Alumio performance insights
Our integration platform has defined a performance for model for businesses of all sizes, with a clear insight into the potential capabilities.
Delivering peak performance during peak sales!
Organizations across industries trust the Alumio iPaaS (integration Platform as a Service) to deliver great uptime, process thousands of transactions per second, and support thousands of cloud-native Alumio environments. While streaming real-time integrations, the platform enables business process orchestration, delivers high-speed data transfers, and can scale to meet high data demands!
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performance results
The following performance insights gathered by Alumio experts include results from asynchronous and synchronous processing scenarios. This involved testing three scenarios importing data, exporting data, and synchronously importing and exporting data.
The performance report has been compiled after rigorous testing with the default 'Professional edition' hosting setup - Alumio version 3.13.0, 8GB, 2 cores. The testing was carried out in the region eu-west-2a (London).
Test 1: Asynchronous approach - importing data (creating tasks)
In this scenario, a data seeder was utilized to create tasks within Alumio. We eliminated the influence of external factors by utilizing a data seeder instead of an API call, database query, GraphQL query, etc. This allowed us to measure the overhead added by Alumio.The following components were used while conducting the test:
An incoming configuration, a range Subscriber (to create 1000 entities per run), an entity transformer, a data filter, a move using a pattern (data transformer), and a value setter.
An incoming configuration, a range Subscriber (to create 1000 entities per run), an entity transformer, a data filter, a move using a pattern (data transformer), and a value setter.
Test 2: Asynchronous approach - exporting data (creating tasks)
In this scenario, a storage publisher was utilized to process tasks within Alumio. This time, we eliminated the influence of external factors by utilizing a storage publisher instead of an API call, database query, GraphQL query, etc. Since each task gets processed sequentially, there was no need for optimizations. However, it is possible to further improve the performance by executing bulk processing or upgrading the hosting environment.
The following components were used: an outgoing configuration, a storage publisher (to process 1000 tasks sequentially per run), an entity transformer, a data filter, a move using a pattern (data transformer), and a value setter.
The following components were used: an outgoing configuration, a storage publisher (to process 1000 tasks sequentially per run), an entity transformer, a data filter, a move using a pattern (data transformer), and a value setter.
Test 3: Synchronous approach - importing & exporting data simultaneously
In this scenario, a data seeder was utilized to create tasks within Alumio. We eliminated the influence of external factors by utilizing a data seeder instead of an API call, database query, GraphQL query, etc. With this approach, we were able to measure the overhead added by Alumio.
The following components were used while conducting the test: an incoming configuration, a range Subscriber (to create 1000 entities per run), an entity transformer, a data filter, a move using a pattern (data transformer), and a value setter.
The following components were used while conducting the test: an incoming configuration, a range Subscriber (to create 1000 entities per run), an entity transformer, a data filter, a move using a pattern (data transformer), and a value setter.
An overview of the new performance results
Asynchronous Approach
The average time taken for 1000 tasks: 42s 776ms
Median time taken for 1000 tasks: 44s 490ms
Average tasks per second: 23.378
Median tasks per second: 22.478
Synchronous Approach
The average time taken for 1000 tasks: 4s 466ms
Median time taken for 1000 tasks: 4s 374 ms
Average tasks per second: 223.914
Median tasks per second: 228.623
Reliable platform performance
at peak moment
A proven integration solution for high-traffic
Seasonal sales, marketing campaigns, and new product launches can lead to peak data loads. The Alumio iPaaS delivers horizontally and vertically scalable high-performance, cloud-native infrastructure, which can easily adapt to accommodate larger transaction volumes. Alumio delivers 99.95%+ uptime, enables data caching and buffering, and provides reactivation procedures.
Scalable integrations
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Designed for high-traffic use cases
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our platform performance!
Network and Infrastructure
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