The bamboo agent to server transfer appears slow for our Installer build artifacts of 16Gig and I was curious if there were any other methods to transfer this data other than through the agent to server mechanism ? Alternativly, does the Bamboo plugin model provide a means to solve this ?
With regards to performance, 'Slow' is 40 min for 16 Gig.
We have resolved this issue by creating a task on the bamboo job, a script 'Transfer Artifacts', which copies the installers to a NFS mount of the servers build results storage. The result of the new task's copy is now a 4 min transfer. On the bamboo job we created an artifact definition, installers, that had a mask that could not be resolved during bamboo's artifact transfer. Post execution of the build, the artifaction definition would be populated in the build results with the correct structure and sizes due to the task.
Thanks for the note on 4.3 ArtifactHandler is interesting but for the moment we are on 3.4 and it will be 6mo+ before migration.
Kudos to the team for the Project/Plan/Stage/Job/Task model.
With Bamboo 4.3, there's an unofficial plugin point that lets you define your own artifact handlers. A custom artifact handler can replace the default ones for publishing and retrieval.
Take a look at the interface called ArtifactHandler. The feature will be much more usable in 4.4 (but there's no decision to make it official for now).
BTW. what does slow mean in this context?
I have a similar issue: the artifacts I'm generating per branch are much smaller that the OP (~320MB for four artifacts), but the transfer rate the agent gets is about 10% of link speed. A transfer that should take a minute takes 10. And I have ~8 branches to build.
Being able to either specify another transport mechanism to upload an artifact or an external location for artifacts (e.g., pick up output that has been SCP'd to somewhere) would be very useful. Either way should preserve other artifact functionality, e.g., links posted to Jira.
Bamboo 5.9 will no longer be supported after June 12, 2017. What does this mean? As part of our End of Life policy, Atlassian supports major versions for two years after the first major iteratio...
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