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Use converged topo in KVM to save PR test CPU#23326

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xwjiang-ms:use_converged_topo_in_kvm
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Use converged topo in KVM to save PR test CPU#23326
xwjiang-ms wants to merge 3 commits intosonic-net:masterfrom
xwjiang-ms:use_converged_topo_in_kvm

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@xwjiang-ms
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Description of PR

Summary:
Fixes # (issue)

Type of change

  • Bug fix
  • Testbed and Framework(new/improvement)
  • New Test case
    • Skipped for non-supported platforms
  • Test case improvement

Back port request

  • 202205
  • 202305
  • 202311
  • 202405
  • 202411
  • 202505
  • 202511

Approach

What is the motivation for this PR?

How did you do it?

How did you verify/test it?

Any platform specific information?

Supported testbed topology if it's a new test case?

Documentation

@mssonicbld
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/azp run

@azure-pipelines
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Azure Pipelines successfully started running 1 pipeline(s).

1. testbed.py: Run ceos_topo_converger at parse time when
   use_converged_peers is enabled and the topology YAML has not
   been pre-converged.  This ensures the test fixtures see the
   converged topology (topo_is_multi_vrf, convergence_data)
   even when the on-disk YAML was not modified by an earlier
   add-topo step.

2. vtestbed.yaml: Only enable use_converged_peers for t0 KVM
   testbeds.  Non-t0 topologies (t1-lag, t2, dualtor, etc.)
   exceed the KVM per-VM VLAN limit (NUM_FP_VLANS_PER_FP=4)
   when all VMs of the same role are consolidated into one
   prime device.

Co-authored-by: Copilot <[email protected]>
@mssonicbld
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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

ceos_topo_converger now computes max_fp_num based on the actual
maximum VLAN count across prime VMs, so enough OVS bridges are
created. The computed value is written to the topology YAML and
picked up by include_vars (overriding the default max_fp_num=4
from group_vars). This is equivalent to passing
-e max_fp_num=<N> on the CLI, but computed automatically.

Also restores use_converged_peers for all KVM testbed entries.

Co-authored-by: Copilot <[email protected]>
@mssonicbld
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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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2 participants