“As every company become a software company,
Security vulnerabilities are the new oil spills”
@jbaruch
#LiquidSoftware
#DevOpsTO
http://jfrog.com/shownotes
This is not a new idea!
@jbaruch
#LiquidSoftware
XP: short feedback Scrum: reducing cycle time to absolute minimum TPS: Decide as late as possible and Deliver as fast as possible Kanban: Incremental change #DevOpsTO
http://jfrog.com/shownotes
The problem is not the code, it’s the data. Big data.
@jbaruch
#LiquidSoftware
#DevOpsTO
http://jfrog.com/shownotes
Slide 21
Update available
Yes
No
Can we verify the update?
No
Yes
Yes
How about no
Do we trust the update?
Time consuming verification
Let’s update!
Yes
Are there any high risks?
No
Do we want it?
No
Slide 22
Slide 23
Features that we want
@jbaruch
#LiquidSoftware
Acceptance tests costs
#DevOpsTO
http://jfrog.com/shownotes
Slide 24
Bigger and rarer updates
Less trust in updates
Pack more features
Continuous updates pattern: Local rollback
@jbaruch
#LiquidSoftware
Problem: update went catastrophically wrong and an over the-air patch can’t reach the device Solution: Have a previous version saved on the device prior to update. Rollback in case problem occurred #DevOpsTO
http://jfrog.com/shownotes
Continuous updates pattern: OTA software updates
@jbaruch
#LiquidSoftware
Problem: physical recalls are costly. Extremely costly. Also, you can’t force an upgrade. Solution: Implement over the air software updates, preferably, continuous updates. #DevOpsTO
http://jfrog.com/shownotes
Slide 34
continuous OTA updates are like normal OTA updates,
but better
@jbaruch
#LiquidSoftware
#DevOpsTO
http://jfrog.com/shownotes
Slide 35
Slide 36
Slide 37
Continuous updates pattern: continuous updates
@jbaruch
#LiquidSoftware
Problem: In batch updates important features wait for non-important features. Solution: Implement continuous updates.
#DevOpsTO
http://jfrog.com/shownotes
Slide 38
Slide 39
KNIGHT-MARE
@jbaruch
#LiquidSoftware
New system reused old APIs 1 out of 8 servers was not updated New clients sent requests to machine contained old code Engineers undeployed working code from updated servers, increasing the load on the not-updated server No monitoring, no alerting, no debugging #DevOpsTO
http://jfrog.com/shownotes
Slide 40
Continuous updates pattern: Automated deployment
@jbaruch
#LiquidSoftware
Problem: People suck at repetitive tasks. Solution: Automate everything.
#DevOpsTO
http://jfrog.com/shownotes
Slide 41
Continuous updates pattern: frequent updates
@jbaruch
#LiquidSoftware
Problem: Seldom deployments generate anxiety and stress, leading to errors. Solution: Update frequently to develop skill and habit. #DevOpsTO
http://jfrog.com/shownotes
Slide 42
Continuous updates pattern: state awareness
@jbaruch
#LiquidSoftware
Problem: Target state can affect the update process and the behavior of the system after the update. Solution: Know and consider target state when updating. Reverting might require revering the state. #DevOpsTO
http://jfrog.com/shownotes
Slide 43
Slide 44
Cloud-dark
@jbaruch
#LiquidSoftware
New rules are deployed frequently to battle attacks Deployment of a single misconfigured rule Included regex to spike CPU to 100% “Affected region: Earth” #DevOpsTO
http://jfrog.com/shownotes
Slide 45
Continuous updates pattern: Progressive Delivery
@jbaruch
#LiquidSoftware
Problem: Releasing a bug affects ALL the users. Solution: Release to a small number of users first effectively reducing the blast radius and observe. If a problem occurs, stop the release, revert or update the affected users. #DevOpsTO
http://jfrog.com/shownotes
Continuous updates pattern: observability
@jbaruch
#LiquidSoftware
Problem: Some problems are hard to trace relying on user feedback only Solution: Implement tracing, monitoring and logging
#DevOpsTO
http://jfrog.com/shownotes
Slide 48
Continuous updates pattern: Rollbacks
@jbaruch
#LiquidSoftware
Problem: Fixes might take time, users suffer in a meanwhile Solution: Implement rollback, the ability to deploy a previous version without delay #DevOpsTO
http://jfrog.com/shownotes
Slide 49
Continuous updates pattern: feature flags
@jbaruch
#LiquidSoftware
Problem: Rollbacks are not always supported by the deployment target platform Solution: Embed 2 versions of the features in the app itself and trigger them with API calls #DevOpsTO
http://jfrog.com/shownotes
Slide 50
Update available
Yes
Do we trust the update?
Yes
Do we want it?
Are there any high risks?
Sure, why not? (auto update) Yes
Let’s update!
No
Slide 51
”
Our goal is to transition from bulk and rare software updates to extremely tiny and extremely frequent software updates; so tiny and so frequent that they provide an illusion of software flowing from development to the update target.
We call it the Liquid Software vision.
@jbaruch
#LiquidSoftware
#DevOpsTO
http://jfrog.com/shownotes