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Partitioning strategy

As explained in Delivering Machine Learning Projects: From design to deployment

A partitioning strategy divides a system into independent subsystems so that an individual subsystem can fail without causing systemic or unacceptable damage.

A partitioning strategy divides a system into independent subsystems so one subsystem can fail without causing systemic or unacceptable damage. Each partition must remain manageable while its failure is tolerated for the time and cost required to restore it. section 9.2.2

Apply the strategy by:

  • Assigning each subsystem a bounded area of responsibility and allowing it to operate autonomously. section 9.2.2
  • Detecting or reporting localized failures to an operating center, then triggering remediation under applicable service-level agreements. section 9.2.2
  • Adding failover, replication, or rapid repair when the required coverage or recovery time demands it. section 9.2.2

Mobile phone networks

Each network cell serves subscribers in its allocated area. A failed subscriber database or antenna-steering strategy creates a localized outage that can be detected centrally and remediated without disabling the entire network. Life-support systems may also partition functions, but require a qualified person to operate failed elements. section 9.2.2

How Delivering Machine Learning Projects: From design to deployment covers it

How deep it goes
Defines subsystem isolation and illustrates detection, remediation, failover, replication, and human intervention, but stops short of implementation detail.
Examples
Uses mobile phone cells and life-support systems to illustrate localized failure, central detection, recovery, and human backup.
What it assumes
Builds on delegative control and requires failures to remain tolerable during the time or cost of resolution.
What you can do after
Operate systems by isolating failures, coordinating remediation, and adding recovery provisions appropriate to tolerated disruption.
How it connects
Connects delegative control with autonomy, failover, replication, service-level agreements, and rapid remediation.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Delivering Machine Learning Projects: From design to deployment. The section links point to the parts of the book it draws on.