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https://issues.apache.org/jira/browse/AIRAVATA-991?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13904558#comment-13904558
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Suresh Marru commented on AIRAVATA-991:
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Hi All,
As we work through the API and Data models, we need to determine how simple
application execution (the application itself may be complex process like a
large MPI, but a single invocation) and composite applications (embodied in
workflows) should be handled. There are multiple ways of doing this:
1) Have the API functions separate from workflows to create, launch and get
status and data for a single node application. The API server absorbs the
difference, the rest of the system is agnostic of the simple vs composite
executions and the resulting data.
2) Have two different parallel paths all the way through the system.
3) Have the API functions, data model agnostics, but at the registry level the
data is organized differently for wokrlfows and applications.
4) Within Airavata, keep the entire trace agnostic (except the orchestrator
invoking gfac directly or through interpreter) and expect the clients to do the
heavy lifting.
Thoughts?
> Craft the Airavata 1.0 API
> --------------------------
>
> Key: AIRAVATA-991
> URL: https://issues.apache.org/jira/browse/AIRAVATA-991
> Project: Airavata
> Issue Type: Story
> Components: Airavata API
> Affects Versions: 0.11
> Reporter: Suresh Marru
> Assignee: Suresh Marru
> Fix For: 1.0
>
>
> An important goal for Airavata 1.0 release is to draft a public facing API
> which includes subset of functionality exposed by the internal SPI and
> higher level functions which can be realized by one of more internal
> components.
> Airavata clients have to be abstracted from internal component level details
> and would like to interact through API through higher order method. Some of
> the capabilities include abilities to Register gateways, computational
> credentials, register and manage applications, create, configure and launch
> experiments (binding them to applications/workflows), monitor real-time and
> poll based progress, query for generated data and analyze results.
> These capabilities can be realized by one or more internal Airavata
> components and the API layers abstracts these out and maps appropriately.
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