What is Apache Aurora and what are its top alternatives?
Top Alternatives to Apache Aurora
- Kubernetes
Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. ...
- Marathon
Marathon is an Apache Mesos framework for container orchestration. Marathon provides a REST API for starting, stopping, and scaling applications. Marathon is written in Scala and can run in highly-available mode by running multiple copies. The state of running tasks gets stored in the Mesos state abstraction. ...
- Apache Mesos
Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers. ...
- 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. ...
- 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). ...
- DC/OS
Unlike traditional operating systems, DC/OS spans multiple machines within a network, aggregating their resources to maximize utilization by distributed applications. ...
- 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. ...
- 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. ...
Apache Aurora alternatives & related posts
Kubernetes
- Leading docker container management solution164
- Simple and powerful128
- Open source106
- Backed by google76
- The right abstractions58
- Scale services25
- Replication controller20
- Permission managment11
- Supports autoscaling9
- Cheap8
- Simple8
- Self-healing6
- No cloud platform lock-in5
- Promotes modern/good infrascture practice5
- Open, powerful, stable5
- Reliable5
- Scalable4
- Quick cloud setup4
- Cloud Agnostic3
- Captain of Container Ship3
- A self healing environment with rich metadata3
- Runs on azure3
- Backed by Red Hat3
- Custom and extensibility3
- Sfg2
- Gke2
- Everything of CaaS2
- Golang2
- Easy setup2
- Expandable2
- Steep learning curve16
- Poor workflow for development15
- Orchestrates only infrastructure8
- High resource requirements for on-prem clusters4
- Too heavy for simple systems2
- Additional vendor lock-in (Docker)1
- More moving parts to secure1
- Additional Technology Overhead1
related Kubernetes posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.
Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.
After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...
Marathon
- High Availability1
- Powerful UI1
- Service Discovery1
- Load Balancing1
- Health Checks1
related Marathon posts
- Easy scaling21
- Web UI6
- Fault-Tolerant2
- Elastic Distributed System1
- High-Available1
- Not for long term1
- Depends on Zookeeper1
related Apache Mesos posts
Docker containers on Mesos run their microservices with consistent configurations at scale, along with Aurora for long-running services and cron jobs.
- Built in Consul integration7
- Easy setup6
- Bult-in Vault integration4
- Built-in federation support3
- Self-healing2
- Autoscaling support2
- Bult-in Vault inegration1
- Stable1
- Simple1
- Nice ACL1
- Managable by terraform1
- Open source1
- Multiple workload support1
- Flexible1
- Easy to start with3
- HCL language for configuration, an unpopular DSL1
- Small comunity1
related Nomad posts
Our backend consists of two major pools of machines. One pool hosts the systems that run our site, manage jobs, and send notifications. These services are deployed within Docker containers orchestrated in Kubernetes. Due to Kubernetes’ ecosystem and toolchain, it was an obvious choice for our fairly statically-defined processes: the rate of change of job types or how many we may need in our internal stack is relatively low.
The other pool of machines is for running our users’ jobs. Because we cannot dynamically predict demand, what types of jobs our users need to have run, nor the resources required for each of those jobs, we found that Nomad excelled over Kubernetes in this area.
We’re also using Helm to make it easier to deploy new services into Kubernetes. We create a chart (i.e. package) for each service. This lets us easily roll back new software and gives us an audit trail of what was installed or upgraded.
- Batch processing with commodity machine1
related YARN Hadoop posts
DC/OS
- Easy to setup a HA cluster5
- Open source3
- Has templates to install via AWS and Azure2
- Easy Setup1
- Easy to get services running and operate them1
related DC/OS posts
related kops posts
- Devops6