The document discusses ensuring dependable operations in cloud computing. It notes that 80% of outages are caused by human/process issues rather than technical faults. The author presents a process-oriented approach to modeling operations as sets of steps executed by agents requiring resources. Faults at one step may surface later, so their framework aims to verify step post

1. NICTA Copyright 2012 From imagination to impact
Dependable Operation
Dr. Liming Zhu
Software Systems Research Group
NICTA (National ICT Australia) &
University of New South Wales
DevOps Days Downunder, 2013
Liming.Zhu@nicta.com.au slideshare.net/LimingZhu/

2. NICTA Copyright 2012 From imagination to impact
Motivation
• Applications fail due to operation issues
– Gartner report: 80% of outage caused by people/process issues
• Sporadic activities: replication/failover, auto-scaling, upgrade…
– Not that dependability issues may trigger mitigating operations but
the converse:
• dependability, often unexpectedly, is affected by these mitigating
activities and other sporadic activities
– Lessons from our own cloud disaster recovery product:
Yuruware.com
• Complex interleaving “sporadic” processes/activities
– Scripts, tools, human
– Activities auto-triggered by policies, monitoring and analysis
– Logs/Events often lack the “process-context”
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3. NICTA Copyright 2012 From imagination to impact
Our Process-Oriented Approach
• Existing artifact-oriented and state-based research
– Log analysis linking back to issues in source code
– Static configuration analysis and constraint checking
– State-based system-level models
• We treat an operation as a set of steps
– Executed by fault-prone agents (scripts/tools/human)
– Requiring various fault-prone resources (computing/nodes/environ)
– Faults at one step may surface later at another step
– Exception handling: error diagnosis, undo/redo, fixing, tolerating…
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4. NICTA Copyright 2012 From imagination to impact
What We Are Working On
• Undo Framework and Undo-ability of Operations
– AWS Cloud API wrapper to allow undo
– Use AI Planning to check undo-ability and plan undo path
• Model, Monitor and Simulate Operations
– Post-condition verification and monitoring of steps
– Use monitored process context for error diagnosis and recovery
– Simulate large-scale operations: probability/time of successful
completion, bottle necks and problems
• Process Mining from Logs
– Mine a process from existing log files
– Detect deviation early or help error diagnosis
Tell us the right problems and approaches!
Liming.Zhu@nicta.com.au slideshare.net/LimingZhu/
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