Big Data Tutorial on Mapping Big Data Applications to Clouds and HPC: Cloudmesh: Software Defined Distributed Systems as a Service SDDSaaS

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Cloudmesh: Software Defined

Distributed Systems as a Service

SDDSaaS

January 26 2015

BigDat 2015: International Winter School on Big Data

Tarragona, Spain, January 26-30, 2015

Geoffrey Fox, Gregor von Laszewski

[email protected]

http://www.infomall.org

School of Informatics and Computing Digital Science Center

Indiana University Bloomington

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Origins and Future of Cloudmesh

• _Past:

_{Needed to move back and forth between}

_{Bare Metal}

_{and different}

VM managers

in FutureGrid using emerging DevOps ideas like

Chef

and

templated (software defined)

image libraries

–

_{Address many different changing tools with abstractions}

• _Integrate

_{new metrics}

_{in form consistent with XSEDE at execution (user)}

and job summary levels

• _{Current Focus/Futures:}

_{Preserves and builds on user/project}

/experiment/provisioning/metrics structure of FutureGrid

• _{Now linking of}

_{system definition}

_and

_{system execution}

_{steps in a common}

Python environment while future additions could include

Software

Defined Networking

–

_{System execution classically called orchestration or workflow i.e. our view of SDDS}

includes infrastructure and software including multiple workflow steps

• _{Now used to support}

_laboratories

_for

_{online classes}

_{in data science and}

for several large scale

data analytics research

,

education

and

standards

projects including

NIST

Public Working Group in Big Data

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FutureGrid

IaaS request popularity by year

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Cloudmesh: from IaaS(NaaS) to Workflow

(Orchestration)

(

SaaS Orchestration

)

Workflow

(

IaaS Orchestration

)

Virtual Cluster

Components

Infrastructure

• _IPython

• _{Pegasus etc.}

• _Heat • _Python

• _{Chef or Puppet}

(Recipes/Puppies)

• _{VMs, Docker,}

Networks, Baremetal

Im

ag

es

Im

ag

es

D

at

a

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Cloudmesh and SDDSaaS Stack for HPC-ABDS

SaaS

PaaS

IaaS

NaaS

BMaaS

Orchestration

Mahout, MLlib, R Mahout, MLlib, R

Hadoop, Giraph, Storm Hadoop, Giraph, Storm

OpenStack, Bare metal OpenStack, Bare metal

OpenFlow OpenFlow

Just examples from 289 components

Cobbler Cobbler

Abstract

Interfaces removes tool dependency

IPython, Pegasus, Kepler, FlumeJava, Tez, Cascading IPython, Pegasus, Kepler, FlumeJava, Tez, Cascading

HPC-ABDS at 4 levels

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Basic Strategy

• _{Goal is to make it easier to deploy and mix together}

the 289 HPC-ABDS software components

• _{Further allow deployment on multiple hardware}

environments including academic clouds (OpenStack,

OpenNebula), commercial clouds (AWS, Azure, GCE)

and (HPC) cluster

• _{Suppose expert has captured execution of software i}

as a Chef recipe R(i) or equivalent

• _{Then we automate deployment of virtual cluster VC(i)}

and instantiate R(i) on VC(i) at supported hardware

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Examples of Chef use in class

• _{We can call different recipes from the same cookbook to customize}

the nodes in our cluster uniquely:

• _{{ "run_list": ["recipe[hadoop:: hadoop_hdfs_namenode]"]} versus}

{ "run_list": ["recipe[hadoop:: hadoop_hdfs_datanode]"]}

• _{We can pass information to set custom values in our configuration}

files:

• _{"hadoop" => { "yarn_site" => {"yarn.resourcemanager.hostname" =>}

“10.39.1.99”}}

• _{Chef can even automate installations that require accepting terms:}

• _{"java" => { "oracle" => { "accept_oracle_download_terms" => true} }}

• _{Beyond installation, Chef can even start services running:}

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CloudMesh Architecture

• _{Cloudmesh is a}

_SDDSaaS

_{toolkit to support}

– A software-defined distributed system encompassing virtualized and bare-metal

infrastructure, networks, application, systems and platform software with a unifying goal of providing Computing as a Service.

– The creation of a tightly integrated mesh of services targeting multiple IaaS

frameworks

– The ability to federate a number of resources from academia and industry. This includes existing FutureSystems infrastructure, Amazon Web Services, Azure, HP Cloud, Karlsruhe using several IaaS frameworks

– The creation of an environment in which it becomes easier to experiment with

platforms and software services while assisting with their deployment and execution.

– The exposure of information to guide the efficient utilization of resources. (Monitoring)

– Support reproducible computing environments

– IPython-based workflow as an interoperable onramp

• _{Cloudmesh exposes both hypervisor-based and bare-metal provisioning to}

users and administrators

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Cloudmesh Functionality

User On-Ramp

Amazon, Azure, FutureSystems, Comet, XSEDE, ExoGeni, Other Science Clouds

Cloudmesh

Information

Services

• _CloudMetrics

Information

Services

• _CloudMetrics

Provisioning

Management

• _Rain

• _{Cloud Shifting} • _{Cloud Bursting}

Provisioning

Management

• _Rain

• _{Cloud Shifting} • _{Cloud Bursting}

Virtual Machine

Management

• _{IaaS Abstraction}

Virtual Machine

Management

• _{IaaS Abstraction}

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Building Blocks of Cloudmesh

• _{Uses internally}

_{Libcloud and Cobbler}

• _{Celery Task/Query manager (AMQP - RabbitMQ)}

• _MongoDB

• _{Accesses via abstractions}

_{external systems/standards}

• _{OpenPBS, Chef}

• _{OpenStack (including tools like Heat), AWS EC2, Eucalyptus,}

Azure

• _{Xsede user management (Amie) via Futuregrid}

• _Implementing

_{Docker, Slurm, OCCI, Ansible, Puppet}

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SDDS Software Defined Distributed Systems

• _Cloudmesh

_{builds infrastructure as SDDS consisting of one or more virtual clusters}

or slices with extensive built-in monitoring

• _{These slices are instantiated on infrastructures with various owners}

• _{Controlled by roles/rules of Project, User, infrastructure}

Python or REST API User in Project User in Project CMPlan CMPlan CMProv CMProv CMMon CMMon Infrastructure (Cluster, Storage, Network, CPS) Infrastructure (Cluster, Storage, Network, CPS) Instance Type

Current State

Management Structure

Provisioning Rules

Usage Rules (depends on user roles) Results Results CMExec CMExec User RolesUser Roles

User role and infrastructure rule dependent security

checks

User role and infrastructure rule dependent security

checks

Request

Execution in Project

Request SDDS

Select

Plan Requested SDDS as _{federated Virtual}

Infrastructures Requested SDDS as

federated Virtual Infrastructures #1Virtual infra. Linux #2 Virtual infra. Windows #3Virtual infra. Linux #4 Virtual infra. Mac OS X Repository Repository Image and Template Library SDDSL SDDSL 

_{One needs general}

hypervisor and

bare-metal slices to

support research



_Gives an

experiment

management

system

that

enables

reproducibility

in

science output.

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What is SDDSL?

• _{There is an active OASIS standard activity}

_TOSCA

_{(Topology and}

Orchestration Specification for Cloud Applications)

• _{But this is similar to mash-ups or workflow (Taverna, Kepler,}

Pegasus, Swift ..) and we know that workflow itself is very

successful but workflow standards are not

–

_{OASIS WS-BPEL}

_{(Business Process Execution Language) didn’t catch on}

–

_{Analogy and differences between IaaS orchestration (TOSCA) and SaaS}

orchestration (BPEL) impo

• _{As basic tools (Cloudmesh) use Python and Python is a popular}

scripting language for workflow, we suggest that

Python

could

be

SDDSL

–

_{IPython Notebooks are natural log of execution provenance}

–

_{Explosion of new Commercial (Google Cloud Dataflow) and Apache}

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Cloudmesh as an On-Ramp

• _{As an On-Ramp, CloudMesh deploys recipes on}

multiple platforms so you can test in one place and do

production on others

• _{Its multi-host support implies it is effective at}

distributed systems

• _{It will support traditional workflow functions such as}

–

_{Specification of an execution dataflow}

–

_{Customization of Recipe}

–

_{Specification of program parameters}

• _{Workflow quite well explored in Python}

_https://

wiki.openstack.org/wiki/NovaOrchestration/Workflo

wEngines

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Comparison of OpenStack Sahara and

Cloudmesh

Feature

Sahara

Cloudmesh

IaaS platform

OpenStack OpenStack, Eucalyptus, Amazon, Azure, HP Cloud

Hadoop cluster

Available Available

Other HPC-ABDS

Not Available Available if correct Recipe or equivalent available

Management

Web UI, REST API Web UI, CLI, REST API

Autoscaling

Manual add/remove

nodes Scaling supported at CM level; higher level needs to invoke

Hierarchical

clusters

Not Available Subcluster with `launcher`, `group` commands

Containers

Not Available Chef, Puppet, Ansible, Docker

Cloud

orchestration

OpenStack Heat

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Cloudmesh: Integrated Access Interfaces

(Horizontal Integration)

GUI

Shell

IPytho

n

IPytho

n

API

REST

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… Register clouds

Multiple clouds are registered

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… Working with VMs in Cloudmesh

VMs

Panel with VM Table (HP)

Search

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… baremetal provisioner

(not released yet)

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Provisioning OpenStack

(not released yet)

View the parallel provisioning tasks execution from AMPQ

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Monitoring and Metrics Interface

• _{Service Monitoring}

• _{Energy/Temperature}

Monitoring

• _{Monitoring of}

Provisioning

• _{Integration with other}

Tools

–

_{Nagios, Ganglia, Inca, FG}

Metrics

–

_{Accounting metrics}

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Cloudmesh MOOC

Videos

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Overview of Cloudmesh on FutureSystems

Tutorial

• _{Getting Started – FutureSystems}

–

_{Account Creation}

–

_{OpenStack (india.futuresystems.org)}

–

Cloudmesh installation (management software)

• _Tutorials

–

_{Tutorial I: Deploying Virtual Cluster}

–

_{Tutorial II: Deploying Hadoop Cluster}

–

_{Tutorial III: Deploying MongoDB Cluster}

• _Resources

–

_Source code

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Getting Started – FutureSystems

Account Creation

• _{Register an account}

–

_{https://portal.futuregrid.org/}

• _{Join a existing project or create a new one}

–

Create:

https://portal.futuregrid.org/node/add/fg-projects

–

Join:

https://portal.futuregrid.org/projects/all

• _{Upload SSH KeyPair}

–

_{https://portal.futuregrid.org/my/ssh-keys}

• _Tutorial:

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Using OpenStack on FutureSystems

Cluster India

• _{IaaS Platform (Havana release, Juno will be available soon)}

• _SSH to

$ ssh –i [keyfile] [portal username]@india.futuregrid.org

• _{Configure an account}

$ Source ~/.cloudmesh/clouds/india/havana/novarc

• _{Enable nova client}

$ module load novaclient

• _Tutorial:

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Cloudmesh Installation

• _{Cloud management software}

• _{Supports OpenStack, Eucalyptus, Amazon}

AWS, Microsoft Azure Virtual Machine, and HP

Cloud

• _{Management on CLI or Web UI}

• _Tutorial:

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Tutorial I: Deploying Virtual Cluster

• _{`cm cluster` Cloudmesh command}

• _{Deploy a cluster}

$ cm cluster create [cluster name] --count=[number of nodes]

• Login to a cluster

$ cm vm login [node name] --ln=[username to login]

• _{Terminate a cluster}

$ cm cluster remove [cluster name]

Tutorial:

http://introduction-to-cloud-computing-on-futuresystems.readthedocs.

org/en/latest/virtual_cluster.html

Cluster Cx

•Run Cluster

Template Tx

• Select Template

SubCluster Cx

• Load Subcluster (if exists)

Container Rx (e.g. chef, puppet, Ansible, Docker) • Call Recipe

Software Sx

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Screenshot of deploying Virtual Cluster

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Tutorial III: Deploying MongoDB Sharded Cluster

• _{Install Config Server}

• _{Start Mongo Shard (replica set) Server}

• _{Connect Shard Servers to a cluster}

• _{Enable Sharding for a database or a collection}

• _Tutorial:

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Cloudmesh Resources

• _Tutorials

–

_Main Home:

http://introduction-to-cloud-computing-on-futuresystem

s.readthedocs.org/en/latest/index.html

–

_Videos:

http://introduction-to-cloud-computing-on-futuresystem

s.readthedocs.org/en/latest/resources.html

• _Cloudmesh

–

_{Documentation with video clips:}

http://cloudmesh.github.io/introduction_to_cloud_com

puting/class/i590.html

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Infra

structure

IaaS

 Software Defined

Computing (virtual Clusters)

 _{Hypervisor, Bare Metal}  Operating System

Platform

PaaS

 Cloud e.g. MapReduce

 _{HPC e.g. PETSc, SAGA}  _{Computer Science e.g.}

Compiler tools, Sensor nets, Monitors

Software-Defined Distributed

System (SDDS) as a Service includes

Network

NaaS

 Software Defined Networks

 _{OpenFlow GENI}

Software

(Application Or Usage)

SaaS

 Use HPC-ABDS

 _{Class Usages e.g. run}

GPU & multicore

 Applications

 _{Control Robot}

FutureSystems uses SDDS-aaS Tools

 Provisioning

 Image Management

 IaaS Interoperability

 NaaS, IaaS tools

 Expt management

 Dynamic IaaS NaaS

 DevOps

FutureSystems uses SDDS-aaS Tools

 Provisioning

 Image Management

 IaaS Interoperability

 NaaS, IaaS tools

 Expt management

 Dynamic IaaS NaaS

 DevOps

CloudMesh is a

SDDSaaS tool that uses Dynamic Provisioning and Image Management to provide custom

environments for general target systems

Involves (1) creating, (2) deploying, and (3) provisioning

of one or more images in a set of machines on demand

http://mycloudmesh.org/

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Dynamic Orchestration and

Dataflow

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Cloudmesh Architecture

• Cloudmesh

Management

Framework

for

monitoring and

operations, user and

project management,

experiment planning

and deployment of

services needed by an

experiment

• _{Provisioning and}

execution

environments to be

deployed on resources

to (or interfaced with)

enable experiment

management.

• _Resources

_.

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CloudMesh User View of SDDS aaS

• _{Note we always consider virtual clusters or slices with nodes that}

may or may not have hypervisors

• _{Well defined user and project management assigning roles}

• _BM-IaaS

_{: Bare Metal (root access) Infrastructure as a service with}

variants e.g. can change firmware or not

• _H-IaaS:

_{Hypervisor based Infrastructure (Machine) as a Service. User}

provided a collection of hypervisors to build system on.

–

Classic Commercial cloud view

• _PSaaS

_{Physical or Platformed System as a Service where user}

provided a configured image on either Bare Metal or a Hypervisor

–

User could request a deployment of Apache Storm and Kafka to control a set

of devices (e.g. smartphones)

–

_{XSEDE software stack}

• _{Related systems administrator view}

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Cloudmesh Components I

• _Cobbler:

Python based provisioning of bare-metal or hypervisor-based systems

• _{Apache Libcloud:}

_{Python library for interacting with many of the}

popular cloud service providers using a unified API. (One Interface To

Rule Them All)

• _Celery

_{is an asynchronous task queue/job queue environment}

based on RabbitMQ or equivalent and written in Python

• _{OpenStack Heat}

_{is a Python orchestration engine for common}

cloud environments managing the entire lifecycle of infrastructure

and applications.

• _Docker

_{(written in Go) is a tool to package an application and its}

dependencies in a virtual Linux container

• _OCCI

_{is an Open Grid Forum cloud instance standard}

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Cloudmesh Components II

• _Chef

_{Ansible Puppet Salt}

_are system

configuration managers. Scripts are used to define system

• _Razor

_{cloud bare metal provisioning from EMC/puppet}

• _Juju

_{from Ubuntu orchestrates services and their}

provisioning defined by charms across multiple clouds

• _Xcat

_{(Originally we used this) is a rather specialized (IBM)}

dynamic provisioning system

• _Foreman

_{written in Ruby/Javascript is an open source}

project that helps system administrators manage servers

throughout their lifecycle, from provisioning and

configuration to orchestration and monitoring. Builds on

Puppet or Chef

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Cloudmesh Provisioning and Execution

• _{Bare-metal Provisioning}

– _{Originally developed a provisioning framework in FutureGrid based on xCAT and Moab.}

(Rain)

– _{Due to limitations and significant changes between versions we replaced it with a}

framework that allows the utilization of different bare-metal provisioners.

– _{At this time we have provided an interface for cobbler and are also targeting an interface}

to OpenStack Ironic.

• _{Virtual Machine Provisioning}

– An abstraction layer to allow the integration of virtual machine management APIs based on the native IaaS service protocols. This helps in exposing features that are otherwise not accessible when quasi protocol standards such as EC2 are used on non-AWS IaaS frameworks. It also prevents limitaions that exist in current implementations, such as libcloud to use OpenStack.

• _{Network Provisioning}

_(Future)

– _{Utilize networks offering various levels of control, from standard IP connectivity to}

completely configurable SDNs as novel cloud architectures will almost certainly leverage NaaS and SDN alongside system software and middleware. FutureGrid resources will make use of SDN using OpenFlow whenever possible though the same level of