1. If you knew what I know or CloudWave - Improving services in the Cloud through collaborative adaptation
Eliot Salant
IBM Haifa Research
CloudWave Project Coordinator

2. Where things are today Grid computing – resources allocated to nodes
Cloud Computing
Elasticity
Scale up
Scale out

3. So, what’s the problem? Hint…

4. Evolution of software delivery
Extensive alpha and beta testing
Runs cost money!
Fail early, fail cheaply

5. Release times (wks) – Windows vs. app

6. The DevOps paradigm Development Operations
“A large segment of DevOps tools delivers automation and configuration to relax stress on developers and operators during continuous delivery… but to support smooth operation data analytics will need to step up to the plate.”

7. How can the Cloud better support DevOps-style development AND adopt DevOps concepts itself?

8. The CloudWave idea
Infrastructure behavior
Application behavior

9. CloudWave overview www.cloudwave-fp7.eu
3 year project sponsored by the EU’s FP7
Just finished the first year
10 partner organizations
6.3 Meuro budget

10. Main project concepts Infrastructure monitoring Application monitoring
FDD
Holistic Cloud
events db
Adaptation engine

11. Some CloudWave Challenges
Execution Analytics
Effective monitoring of infrastructure
Effective monitoring of applications
Event filtering, consolidation
Complex event processing
Coordinated Adaptation
Machine Learning techniques
Modeling adaptation scenarios
Feedback Driven Design
Insights to aid developers
Test plan evolution through analytics

12. Strategy
Implementation
Use cases
Research

13. Functional Decomposition
CW DevOp engineer
Development Env
Feedback
App changes
Deployment
Feedback
Runtime Environment
Level 1 decomposition
Configuration
Feedback
CloudWave Admin
Administration Env.
Status visual.
Administration

14. Terminology OpenStack – Open Source cloud computing platform
Heat – Orchestration tool for deployment on OpenStack cloud
HOT – Heat Orchestration Template
Ceilometer – OpenStack resource monitoring tool
Enactment point – Sets the state of the application for adaptation

15. Concept Monitoring data OpenStack action Enactment point definition
Application adaptation
request
Enactment trigger
User input
Physical machine
Cloud Stack
Mgr
Application and monitoring environment
Application and monitoring environment
Living State
Manager
Heat Engine
Monitoring collection and Analysis
FDD
Coordinated Adaptation

16. Application logging tools
CW Monitoring
Physical machine: Nova Compute Node
OpenStack Controller Node
CWE dispatcher
Mongo db
Celiometer Collector
Application code
Application logging tools
CW probe
CW.so library VM
Celiometer Agent
CW Pollister
Pollster1…
PollsterN

17. Adding analytics CelioEsper To Living State Manager Other CEP Engines
OpenStack Controller Node
CWE dispatcher
Mongo db
Celiometer Collector
CelioEsper
Esper
Other CEP Engines
To Living State
Manager
From monitoring

18. Living State Manager HOT++ CW Grunt Heat Engine Adaptation Engine
From Ceiloesper

19. All together now

20. Coordinated Adaptation

21. Directions for Coordinated Adaptation
Machine learning to react to enactment point triggers
Adaptation of both infrastructure and application
Determination of new enactment points

22. Some challenges Multiple layers for adaptation App Middleware
Virtual machine
Physical machine
Data center
Cloud
Federated clouds

23. Coordinated adaptation challenges
Ultimate effect of adaptation actions at different levels not always clear
Sample set for machine learning
Standardizing application adaptations …

24. Example of potential coordinated adaptation
Computations on a mobile phone vs. in Cloud
IoT devices – autonomy vs. centralized control

25. Feedback Drive Design
Better monitoring information and analysis to help developers
Analysis of Adaptation Engine efficiency
Feedback driven testing
Evolution of testing
Problem recreation

26. FDD Challenges Effective feedback visualization
Intelligent hints to developers (analysis)
What-if analysis

27. In summary…