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Move some perf benchmarks from hetzner to aws arm github runners (#12393)
## Problem We want to move some benchmarks from hetzner runners to aws graviton runners ## Summary of changes Adjust the runner labels for some workflows. Adjust the pagebench number of clients to match the latecny knee at 8 cores of the new instance type Add `--security-opt seccomp=unconfined` to docker run command to bypass IO_URING EPERM error. ## New runners https://us-east-2.console.aws.amazon.com/ec2/home?region=us-east-2#Instances:instanceState=running;search=:github-unit-perf-runner-arm;v=3;$case=tags:true%5C,client:false;$regex=tags:false%5C,client:false;sort=tag:Name ## Important Notes I added the run-benchmarks label to get this tested **before we merge it**. [See](https://github.com/neondatabase/neon/actions/runs/15974141360) I also test a run of pagebench with the new setup from this branch, see https://github.com/neondatabase/neon/actions/runs/15972523054 - Update: the benchmarking workflow had failures, [see] (https://github.com/neondatabase/neon/actions/runs/15974141360/job/45055897591) - changed docker run command to avoid io_uring EPERM error, new run [see](https://github.com/neondatabase/neon/actions/runs/15997965633/job/45125689920?pr=12393) Update: the pagebench test run on the new runner [completed successfully](https://github.com/neondatabase/neon/actions/runs/15972523054/job/45046772556) Update 2025-07-07: the latest runs with instance store ext4 have been successful and resolved the direct I/O issues we have been seeing before in some runs. We only had one perf testcase failing (shard split) that had been flaky before. So I think we can merge this now. ## Follow up if this is merged and works successfully we must create a separate issue to de-provision the hetzner unit-perf runners defined [here](https://github.com/neondatabase/runner/blob/91a41729af5b168d42e8acab0a7c38fde031113e/ansible/inventory/hosts_metal#L111)
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@@ -7,6 +7,7 @@ self-hosted-runner:
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- small-metal
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- small-arm64
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- unit-perf
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- unit-perf-aws-arm
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- us-east-2
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config-variables:
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- AWS_ECR_REGION
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@@ -306,14 +306,14 @@ jobs:
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statuses: write
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contents: write
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pull-requests: write
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runs-on: [ self-hosted, unit-perf ]
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runs-on: [ self-hosted, unit-perf-aws-arm ]
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container:
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image: ${{ needs.build-build-tools-image.outputs.image }}-bookworm
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credentials:
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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# for changed limits, see comments on `options:` earlier in this file
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options: --init --shm-size=512mb --ulimit memlock=67108864:67108864
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options: --init --shm-size=512mb --ulimit memlock=67108864:67108864 --ulimit nofile=65536:65536 --security-opt seccomp=unconfined
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strategy:
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fail-fast: false
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matrix:
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@@ -1,4 +1,4 @@
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name: Periodic pagebench performance test on unit-perf hetzner runner
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name: Periodic pagebench performance test on unit-perf-aws-arm runners
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on:
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schedule:
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@@ -40,7 +40,7 @@ jobs:
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statuses: write
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contents: write
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pull-requests: write
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runs-on: [ self-hosted, unit-perf ]
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runs-on: [ self-hosted, unit-perf-aws-arm ]
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container:
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image: ghcr.io/neondatabase/build-tools:pinned-bookworm
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credentials:
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@@ -1,4 +1,4 @@
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name: Periodic proxy performance test on unit-perf hetzner runner
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name: Periodic proxy performance test on unit-perf-aws-arm runners
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on:
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push: # TODO: remove after testing
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@@ -32,7 +32,7 @@ jobs:
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statuses: write
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contents: write
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pull-requests: write
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runs-on: [self-hosted, unit-perf]
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runs-on: [self-hosted, unit-perf-aws-arm]
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timeout-minutes: 60 # 1h timeout
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container:
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image: ghcr.io/neondatabase/build-tools:pinned-bookworm
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+4
-3
@@ -55,9 +55,10 @@ def test_pageserver_characterize_throughput_with_n_tenants(
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@pytest.mark.parametrize("duration", [20 * 60])
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@pytest.mark.parametrize("pgbench_scale", [get_scale_for_db(2048)])
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# we use 1 client to characterize latencies, and 64 clients to characterize throughput/scalability
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# we use 64 clients because typically for a high number of connections we recommend the connection pooler
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# which by default uses 64 connections
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@pytest.mark.parametrize("n_clients", [1, 64])
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# we use 8 clients because we see a latency knee around 6-8 clients on im4gn.2xlarge instance type,
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# which we use for this periodic test - at a cpu utilization of around 70 % - which is considered
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# a good utilization for pageserver.
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@pytest.mark.parametrize("n_clients", [1, 8])
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@pytest.mark.parametrize("n_tenants", [1])
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@pytest.mark.timeout(2400)
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def test_pageserver_characterize_latencies_with_1_client_and_throughput_with_many_clients_one_tenant(
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