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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Cluster Management
  5. Apache Aurora vs Gardener

Apache Aurora vs Gardener

OverviewComparisonAlternatives

Overview

Apache Aurora
Apache Aurora
Stacks69
Followers96
Votes0
Gardener
Gardener
Stacks16
Followers41
Votes2
GitHub Stars3.3K
Forks540

Apache Aurora vs Gardener: What are the differences?

Developers describe Apache Aurora as "An Apcahe Mesos framework for scheduling jobs, originally developed by Twitter". 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. On the other hand, Gardener is detailed as "Manage Kubernetes clusters across multiple cloud providers". 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.

Apache Aurora and Gardener can be categorized as "Cluster Management" tools.

Apache Aurora and Gardener are both open source tools. Gardener with 1.09K GitHub stars and 151 forks on GitHub appears to be more popular than Apache Aurora with 615 GitHub stars and 231 GitHub forks.

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Detailed Comparison

Apache Aurora
Apache Aurora
Gardener
Gardener

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.

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.

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
Central dashboard for comfortable interaction - enables users to easily keep track of their clusters’ health, and operators to monitor, debug, and analyze the clusters they are responsible for; Command line client - simplifies administrative tasks by introducing easy higher-level abstractions with simple commands that allow to condense and multiplex information & actions from/to a set of seed and shoot clusters
Statistics
GitHub Stars
-
GitHub Stars
3.3K
GitHub Forks
-
GitHub Forks
540
Stacks
69
Stacks
16
Followers
96
Followers
41
Votes
0
Votes
2
Pros & Cons
No community feedback yet
Pros
  • 2
    It works across clouds and on-prem
Integrations
Apache Mesos
Apache Mesos
Vagrant
Vagrant
Kubernetes
Kubernetes

What are some alternatives to Apache Aurora, Gardener?

Nomad

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

Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers.

DC/OS

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

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.

YARN Hadoop

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

Atmosly

AI-powered Kubernetes platform for developers & DevOps. Deploy applications without complexity, with intelligent automation and one-click environments.

kops

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

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

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

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.

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