paas on openstack

SINGLE PLATFORM. COMPLETE SCALABILITY.

PaaS on OpenStack@natishalomCTO & Founder GigaSpaces

Agenda

Defining the PaaS

Different paths to PaaS

PaaS on OpenStack

Demo (Optional)

Defining the PaaS

There is a difference between knowing the PaaS (path), and walking the PaaS (path).

Morpheus in “The Matrix”

Quiz: What do you

expect from a PaaS?

Agenda

Defining the PaaS

PaaS on OpenStack

Demo (Optional)

Different Paths to PaaS

Productivity vs. Control tradeoffs

Google App Engine Architecture

Control assumptions

• HW configuration• Operating system• Language (Java/Paython)• Middleware stack (data-

base, messaging,…)• Architecture• Performance (Quota :

CPU, Mem, Net,..)• Data center location

• Application Code• Selecting the middleware

stack from a predefined list.

Heroku Architecture

Routing Mesh

Dyno Grid

SQL Database

Memory Cache

Control assumptions

• HW configuration• Operating system• Language (Ruby)• Middleware stack (data-

base, messaging…)– Flexibility of choices

• Architecture• Performance (dyno)• Data center location

• Application Code• Selecting the middleware

stack from a predefined list

Elastic BeanstalkApplication

Elastic Beanstalk Architecture

AutoScaling

http://myapp-staging.elasticbeanstalk.com/

Elastic Load Balancer

Apache

Tomcat

Amazon Linux AMI

Your Running Application

EC2 Instances

VersionVersion

VersionEnvironment

Control assumptions

Amazon• Operating system• Language (Java)• Middleware stack

(tomcat, RDS…)– Can be easily extended

• Architecture (Web)• Storage• Data center

You• Application Code• Selecting the middleware

stack (anything beyond tomcat)

• HW configuration• Performance • Limited control over the

OS using linux tools• JVM tuning/configuration

Productivity Myths

• You have to give up control for more simplicity– Not always…

• Less code = more productivity– Productivity is measured by units of

features being delivered (not lines of code)

• Opinionated architecture (Rails/Grails) is extremely productive

Carlos Ble's post Goodbye Google App Engine

“..developing on GAE introduced such a design complexity that working around it pushes us 5 months behind schedule.”

So Who’s Better?

Google/Heroku• Top-down sandbox

approach• Highly opinionated• Designed for extreme

simplicity at expense of user control

Amazon • Bottom-up approach• Designed for extreme

simplicity with a significantly higher degree of control

Fits a small subset of apps

Fits a larger spectrum of apps

Agenda

Defining the PaaS

PaaS on OpenStack

Demo (Optional)

PaaS on OpenStack – Aim Higher

• Anyone should be able to:– Build their own PaaS in a snap– Run on any cloud (public/private)– Gain multi-tenancy, elasticity… Without code changes.

• Provide a significantly higher degree of control without substantial complexity– Language choice– OS– Middleware stack

• Should come pre-integrated with popular stack– Spring,Tomcat, DevOps, NoSQL, Hadoop…

• Designed to run the most demanding mission-critical apps

The Building Blocks..

Service Orchestration

Recipe

Service

• Provision• Automation• Multi-tenancy• Management/Monitoring

• Package• Configuration• Life cycle

• Any process or group of processes• DB, Web, NoSQL

Service Orchestration Layer

Grid Service ManagerAgent

Grid Service Container

GigaSpaces Application Cluster

Public Cloud Private CloudBare metal

Scale-out

Scale-in

DeployControl

Data Center/Cloud

Life cycle Provisioning Monitoring Statistics

Zoom-In…

Service Recipe (Proposal)

service { name "cassandra-service" icon new File("icon.png") defaultScalingUnit "small" IpRange "*.*.*.*"

lifecycle { //life cycle events can be shell scripts or groovy closures that receive the admin as a parameter //here you can implement logic to download binaries from any repository or file server install {ServiceContext serviceContext -> myCalculatedParam = serviceContext.serviceInstance.localHostAddress.hostName; masterNodeIp = serviceContext.getServiceInstanceMatching(name("cassandra-master")).localHostAddress.hostName serviceContext.environmentParameters["localHostName"] = myCalculatedParam; port = serviceContext.portLocator.nextAvailablePort serviceContext.environmentParameters["port"] = port //inject runtime parameters to a config file / script using a utility class serviceContext.templateReplacer.replace("cassandra.yaml", serviceContext.environmentParameters) "install.sh".execute(); } uninstall "install.sh" relocate "relocate.sh" preStart "pre-start.sh" start "start.sh" postStart "post-start.sh" preShutdown "pre-shutdown.sh" shutdown "shutdown.sh" postShutdown "post-shutdown.sh" }

Service Recipe Monitors & SLA

monitoring { pluginClass "org.openspaces.usm.JmxMetricsCollector" config { jmxOperations["org.apache.cassandra.db:CompactionManager:CompletedTasks:Cassandra": "Completed Tasks", "org.apache.cassandra.db:CompactionManager:PendingTasks:Cassandra": "Pending Tasks", "org.apache.cassandra.db:CompactionManager:ColumnFamilyInProgress:Cassandra": "Column Family In Progress"]; jmxHost "127.0.0.1"; jmxPort 8080; } }

sla { deploymentConstraints { scalingUnit small } scalingRules { rule { priority 1 when {thisSerice().anyInstace."Disk Space".lessThan(30.MB) } add 2.ScalingUnits }

rule { priority 2 when {thisSerice().anyInstace."CPU Utilization".lessThan(30.Percent).for(5.Minutes)} remove 1.ScalingUnit

rule { when (alertOfType("CPU Utilization").raisedFor(anyServiceNode())) } // }

Agenda

Defining the PaaS

PaaS on OpenStack

Demo (Optional)

You take the control seat.

How does it work?

The Demo

• Use Cassandra as a private case for a service

• Demonstrate what it takes to– Deploy– Manage– Handle failure– Scale– Monitor

The Deployment Process

CassandraInstallation

4) Provision a Machine and installGigaSpaces

5) Start containers

6) Start cassandra

CassandraInstances

7) Add instance

3) Deploy

2) Pack

1) Deploy Cassandra

DevOps CLIElastic Service

Manager

Continuous Availability

CassandraInstances

USM starts new instance

Machine failure

CassandraInstances

Elastic ServiceManager

Instance failure

Elastic manager starts a new instance on another machine

Continuous Scalability

CassandraInstances

Monitor

Not enough resources to meet the SLA

Add resources to meet the SLA

Multi-Tenancy

Tenant A

Tenant B

Tenant C

Add shared tenant

Add private tenant

Composite Application

Apache

Tomcat

Cassandra

Monitoring

• Redirect console output• Monitor statistics through JMX• Pluggable monitoring• Management console:

– Web– CLI– API (REST, Groovy, Java)

• Alerts

Current Status

• JClouds provider for OpenStack is ready– Developed in Collaboration with GridDynamics & Adrian

Cole– Integrated with OpenStack/Cactus build– Required a few patch updates to OpenStack code base

• Continuous collaboration with Citrix– Integrate the platform with the underlying IaaS stack

• Better performance/utilization– Full stack (pre-engineered) enterprise-ready solution

Join the Effort

• Call for action– Try out the provider jclouds– Establish a PaaS working group to drive PaaS

within OpenStack community

• Register now for the beta program– www.gigaspaces.com

• Learn more..– natishalom.typepad.com– blog.gigaspaces.com

Summary

• Curving out complexity, opinionated architecture, relying on someone else’s stack is only one way to achieve productivity at the expense of control

• With OpenStack we can aim higher and make the application infrastructure simpler and better suited for the cloud in the first place

GigaSpaces Cloud Enabled Platform gigaspaces.com/paas-enablement

gigaspaces.com/saas-enablement

GigaSpaces XAP Product Overview:http://www.gigaspaces.com/wiki/

paas on openstack

agenda copyright

control assumptions

productive copyright

control tradeoffs copyright

heroku architecture

service recipe proposalservice

paas path

utility class servicecontext

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