Tyger is a framework for remote signal processing. It enables reliable transmission of data to remote computational resources, where the data can be processed and transformed as it streams in. It was designed for streaming raw signal data from an MRI scanner to the cloud, where much more compute power is typically available to reconstruct images from the signal. However, its application is not limited to MRI and it could be used in a variety of domains and scenarios.
At a high level, Tyger is a REST API that abstracts over an Azure Kubernetes
cluster and Azure Blob storage. Tyger can also be installed locally, requiring
only Docker. Future plans include support for on-prem Kubernetes deployments. It
includes a command-line tool, tyger, for easy interaction with this API. Users
specify signal processing code as a container image.
Tyger is centered around stream processing, allowing data to be processed as it is acquired, without needing to wait for the complete dataset. It is based on an asynchronous model, where data producers do not need to wait for the availability of data consumers. Additionally, data consumers can operate during or after data production, since data streams are Write Once Read Many (WORM).
Signal processing code can be written in any language, as long as it can read and write to named pipes (which are file-like but do not support random access). There is no SDK, meaning you can develop, test, and debug code on your laptop using only files, without Tyger dependencies. Then, you build a container image to run the same code in the cloud with Tyger.
Tyger is designed to be both powerful and easy to use. Its implementation is also simple, since a lot of the heavy lifting is done by proven technologies like Kubernetes and Azure Blob Storage.
See the documentation at https://microsoft.github.io/tyger
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