jm + ami   2

Airflow/AMI/ASG nightly-packaging workflow
Some tantalising discussion on twitter of an Airflow + AMI + ASG workflow for ML packaging:

'We build models using Airflow. We deploy new models as AMIs where each AMI is model + scoring code. The AMI is hence a version of code + model at a point in time : #immutable_infrastructure. It's natural for Airflow to build & deploy the model+code with each Airflow DAG Run corresponding to a versioned AMI. if there's a problem, we can simply roll back to the previous AMI & identify the problematic model building Dag run. Since we use ASGs, Airflow can execute a rolling deploy of new AMIs. We could also have it do a validation & ASG rollback of the AMI if validation fails. Airflow is being used for reliable Model build+validation+deployment.'
ml  packaging  airflow  asg  ami  deployment  ops  infrastructure  rollback 
september 2016 by jm
Netflix: Your Linux AMI: optimization and performance [slides]
a fantastic bunch of low-level kernel tweaks and tunables which Netflix have found useful in production to maximise productivity of their fleet. Interesting use of SCHED_BATCH process scheduler class for batch processes, in particular. Also, great docs on their experience with perf and SystemTap. Perf really looks like a tool I need to get to grips with...
netflix  aws  tuning  ami  perf  systemtap  tunables  sched_batch  batch  hadoop  optimization  performance 
december 2013 by jm

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