Abstract Image Management and
Universal Image Registration for
Cloud and HPC Infrastructures
https://portal.futuregrid.org
Javier Diaz, Gregor von Laszewski, Fugang Wang and Geoffrey Fox
Community Grids Lab
Motivation
• FutureGrid (FG) is a testbed providing users with grid, cloud, and high performance computing
resources
• One of the goals of FutureGrid is to provide a
testbed to perform experiments in a reproducible way among different infrastructures
• We need mechanism to ease the use of these infrastructures
Introduction I
• Image management is a key component in any modern compute infrastructure (virtualized or non-virtualized)
• Processes part of the image management life-cycle:
Introduction II
• Targeting multiple infrastructures amplifies the need for mechanisms to ease these image
management processes
• We have identified two mechanisms
– Introduce standards and best practices to interface with the infrastructure (OVF, OCCI, Amazon EC2)
– Provide tools that interface with these standards and expose the functionality to the users while hiding the underlying complexities
FutureGrid Image Management
Framework
• Framework provides users with the tools needed to ease image management across infrastructures
• Users choose the software stacks of their images and the infrastructure/s
• Targets end-to-end workflow of the image life-cycle
• Create, store, register and deploy images for both virtualized and non-virtualized resources in a
transparent way
• Allows users to have access to bare-metal
provisioning (departure from typical HPC centers)
– Users are not locked into a specific computational environment offered typically by HPC centers
Image Generation
• Creates images according to user’s specifications:
• OS type and version • Architecture
• Software Packages
• Software installation may be aided by Chef
• Images are not aimed to any specific infrastructure
• Image stored in Repository or returned to user
Image Repository
• Service to query, store, and update images
• Unique interface to store various kind of images for different systems
• Images are augmented with some metadata which is maintained in a searchable catalog
• Keep data related with the usage to assist performance monitoring and accounting
Image Metadata
Field Name Description
imgId Image’s unique identifier owner owner
os Operating system
description Description of the image
tag Image’s keywords
vmType Virtual machine type
imgType Aim of the image
permission Access permission
imgStatus Status of the image createdDate Upload date
lastAccess Last time the image was accessed accessCount # times the image has been
accessed
size Size of the image
User Metadata
Field
Name Description
userId User’s unique identifier
fsCap Disk max usage (quota) fsUsed Disk space used
lastLogin Last time user used the framework
status Active, pending, disable
role Admin, User
Image Registration I
•
Adapts and registers images into specific
infrastructures
•
Two main infrastructures types are considered
to adapt the image:
– HPC: Create network bootable images that can run in bare-metal machines (xCAT/Moab)
Image Registration II
• User specifies where to register the image
• Optionally, user can select kernel from a catalog
• Decides if an image is secure enough to be registered
• The process of registering an image only needs to be done once per infrastructure
Tests Results obtained from the
Analysis of the Image
Methodology
• Software deployed on the FutureGrid India cluster
– Intel Xeon X5570 servers with 24GB of memory – Single drive 500GB with 7200RPMm 3Gb/s
– Interconnection network of 1Gb Ethernet
• Software Client is in India’s login node
• Image Generation supported by OpenNebula
• Image Repository supported by Cumulus (store images) and MongoDB (store metadata)
• HPC supported by xCAT, Moab and Torque
• Performed different tests to evaluate the Image Generation and the Image Registration tools
Scalability of Image Generation I
• Concurrent requests to create CentOS images from scratch
Scalability of Image Generation II
•
Analyze how the time is spent within the
image creation process
•
Only one OpenNebula compute node to better
analyze the behavior of each step of the
process
•
Concurrent requests to create CentOS and
Ubuntu images
•
Image creation performed from scratch and
reusing a base image from the repository
Create Image from Scratch
CentOS
Create Image from Base Image
https://portal.futuregrid.org
CentOS
Scalability of Image Registration
• Register the same CentOS image in different infrastructures:
– OpenStack (Cactus version configured with KVM hypervisor)
– Eucalyptus (2.03 version configured with XEN hypervisor)
– HPC (netboot image using xCAT and Moab)
• Concurrent registrations in Eucalytpus and Openstack
• Only one request at a time is allowed for HPC
Register Images on Cloud
http://futuregrid.org
Eucalyptus
Conclusions I
•
We have introduced the FG
user-controlled
image management framework to handle
images for different infrastructures
•
Framework abstracts the details of each
underlying system
•
Users can easily create and manage
customized environments within FG
•
Replicate software stack on the supported
cloud and bare-metal infrastructures
Conclusions II
• Image management results show a linear increase in response to concurrent requests
• Image Generation
– Create image from scratch in only 6 min and using a base image in less than 2 min
– Scale by adding more nodes to the cloud
– Support different OS and arch due to virtualization
• Image Registration registers images in any supported infrastructure in less than 3 min
