IBM Machine Learning using Cloud functions
August 25, 2020

IBM Machine Learning using Cloud functions

Frank Ovanessians | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM Cloud Object Storage

There is an initiative to design in automation and machine learning into all of Epiroc's surface mining drills. We want the drill to optimize drilling functions in order to lengthen life of drill components and save fuel. The drill runs predictive models based on the drilling of one hole in a pattern then decides based on the data how to optimize the next series of 100-200 holes. The machine will also predict maintenance cycles, in hours, based on past usage and sister machines in the field.
  • Python compiler is fast.
  • Storing and sharing files.
  • Security features.
  • Difficult to find functions.
  • Need a centralized menu system.
  • Faster compiler speeds for Python code.
  • Immediate benefit on predictive models.
  • Centralized cloud location allows instant transfer and sharing of data.
  • Allows internal servers to handle storage while IBM cloud computes models.
No, it has not been used for my projects.
Extremely fast data transfer rate. No downtime reported.
This has not been a factor in our calculations.
Colorizes errors, allows the user to break up the code in functional blocks, that makes it easier to debug.
  • IBM Analytics for Apache Spark
Great engine for extremely fast processing .
Python machine learning where the files can be tested and compiled immediately and shared with users.

IBM Cloud Object Storage Feature Ratings

Service-level Agreement (SLA) uptime
Monitoring tools
Security controls