A hosted background job solution that lets you run your containers with dynamic scale, detailed analytics and world class customer support. Run short lived containers quickly, or even containers needing to work across multiple days. Whether it's a one-off job, or one that needs 1000's of workers running in parallel, we've got you covered.
Containerize your background tasks with confidence
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Flexible Deployment Options
Run your containers on our shared infrastructure.
Dedicated hardware for your workloads. A great option when you need consistent performance and throughput. Our autoscale technology helps you scale up and down based on your usage.
You run workers on your own hardware, and we take care of the authentication, scheduling, and everything else. If you have access to your own infrastructure and/or have higher security needs, this is often a great fit.
Run IronWorker in-house. When compliance and security is paramount, an On-Premise install is key. The top deployment choice for our customers in the healthcare and government agencies.
Grocery stores are rapidly pushing into digitized customer analytics to better understand marketing strategies. Iron.io integrated with Whole Foods to provide an ETL framework enabling big data analysis to drive customer insights. With the auto-scaling optionality of Iron Worker, allowing large tasks to be broken into small pieces and tackled by many Workers operating in parallel, Whole Foods has the firepower to ensure no data challenge is too complex to tackle.
Gain greater compute insights of your tasks in real time to better optomize resource allocation and scheduling. Track tasks experiencing greater usage to understand the changing nature of your target audience, and identify opportunities to streamline your compute.
With Worker's redundancy and centralized task queue, your jobs won't fall through the cracks. Iron Worker's intuitive UI lets you schedule your tasks for specific dates and times, set a frequency/delay timer for task repetition, or enable tasks to be processed on demand.
