Jenkins Pipeline for testing with a large dataset












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We're working on building a Jenkins build & test pipeline for our Computer Vision application (Dockerized). Naturally, we have a huge dataset to perform the testing (~32 GB). Any ideas on how to build such a pipeline?



Some options I'm exploring are




  • Making a repository on BitBucket with the data, include it into the Jenkins pipeline, mount it into the Docker and run the test.

  • Upload the data on an S3 instance, fetch from Jenkins and perform the test?? (Don't know how that works)


If there is a standard practice for this, I couldn't find it. Any ideas would be helpful. Thanks!










share|improve this question






















  • Could you store the dataset in an EBS volume and mount that each time? Rather than paying all of the data transfer fees. Or could use EFS?
    – ajtrichards
    Nov 13 '18 at 9:45


















0














We're working on building a Jenkins build & test pipeline for our Computer Vision application (Dockerized). Naturally, we have a huge dataset to perform the testing (~32 GB). Any ideas on how to build such a pipeline?



Some options I'm exploring are




  • Making a repository on BitBucket with the data, include it into the Jenkins pipeline, mount it into the Docker and run the test.

  • Upload the data on an S3 instance, fetch from Jenkins and perform the test?? (Don't know how that works)


If there is a standard practice for this, I couldn't find it. Any ideas would be helpful. Thanks!










share|improve this question






















  • Could you store the dataset in an EBS volume and mount that each time? Rather than paying all of the data transfer fees. Or could use EFS?
    – ajtrichards
    Nov 13 '18 at 9:45
















0












0








0







We're working on building a Jenkins build & test pipeline for our Computer Vision application (Dockerized). Naturally, we have a huge dataset to perform the testing (~32 GB). Any ideas on how to build such a pipeline?



Some options I'm exploring are




  • Making a repository on BitBucket with the data, include it into the Jenkins pipeline, mount it into the Docker and run the test.

  • Upload the data on an S3 instance, fetch from Jenkins and perform the test?? (Don't know how that works)


If there is a standard practice for this, I couldn't find it. Any ideas would be helpful. Thanks!










share|improve this question













We're working on building a Jenkins build & test pipeline for our Computer Vision application (Dockerized). Naturally, we have a huge dataset to perform the testing (~32 GB). Any ideas on how to build such a pipeline?



Some options I'm exploring are




  • Making a repository on BitBucket with the data, include it into the Jenkins pipeline, mount it into the Docker and run the test.

  • Upload the data on an S3 instance, fetch from Jenkins and perform the test?? (Don't know how that works)


If there is a standard practice for this, I couldn't find it. Any ideas would be helpful. Thanks!







git docker jenkins amazon-s3






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share|improve this question











share|improve this question




share|improve this question










asked Nov 13 '18 at 9:41









Ali Kareem RajaAli Kareem Raja

199217




199217












  • Could you store the dataset in an EBS volume and mount that each time? Rather than paying all of the data transfer fees. Or could use EFS?
    – ajtrichards
    Nov 13 '18 at 9:45




















  • Could you store the dataset in an EBS volume and mount that each time? Rather than paying all of the data transfer fees. Or could use EFS?
    – ajtrichards
    Nov 13 '18 at 9:45


















Could you store the dataset in an EBS volume and mount that each time? Rather than paying all of the data transfer fees. Or could use EFS?
– ajtrichards
Nov 13 '18 at 9:45






Could you store the dataset in an EBS volume and mount that each time? Rather than paying all of the data transfer fees. Or could use EFS?
– ajtrichards
Nov 13 '18 at 9:45














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