I responded in the gdoc.  Here’s a copy.

One of my goals for delegation is to avoid asking people to write policy 
statements specific to any particular domain-specific solver.  People ought to 
encode policy however they like, and the system ought to figure out how best to 
enforce that policy  (delegation being one option).

Assuming that's a reasonable goal, I see two options for delegation to  
solverScheduler

(1) SolverScheduler exposes a custom constraint class.  Congress generates the 
LP program from the Datalog, similar to what is described in this doc, and 
gives that LP program as custom constraints to the  SolverScheduler.  
SolverScheduler is then responsible for enforcing that policy both during 
provisioning of new servers and for monitoring/migrating servers once 
provisioning is finished.

(2) The Congress adapter for SolverScheduler understands the semantics of 
MemoryCapacityConstraint, identifies when the user has asked for that 
constraint, and replaces that part of the LP program with the 
MemoryCapacityConstraint.

We probably want a combination of (1) and (2) so that we handle any gaps in the 
pre-defined constraints that SolverScheduler has, while at the same time 
leveraging the pre-defined constraints when possible.

Tim


On Mar 17, 2015, at 6:09 PM, Yathiraj Udupi (yudupi) 
<[email protected]<mailto:[email protected]>> wrote:

Hi Tim,

I posted this comment on the doc.  I am still pondering over a possibility of 
have a policy-driven scheduler workflow via the Solver Scheduler placement 
engine, which is also LP based like you describe in your doc.
I know in your initial meeting, you plan to go over your proposal of building a 
VM placement engine that subscribes to the Congress DSE,  I probably will 
understand the Congress workflows better and see how I could incorporate this 
proposal to talk to the Solver Scheduler to make the placement decisions.

The example you provide in the doc, is a very good scenario, where a VM 
placement engine should continuously monitor and trigger VM migrations.

I am also interested in the case of a policy-driven scheduling for the initial 
creation of VMs. This is where say people will call Nova APIs and create a new 
set of VMs. Here the scheduler workflow should address the constraints as 
imposed from the user's policies.

Say the simple policy is " Host's free RAM >= 0.25 * Memory_Capacity"
I would like the scheduler to use this policy as defined from Congress, and 
apply it during the scheduling as part of the Nova boot call.

I am really interested in and need help in coming up with a solution 
integrating Solver Scheduler, so say if I have an implementation of a 
"MemoryCapacityConstraint", which takes a hint value "free_memory_limit" (0.25 
in this example),
could we have a policy in Datalog

placement_requirement(id) :-
nova:host(id),
solver_scheduler:applicable_constraints(id, ["MemoryCapacityConstraint", ]),
applicable_metadata(id, {"free_memory_limit": 0.25, })

This policy could be set and delegated by Congress to solver scheduler via the 
"set_policy" API. or the Solver Scheduler can query Congress via a "get_policy" 
API to get this policy, and incorporate it as part of the solver scheduler 
workflow ?

Does this sound doable ?

Thanks,
Yathi.



On 3/16/15, 11:05 AM, "Tim Hinrichs" 
<[email protected]<mailto:[email protected]>> wrote:

Hi all,

The feedback on the POC delegation proposal has been mostly positive.  Several 
people have asked for a meeting to discuss further.  Given time zone 
constraints, it will likely be 8a or 9a Pacific.  Let me know in the next 2 
days if you want to participate, and we will try to find a day that everyone 
can attend.

https://docs.google.com/document/d/1ksDilJYXV-5AXWON8PLMedDKr9NpS8VbT0jIy_MIEtI/edit<https://urldefense.proofpoint.com/v2/url?u=https-3A__docs.google.com_document_d_1ksDilJYXV-2D5AXWON8PLMedDKr9NpS8VbT0jIy-5FMIEtI_edit&d=AwMFAg&c=Sqcl0Ez6M0X8aeM67LKIiDJAXVeAw-YihVMNtXt-uEs&r=B6BWd4kFfgOzAREgThxkmTZKy7dDXE2-eBAmL0PBK7s&m=uiVXAFxgoK-F8a3oNLDykcTSmPGUMW2_kFB_BnUEBFg&s=GWRQesGone_FbZRHXZmIcQd5MB20CHkriADqVNVnxiA&e=>

Thanks!
Tim
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