Apache Aurora vs Magneto
Overview
Share your Stack
Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
CLI (Node.js)
Manual
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. | Magneto was built by Automation Engineers for Automation Engineers out of necessity for a mobile centric test automation framework that's easy to setup, run and utilize. |
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 | Log watching, skipping, tagging, blocking, screenshots, videos and even an interactive shell. |
Statistics | |
Stacks 69 | Stacks 14 |
Followers 96 | Followers 27 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Apache Aurora, Magneto?
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.
Appium
Appium is an open source test automation framework for use with native, hybrid, and mobile web apps. It drives iOS and Android apps using the WebDriver protocol. Appium is sponsored by Sauce Labs and a thriving community of open source developers.
DC/OS
Unlike traditional operating systems, DC/OS spans multiple machines within a network, aggregating their resources to maximize utilization by distributed applications.
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.
EarlGrey
EarlGrey is a native iOS UI automation test framework that enables you to write clear, concise tests. With the EarlGrey framework, you have access to enhanced synchronization features. EarlGrey automatically synchronizes with the UI, network requests, and various queues; but still allows you to manually implement customized timings, if needed.
