If you knew what I know or CloudWave - Improving services in the Cloud through collaborative adaptation Eliot Salant [email protected] IBM Haifa Research.

If you knew what I knowor

CloudWave - Improving services in the Cloud through collaborative adaptation

Eliot Salant

[email protected]

IBM Haifa Research

CloudWave Project Coordinator

Where things are today

Grid computing – resources allocated to nodes

Cloud ComputingElasticity

Scale upScale out

So, what’s the problem? Hint…

Evolution of software delivery

Runs cost money!

Fail early, fail cheaply

Extensive alpha and beta testing

Release times (wks) –Windows vs. app

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.” http://siliconangle.com/blog/2014/12/23/predictions-for-devops-in-2015-the-year-of-smart-devops/

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

The CloudWave idea

Infrastructure behavior

Application behavior

CloudWave overviewwww.cloudwave-fp7.eu

3 year project sponsored by the EU’s FP7Just finished the first year

10 partner organizations

6.3 Meuro budget

Main project concepts

Holistic Cloudevents db

Application monitoringInfrastructuremonitoring

Adaptation engine

FDD

Some CloudWave Challenges

Strategy

Functional Decomposition

CW DevOp engineer

Development Env

Administration Env.

Runtime Environment

Feedback

App changes

FeedbackDeployment

FeedbackConfiguration CloudWave Admin

Status visual.

Administration

Level 1 decomposition

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

Concept

Application and monitoring environment

Monitoring collection and

Analysis Coordinated Adaptation

Monitoring data

Enactment point definition

Enactment trigger

Living State Manager

User input

OpenStack action

Application adaptation request

Heat Engine

FDD

Physical machine

Application and monitoring environment

Cloud Stack Mgr

CW Monitoring

Physical machine: Nova Compute Node

CW.so library

CW Pollister

PollsterN

Pollster1…

Application code

Application logging

tools

Celiometer Agent

CW probe

VM

OpenStack Controller Node

CWE dispatcher

Mongo db

Celiometer Collector

Adding analytics

OpenStack Controller Node

CWE dispatcher

Mongo db

Celiometer Collector

CelioEsper

EsperOther CEP

Engines

To Living StateManager

From monitoring

Living State Manager

HOT++

Heat Engine

Adaptation Engine

CW Grunt

From Ceiloesper

All together now

Coordinated Adaptation

Directions for Coordinated Adaptation

• Machine learning to react to enactment point triggers

• Adaptation of both infrastructure and application

• Determination of new enactment points

Some challenges• Multiple layers for adaptation

Coordinated adaptation challenges

• Ultimate effect of adaptation actions at different levels not always clear

• Sample set for machine learning

• Standardizing application adaptations

• …

Example of potential coordinated adaptation

• Computations on a mobile phone vs. in Cloud

• IoT devices – autonomy vs. centralized control

Feedback Drive Design

• Better monitoring information and analysis to help developers

• Analysis of Adaptation Engine efficiency

• Feedback driven testing– Evolution of testing

• Problem recreation

FDD Challenges

• Effective feedback visualization

• Intelligent hints to developers (analysis)

• What-if analysis

In summary…