AppFog (discontinued) vs. AutoSys Workload Automation

It was very good to use in small scale projects. Considering the high end projects with many instances and multi-platform architectures, it is better to test before the application is deployed. I think few of the questions can be general - who are the system users and what size is the application focussing on? How much resources are required? Will the application require any additional services?

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In Informatica or Spark ETL jobs loading data into a Data Warehouse using AutoSys Workload Automation triggers ETL pipelines, monitors completion of jobs and also triggers the power bi report refresh. AutoSys Workload Automation can schedule jobs based on file arrival, and provide alerts if any data loads get failed. A small data team managing greater than 100 jobs. Buying and maintaining AutoSys Workload Automation is overkill in terms of cost, complexity and maintenance does not justify the value

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• Quick deployment of pre-built virtual machines
• Some of the virtual machines also are readily available with a pack of softwares
• Good Stability. Using it as a student, I have never experienced any downtime issues with the projects deployed on AppFog.

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• AutoSys Workload Automation is our scheduler that automates and monitors workflows across all our system reducing manual runs
• Applications which run over multiples systems(cloud, on premise) are coordinated using AutoSys Workload Automation
• AutoSys Workload Automation clustering or failover ensures that workloads continue without any issue.
• AutoSys Workload Automation maintains execution logs and job history, which helps in compliance, audit trails, and root-cause analysis.

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• Though it is good and easy for developers, it lacks operational activities and monitoring tools.
• It is easy to deploy WAR on AppFog with its console but sometimes it can lack on the performance and feasibility.

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• In AutoSys Workload Automation, Workflow and job dependencies are shown in a static way, which makes user difficult to visualize more complex job chains or debug failures in a graphical view.
• Latest schedulers (like Control-M, Airflow) allow more easy workflow design makes user to understand it better, but AutoSys Workload Automation relies heavily on JIL scripts and text-based job definitions.
• AutoSys Workload Automation interface is very slow when searching or filtering over thousand of jobs

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AutoSys Workload Automation is a place to schedule, monitor, and manage thousands of jobs. Time, file arrival, dependencies are much very flexible. Once jobs are set up they run consistently with minimal intervention. AutoSys Workload Automation is powerful but very complex o understand. Mainly for beginners the interface is not user friendly. AutoSys Workload Automation is very useful in terms of job scheduling and automation. AutoSys Workload Automation is also useful for strong logging and reporting purpose. AutoSys Workload Automation has reduced a lot of human efforts and manual processing.

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Primarily because it used to have a good free tier earlier, which it does not anymore. It's simple, and things are available to use. Compared to it's competitors, it does has less features, but that kind of acts in its favor. That adds to the simplicity, and ease of use for a new user.

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In AutoSys Workload Automation, strong legacy presence, proven reliability, slightly simpler for basic scheduling if user already have in-house AutoSys Workload Automation expertise. so we already had investments in AutoSys Workload Automation, trained team, and large numbers of jobs running thus making AutoSys Workload Automation more cost-effective to continue rather than migrate to use AutoSys Workload Automation over Control-M. All our workloads are heavily batch-driven (SAP, ETL) real-time pipelines. AutoSys Workload Automation provides the robustness and enterprise support that Airflow lacks without heavy internal engineering overhead.

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• Our project was deployed with good efficiency and easily accessible.
• The platform was much recommeded across the groups and peers.

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• Critical job process consistently complete on time without delays
• Significant reduction in team effort due to this resources for available for higher-value tasks. Human intervention is reduced due to this incident costs are also reduced.
• Faster incident resolution, improved productivity, and lower downtime.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info