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This repo publishes the applications used in the paper [ENSURE: Efficient Scheduling and Autonomous Resource Management in Serverless Environments] (https://www3.cs.stonybrook.edu/~anshul/acsos20_ensure.pdf). The solution proposed in the paper is available in (https://github.com/pacelab/ensure)

Requirements for individual applications are as follows:

Application: Requirement

  • EmailGen S3 credentials (variable aws_access_id, aws_secret_id)

  • StockAnalysis Redis credentials (variable redis-host-1 to 3)

  • File encryption S3 + redis credentials

  • Sentiment Review S3 credentials

  • Sort S3 credentials

  • Matrix multiplication S3 credetials

  • Image-resizing S3 credentials

  • Real time analytics Redis + Kafka credentials

  • CFD S3 credentials

  • Nearest neighbors S3 credentials

To run the applications, a functional OpenWhisk cluster is required, along with application specific requirements mentioned above. The run commands for the applications with default parameters are as follows

  • wsk -i action update emailGen_v1 --docker pacelab/aws_py emailGen/emailGen.py

  • wsk -i action update stockAnalysis_v1 --docker pacelab/aws_py stockAnalysis/stockAnalysis.py

  • wsk -i action update fileEncrypt_v1 fileEncrypt/db_fileEncrypt.py --docker pacelab/aws_file_encrypt -t 90000 # should rename it to fileEncrypt_v1

  • wsk -i action update serving_lrReview_v1 review/serving_lrReview.py --docker pacelab/aws_pyml -t 300000

  • wsk -i action update sort_v1 --docker pacelab/aws_py sorting/sort_v1.py -t 300000 -m 512

  • wsk -i action update matmulaction_v2 --docker pacelab/aws_pyml matrix_mult/matmul_action.py -t 300000 -m 512

  • wsk -i action update euler3d_cpu_v1 --docker pacelab/aws_py ../rodinia_cfd/driverCfd/euler3d_cpu.py -t 90000 -m 512

  • wsk -i action update realTimeAnalytics_v1 --docker pacelab/aws_py ../realTimeAnalytics/dockerBasedAction/realTimeAnalytics_v1.py

  • wsk -i action update rodinia_nn_v1 --docker pacelab/aws_py ../rodinia_nn/driverNn/nn.py

  • wsk -i action update imageResizing_v1 --docker pacelab/aws_pyml ../imageResizing/dockerBasedAction/imageResizing.py

All the actions/functions have default parameters and can be invoked without specifying input parameters.

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