CLEVER

Andrea Fornaia

Consortium GARR

A light middleware for Private/Hybrid Cloud

Grid and Cloud workshop. Peking University, Beijing (China).

Monday, 23 April 2012

Cloud: a definition

“Cloud Computing is a large-scale distributed computing paradigm that is driven by economies of scale, in which a pool virtualized resources are delivered on demand to external customers over the Internet.”

[I. Foster et al. (2008)]

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Three different cloud service levels

Virtualization

Hardware

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

A Cloud classification: Public, Private and Hybrid Clouds

» Public Clouds » Management of Virtual Machine instances within a proprietary infrastructure.

» Many different customers can run and control their own applications.

» Access from a remote interface using a specific protocol.

» Private Clouds » Infrastructure owned by a single organization offering its internal computing

resources to local users: do not “sell“ computing capacity.

» Open Source tools employment, dedicated operating environment offered to local users with high trust level

» Hybrid Clouds » A private cloud which adds to the local infrastructure more computing

capacity with resources coming from an external public clouds.

» External resources access allowed over the Internet, using remote interfaces.

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Private/Hybrid Cloud middlewares: a reference stack » Features of Private/Hybrid cloud middlewares:

External Cloud Interfaces

Security Federation Contextualization

Autoscaling

Dynamic Resource Scheduling

VE Deployment

Data Management Networking

Configuration

Disk Image Management

Resource Monitoring

High-level Management

Virtual Infrastructure Management

» Middleware for Virtual Infrastructure Management: essentially dynamic orchestrator of Virtual Environments (VEs).

» Middleware for High-level Management: transforms existing infrastructures into an IaaS clouds with cloud-like interfaces; adds Security, Contextualization, Federation and other ”high-level” mechanisms.

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Private/Hybrid Cloud middlewares: existing solutions » Virtual Infrastructure Management Middlewares: OpenQRM and

OpenNebula ˃ Deploy and manage VEs: individually or in groups needing parallel

scheduling on local resources or external public clouds.

˃ Automate VE setup regardless of the underlying virtualization layer.

˃ Lack mechanisms for building hybrid IaaS clouds: public cloud-like interfaces, the ability to deploy VMs on external clouds and other High-level functionalities.

» High-level Middlewares: Globus Nimbus and Eucalyptus ˃ Transform existing infrastructure into an IaaS cloud with cloud-like

interfaces.

˃ Compatible with the Amazon EC2 or Web Services Resource Framework (WSRF) interfaces and offers self-configuring virtual cluster support.

˃ Include Cloud-like interfaces and higher-level functionalities for security, contextualization.

˃ Limited VI management capabilities: lack the features of middlewares specialized in VI management.

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

A new cloud computing middleware: CLEVER » Acts as a middleware for the management of Private and Hybrid

cloud computing infrastructures.

» Specifically integrates VI Management layer functionalities.

» Provides simple and easily accessible interfaces:

˃ Integration of security, contextualization and other high-level functionalities made available from higher level software components;

˃ Interconnection of different heterogeneous cloud computing infrastructures.

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Main features of CLEVER

» All inside a JAR, no installation required » Easy to deploy, easy to remove » Light in requirements » Fully pluggable and customizable » High scalability, easy to add new nodes to you cloud » Firewall pass through » Fault tolerant aware » Auto configuration: you only customize you middleware in

order to run in any node of you infrastructure. The middleware will auto generate the configuration required

» Manage distributed and heterogeneous resources, even it they are in separated networks

» Federation of different CLEVER cloud achieved

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

General Architecture on the reference scenario

» N computing nodes containing one host level Management module: Host Manager.

» One node includes a cluster level Management module: Cluster Manager.

» External components: XMPP Server and Distributed Database.

» Middleware entities “talks” in an XMPP chat room exploiting the presence feature.

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

CLEVER Architecture

» Host Manager (HM)

˃ Communicates with the hosts’ OS, hypervisor and distributed file-system on which the VE disk-images are stored.

˃ Performs both physical resources and VEs monitoring.

˃ Runs VEs on the physical hosts even performing their migration.

» Cluster Manager (CM)

˃ Coordinates the HMs and performs operations on the Distributed Database.

˃ Acts as an interface between the clients and the HM.

˃ Performs the user VE disk-images management and the monitoring of the overall cluster state.

˃ At least one CM has to be deployed on each cluster: many of them should exist to enable fault-tolerance.

˃ A master CM will be in active state while the other ones will remain in a monitoring state: automatic active CM re-election.

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

XMPP for the communication layer

» Administration XMPP Room ˃ Admin consoles join this room in order to interact whit the unique CM active in the CLEVER

private cloud.

˃ CM will forward the Admin requests to the properly HMs within the External Communication Room.

» External Communication XMPP Room ˃ Each HM joins this room in order to receive commands from the CM.

˃ In case of failure of the CM, the other HMs will start an algorithm in order to create a new CM

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

XMPP & Distributed Database

» XMPP (ejabberd)

˃ Offers a decentralized communication channel: more XMPP server could exists.

˃ Using more servers avoids a central point of failure.

˃ Both CMs and HMs “talks” in a chat room exploiting the presence feature.

˃ Information about the cluster state (connected hosts) offered directly by the protocol.

˃ It is easy to add new nodes in the infrastructure, the new node only needs to connect to the chat room to notify his presence: scalability.

» Distributed Database (sedna)

˃ Database containing the overall set of information related to the middleware: the current state of the VEs, data related to the XMPP connection.

˃ Developed according to a well structured approach, for enabling fault tolerance features.

˃ Used by both the Active/Idle CMs and XMPP server(s).

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Host Manager Components: Host Coordinator

» Each HM component mapped an a different OS process: high modularity and fault tolerance.

» The core of the Host Manager: it coordinates all the HM internal components using a specific Internal Communication protocol (D-BUS or JMS).

» Through the CM interface communicates with the CMs exchanging XMPP chat messages on the specific room (VEs allocation, Monitoring State, etc.).

All inside a JAR

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Host Manager: Monitor and Low-level components

» Monitor: Resource usage monitoring for each host. Information organized and made available for the HM coordinator.

» Hypervisor Interface: middleware back-end to the host hypervisor. Different virtualization technologies could be employed using different plug-ins structure has to be developed.

» Image Manager: supply to the Hypervisor Interfaces the needed VE disk-image corresponding to a specific VE. Different plug-ins associated to different data access/transfer method.

» Network Manager: Gathers information about the host network state. Manages host network (OS level) according to the guidelines provided by the HM Coordinator: dynamic creation of network bridges, routing and firewalling rules.

All inside a JAR

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Cluster Manager Components: Cluster Coordinator

» Database Manager: interacts with the database used to store information needed to the cluster handling. Database Manager must maintain the data strictly related to the cluster state.

» Performance Estimator: Analysis of the set of data collected from the Coordinator, in order to compute and provide a probable trend estimation of the collected measures.

» Image Manager: manages registration and upload within the Cluster Storage System of the VEs disk-images. The Storage Manager is used to perform the registration process of such files and manage the internal cluster distributed file system.

All inside a JAR

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Agent based: fully pluggable and fault tolerant

» Separated process for Each Agent/Plugin » Re-spawn of the Agent/Plugin in case of failure » Agent/Plugin loaded and removed at runtime (eaven new features) » CLEVER can be customized in order to achieve not only cloud task,

but even more.

JVM JVM JVM JVM

IPC (D-BUS)

Cluster Coordinator

Image Loader

Hypervisor Interface

Image Loader

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Federation process using XMPP

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Future Works: CLEVER on gLite Grid middleware

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012

Thank you for attention

Grid and Cloud workshop. Peking University, Beijing (China). Monday, 23 April 2012