Apache Aurora vs DC/OS
Overview
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Detailed Comparison
Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation. | Unlike traditional operating systems, DC/OS spans multiple machines within a network, aggregating their resources to maximize utilization by distributed applications. |
Deployment and scheduling of jobs;The abstraction a “job” to bundle and manage Mesos tasks;A rich DSL to define services;Health checking;Failure domain diversity;Instant provisioning | High Resource Utilization;Mixed Workload Colocation;Container Orchestration;Resource Isolation;Stateful Storage;Package Repositories;Public Cloud;Private Cloud;On-Premise;Command Line Interface;Web Interface;Elastic Scalability;High Availability;Zero Downtime Upgrades;Service Discovery;Load Balancing;Production-Ready |
Statistics | |
GitHub Stars - | GitHub Stars 2.4K |
GitHub Forks - | GitHub Forks 488 |
Stacks 69 | Stacks 109 |
Followers 96 | Followers 180 |
Votes 0 | Votes 12 |
Pros & Cons | |
No community feedback yet | Pros
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Integrations | |
What are some alternatives to Apache Aurora, DC/OS?
Nomad
Nomad is a cluster manager, designed for both long lived services and short lived batch processing workloads. Developers use a declarative job specification to submit work, and Nomad ensures constraints are satisfied and resource utilization is optimized by efficient task packing. Nomad supports all major operating systems and virtualized, containerized, or standalone applications.
Apache Mesos
Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers.
Mesosphere
Mesosphere offers a layer of software that organizes your machines, VMs, and cloud instances and lets applications draw from a single pool of intelligently- and dynamically-allocated resources, increasing efficiency and reducing operational complexity.
Gardener
Many Open Source tools exist which help in creating and updating single Kubernetes clusters. However, the more clusters you need the harder it becomes to operate, monitor, manage and keep all of them alive and up-to-date. And that is exactly what project Gardener focuses on.
YARN Hadoop
Its fundamental idea is to split up the functionalities of resource management and job scheduling/monitoring into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM).
Atmosly
AI-powered Kubernetes platform for developers & DevOps. Deploy applications without complexity, with intelligent automation and one-click environments.
kops
It helps you create, destroy, upgrade and maintain production-grade, highly available, Kubernetes clusters from the command line. AWS (Amazon Web Services) is currently officially supported, with GCE in beta support , and VMware vSphere in alpha, and other platforms planned.
Elastic Apache Mesos
Elastic Apache Mesos is a web service that automates the creation of Apache Mesos clusters on Amazon Elastic Compute Cloud (EC2). It provisions EC2 instances, installs dependencies including Apache ZooKeeper and HDFS, and delivers you a cluster with all the services running.
Peloton
A Unified Resource Scheduler to co-schedule mixed types of workloads such as batch, stateless and stateful jobs in a single cluster for better resource utilization. Designed for web-scale companies with millions of containers and tens of thousands of nodes.
Kocho
Kocho provides a set of mechanisms to bootstrap AWS nodes that must follow a specific configuration with CoreOS. It sets up fleet meta-data, and patched versions of fleet, etcd, and docker when using Yochu.
