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1Summer School on Grid and Cloud Workflows and Gateways 2013
“Cloud bursting”on SZTAKI Cloud
Attila Csaba MarosiCloud Computing Research Group
MTA SZTAKI LPDS marosi.attila@sztaki.mta.hu
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Outline• Terminology• Recap: SZTAKI Cloud and LPDS Cloud• Cloud-Manager• Cloud bursting definition, scalability in general• Scaling scenarios @ SZTAKI Cloud• Summary• Additional Reading and References
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Terminology I.• Based on deployment model:
o Public Cloud – “The cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.” 3
o Private Cloud – “The cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on premise or off premise.”3
o Hybrid Cloud – Environment created by the combination of public and private cloud offerings
o (Community Cloud) 3
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Terminology II.• Based on location:
o Internal Cloud – Subset of the Private Cloud model where it is offered by an IT organization to its own business1 (“on premise”3 ).
o External Cloud – Not hosted by own organization and offered by a 3rd party. It can be either public or private 1 (“off premise”3 ).
• Point of view of architectural service layerso Software as a Service (SaaS) o Platform as a Service (PaaS) o Infrastructure as a Service (IaaS) – Cloud bursting (scaling) at this level
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Recap• SZTAKI Cloud*
o Institutional IaaS Cloud service by SZTAKI (private, internal)o 7 nodes (7*64 Core, 7*256GB RAM), 2*32TB Storageo OpenNebula 3.8.3 basedo Quotas for users
• LPDS Cloud*
o Similar, but smaller scaleo Internal private cloud for LPDS
• Typically we use the LPDS Cloud for internal needs and scale out to SZTAKI Cloud when needed.
* Sándor Ács: “SZTAKI Cloud”. Monday, 1st July @ 12:00.
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Definition, scalability• Cloud Bursting:
o “Cloud bursting is an application deployment model in which an application runs in a private cloud or data center and bursts into a public cloud when the demand for computing capacity spikes.”4
• However more generally, cloud bursting is a subset of the general scaling out problem
• Can be split into 2 parts:1. Capability to scale out to a cloud to maintain QoS requirements (e.g.,
for handling short term spikes in computing capacity demand).2. making the decision of (a) when, (b) how much, (c) how long and (d)
where to scale out.
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The ability to scale out (to a cloud) + Making the decision
Scaling out scenarios (with SZTAKI Cloud)In this talk
Auto-scaling techniques“Cloud bursting from WS-PGRADE/ gUSE” Thursday, 11:00-11:30
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Cloud-Manager• Part of the FCM5 (“Federated Cloud
Management”) Architecture• We’ll now focus on the Cloud-Manager
o For FCM c.f., Attila Kertesz: “Cloud Federation Approaches” – @ 11:00 Today
• Schedules service calls to VMs and manages VMs
• REST/SOAP Web service interface for service call and VM queues
• The Cloud Resource Manager (CRM) component is responsible for the scaling decision (when/ where/ … )
• Initially it was intended for scaling services in a single cloud
• We use this component internally for different scaling (bursting) multi-cloud scenarios.
Cloud-Manager
Q1
Clouda
VMQx
Clouda
VMQy
Clouda VM Handler
VAx VAy
VMx1
VMx2
VMxn
Clouda
…
VMy1
VMy2
VMym
…
Generic Meta-Broker Service
FCM Repository
VAx..VAy
Service Handler
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Cloud-Manager1. Single queue for incoming service
calls (or tasks)2. Multiple VM queues
o Different one for each VA and resource combination
o VM queues can be managed automatically (CRM) or manually
3. Manages VM lifecycle (EC2 REST API)4. Performs the scheduling of service
calls to resources (Q1→VM)
Cloud-Manager
Q1
Clouda
VMQx
Clouda
VMQy
Clouda VM Handler
VAx VAy
VMx1
VMx2
VMxn
Clouda
…
VMy1
VMy2
VMym
…
1 2
34Service Handler
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Scenarios @ SZTAKI
Destination/ Source Public Private
PrivatePrivate→Public
(Scenario A. – “Cloud bursting”)
Private→Private(Scenario B.)
Volunteer Volunteer→Public(Scenario C/1.)
Volunteer→Private(Scenario C/2.)
• Source: Current infrastructure type (not necessarily cloud based!)• Destination: target cloud infrastructure type
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Destination/ Source Public Private
PrivatePrivate→Public
(Scenario A. – “Cloud bursting”)
Private→Private(Scenario B.)
Volunteer Volunteer→Public(Scenario C/1.)
Volunteer→Private(Scenario C/2.)
Scenario A: Private → Public
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Scenario A: Private → Public• Form a hybrid cloud: when local resources are insufficient
allocate resources from a public cloud provider• Real world example: Prezi.com
o Uses private resources w/ Amazon EC2 to handle peak traffico Batch processing of tasks
• Zip files for download, fetch images for presentations, conversion jobso Prezi.com Scale Contest – http://prezi.com/scale/
• Jobs 5 seconds max in queue, VMs 2 minute boot time, instances paid by the hour – minimize cost while honor requirements
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Scenario A: Private → Public• In SZTAKI We have the following possibilities for bursting:
1. OpenNebula based bursting 2. Cloud-Manager based bursting
• However we prefer to use private clouds over public ones – bursting to public clouds is set up as absolute last resort
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OpenNebula: Building a Hybrid Cloud (Scenario A)*
• OpenNebula supports accessing multiple remote providers through the EC2 API – not necessarily just Amazon EC2
• Remote provider appears as new host in OpenNebula• Resource limits by administrator
for number and type of instances• VMs can be started in EC2 or
locally• VM counterpart at remote provider
– EC2 section in VM template
• Network connectivity via VPN
* Sándor Ács: “OpenNebula”. Monday, 1st July @ 11:00.
On-demand Scaling of Computing Clusters• E.g., elastic execution of a Condor
computing cluster• Dynamic growth of the number of worker
nodes to meet demands using EC2• Private network with NIS and NFS• EC2 worker nodes connect via VPN
On-demand Scaling of Web Servers• E.g., elastic execution of the NGinx
web server• The capacity of the elastic web
application can be dynamically increased or decreased by adding or removing NGinx instances
OpenNebula: Hybrid Cloud Use Cases*
* Sándor Ács: “OpenNebula”. Monday, 1st July @ 11:00.
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Cloud-Manager: multi-cloud (Scenario A)
• Cloud-Manager supports multiple providers through the EC2 REST/ SOAP API o OpenNebula, OpenStack, Eucalyptus and
Amazon EC2
• Primarily for scaling Distributed Computing Infrastructures (DCIs)
• Service calls are bound to VA’s o Each configured provider must have the
counterpart (AMI-ID)
• Network connectivity via VPN when needed
Cloud-Manager
Q1
Clouda
VMQx
Cloudb
VMQx
Clouda
Handler
VAx VAy
VMx1
VMx2
VMxn
Clouda
…
VMx1
VMx2
VMxm
…
Service Handler
Cloudb
Handler
Cloudb
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Destination/ Source Public Private
PrivatePrivate→Public
(Scenario A. – “Cloud bursting”)
Private→Private(Scenario B.)
Volunteer Volunteer→Public(Scenario C/1.)
Volunteer→Private(Scenario C/2.)
Scenario B: Private → Private
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Scenario B: Private → Private• Scale from a private infrastructure to another private
infrastructureo E.g., scale from your local infrastructure (e.g., private internal) to
another academic cloud (e.g., private external)
• Typical use case for us: scaling out from LPDS Cloud to SZTAKI Cloud (however both can be considered as internal clouds)
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SZTAKI: Scenario B+A (1/2.) • We scale primarily
computing clusters (Condor, BOINC) with Cloud-Manager1. We use the LPDS Cloud
(private)2. Scale out to SZTAKI cloud
(private)3. As last resort scale out to
Amazon EC2 (public)
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SZTAKI: Scenario B+A (1/2.) • The master node (1) and the
Cloud-Manager (2) are hosted usually on a dedicated resource
• VPN head (3) must be typically on a public IP nodeo We use a patched version on TINC
with public key authentication
• The Cloud Resource Manager (4) is responsible for auto-scaling
• New VM instances are created and destroyed through the EC2 REST/SOAP API (5)
1
2
3
4
5
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Example: Scaling a Condor cluster with Cloud-Manager
1. CM Service calls → Jobs for Condor• Through REST/SOAP interface: (e.g., WS-PGRADE/ gUSE)
2. VPN Head on public IP3. Manager node: Cloud-Manager and Condor Master
1
2
3
4
4
4
4. VAs are deployed at LPDS, SZTAKI, Amazon EC2• Contextualization by
Cloud-Manager: • Key for VPN • VPN Head public
IP • Condor Master IP
on VPN
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Example: Scaling a Condor cluster with Cloud-Manager
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Destination/ Source Public Private
PrivatePrivate→Public
(Scenario A. – “Cloud bursting”)
Private→Private(Scenario B.)
Volunteer Volunteer→Public(Scenario C/1.)
Volunteer→Private(Scenario C/2.)
Scenario C: Volunteer → {Public, Private}
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Scenario C: Volunteer → {Public, Private}
• LPDS runs multiple BOINC based volunteer computing projects – SZTAKI Desktop Grid, EDGeS@homeo People donate their computers’ idle computing cycles to science
o We do not own the resourceso We do not have any control over the resources
• These resources are “free” however not very reliableo Jobs might be returned late or gone missing
• We burst to clouds to provide reliable computing resources for problematic jobs when neededo LPDS → SZTAKI → Academic Clouds →Amazon EC2
• C.f., Jozsef Kovacs: “Integrating clouds with grid systems – the SZTAKI-BOINC experience” @ 11:30
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Summary
• Bursting (scaling) consist of the capability + decision making• In this presentation I showed some scenarios from SZTAKI:
o Private → {Public, Private}; Volunteer → {Private, Public}o OpenNebula and Cloud-Manager based
• The decision making process (i.e., auto-scaling) will be the topic of my presentation on Thursdayo “Cloud bursting from WS-PGRADE/ gUSE” – Thursday, 11:00-11:30
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References and Additional reading
[1] Nair, S. K., Porwal, S., Dimitrakos, T., Ferrer, A. J., Tordsson, J., Sharif, T., Sheridan, C., Rajarajan, M. & Khan, A. U. (2010). Towards secure cloud bursting, brokerage and aggregation. Paper presented at the IEEE European conference on Web Services, 1 Dec 2010 – 3 Dec 2010, Cyprus.
[2] D. McDysan: Cloud Bursting Use Case. IETF. http://tools.ietf.org/html/draft-mcdysan-sdnp-cloudbursting-usecase-00
[3] National Institute of Standards and Technology (NIST): The NIST Definition of Cloud Computing. September, 2011. http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
[4] SearchCloudComputing http://searchcloudcomputing.techtarget.com/definition/cloud-bursting
[5] A. Cs. Marosi, G. Kecskemeti, A. Kertesz and P. Kacsuk, FCM: an Architecture for Integrating IaaS Cloud Systems. In Proceedings of The Second International Conference on Cloud Computing, GRIDs, and Virtualization. Rome, Italy. September, 2011.
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Thank you!Questions?
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