apache/mesos 的主要功能有哪些？

apache/mesos 的主要功能包括：Distributed Computing Frameworks, Two-Level Scheduling, Offer-Based Allocation, Multi-Framework Orchestration, Distributed Cluster Management, Distributed Infrastructure Orchestration, Workload Isolation, Resource Isolation。

apache/mesos 有哪些开源替代品？

apache/mesos 的开源替代品包括： dask/dask — Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows… apache/storm — Storm is a distributed stream processing framework designed to execute unbounded computations across a cluster to… baidu/braft — braft is an embeddable C++ library that implements the Raft consensus algorithm, providing a distributed consensus… ltsopensource/light-task-scheduler — Light Task Scheduler is a distributed job scheduling and workflow orchestration platform designed for managing… hashicorp/raft — This is a Raft consensus library and distributed consensus engine implemented in Go. It provides the primitives… linkedin/school-of-sre — This project is a comprehensive educational resource and curriculum focused on site reliability engineering,…

Mesos

Apache Mesos 是一个分布式系统内核和集群资源管理器，抽象了节点池中的 CPU、内存和存储。它作为一个分布式基础设施编排器，提供了一个在共享物理或虚拟机器集上运行多个编排框架的层。

该系统充当资源隔离引擎，将共享集群划分为隔离的容器以并发运行各种工作负载。它实现了多框架编排，允许不同的分布式应用框架共享单个基础设施，从而最大化硬件利用率。

该项目涵盖了大规模计算分发和分布式集群管理。其功能包括管理分布式资源，并跨多个应用隔离计算能力，以防止干扰并确保共享服务器上的稳定性能。

Features

Distributed Computing Frameworks - Provides a distributed infrastructure for running multiple computing frameworks across networked machines.
Two-Level Scheduling - Implements a two-level scheduling mechanism that delegates task launching to individual frameworks.
Offer-Based Allocation - Distributes cluster resources by offering available CPU and memory to frameworks for acceptance or rejection.
Multi-Framework Orchestration - Supports running several different orchestration frameworks on a single shared infrastructure.
Distributed Cluster Management - Manages a pool of shared computing resources across multiple nodes to ensure efficient hardware utilization.
Distributed Infrastructure Orchestration - Provides a layer for running multiple orchestration frameworks on a shared set of physical or virtual machines.
Workload Isolation - Divides a shared cluster into isolated containers to run diverse workloads concurrently without interference.
Resource Isolation - Partitions system resources across applications to prevent interference and maintain stable performance.
Heartbeat Monitors - Monitors worker node availability and cluster health via periodic heartbeat signals between master and agents.
Distributed Systems Kernels - Abstracts CPU, memory, and storage across a pool of nodes to function as a distributed systems kernel.
Namespace-Based Isolation - Implements resource isolation using Linux kernel namespaces and control groups to prevent application interference.
Cluster Resource Managers - Acts as a cluster resource manager that provisions and scales compute power across diverse infrastructure.
Cluster Resource Isolation - Provides strict isolation of compute resources to allow multiple frameworks to run concurrently on shared hardware.
Multi-Framework Orchestration - Enables multiple orchestration frameworks to share a single physical infrastructure to maximize hardware utilization.
Replicated State Machines - Maintains consistent cluster state across multiple master nodes using a distributed consensus algorithm.
Framework Registrations - Allows different orchestration engines to connect to the cluster runtime dynamically without restarting the master.
Distributed Compute Environments - Provides a distributed compute environment for executing workloads across a vast network of servers.
Container Orchestration - Distributed systems kernel for resource management.
Workload Orchestration and Scheduling - Distributed systems kernel for resource abstraction.

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Mesos

Features

Distributed Computing Frameworks - Provides a distributed infrastructure for running multiple computing frameworks across networked machines.
Two-Level Scheduling - Implements a two-level scheduling mechanism that delegates task launching to individual frameworks.
Offer-Based Allocation - Distributes cluster resources by offering available CPU and memory to frameworks for acceptance or rejection.
Multi-Framework Orchestration - Supports running several different orchestration frameworks on a single shared infrastructure.
Distributed Cluster Management - Manages a pool of shared computing resources across multiple nodes to ensure efficient hardware utilization.
Distributed Infrastructure Orchestration - Provides a layer for running multiple orchestration frameworks on a shared set of physical or virtual machines.
Workload Isolation - Divides a shared cluster into isolated containers to run diverse workloads concurrently without interference.
Resource Isolation - Partitions system resources across applications to prevent interference and maintain stable performance.
Heartbeat Monitors - Monitors worker node availability and cluster health via periodic heartbeat signals between master and agents.
Distributed Systems Kernels - Abstracts CPU, memory, and storage across a pool of nodes to function as a distributed systems kernel.
Namespace-Based Isolation - Implements resource isolation using Linux kernel namespaces and control groups to prevent application interference.
Cluster Resource Managers - Acts as a cluster resource manager that provisions and scales compute power across diverse infrastructure.
Cluster Resource Isolation - Provides strict isolation of compute resources to allow multiple frameworks to run concurrently on shared hardware.
Multi-Framework Orchestration - Enables multiple orchestration frameworks to share a single physical infrastructure to maximize hardware utilization.
Replicated State Machines - Maintains consistent cluster state across multiple master nodes using a distributed consensus algorithm.
Framework Registrations - Allows different orchestration engines to connect to the cluster runtime dynamically without restarting the master.
Distributed Compute Environments - Provides a distributed compute environment for executing workloads across a vast network of servers.
Container Orchestration - Distributed systems kernel for resource management.
Workload Orchestration and Scheduling - Distributed systems kernel for resource abstraction.

Mesos 的开源替代方案

相似的开源项目，按与 Mesos 的功能重合度排序。

dask/dask
dask/dask
13,746在 GitHub 上查看
Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows from single machines to large clusters. It functions as a cluster resource manager that orchestrates computational logic by representing tasks and their dependencies as directed acyclic graphs. This architecture allows the system to automate the distribution of workloads across available hardware while managing complex execution requirements. The project distinguishes itself through a lazy evaluation engine that defers data operations until they are explicitly requested, enabl
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baidu/braft
baidu/braft
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braft is an embeddable C++ library that implements the Raft consensus algorithm, providing a distributed consensus engine for building fault-tolerant, replicated state machines. At its core, it manages leader election, log replication, cluster membership changes, and state machine synchronization across a cluster of nodes, ensuring strong consistency and data durability even in the face of node failures. The library distinguishes itself through a comprehensive set of mechanisms for reliable distributed coordination. It uses a randomized timeout-based leader election process with term manageme
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apache/storm
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Storm is a distributed stream processing framework designed to execute unbounded computations across a cluster to process real-time data streams. It functions as a data pipeline orchestrator that allows users to define and deploy declarative data flow graphs connecting streaming sources to processing components. The system operates as a multi-tenant distributed compute engine that isolates workloads and limits resource usage across shared clusters using dedicated pools and access control. It is also a secure distributed processing engine that employs encrypted node communication and SSL-secur
Java
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hashicorp/raft
hashicorp/raft
9,037在 GitHub 上查看
This is a Raft consensus library and distributed consensus engine implemented in Go. It provides the primitives necessary to build fault-tolerant distributed services by implementing a replicated state machine that ensures a group of servers agree on a shared system state through leader election and log replication. The project distinguishes itself through a pluggable architecture for storage backends and snapshot storage, decoupling the consensus logic from physical persistence. It includes specialized mechanisms for leadership transfer, protocol version management to support rolling upgrade
Go
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常见问题解答

apache/mesos 是做什么的？