Apache Aurora Reviews & Product Details

It is one of easiest coordinator and scheduler service for jobs. Review collected by and hosted on G2.com.

Nothing as such. Everything is fulfilling my needs. Review collected by and hosted on G2.com.

Efficiently distributing tasks across a cluster of machines, Aurora has proven a popular choice for users looking to scale their large deployments. Handling those large-scale demands efficiently, its scalable capabilities have not gone unnoticed.

Aurora prioritizes fault tolerance, boasting a reliable system due to managing failures with its effective mechanisms. It guarantees high availability of tasks and jobs, solidifying its capacity for fault-tolerant execution.

Providing adaptability to different infrastructure setups, Apache Aurora offers flexibility by integrating with varying managers of resources like Apache Mesos or Kubernetes and supporting various storage backends for deployment environments.

Apache Aurora provides a top-notch interface for defining and administering jobs, a feature that users find pretty impressive. This allows for easy management of complex workflows, thanks to the ability to specify job requirements, resource constraints, and dependencies, which give granular control over task execution. Review collected by and hosted on G2.com.

Apache Aurora's bulkiness may not be ideal for small-scale deployments. While the software is meant to cater to large-scale setups, I think it's too complicated and intense for smaller operations with limited resources. Considering your unique requirements, the investment in handling and administering Apache Aurora may not be worth it for modest deployments.

Unlike other orchestration and job scheduling frameworks, Apache Aurora's community and adoption are lower. As a result, limited community support, resources, and third-party integrations may be available to users, especially when compared to more commonly used alternatives. Review collected by and hosted on G2.com.

One of the things that I like best about Apache Aurora is its reliability and high availability. The platform is designed to handle failures gracefully and ensure that our applications are always up and running. This has been especially important for our critical applications, as we can now rest assured that they will be available when our users need them. Additionally, the platform's user-friendly interface and ability to scale up or down as needed have also been major advantages for our team. Overall, I am extremely satisfied with the performance and reliability of Apache Aurora. Review collected by and hosted on G2.com.

One of the things that I dislike about Apache Aurora is that it can be a bit difficult to set up and configure at times. While the platform is relatively easy to use once you get the hang of it, the initial setup process can be a bit overwhelming. Additionally, the documentation and support resources could be improved, as there have been a few instances where I have had difficulty finding the information I needed to solve a specific problem. However, I should note that these issues are relatively minor, and overall I am extremely satisfied with the platform. Review collected by and hosted on G2.com.

I have used various workflow management tools and job schedulers like Marathon, YARN Hadoop. Still, I like using Apache Aurora the most due to its capability to do the heavy lifting for workflows. It can manage resources and resolve dependencies. One can do required configuration management at lower levels also. It helps in doing complex tasks quickly. Review collected by and hosted on G2.com.

It is not suitable for small projects having a small infrastructure. And it has a good level of a learning curve to have good hands-on in it. It is best for big projects with a good number of users and cron jobs but not for small projects with fewer use cases for background jobs. Review collected by and hosted on G2.com.

API AND CLI interaction : It makes easy to connect with scheduler programmatically which makes it easier to connect with external utilities to automate tasks.

Job scheduling:

It allows you to define tasks, dependencies, resource requirements and create complex workflows.

Scalability:

It can handle large scale deployments which makes it robust in handling large amounts of task management. Review collected by and hosted on G2.com.

1. No GUI based management console

2. Dynamic resource allocation

No built-in feature for allocating resources to tasks based on demand.

3. Container orchestration:

Aurora focuses primarily on long-running services and lacks some advanced container management features, such as rolling deployments, health checks, and container networking. Review collected by and hosted on G2.com.

Apache Aurora is a robust and scalable job scheduler, ideal for managing large-scale distributed systems. Its fault-tolerant design ensures high availability, while its user-friendly interface streamlines task management. With powerful features and seamless integration, Aurora excels in orchestrating complex workloads efficiently. A top choice for modern infrastructure management. Review collected by and hosted on G2.com.

Complex setup and configuration can be challenging for newcomers. Limited documentation and community support may hinder troubleshooting. Aurora's learning curve may deter users seeking quick deployment. Review collected by and hosted on G2.com.

Been using Apache Aurora for a long time. The best part of Aurora is the scale at which it can run. Previously we were using some in-house tech long-running data ingestion services. Review collected by and hosted on G2.com.

The major issue was to get this up and running in our infra and make other services compatible to utilise the tech to its full potential. Apart from that, there are some minor bugs which sometimes become a blocker. Review collected by and hosted on G2.com.

Task management is easy and robust with the clusters of machines, and Aurora guarantees the high availability of tasks and jobs, which makes it well-suited for enterprise application deployment. Review collected by and hosted on G2.com.

Unless the jobs are not more extensive, there is no need to use Aurora. Apache Aurora doesn't have GUI based management console, which would have been an efficient way to do the configuration. Review collected by and hosted on G2.com.

Apache Aurora is an exceptional open-source framework that excels in managing scalable and fault-tolerant distributed systems. With its impressive scalability, fault tolerance mechanisms, and powerful job scheduling capabilities, it empowers organizations to build resilient and efficient applications. The API-driven operations and supportive community further enhance its value as a reliable framework for distributed system management. Review collected by and hosted on G2.com.

Some potential challenges with Apache Aurora include its steep learning curve, perceived complexity, lack of built-in GUI, limited language support, and potentially smaller user community compared to other frameworks. However, these factors can vary depending on individual experiences and specific use cases. Review collected by and hosted on G2.com.

Apache Aurora can easily manage my thousands of tasks across a cluster of machines. Apache Aurora provides a rich set of APIs that enable programmatic control as well as, it supports other tools and frameworks, like Apache Mesos. Review collected by and hosted on G2.com.

When I tried to set up Apache, Aurora was very complex to configure. Using Apache Mesos requires or dependence on significant hardware resources. it is de designed for managing long-running only. Review collected by and hosted on G2.com.