Jump to: navigation, search

Difference between revisions of "Auto-scaling SIG/Theory of Auto-Scaling"

(Theory of Auto-Scaling: components)
m (Components of Auto-Scaling)
Line 62: Line 62:
** Congress
** Congress
** Heat
** Heat
** Tacker
** Vitrage
** Vitrage
** Watcher
** Watcher

Revision as of 23:19, 15 May 2019

Theory of Auto-Scaling

General Description

<fill in>

Conceptual Diagram

Auto-Scaling Architecture Component Diagram

If you prefer PlantUML


cloud Cloud\n {

 rectangle host as "Host" {
 rectangle host2 as "Host" {
   agent VM
   agent VM2 as "VM"
   agent Container
   agent Container2 as "Container"


agent MS as "Monitoring Service" agent DS as "Decision Services\n(Clustering,\nOptimization,\nRoot Cause)" agent Heat as "Orchestration \nEngine"

host -down-> MS VM -down-> MS Container -down-> MS : "Metric \nSamples"

MS -down-> DS : "Alarms" MS -down-> Heat : "Alarms"

DS -right-> Heat : "Scaling Commands"

Heat -up-> host : "Orchestration" Heat -up-> VM2 : "Orchestration" Heat -up-> Container2 : "Orchestration"


Components of Auto-Scaling

OpenStack offers a rich set of services to build, manage, orchestrate, and provision a cloud. This gives administrators some choices in how to best serve their customer's needs.

  • Scaling units - There are a number of components that can be controlled with Auto-Scaling.
    • Compute Host
    • VM running on a Compute Host
    • Container running on a Compute Host
    • Network Attached Storage
    • Virtual Network Functions
  • Monitoring Service
  • Alarming Service
  • Decision Services - There are a number of services in OpenStack that can interpret metrics and alarms based on configured logic and produce commands to Orchestration Engines
    • Congress
    • Heat
    • Vitrage
    • Watcher
  • Orchestration Engines
    • Heat
    • Senlin is a clustering engine for OpenStack, and can orchestrate auto-scaling
    • Tacker

Considerations and Guidelines

  • Monitoring takes resources, plan accordingly
  • Avoid scaling too quickly or too often
  • Don't expect instantaneous scaling (see above)
  • Be aware of where the logic for scaling is (alarm thresholds, decision services)

Anecdotes and Stories