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fix(ci): flaky Fabric 2.x run tx endpoint test #718
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petermetz
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Sep 3, 2021
Epic facepalm once again. Turns out the default restart try count of supervisord is too low which leads to race conditions. Increasing the retry count from 4 to 20 should do it, this way the fabric-network process (see supervisord.conf file) should be 5 times as "patient" waiting for the docker daemon to launch within the AIO container. What was happening before is that the fabric-network script tried launching itself in parallel with the docker daemon, but it would time out before the docker daemon could come online. Published these images as ghcr.io/hyperledger/cactus-fabric2-all-in-one:2021-09-02--fix-876-supervisord-retries and ghcr.io/hyperledger/cactus-fabric-all-in-one:2021-09-02--fix-876-supervisord-retries Fixes hyperledger-cacti#718 Fixes hyperledger-cacti#876 Fixes hyperledger-cacti#320 Fixes hyperledger-cacti#319 Signed-off-by: Peter Somogyvari <peter.somogyvari@accenture.com>
petermetz
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that referenced
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Sep 7, 2021
Epic facepalm once again. Turns out the default restart try count of supervisord is too low which leads to race conditions. Increasing the retry count from 4 to 20 should do it, this way the fabric-network process (see supervisord.conf file) should be 5 times as "patient" waiting for the docker daemon to launch within the AIO container. What was happening before is that the fabric-network script tried launching itself in parallel with the docker daemon, but it would time out before the docker daemon could come online. Published these images as ghcr.io/hyperledger/cactus-fabric2-all-in-one:2021-09-02--fix-876-supervisord-retries and ghcr.io/hyperledger/cactus-fabric-all-in-one:2021-09-02--fix-876-supervisord-retries Fixes #718 Fixes #876 Fixes #320 Fixes #319 Signed-off-by: Peter Somogyvari <peter.somogyvari@accenture.com>
RafaelAPB
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Mar 9, 2022
Epic facepalm once again. Turns out the default restart try count of supervisord is too low which leads to race conditions. Increasing the retry count from 4 to 20 should do it, this way the fabric-network process (see supervisord.conf file) should be 5 times as "patient" waiting for the docker daemon to launch within the AIO container. What was happening before is that the fabric-network script tried launching itself in parallel with the docker daemon, but it would time out before the docker daemon could come online. Published these images as ghcr.io/hyperledger/cactus-fabric2-all-in-one:2021-09-02--fix-876-supervisord-retries and ghcr.io/hyperledger/cactus-fabric-all-in-one:2021-09-02--fix-876-supervisord-retries Fixes hyperledger-cacti#718 Fixes hyperledger-cacti#876 Fixes hyperledger-cacti#320 Fixes hyperledger-cacti#319 Signed-off-by: Peter Somogyvari <peter.somogyvari@accenture.com>
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Describe the bug
The test below fails occasionally and only on the CI servers of GHA, not reproducible on development machines unfortunately.
packages/cactus-plugin-ledger-connector-fabric/src/test/typescript/integration/fabric-v2-2-x/run-transaction-endpoint-v1.test.ts
To Reproduce
Keep submitting PRs and you'll hit this issue every once in a while, forcing you to re-run the CI and then have it pass...
Expected behavior
Tests are as stable as possible.
Logs/Stack traces
Screenshots
N/A
Cloud provider or hardware configuration:
GitHub Actions Runner
Operating system name, version, build:
Ubuntu 18/20 LTS
Hyperledger Cactus release version or commit (git rev-parse --short HEAD):
main
@ fea547fHyperledger Cactus Plugins/Connectors Used
Fabric
Additional context
This seems to be the last bug standing after several other ones were fixed recently as part of the effort to make #656 possible.
Guess on what might be going wrong: The Fabric 2.x AIO container may be hanging at boot with a race condition that it cannot recover from. This is more likely than it being just a not enough time on slow hardware type of thing because usually 3 out of 4 runs in the CI matrix pass in 30 minutes but then the 4th one takes an hour+ and still times out...
cc: @takeutak @sfuji822 @hartm @jonathan-m-hamilton @AzaharaC @jordigiam @kikoncuo @jagpreetsinghsasan
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