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Yahya Al-Hazmi | Technische Universität Berlin
yahya.al-hazmi@tu-berlin.de
XIFI Webinar | GoToWebinar | February 23, 2015, 11-12 AM CET
FIWARE Lab Solution for Managing
Resources & Services in a Cloud
Federation
http://lab.fiware.org
Agenda
 Introduction
 FIWARE Lab
 Federation Architecture Overview
 Cloud Federation Management
 Conclusion
 Discussion
1
Introduction (1)
 We need an open ecosystem or platform for open innovation
 Cloud capacity and services are of great value to support open innovation
and facilitate start-up incubation through infrastructure resource
 How to create a large distributed cloud to boost innovation across
European regions?
• This requires
› either large investments by a single player or
› an agreement among many players (federation)
• Of course, when different players team up together within a federation, they do not
want to lose all the control on their own infrastructure.
 There are several challenges and motivations behind cloud federation in
the literature, as well as different federation models and approaches
2
Introduction (2)
 There is no „best“ cloud federation approach
• Different approaches exist and each has its pros/cons
• Depend on different requirements
 We focus on Cloud Federation conducted within XIFI project to build the
federation of cloud infrastructures for the Future Internet Lab (FIWARE Lab)
 FIWARE Lab:
• Is an open innovation platform to develop Future Internet (FI) applications
• Offers a rich catalogue of services available either in SaaS or PaaS modality, the
so called Generic Enabler implementations (GEis)
› FIWARE GEs: set of general-purpose platform functions available through APIs
• Provides also a wide offer of FI facilities (e.g. sensor networks, 4G networks,
etc.) that provide advanced experimental capacities to developers allowing them
to link their applications with actual infrastructures and test them in real world
settings
3
FIWARE Lab
 FIWARE Lab is the Community Cloud for European FI-PPP developers
enabled by advanced FI infrastructures in Europe
 XIFI, as part of the overall vision of FI-PPP and following the principle “eat
your own dog food”, is based on FI-PPP technologies delivered by FIWARE
4
FIWARE Lab: the “meeting point”
where innovation takes place
5
Entrepreneurs, Developers
• Develop once for a large market
• Easily meet potential customers
• Marketing, promotion
• Ability to test with real data and
end users
• Simple yet powerful APIs that
accelerate product development
App Customers and Data providers
• Connect to entrepreneurs
• Put their data at work
• Bring new innovative services to end
users
• Be more efficient
• Social Reputation
FIWARE Technology Providers
• “Competitive” approach
• Connect to entrepreneurs: jointly
exploit the opportunities
 4,2 M€ promotion campaign
• Campus Party events
• Startup Weekend events
• Chambers of Commerce
• 870 K€ in prizes
 100 M€ of funding devoted
to entrepreneurs in phase 3
of the FIWARE program
Distributed Cloud for FIWARE Lab
6
• 17 nodes in Europe
providing up to
3000+ cores,
16TB+ Ram,
750TB+ HD
• A node is a data-
center (or more
linked)
• Connectivity node-
to-node offered
through GEANT /
NRENs
• Service topology
depending on GEs
release and UC
requirements
• 17 nodes in Europe
providing up to
3000+ cores,
16TB+ Ram,
750TB+ HD
• A node is a data-
center (or more
linked)
• Connectivity node-
to-node offered
through GEANT /
NRENs
• Service topology
depending on GEs
release and UC
requirements
The Federation “topology”
Identity Federation
Identity Federation
Spain
(M)
Spain
(M)
Italy
(M)
Italy
(M)
France
(S)
France
(S)
Ireland
(S)
Ireland
(S)
German
y (S)
Load Balancer
Synchronize
Spain
(M)
Italy
(M)
France
(S)
Ireland
(S)
Germany
(S)
Note:
• Not all the links are
shown
• For simplicity only five
nodes are depicted
M (master):
management and
operation layers
S (slave):
operation layer
7
General Architecture
8
Centralized Federation
Management
• Find available resources
• Compare resources
• Deploy GEs
• Federated Monitoring
Distributed Resources
• Access GEs
• Access VMs
• Monitoring data
• IdM & AC
• Network configuration
FIWARE Lab cloud federation management
from App developers’ viewpoint
 Focusing on innovative components that, working in an orchestrated
manner, perform core operations dealing with the management of
resources and services from an application developer viewpoint, in
particular:
i. the ability to deploy multi-tier applications across the federation
a. Due to regulatory or security reasons each tier may need to be deployed in different
infrastructure
b. Select among a set of configuration tools helping developers to minimize chronophage
operations
ii. the provisioning of real-time information about the services (GEis) available
in the federation through standardized RESTfull API
iii. a centralized mechanism to handle large-scale monitoring data gathered
through the federated underlying resources, by establishing a well-defined
and standardized API for storing, aggregating and publishing such data
9
Simplified architecture: cloud federation
management from App developers’ viewpoint
10
IdM: Identity Management
IMM: Infrastructure Monitoring
Middleware
DCRM: Data Center Resource
Management ( OpenStack-
Based)
Platform-as-a-Services (Pegasus)
 Enables a user to deploy easily any kind of application (single VM, single GEi or
multiple GEis)
 Offers the opportunity to deploy multi-tier applications, where each tier can be
accommodated by a different infrastructure of the federation
11
 No restriction of the
platform technology
• The developer is free to
select his own platform
• Products that will be
supported: J2EE, Apache,
DB: MySQL, PostgreSQL,
PHP, …
 Automate how you build,
deploy, and manage your
infrastructure using Chef
or Puppet (Sagitta)
Platform-as-a-Services (Pegasus)
 Deployment design: concrete number of machines, VM structure: products,
application components, load balancers, final network structure
 Deployment execution: orchestration of different steps: configuration of the
cloud services, configuration of IaaS/NaaS, creation of the VMs with the
software inside, configuration of the monitoring system, etc.
 Infrastructure control layer: creation and configuration of VMs+software,
interaction with IaaS/NaaS providers, deployment and execution of VMs
 Monitoring: configuration of the monitoring probes in order to recover the
data from the VMs, network and or process
 Adaptation and scalability of the applications (multi-tenancy)
12
Deployment and Configuration Adapter (DCA)
 DCA caters for the persistency of all
pertinent information related to the
whole lifecycle of services (GEis)
 DCA exposes a RESTful API that
can be used by interested users to
collect all needed information
regarding GE instances available in
the cloud federation either as SaaS
or PaaS offerings
 DCA is a flexible component that
accommodates different accessing
policies, following infrastructure
owners’ requirements
13
Deployment and Configuration Adapter (DCA)
 Challenges:
i. Respecting potential stringent access policies applied by the infrastructure
owners (Slave Nodes) not willing to provide administrative privileges to external
parties
ii. Unambiguous identification of the deployment of a specific GEi in several
infrastructures
 Solutions:
i. Software component (Python script), which is able to collect respective
information through the OpenStack Nova and Glance components, is used by
the infrastructure administrator to edit and customize the parameters of the
Python script before installing it on the controller of the infrastructure (DCRM)
ii. The information is made available to the DCA through a particular configuration
done by the Pegasus during GEi deployment through the use of the
metadata service offered by the OpenStack
› inserting a specific value (called NID) in the Glance metadata that uniquely and
unambiguously allows for GEi identification across the cloud federation
14
Federation Monitoring
 Attached to the local monitoring
system(s), a cross-domain
adaptation mechanism, denoted
as Infrastructure Monitoring
Middleware (IMM), unifies the
format of and the accessibility
to the collected data
 The Federation Monitoring
fulfilling the next operational
layer is in charge of storing and
publishing the unified data-set
by defining a Fed. Monitoring
API
• This layer is able to elaborate
the data by leveraging on Big
Data analysis techniques and
providing aggregation features
15
Federation Monitoring
 Fed. Monitoring components:
• Context Broker: the IMM notify
the monitoring data as NGSI
context format into the CB that
handles the datasets and updates
the metrics into Hadoop
• Apache Hadoop: provides
scalable, reliable and distributed
data processing and storage
› perform aggregating operations to
the data coming from the
subscription with the CB
› all Hadoops are federated in order
to maintain the service in high
availability
› only the Hadoop deployed in the
Master Node is allowed to perform
operations with the relational
database
16
Federation Monitoring
• Relational database: required to
store the elaborated data
• Fed. Monitoring API Server: API
for users to access the processed
monitoring data stored in the
relational database, and real-time
data from the federation
 Only master node hosts specific
federation-aware functionalities
17
Managing resources in multi-tier application:
a real case scenario
 An application developer willing to offer a weather service
• by allowing subscribed users to check, via a website, weather conditions or be
automatically informed of sudden weather changes
• Weather information are collected through a network including several sensors
 S/he selects:
• the Orion Context Broker GEi: to publish the data collected by the sensor
• the Complex Event Processing GEi: to process the information from sensors and to
create events through customized threshold
• the WireCloud GEi: to properly display this information in a webpage,
 Due to regulatory reason, Pegasus deploys them in two clouds (two-
infrastructure application)
 DCA allows a user to query its API providing all VMs created by him
 Monitoring API is used to get monitoring infos using a unique ID of the VM
18
Conclusion
 Addressed FIWARE Lab solutions
• for seamless deployment of services across the federation and ability of services to
span across different members of the federation
• For monitoring of the resources and data which can be aggregated with a common
structure
• be offered as an open ecosystem for innovation at the developers’ disposal
 These solutions are implemented and deployed in FIWARE Lab that includes
a running federation of 17 infrastructures distributed across Europe
 Developers can get an account by registering through the Cloud Portal and
enjoy the offerings
 How to use/interact/start working is presented in the upcoming Webinar “XIFI
for developers” on Wednesday, February 25, 2015.
19
Acknowledgment
The research work has received funding
from the EU FP7 grant agreement no.
604590 XIFI Project. The authors would
like to thank the project partners for their
contribution, especially Panos Trakadas,
Pablo Rodríguez, Silvio Cretti and Attilio
Broglio.
20
http://xifi.org
http://fiware.org
http://lab.fiware.org
Join us!
21

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fiware-lab-dev-6.pdf

  • 1. Yahya Al-Hazmi | Technische Universität Berlin yahya.al-hazmi@tu-berlin.de XIFI Webinar | GoToWebinar | February 23, 2015, 11-12 AM CET FIWARE Lab Solution for Managing Resources & Services in a Cloud Federation http://lab.fiware.org
  • 2. Agenda  Introduction  FIWARE Lab  Federation Architecture Overview  Cloud Federation Management  Conclusion  Discussion 1
  • 3. Introduction (1)  We need an open ecosystem or platform for open innovation  Cloud capacity and services are of great value to support open innovation and facilitate start-up incubation through infrastructure resource  How to create a large distributed cloud to boost innovation across European regions? • This requires › either large investments by a single player or › an agreement among many players (federation) • Of course, when different players team up together within a federation, they do not want to lose all the control on their own infrastructure.  There are several challenges and motivations behind cloud federation in the literature, as well as different federation models and approaches 2
  • 4. Introduction (2)  There is no „best“ cloud federation approach • Different approaches exist and each has its pros/cons • Depend on different requirements  We focus on Cloud Federation conducted within XIFI project to build the federation of cloud infrastructures for the Future Internet Lab (FIWARE Lab)  FIWARE Lab: • Is an open innovation platform to develop Future Internet (FI) applications • Offers a rich catalogue of services available either in SaaS or PaaS modality, the so called Generic Enabler implementations (GEis) › FIWARE GEs: set of general-purpose platform functions available through APIs • Provides also a wide offer of FI facilities (e.g. sensor networks, 4G networks, etc.) that provide advanced experimental capacities to developers allowing them to link their applications with actual infrastructures and test them in real world settings 3
  • 5. FIWARE Lab  FIWARE Lab is the Community Cloud for European FI-PPP developers enabled by advanced FI infrastructures in Europe  XIFI, as part of the overall vision of FI-PPP and following the principle “eat your own dog food”, is based on FI-PPP technologies delivered by FIWARE 4
  • 6. FIWARE Lab: the “meeting point” where innovation takes place 5 Entrepreneurs, Developers • Develop once for a large market • Easily meet potential customers • Marketing, promotion • Ability to test with real data and end users • Simple yet powerful APIs that accelerate product development App Customers and Data providers • Connect to entrepreneurs • Put their data at work • Bring new innovative services to end users • Be more efficient • Social Reputation FIWARE Technology Providers • “Competitive” approach • Connect to entrepreneurs: jointly exploit the opportunities  4,2 M€ promotion campaign • Campus Party events • Startup Weekend events • Chambers of Commerce • 870 K€ in prizes  100 M€ of funding devoted to entrepreneurs in phase 3 of the FIWARE program
  • 7. Distributed Cloud for FIWARE Lab 6 • 17 nodes in Europe providing up to 3000+ cores, 16TB+ Ram, 750TB+ HD • A node is a data- center (or more linked) • Connectivity node- to-node offered through GEANT / NRENs • Service topology depending on GEs release and UC requirements • 17 nodes in Europe providing up to 3000+ cores, 16TB+ Ram, 750TB+ HD • A node is a data- center (or more linked) • Connectivity node- to-node offered through GEANT / NRENs • Service topology depending on GEs release and UC requirements
  • 8. The Federation “topology” Identity Federation Identity Federation Spain (M) Spain (M) Italy (M) Italy (M) France (S) France (S) Ireland (S) Ireland (S) German y (S) Load Balancer Synchronize Spain (M) Italy (M) France (S) Ireland (S) Germany (S) Note: • Not all the links are shown • For simplicity only five nodes are depicted M (master): management and operation layers S (slave): operation layer 7
  • 9. General Architecture 8 Centralized Federation Management • Find available resources • Compare resources • Deploy GEs • Federated Monitoring Distributed Resources • Access GEs • Access VMs • Monitoring data • IdM & AC • Network configuration
  • 10. FIWARE Lab cloud federation management from App developers’ viewpoint  Focusing on innovative components that, working in an orchestrated manner, perform core operations dealing with the management of resources and services from an application developer viewpoint, in particular: i. the ability to deploy multi-tier applications across the federation a. Due to regulatory or security reasons each tier may need to be deployed in different infrastructure b. Select among a set of configuration tools helping developers to minimize chronophage operations ii. the provisioning of real-time information about the services (GEis) available in the federation through standardized RESTfull API iii. a centralized mechanism to handle large-scale monitoring data gathered through the federated underlying resources, by establishing a well-defined and standardized API for storing, aggregating and publishing such data 9
  • 11. Simplified architecture: cloud federation management from App developers’ viewpoint 10 IdM: Identity Management IMM: Infrastructure Monitoring Middleware DCRM: Data Center Resource Management ( OpenStack- Based)
  • 12. Platform-as-a-Services (Pegasus)  Enables a user to deploy easily any kind of application (single VM, single GEi or multiple GEis)  Offers the opportunity to deploy multi-tier applications, where each tier can be accommodated by a different infrastructure of the federation 11  No restriction of the platform technology • The developer is free to select his own platform • Products that will be supported: J2EE, Apache, DB: MySQL, PostgreSQL, PHP, …  Automate how you build, deploy, and manage your infrastructure using Chef or Puppet (Sagitta)
  • 13. Platform-as-a-Services (Pegasus)  Deployment design: concrete number of machines, VM structure: products, application components, load balancers, final network structure  Deployment execution: orchestration of different steps: configuration of the cloud services, configuration of IaaS/NaaS, creation of the VMs with the software inside, configuration of the monitoring system, etc.  Infrastructure control layer: creation and configuration of VMs+software, interaction with IaaS/NaaS providers, deployment and execution of VMs  Monitoring: configuration of the monitoring probes in order to recover the data from the VMs, network and or process  Adaptation and scalability of the applications (multi-tenancy) 12
  • 14. Deployment and Configuration Adapter (DCA)  DCA caters for the persistency of all pertinent information related to the whole lifecycle of services (GEis)  DCA exposes a RESTful API that can be used by interested users to collect all needed information regarding GE instances available in the cloud federation either as SaaS or PaaS offerings  DCA is a flexible component that accommodates different accessing policies, following infrastructure owners’ requirements 13
  • 15. Deployment and Configuration Adapter (DCA)  Challenges: i. Respecting potential stringent access policies applied by the infrastructure owners (Slave Nodes) not willing to provide administrative privileges to external parties ii. Unambiguous identification of the deployment of a specific GEi in several infrastructures  Solutions: i. Software component (Python script), which is able to collect respective information through the OpenStack Nova and Glance components, is used by the infrastructure administrator to edit and customize the parameters of the Python script before installing it on the controller of the infrastructure (DCRM) ii. The information is made available to the DCA through a particular configuration done by the Pegasus during GEi deployment through the use of the metadata service offered by the OpenStack › inserting a specific value (called NID) in the Glance metadata that uniquely and unambiguously allows for GEi identification across the cloud federation 14
  • 16. Federation Monitoring  Attached to the local monitoring system(s), a cross-domain adaptation mechanism, denoted as Infrastructure Monitoring Middleware (IMM), unifies the format of and the accessibility to the collected data  The Federation Monitoring fulfilling the next operational layer is in charge of storing and publishing the unified data-set by defining a Fed. Monitoring API • This layer is able to elaborate the data by leveraging on Big Data analysis techniques and providing aggregation features 15
  • 17. Federation Monitoring  Fed. Monitoring components: • Context Broker: the IMM notify the monitoring data as NGSI context format into the CB that handles the datasets and updates the metrics into Hadoop • Apache Hadoop: provides scalable, reliable and distributed data processing and storage › perform aggregating operations to the data coming from the subscription with the CB › all Hadoops are federated in order to maintain the service in high availability › only the Hadoop deployed in the Master Node is allowed to perform operations with the relational database 16
  • 18. Federation Monitoring • Relational database: required to store the elaborated data • Fed. Monitoring API Server: API for users to access the processed monitoring data stored in the relational database, and real-time data from the federation  Only master node hosts specific federation-aware functionalities 17
  • 19. Managing resources in multi-tier application: a real case scenario  An application developer willing to offer a weather service • by allowing subscribed users to check, via a website, weather conditions or be automatically informed of sudden weather changes • Weather information are collected through a network including several sensors  S/he selects: • the Orion Context Broker GEi: to publish the data collected by the sensor • the Complex Event Processing GEi: to process the information from sensors and to create events through customized threshold • the WireCloud GEi: to properly display this information in a webpage,  Due to regulatory reason, Pegasus deploys them in two clouds (two- infrastructure application)  DCA allows a user to query its API providing all VMs created by him  Monitoring API is used to get monitoring infos using a unique ID of the VM 18
  • 20. Conclusion  Addressed FIWARE Lab solutions • for seamless deployment of services across the federation and ability of services to span across different members of the federation • For monitoring of the resources and data which can be aggregated with a common structure • be offered as an open ecosystem for innovation at the developers’ disposal  These solutions are implemented and deployed in FIWARE Lab that includes a running federation of 17 infrastructures distributed across Europe  Developers can get an account by registering through the Cloud Portal and enjoy the offerings  How to use/interact/start working is presented in the upcoming Webinar “XIFI for developers” on Wednesday, February 25, 2015. 19
  • 21. Acknowledgment The research work has received funding from the EU FP7 grant agreement no. 604590 XIFI Project. The authors would like to thank the project partners for their contribution, especially Panos Trakadas, Pablo Rodríguez, Silvio Cretti and Attilio Broglio. 20