Open Stack

So getting back to this thread.

I'd like to split it up into a few sections to address the HA and long-running-actions cases, which I believe are 2 seperate (but connected) questions.

=== Long-running actions ===

First, let me describe a little bit about what I believe are the execution models that taskflow currently targets (but is not limited to just targeting in general).

The first execution model I would call the local execution model, this model involves forming tasks and flows and then executing them inside an application, that application is running for the duration of the workflow (although if it crashes it can re-establish the task and flows that it was doing and attempt to resume them). This could also be what openstack projects would call the 'conductor' approach where nova, ironic, trove have a conductor which manages these long-running actions (the conductor is alive/running throughout the duration of these workflows, although it may be restarted while running). The restarting + resuming part is something that openstack hasn't handled so gracefully currently, typically requiring either some type of cleanup at restart (or by operations), with taskflow using this model the resumption part makes it possible to resume from the last saved state (this connects into the persistence model that taskflow uses, the state transitions, how execution occurrs itself...).

The second execution model is an extension of the first, whereby there is still a type of 'conductor' that is managing the life-time of the workflow, but instead of locally executing tasks in the conductor itself tasks are now executed on remote-workers (see http://tinyurl.com/lf3yqe4
). The engine currently still is 'alive' for the life-time of the execution, although the work that it is doing is relatively minimal (since its not actually executing any task code, but proxying those requests to others works). The engine while running does the conducting of the remote-workers (saving persistence details, doing state-transtions, getting results, sending requests to workers...).

As you have already stated, if a task is going to run for 5+ days (some really long hadoop job for example) then these 2 execution models may not be suited for this type of usage due to the current requirement that the engine overseeing the work must be kept alive (since something needs to recieve responses and deal with state transitions and persistence). If the desire is to have a third execution model, one that can handle with extremly long-running tasks without needing an active mechanism that is 'alive' during this process then I believe that would call for the creation of a new engine type in taskflow (https://github.com/openstack/taskflow/tree/master/taskflow/engines) that deals with this use-case. I don't beleive it would be hard to create this engine type although it would involve more complexity than what exists. Especially since there needs to be some 'endpoint' that recieves responses when the 5+ day job actually finishes (so in this manner some type of code must be 'always' running to deal with these responses anyway). So that means there would likely need to be a 'watchdog' process that would always be running that itself would do the state-transitions and result persistence (and so-on), in a way this would be a 'lazy' version of the above first/second execution models.

=== HA ===

So this is an interesting question, and to me is strongly connected to how your engines are executing (and the persistence and state-transitions that they go through while running). Without persistence of state and transitions there is no good way (a bad way of course can be created, by just redoing all the work, but that's not always feasible or the best option) to accomplish resuming in a sane manner and there is also imho no way to accomplish any type of automated HA of workflows. Since taskflow was concieved to manage the states and transitions of tasks and flows it gains the ability to do this resuming but it also gains the ability to automatically provide execution HA to its users.

Let me describe:

When you save the states of a workflow and any intermediate results of a workflow to some database (for example) and the engine (see above models) which is being used (for example the conductor type from above) the application containing that engine may be prone to crashes (or just being powered off due to software upgrades...). Since taskflows key primitives were made to allow for resuming when a crash occurs, it is relatively simple to allow another application (also running a conductor) to resume whatever that prior application was doing when it crashed. Now most users of taskflow don't want to have to do this resumption manually (although they can if they want) so it would be expected that the other versions of that application would be running would automatically 'know' how to 'take-over' the work of the failed application. This is where the concept of the taskflows 'jobboard' (http://tinyurl.com/klg358j) comes into play, where a jobboard can be backed by something like zookeeper (which provides notifications of lock lose/release to others automatically). The jobboard is the place where the other applications would be looking to 'take-over' the other failed applications work (by using zookeeper 'atomic' primitives designed for this type of usage) and they would also be releasing the work back for others to 'take-over' when there own zookeeper connection is lost (zookeeper handles this this natively).

--

Now as for how much of mistral would change from the above, I don't know, but thats why it's a POC.

-Josh

From: Joshua Harlow <harlowja at yahoo-inc.com<mailto:harlowja at yahoo-inc.com>>
Date: Friday, March 21, 2014 at 1:14 PM
To: "OpenStack Development Mailing List (not for usage questions)" <openstack-dev at lists.openstack.org<mailto:openstack-dev at lists.openstack.org>>
Cc: "OpenStack Development Mailing List (not for usage questions)" <openstack-dev at lists.openstack.org<mailto:openstack-dev at lists.openstack.org>>
Subject: Re: [openstack-dev] [Mistral][TaskFlow] Long running actions

Will advise soon, out sick with not so fun case of poison oak, will reply next week (hopefully) when I'm less incapacitated...

Sent from my really tiny device...

On Mar 21, 2014, at 3:24 AM, "Renat Akhmerov" <rakhmerov at mirantis.com<mailto:rakhmerov at mirantis.com>> wrote:

Valid concerns. It would be great to get Joshua involved in this discussion. If it’s possible to do in TaskFlow he could advise on how exactly.

Renat Akhmerov
@ Mirantis Inc.



On 21 Mar 2014, at 16:23, Stan Lagun <slagun at mirantis.com<mailto:slagun at mirantis.com>> wrote:

Don't forget HA issues. Mistral can be restarted at any moment and need to be able to proceed from the place it was interrupted on another instance. In theory it can be addressed by TaskFlow but I'm not sure it can be done without complete redesign of it


On Fri, Mar 21, 2014 at 8:33 AM, W Chan <m4d.coder at gmail.com<mailto:m4d.coder at gmail.com>> wrote:
Can the long running task be handled by putting the target task in the workflow in a persisted state until either an event triggers it or timeout occurs?  An event (human approval or trigger from an external system) sent to the transport will rejuvenate the task.  The timeout is configurable by the end user up to a certain time limit set by the mistral admin.

Based on the TaskFlow examples, it seems like the engine instance managing the workflow will be in memory until the flow is completed.  Unless there's other options to schedule tasks in TaskFlow, if we have too many of these workflows with long running tasks, seems like it'll become a memory issue for mistral...


On Thu, Mar 20, 2014 at 3:07 PM, Dmitri Zimine <dz at stackstorm.com<mailto:dz at stackstorm.com>> wrote:

For the 'asynchronous manner' discussion see http://tinyurl.com/n3v9lt8; I'm still not sure why u would want to make is_sync/is_async a primitive concept in a workflow system, shouldn't this be only up to the entity running the workflow to decide? Why is a task allowed to be sync/async, that has major side-effects for state-persistence, resumption (and to me is a incorrect abstraction to provide) and general workflow execution control, I'd be very careful with this (which is why I am hesitant to add it without much much more discussion).

Let's remove the confusion caused by "async". All tasks [may] run async from the engine standpoint, agreed.

"Long running tasks" - that's it.

Examples: wait_5_days, run_hadoop_job, take_human_input.
The Task doesn't do the job: it delegates to an external system. The flow execution needs to wait  (5 days passed, hadoob job finished with data x, user inputs y), and than continue with the received results.

The requirement is to survive a restart of any WF component without loosing the state of the long running operation.

Does TaskFlow already have a way to do it? Or ongoing ideas, considerations? If yes let's review. Else let's brainstorm together.

I agree,
that has major side-effects for state-persistence, resumption (and to me is a incorrect abstraction to provide) and general workflow execution control, I'd be very careful with this
But these requirement  comes from customers'  use cases: wait_5_day - lifecycle management workflow, long running external system - Murano requirements, user input - workflow for operation automations with control gate checks, provisions which require 'approval' steps, etc.

DZ>


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--
Sincerely yours
Stanislav (Stan) Lagun
Senior Developer
Mirantis
35b/3, Vorontsovskaya St.
Moscow, Russia
Skype: stanlagun
www.mirantis.com<http://www.mirantis.com/>
slagun at mirantis.com<mailto:slagun at mirantis.com>
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