This document outlines an agenda for a DevOps event on auto-scaling. The agenda includes welcome remarks, presentations on auto-scaling use cases and a Kontena demo. There is also a scheduled auto-scale demo showing how resource groups can be provisioned and scaled up/down automatically based on metrics and policies in OpenStack Heat. The document argues that auto-scaling can be simplified using standardized metrics and workloads that scale out horizontally rather than vertically. It notes auto-scaling can be implemented in a few hours and at very low cost using services like Datadog to monitor metrics and trigger scaling policies.

1. BEER & DEVOPS
NOVEMBER 24 - 2016

2. M A K E S I T W O R K
Welcome
Auto-scale use-cases
Auto-scale demo
Break
Kontena demo & presentation
Mingling
AGENDA

3. M A K E S I T W O R K

4. M A K E S I T W O R K
TRUSTED PARTNER FOR RUNNING BUSINESS
CRITICAL ICT SERVICES

5. M A K E S I T W O R K
DATACENTER & CLOUD
ADOPTION PHASES
MATURITY
BENEFITS

6. RESOURCE GROUP
MINIMUM SIZE / MAXIMUM SIZE
RESOURCE GROUP
HORIZONTAL SCALING
M A K E S I T W O R K
AUTOSCALE
WHAT IT IS?
TRIGGERS
RESOURCE LOAD (CEILOMETER)
EXTERNAL EVENT (HTTP POST)

7. M A K E S I T W O R K
Known variable load Your VDI infrastructure
Unpredictable load Finland Tax information
Steadily increasing load Airbnb
Batch load Payroll processing
AUTOSCALE USE CASE

8. M A K E S I T W O R K
SCHEDULED OR ON-DEMAND
ORCHESTRATION USE CASE
Disaster recovery Recover to new another site
Ad-hoc Try new plug-in
Duplicate Clone DEV/QA environment
Batch load Software build process
M A K E S I T W O R K

9. M A K E S I T W O R K
AZ1 AZ2
Application
Tier
Web Tier
Data Tier
www.acme.com
Load Balancing
SCALABLE WEB APP

10. M A K E S I T W O R K
PROVISION SERVERS/STACK
AUTO ADD NODES TO DATADOG
(SCHEDULED) CREATE LOAD
AUTO-SCALE UP
(SCHEDULED) DECREASE LOAD
AUTO-SCALE DOWN
DEMO

11. M A K E S I T W O R K
Sum of
CPU LOAD
Listing of
nodes
Listing of
alarms
Listing of
stacks

12. M A K E S I T W O R K
asg:
type: OS::Heat::AutoScalingGroup
properties:
min_size: 1
max_size: 3
resource:
type: OS::Nova::Server
properties:
key_name: {get_param: key_name}
flavor: {get_param: flavor}
image: {get_param: image}
availability_zone: {get_param: availability_zone}
networks:
- network: { get_param: dmz_network }
metadata: {"metering.stack": {get_param: "OS::stack_id"}}
user_data_format: RAW
user_data:
get_resource: cloud_config_stress
scale_up_policy:
type: OS::Heat::ScalingPolicy
properties:
adjustment_type: change_in_capacity
auto_scaling_group_id: {get_resource: asg}
cooldown: 60
scaling_adjustment: 1
scale_down_policy:
type: OS::Heat::ScalingPolicy
properties:
adjustment_type: change_in_capacity

13. RESOURCE GROUP
MINIMUM SIZE
RESOURCE GROUP
SCALE OUT SIZE
CEILOMETER
METRICS
ALARM
HEAT ENGINE
RESOURCE POLICY
USER DATA
WEBHOOK
M A K E S I T W O R K
AUTOSCALE
SIMPLIFIED
METRICS

14. M A K E S I T W O R K
HOW HARD CAN IT BE?
We built this demo from
‘scratch’ in ~3 hours
including planning,
registration to Datadog
and recording
DEMO COSTS
Extra 4GB RAM Server*2
20 minutes
TOTAL = 0,05€

15. M A K E S I T W O R KM A K E S I T W O R K
STANDARDIZED WORKLOADS – SCALE OUT, NOT UP
HOW MUCH TO CHANGE AT EACH TIME
DATA HANDLING
CONFIGURATION MANAGEMENT
CONSIDERATIONS