Designing workflow


A workflow (also called as “pipeline”) consists of tasks and a task is realized by Operator.

MONAI Deploy App SDK has useful built-in operators you can reuse (the list of operators would keep growing with your contribution!).

If the built-in operators do not work for you, you can implement your operators. We will guide you throughout the sections in this document.

A workflow is a form of a graph which is usually a Directed Acyclic Graph (DAG).

One-operator workflow

The simplest form of the workflow would be a one-operator workflow.

%%{init: {"theme": "base", "themeVariables": { "fontSize": "16px"}} }%% classDiagram direction LR class MyOperator { <in>input_path : DISK output_path(out) DISK }

⠀⠀A one-operator workflow

Above graph shows an Operator (named MyOperator) that load file from the input_path in the local file system (DISK type), process the file, and write the processed data into output_path in the local file system (DISK type).

In the workflow description, DISK means a Storage Type. If the input or the output data is supposed in memory, you can use IN_MEMORY type.

Linear workflow

Let’s see another workflow example whose operators are connected linearly.

%%{init: {"theme": "base", "themeVariables": { "fontSize": "16px"}} }%% classDiagram direction LR Task1 --|> Task2 : output1...input2 Task2 --|> Task3 : output2...input3 class Task1 { <in>input1 : DISK output1(out) IN_MEMORY } class Task2 { <in>input2 : IN_MEMORY output2(out) IN_MEMORY } class Task3 { <in>input3 : IN_MEMORY output3(out) DISK }

⠀⠀A linear workflow

In this example, Task1 accepts its input (path) from the disk, and the processed data is set to output1 of Task1 in memory. The memory object (output1) is passed to Task2 as an input (input2). Similarly, output2 of Task2 is passed to Task3 as input3 and the final result would be saved in a file in the folder where output3 is referring.

Data Type and Domain Object

In addition to the Storage Type, each input or output of an operator has another property – Data Type.

Data Type specifies a Type Hint of an input/output of an operator and the type of value in the input/output is verified in execution time.

Data Type can be a type hint such as str, Any, Union, List[Union[str, int]].

There are built-in data types that MONAI Deploy App SDK supports which are called Domain Objects.

Domain Object classes inherits Domain class and they provides a useful set of standard input/output data types such as DataPath, Image, DicomStudy, and so on.

Those domain object classes are controllable by the SDK so can be optimized further in the future.

The full list of Domain Object classes are available here.


The functionality of mapping DataPath to the input and output of root and leaf operator(s) is absent starting with Release V0.6 of this App SDK, due to the move to rely on Holoscan SDK. It is planned to be re-introduced at a later time. For the time being, the application's input and output folders are passed to the root and leaf operators' constructor, as needed.

Among those classes, DataPath data type is special.

  • If an operator in the workflow graph is a root node (a node with no incoming edges) and its input’s (<data type>, <storage type>) == (DataPath, DISK), the input path given by the user during the execution would be mapped into the input of the operator.

  • If an operator in the workflow graph is a leaf node (a node with no outgoing edges) and its output’s (<data type>, <storage type>) == (DataPath, DISK), the output path given by the user during the execution would be mapped into the output of the operator.

In A linear workflow example above, if the workflow is processing the image data, operators’ input/output specification would look like this:

Note that input1 and output3 are DataPath type with IOType.DISK. Those paths are mapped into input and output paths given by the user during the execution.


The above workflow graph is the same as a Simple Image Processing App. Please look at the tutorial to see how such an application can be made with MONAI Deploy App SDK.

Complex Workflows

Multiple inputs and outputs

You can design a complex workflow like below that some operators have multi-inputs or multi-outputs.

%%{init: {"theme": "base", "themeVariables": { "fontSize": "16px"}} }%% classDiagram direction TB Reader1 --|> Processor1 : image...{image1,image2}\nmetadata...metadata Reader2 --|> Processor2 : roi...roi Processor1 --|> Processor2 : image...image Processor2 --|> Processor3 : image...image Processor2 --|> Notifier : image...image Processor1 --|> Writer : image...image Processor3 --|> Writer : seg_image...seg_image class Reader1 { <in>input_path : DISK image(out) IN_MEMORY metadata(out) IN_MEMORY } class Reader2 { <in>input_path : DISK roi(out) IN_MEMORY } class Processor1 { <in>image1 : IN_MEMORY <in>image2 : IN_MEMORY <in>metadata : IN_MEMORY image(out) IN_MEMORY } class Processor2 { <in>image : IN_MEMORY <in>roi : IN_MEMORY image(out) IN_MEMORY } class Processor3 { <in>image : IN_MEMORY seg_image(out) IN_MEMORY } class Writer { <in>image : IN_MEMORY <in>seg_image : IN_MEMORY output_image(out) DISK } class Notifier { <in>image : IN_MEMORY }

⠀⠀A complex workflow