Cloud-ready event driven architecture
Platform as a service
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The framework reduces system complexity by allowing a declarative approach to complex event processing, with strict inbuilt causality records supporting selection of contextual and related data.
By reducing gaps between specification and implementation, we reduce development and maintenance costs.
The runtime is built from the ground up on cloud-ready technology, and consistent rules in the framework are built around promises that every runtime can keep, no matter the scale.
Dynamic scalability and increased reliability improve capability and reduce platform costs.
The Condense Framework, Light, and Cloud are currently in a developer preview. You can try Condense Light right now! We are working with partners to steer development to ensure a practical, real-world-ready product.
Interested? Tell us about your project at firstname.lastname@example.org
and try the Condense Light preview!
The core features of the Condense Framework are largely complete. As the framework is used, we can ensure that we are choosing sensible defaults and conventions, to help pursue our goal of zero boilerplate.
Effort is being put into testing and dev support features. Using a local proxy for the live domain we expect developers will be able to rerun any historical execution (or entire sequence of executions), and isolated hypotheticals in the debugger.
Condense Light runs in-process using Couchbase as a storage provider.
The final version of Light will likely ship with an alternative storage provider without dependencies.
We are expecting to offer Condense Light as a free product.
Condense Cloud currently runs smoothly on AWS, using EC2, SQS, SNS and Couchbase. It is capable of working in auto-scaling clusters, and the machine image will self-configure itself from S3 and join the cluster.
Effort is going into ease of domain configuration, and remote query.
From the initial prototypes, the Condense Runtime was developed and tested on cloud-ready scalable storage and messaging solutions.
Analytics will be able to provide an overview of domain data, and the graph of execution records, and related data.
Experimental work is being performed on domain analytics. The deep causality information recorded by the framework enables ease of reporting on aggregate business process flow and similar metrics (eg: sales funnel).