How to apply cost saving patterns for Atlassian Data Center on AWS deployments
Goal
You want to facilitate the Atlassian Data Center on AWS quick starts for performance and functional testing without breaking the bank.
~75% cost savings over regular usage
Challenges
AWS (and other cloud providers) offer significant cost saving options, but this usually requires some proficiency
Atlassian does not seem to be overly concerned with paying more for AWS usage than necessary
likely remedied by large scale user discounts and purchasing options (reserved instances)
also applies to JPT I think
Diverging quick start branches complicate collaboration
this will hopefully get resolved down the road
Quick start branches
Cost | Features | Landing page | Repositories | |
---|---|---|---|
AWS | | | ||
Atlassian | | | ||
Utoolity | | | TBD (community summary) | https://bitbucket.org/utoolitylabs/profile/repositories?search=quickstart |
Cost saving options / status
Option / Status | AWS | Atlassian | Utoolity | Notes |
---|---|---|---|---|
Resource configuration | ||||
Facilitate current instance types |
| |||
Default to inexpensive parameters |
| |||
Facilitate EC2 spot instances ('use spot') | | |
| ||
Resource utilization | ||||
Reuse/Disable optional components |
| |||
Stop cluster during off-hours ('cold standby') | | |
| ||
Terminate cluster during off-hours (fully automated backup/restore) |
| |||
Reserved instances | N/A | N/A | N/A |
|
Related news
AWS regularly releases new features that can further increase the scope and efficiency of these cost saving patterns, e.g. just recently:
Amazon RDS Enables Stopping and Starting of Multi-AZ Database Instances
Scale Amazon EC2 Instances across On-Demand, Spot and RIs in a Single Auto Scaling Group
Conceptually this allows to aggressively and easily facilitate EC2 spot instances for production workloads.
Step-by-step guide
TBD
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