Skip to Main Content
IBM Data and AI Ideas Portal for Customers

This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (

Shape the future of IBM!

We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:

Search existing ideas

Start by searching and reviewing ideas and requests to enhance a product or service. Take a look at ideas others have posted, and add a comment, vote, or subscribe to updates on them if they matter to you. If you can't find what you are looking for,

Post your ideas

Post ideas and requests to enhance a product or service. Take a look at ideas others have posted and upvote them if they matter to you,

  1. Post an idea

  2. Upvote ideas that matter most to you

  3. Get feedback from the IBM team to refine your idea

Specific links you will want to bookmark for future use

Welcome to the IBM Ideas Portal ( - Use this site to find out additional information and details about the IBM Ideas process and statuses.

IBM Unified Ideas Portal ( - Use this site to view all of your ideas, create new ideas for any IBM product, or search for ideas across all of IBM. - Use this email to suggest enhancements to the Ideas process or request help from IBM for submitting your Ideas.

IBM Employees should enter Ideas at

Status Submitted
Created by Guest
Created on Feb 20, 2024

Ability to control cplex memory consumption

Nowadays optimization runs are more and more conducted in the cloud, in kubernetes environments. In kubernetes, the processes run inside containers in what are called pods. To prevent a pod to be killed when the node (machine) capacity is exceeded, one needs to set a cpu and memory limit that the process inside the pod does not exceed; Typically CPU and memory limits. If a pod exceeds the given limits, the kubernetes orchestrator kills it.

The problem with cplex is that there is no way to control its cpu and memory consumption so that they do not exceed the given limit. Even setting various cplex parameters like IloCplex.Param.Threads, IloCplex.Param.WorkMem, Emphasis.Memory and MIP.Limits.TreeMemory does not enforce a global limit. Indeed, only the branch&bound procedure seems affected by these parameters, not presolve, probing, lexicographic, etc. The fact that lexicographic optimization explodes in terms of memory consumption is particularly impacting. I even opened a bug ticket because I have a case where settings these parameters to get a 1GB memory limit results into a 8GB memory consumption during the branch&bound.

To workaround this issue, we set the cplex parameters to try to control the memory consumption and then set a pod limit far above the cplex limit to keep some slack. But still some optimization runs are randomly killed when the datasets are in such a way that cplex consumes more memory than usual. The impact is very significant as cplex cannot be used in a reliable manner in production in a cloud environment.

Needed By Yesterday (Let's go already!)