Bump serverless ES index node memory to 1.5g#233516
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## Summary This PR bumps the memory setting for elasticsearch-serverless docker image index node from 1g to 1.5g. This addresses test failures (see elastic#232808 and elastic#232806) that we saw after elastic/elasticsearch-serverless#4362. The tests were running with high ES heap usage already (~99%) and this is now surfaced because new shards are no longer allocated in that scenario. This memory bump is a quick measure to unblock pipelines and we should investigate whether we could change the test to run with less resources in the future.
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## Summary This PR bumps the memory setting for elasticsearch-serverless docker image index node from 1g to 1.5g. This addresses test failures (see elastic#232808 and elastic#232806) that we saw after elastic/elasticsearch-serverless#4362. The tests were running with high ES heap usage already (~99%) and this is now surfaced because new shards are no longer allocated in that scenario. This memory bump is a quick measure to unblock pipelines and we should investigate whether we could change the test to run with less resources in the future.
MichelLosier
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## Summary This PR bumps the memory setting for elasticsearch-serverless docker image index node from 1g to 1.5g. This addresses test failures (see elastic#232808 and elastic#232806) that we saw after elastic/elasticsearch-serverless#4362. The tests were running with high ES heap usage already (~99%) and this is now surfaced because new shards are no longer allocated in that scenario. This memory bump is a quick measure to unblock pipelines and we should investigate whether we could change the test to run with less resources in the future.
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Summary
This PR bumps the memory setting for elasticsearch-serverless docker image index node from 1g to 1.5g.
This addresses test failures (see #232808 and #232806) that we saw after https://github.com/elastic/elasticsearch-serverless/pull/4362. The tests were running with high ES heap usage already (~99%) and this is now surfaced because new shards are no longer allocated in that scenario.
This memory bump is a quick measure to unblock pipelines and we should investigate whether we could change the test to run with less resources in the future.