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test: remove snapshot restore perf test from PR CI
With switching our nightly tests to use cgroupsv1, these two tests are absolutely identical (beyond minor differences in configuration). Thus remove the CI one to increase stability. Signed-off-by: Patrick Roy <[email protected]>
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tests/integration_tests/performance/test_snapshot_perf.py

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@@ -353,80 +353,3 @@ def test_snapshot_create_latency(
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st_core.add_pipe(producer=prod, consumer=cons, tag=microvm_cfg)
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# Gather results and verify pass criteria.
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st_core.run_exercise()
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@pytest.mark.parametrize("guest_mem_mib", [256, 512])
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def test_snapshot_resume_latency(
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microvm_factory,
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guest_kernel,
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rootfs,
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guest_mem_mib,
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io_engine,
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st_core,
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bin_cloner_path,
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):
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"""
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Test scenario: Snapshot load performance measurement.
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Testing matrix:
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- Guest kernel: All supported ones
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- Rootfs: Ubuntu 18.04
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- Microvm: 2vCPU with 256/512 MB RAM
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TODO: Multiple microvm sizes must be tested in the async pipeline.
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"""
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logger = logging.getLogger("snapshot_load")
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vcpus = 2
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microvm_cfg = f"{vcpus}vcpu_{guest_mem_mib}mb.json"
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vm = microvm_factory.build(guest_kernel, rootfs, monitor_memory=False)
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vm.spawn(use_ramdisk=True)
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vm.basic_config(
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vcpu_count=vcpus,
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mem_size_mib=guest_mem_mib,
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use_initrd=True,
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rootfs_io_engine=io_engine,
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)
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iface = NetIfaceConfig()
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vm.add_net_iface(iface)
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vm.start()
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# Check if guest works.
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exit_code, _, _ = vm.ssh.execute_command("ls")
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assert exit_code == 0
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# Create a snapshot builder from a microvm.
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snapshot_builder = SnapshotBuilder(vm)
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disks = [vm.rootfs_file]
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snapshot = snapshot_builder.create(
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disks, rootfs.ssh_key(), use_ramdisk=True, net_ifaces=[iface]
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)
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vm.kill()
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st_core.name = "snapshot_resume_latency"
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st_core.iterations = SAMPLE_COUNT
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st_core.custom["guest_config"] = microvm_cfg.strip(".json")
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st_core.custom["io_engine"] = io_engine
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st_core.custom["snapshot_type"] = "FULL"
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prod = producer.LambdaProducer(
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func=snapshot_resume_producer,
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func_kwargs={
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"logger": logger,
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"vm_builder": MicrovmBuilder(bin_cloner_path),
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"snapshot": snapshot,
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"use_ramdisk": True,
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},
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)
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cons = consumer.LambdaConsumer(
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func=lambda cons, result: cons.consume_stat(
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st_name="max", ms_name="latency", value=result
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),
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func_kwargs={},
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)
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eager_map(
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cons.set_measurement_def,
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snapshot_resume_measurements(microvm_cfg, io_engine.lower()),
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)
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st_core.add_pipe(producer=prod, consumer=cons, tag=microvm_cfg)
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# Gather results and verify pass criteria.
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st_core.run_exercise()

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