containers using just a GUI. The DockStation helps to manage projects and container settings, e.g. bind a local host to a project, simple version changing, map ports, assign and reassign environment variables, change entry point and start command instructions, configure volumes, quick access to image documentation, quick services containers cleanup and a lot of other useful functionality. The application helps to manage and observe remote containers. We provide many tools, such as as log monitoring, searching logs, grouping, running tools, and getting container info. We also provide amazing authorization tools for remote connections. -
23
Kruise
Automated management of large-scale applications on Kubernetes
OpenKruise is an extended component suite for Kubernetes, which mainly focuses on automated management of large-scale applications, such as deployment, upgrade, ops, and availability protection. Most features provided by OpenKruise are built primarily based on CRD extensions. They can work in pure Kubernetes clusters without any other dependencies. Kubernetes itself has already provided some features for application deployment and management, such as some basic Workloads. However, it is far from enough to deploy and manage lots of applications in large-scale production clusters. OpenKruise can be easily installed in any Kubernetes cluster. It makes up for defects of Kubernetes, including but not limited to application deployment, upgrade, protection, and operations. -
24
OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
Run ML/AI or any type of workload with optimal performance and infrastructure cost. OptScale allows ML teams to multiply the number of ML/AI experiments running in parallel while efficiently managing and minimizing costs associated with cloud and infrastructure resources. OptScale MLOps capabilities include ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments, experiment tracking, and more. The solution enables ML/AI engineers to run automated experiments based on datasets and hyperparameter conditions within the defined infrastructure budget. Certified FinOps solution with the best cloud cost optimization engine, providing rightsizing recommendations, Reserved Instances/Savings Plans, and dozens of other optimization scenarios. With OptScale, users get complete cloud resource usage transparency, anomaly detection, and extensive functionality to avoid budget overruns. -
25
Sysbox
Open-source, next-generation "runc" that empowers rootless containers
An open-source, next-generation "runc" that empowers rootless containers to run workloads such as Systemd, Docker, and Kubernetes, just like VMs. Think of it as a "container supercharger": it enables your existing container managers/orchestrators (e.g., Docker, Kubernetes, etc.) to deploy containers that have hardened isolation and can run almost any workload that runs in VMs. Sysbox does this by making the container resemble a VM-like environment as much as possible, using advanced OS virtualization techniques. Unlike alternative runtimes such as Kata and KubeVirt, it does not use VMs. This makes it easier to use (particularly in cloud environments by avoiding nested virtualization), although it does not provide the level of isolation that VM-based runtimes do.
