The document describes Rackspace's Analytical Compute Grid (ACG), an elastic "big data" infrastructure built on Rackspace Private Cloud powered by OpenStack. The ACG allows hosting of ever-growing data sets, rapid scalability, and ease of maintenance. It utilizes a variety of storage types and leverages open source technology. The architecture includes hypervisor servers, databases, and an indexing structure that distributes data across instances and enables parallelized queries of large data sets.
Rackspace’s Enterprise Business Intelligence group (EBI) was looking for a cost-effective way to support the reporting and information needs of its internal users, which include business and operations personnel. It was also looking to scale out new infrastructure in order to meet their increasing business demands, house increasing amounts of data, and customize the collection of data, while seeking a way to move away from their legacy Data Warehouse solution. To do this, Rackspace built the Analytical Compute Grid (ACG) by using Hadoop, Cassandra and PostgreSQL with an OpenStack cloud. Read more about it in this presentation.
The combination of scalable ANSYS design and simulation software and HPC clusters with Panasas parallel storage has demonstrated new and significant productivity advantages for workflows in computer aided engineering (CAE) applications. The combination provides
dramatic cost-performance improvements and speeds time-to-results for engineering simulation solutions on commodity HPC clusters
Panasas ® California Institute of Technology Success StoryPanasas
The Center for Advanced Computing Research (CACR) at the California Institute of Technology (Caltech) operates large-scale computing facilities for numerous campus
research groups who have big data design and discovery requirements. CACR has a full-time, 25-person staff with expertise in data-intensive scientific discovery, physicsbased simulation, scientific software engineering, visualization, and novel computer
architectures. It provides technical assistance such as porting code, designing and specifying resources, and advanced IT integration.
Rackspace’s Enterprise Business Intelligence group (EBI) was looking for a cost-effective way to support the reporting and information needs of its internal users, which include business and operations personnel. It was also looking to scale out new infrastructure in order to meet their increasing business demands, house increasing amounts of data, and customize the collection of data, while seeking a way to move away from their legacy Data Warehouse solution. To do this, Rackspace built the Analytical Compute Grid (ACG) by using Hadoop, Cassandra and PostgreSQL with an OpenStack cloud. Read more about it in this presentation.
The combination of scalable ANSYS design and simulation software and HPC clusters with Panasas parallel storage has demonstrated new and significant productivity advantages for workflows in computer aided engineering (CAE) applications. The combination provides
dramatic cost-performance improvements and speeds time-to-results for engineering simulation solutions on commodity HPC clusters
Panasas ® California Institute of Technology Success StoryPanasas
The Center for Advanced Computing Research (CACR) at the California Institute of Technology (Caltech) operates large-scale computing facilities for numerous campus
research groups who have big data design and discovery requirements. CACR has a full-time, 25-person staff with expertise in data-intensive scientific discovery, physicsbased simulation, scientific software engineering, visualization, and novel computer
architectures. It provides technical assistance such as porting code, designing and specifying resources, and advanced IT integration.
Apache Camel has fundamentally changed the way enterprise Java™ developers think about system-to-system integration by making enterprise integration patterns (EIP) a simple declaration in a lightweight application wrapped and delivered as a single JAR.
Slides from our introduction to Ceph and OpenStack webinar. You can watch the webinar on demand also here http://www.inktank.com/news-events/webinars/.
Improving Python and Spark (PySpark) Performance and InteroperabilityWes McKinney
Slides from Spark Summit East 2017 — February 9, 2017 in Boston. Discusses ongoing development work to accelerate Python-on-Spark performance using Apache Arrow and other tools
This presentation focusses on all the Oracle RAC 12c Rel. 2 related features that ensure continuous availability of the applications using an Oracle RAC database for High Availability.
This presentation introduces various new features in Oracle's Universal Installer (OUI), configuration and related tools. This presentation was first presented in the course of the Oracle Database 2017 conference.
Spectrum Scale - Diversified analytic solution based on various storage servi...Wei Gong
This slides describe diversified analytic solutions based on Spectrum Scale with various deployment mode, such as storage rich-server, share storage, IBM DeepFlash 150 and Elastic Storage Server. It deep dives several advanced data management features and solutions for BD&A workload derived from Spectrum Scale.
Oracle RAC 12c Best Practices with Customer Example (Sanger) as presented during Oracle Open World 2013 (OOW13).
This is part one of the Oracle RAC 12c "reindeer series" used for OOW13 Oracle RAC-related presentations.
6 Storage Workloads Ideal for Microsoft AzureBuurst
Is your organization looking to move on-premises storage workloads to Microsoft Azure?
We’ve helped hundreds of our customers move their storage workloads to Azure--without re-architecting their applications. We’ll review the 6 on-premises storage workloads ideal to move to Azure today.
In this webinar, we covered:
-6 Ideal Workloads to migrate including disaster recovery, cloud backup and more!
-Lessons Learned from helping customers do cloud workload migrations
-How to migrate on-premises file storage to Azure
-How to extend native Azure storage capabilities
-What cloud storage offers that on-premises storage options can’t
-Demo: deploy a virtual NAS on Azure in minutes
Learn more at https://www.softnas.com/azure.
Aerospike meetup july 2019 | Big Data DemystifiedOmid Vahdaty
Building a low latency (sub millisecond), high throughput database that can handle big data AND linearly scale is not easy - but we did it anyway...
In this session we will get to know Aerospike, an enterprise distributed primary key database solution.
- We will do an introduction to Aerospike - basic terms, how it works and why is it widely used in mission critical systems deployments.
- We will understand the 'magic' behind Aerospike ability to handle small, medium and even Petabyte scale data, and still guarantee predictable performance of sub-millisecond latency
- We will learn how Aerospike devops is different than other solutions in the market, and see how easy it is to run it on cloud environments as well as on premise.
We will also run a demo - showing a live example of the performance and self-healing technologies the database have to offer.
Fast, In-Memory SQL on Apache Cassandra with Apache Ignite (Rachel Pedreschi,...DataStax
Are your read latencies not meeting your SLAs? Do you want to write SQL-99 queries against your Cassandra Data? Do you need transactions and ACID compliance?
Well, look no further! Apache Ignite can slide between your application and your Cassandra cluster, provide true in-memory performance, supply full SQL-99 support and maintain the same “Always On” availability guarantees that you have come to know and love with Cassandra.
In this session you will learn how Apache Ignite can turbocharge your Cassandra cluster without sacrificing availability guarantees. In this talk we’ll cover:
An overview of the Apache Ignite architecture
How to deploy Apache Ignite in minutes on top of Cassandra
How companies use this powerful combination to handle extreme OLTP workloads
About the Speakers
Rachel Pedreschi Principal Solutions Architect, GridGain
Rachel is Principal Solutions Architect at GridGain Systems. A ""Big Data Geek-ette,"" Rachel is no stranger to the world of high performance database systems. She is a Cassandra, Vertica, Informix and Redbrick certified DBA on top of her work with Apache Ignite and has 20 years of business intelligence and ETL tool experience. Rachel has an MBA from SFSU and a BA in Math from University of California, Santa Cruz. She loves collecting new experiences around the world!
Oracle RAC on Extended Distance Clusters - PresentationMarkus Michalewicz
NOTE that a newer version of this presentation (covering Oracle RAC 12c Release) has been uploaded to my SlideShare: https://www.slideshare.net/MarkusMichalewicz/oracle-extended-clusters-for-oracle-rac
This presentation can be used as an illustration for some of the ideas and best practices discussed in the paper "Oracle RAC and Oracle RAC One Node on Extended Distance (Stretched) Clusters"
Amazon RDS makes it easy to set up, operate, and scale a relational database in the cloud. We’ll look at what RDS does (and does not) do to manage the “muck” of database operations.
Speakers:
Bill Baldwin - Global Enterprise Support Lead, AWS Enterprise Support
Gareth Eagar - Solutions Architect, AWS Solutions Architect
Apache Camel has fundamentally changed the way enterprise Java™ developers think about system-to-system integration by making enterprise integration patterns (EIP) a simple declaration in a lightweight application wrapped and delivered as a single JAR.
Slides from our introduction to Ceph and OpenStack webinar. You can watch the webinar on demand also here http://www.inktank.com/news-events/webinars/.
Improving Python and Spark (PySpark) Performance and InteroperabilityWes McKinney
Slides from Spark Summit East 2017 — February 9, 2017 in Boston. Discusses ongoing development work to accelerate Python-on-Spark performance using Apache Arrow and other tools
This presentation focusses on all the Oracle RAC 12c Rel. 2 related features that ensure continuous availability of the applications using an Oracle RAC database for High Availability.
This presentation introduces various new features in Oracle's Universal Installer (OUI), configuration and related tools. This presentation was first presented in the course of the Oracle Database 2017 conference.
Spectrum Scale - Diversified analytic solution based on various storage servi...Wei Gong
This slides describe diversified analytic solutions based on Spectrum Scale with various deployment mode, such as storage rich-server, share storage, IBM DeepFlash 150 and Elastic Storage Server. It deep dives several advanced data management features and solutions for BD&A workload derived from Spectrum Scale.
Oracle RAC 12c Best Practices with Customer Example (Sanger) as presented during Oracle Open World 2013 (OOW13).
This is part one of the Oracle RAC 12c "reindeer series" used for OOW13 Oracle RAC-related presentations.
6 Storage Workloads Ideal for Microsoft AzureBuurst
Is your organization looking to move on-premises storage workloads to Microsoft Azure?
We’ve helped hundreds of our customers move their storage workloads to Azure--without re-architecting their applications. We’ll review the 6 on-premises storage workloads ideal to move to Azure today.
In this webinar, we covered:
-6 Ideal Workloads to migrate including disaster recovery, cloud backup and more!
-Lessons Learned from helping customers do cloud workload migrations
-How to migrate on-premises file storage to Azure
-How to extend native Azure storage capabilities
-What cloud storage offers that on-premises storage options can’t
-Demo: deploy a virtual NAS on Azure in minutes
Learn more at https://www.softnas.com/azure.
Aerospike meetup july 2019 | Big Data DemystifiedOmid Vahdaty
Building a low latency (sub millisecond), high throughput database that can handle big data AND linearly scale is not easy - but we did it anyway...
In this session we will get to know Aerospike, an enterprise distributed primary key database solution.
- We will do an introduction to Aerospike - basic terms, how it works and why is it widely used in mission critical systems deployments.
- We will understand the 'magic' behind Aerospike ability to handle small, medium and even Petabyte scale data, and still guarantee predictable performance of sub-millisecond latency
- We will learn how Aerospike devops is different than other solutions in the market, and see how easy it is to run it on cloud environments as well as on premise.
We will also run a demo - showing a live example of the performance and self-healing technologies the database have to offer.
Fast, In-Memory SQL on Apache Cassandra with Apache Ignite (Rachel Pedreschi,...DataStax
Are your read latencies not meeting your SLAs? Do you want to write SQL-99 queries against your Cassandra Data? Do you need transactions and ACID compliance?
Well, look no further! Apache Ignite can slide between your application and your Cassandra cluster, provide true in-memory performance, supply full SQL-99 support and maintain the same “Always On” availability guarantees that you have come to know and love with Cassandra.
In this session you will learn how Apache Ignite can turbocharge your Cassandra cluster without sacrificing availability guarantees. In this talk we’ll cover:
An overview of the Apache Ignite architecture
How to deploy Apache Ignite in minutes on top of Cassandra
How companies use this powerful combination to handle extreme OLTP workloads
About the Speakers
Rachel Pedreschi Principal Solutions Architect, GridGain
Rachel is Principal Solutions Architect at GridGain Systems. A ""Big Data Geek-ette,"" Rachel is no stranger to the world of high performance database systems. She is a Cassandra, Vertica, Informix and Redbrick certified DBA on top of her work with Apache Ignite and has 20 years of business intelligence and ETL tool experience. Rachel has an MBA from SFSU and a BA in Math from University of California, Santa Cruz. She loves collecting new experiences around the world!
Oracle RAC on Extended Distance Clusters - PresentationMarkus Michalewicz
NOTE that a newer version of this presentation (covering Oracle RAC 12c Release) has been uploaded to my SlideShare: https://www.slideshare.net/MarkusMichalewicz/oracle-extended-clusters-for-oracle-rac
This presentation can be used as an illustration for some of the ideas and best practices discussed in the paper "Oracle RAC and Oracle RAC One Node on Extended Distance (Stretched) Clusters"
Amazon RDS makes it easy to set up, operate, and scale a relational database in the cloud. We’ll look at what RDS does (and does not) do to manage the “muck” of database operations.
Speakers:
Bill Baldwin - Global Enterprise Support Lead, AWS Enterprise Support
Gareth Eagar - Solutions Architect, AWS Solutions Architect
This is a content overview of the important information and details for sponsors of the upcoming OpenStack Summit in Tokyo, Japan taking place October 27 - 30.
You can watch a recording of the webinar here: https://openstack.webex.com/openstack/ldr.php?RCID=d48605b7ca9fdccd990ab20eb9334be8
The Foundation marketing team put together a high level overview of 2H 2015 plans in order to get input from the marketing community and provide more information on how marketers can take advantage of the work, as well as get involved and contribute.
An overview of the 1H2016 OpenStack Marketing Plan shared with the marketing community during our regular calls. Learn more at https://wiki.openstack.org/wiki/Governance/Foundation/Marketing#Open_Marketing_Meetings_2016
A few quick points for those who may be attending an OpenStack Summit for the first time. We are excited to see you in Barcelona, Spain October 25-28, 2016.
Scaling Xen Within Rackspace Cloud ServersRackspace
Rackspace has years of experience with running Xen at scale, starting with Xen and migrating to XenServer. We will share why we use Xen/XenServer along with some of the issues that we've experienced. We will touch on our experience with migrating from Xen to XenServer and the challenges there. We will share information about Rackspace Cloud Servers architecture, and touch briefly on OpenStack when doing so. We will explain how we use Xen to quickly deploy new Openstack services with what we call Nova on Nova. And finally, we will discuss what additional features and improvements are needed and why.
Rackspace has years of experience with running Xen at scale, starting with Xen and migrating to XenServer. We will share why we use Xen/XenServer along with some of the issues that we've experienced. We will touch on our experience with migrating from Xen to XenServer and the challenges there. We will share information about Rackspace Cloud Servers architecture, and touch briefly on OpenStack when doing so. We will explain how we use Xen to quickly deploy new Openstack services with what we call Nova on Nova. And finally, we will discuss what additional features and improvements are needed and why.
Cloud orchestration stacks are an important component in completing the move to a private cloud. In this rapid fire session, speakers representing key cloud orchestration stacks will have 10 minutes each to present their responses to key questions about the functions, features and capabilities of each cloud stack. Questions include: services and capabilities offered; languages, operating systems, APIs and image formats supported; virtualization stacks supported; management tools; portability; hardware, capacity, performance and availability constraints, pricing and more. Presentations will be followed by an open Q and A discussion.
This presentation covers the OpenStack cloud stack.
Openstack presentation presented to the Sysadmins Guild in Australia. Talks about what Openstack is, where it's coming from, how it is evolving and growing and where it's going.
Operating OpenStack - Case Study in the Rackspace CloudRainya Mosher
Presentation given in Seoul, South Korea at the Cloud and Data Center Conference in March 2014. Introduces the concept of the Rackspace Hybric Cloud Experience, the product platforms that are being used to make that happen, and then focuses on the operation and deployment of the Public Cloud.
The evolution of cloud requires not only virtualised server resources but also on demand, utility consumption of physical hardware resources delivered in real time.
As the world of system and application deployment continues to change, the sys admin and security community needs to change with it. With agile development, continuous deployment, the pace of change in IT has only increased. Add in Dev/Ops and the traditional sys admin and security processes just don’t work. How can you rapidly deliver servers and applications while making sure they are built reliably and securely. Rackspace has been developing a tool to help them design, deploy and security assess complex configurations for customers called Checkmate. This talk will cover the concepts behind and the architecture of Checkmate and how it helps minimize the time to deploy systems and verify they have been created to spec and in a secure state. A discussion of how Checkmate has inspired the concept of Test Driven Security based on the Test Driven Development model familiar to the development world.
In this webinar, we will review all important information for sponsors packages, add-ons, venue details, and how to become a sponsor.
Webinar recording: https://youtu.be/kUjMTNoX6yM
OpenStack celebrates its fifth birthday, July 19, 2015, and this presentation provides an update on the community momentum, as well as what's next. #openstack5bday
At OpenStack Day CEE 2015, we discuss the latest user survey results, some real-world OpenStack case studies and how new users and cloud operators can get involved with the community.
Designing an OpenStack Summit Session Submission for SuccessOpenStack Foundation
Niki Acosta, Anne Gentle and Diane Mueller share tips on creating a successful CFP for an OpenStack Summit
Here is a link to the webinar: https://www.youtube.com/watch?v=CxFYNZ4jqik&feature=youtu.be
You can access the recording of this webinar here: https://www.youtube.com/watch?v=yp_bKzhMaT0&feature=youtu.be
You can download the sponsorship prospectus here: https://www.openstack.org/assets/vancouver-summit/openstack-vancouver-prospectus-draft-12-19-2014.pdf
1. Analytical Compute Grid
(ACG)
Elastic “Big Data” Infrastructure
Rackspace® Private Cloud powered by OpenStack® Use Case
by Natasha Gajic
October 17, 2012
2. Rackspace’s EBI Environment
Current Environment “Big Data” Problem
Windows and Linux Cost of purchasing
operating systems additional licenses
Oracle and Microsoft Time required to set up
databases solutions new hardware
Microsoft and Oracle Increased demand for DBA
replication technology resources
SSIS System performance
Informatica System scalability
Dedicated servers Capacity
Rapid data set growth
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2
3. Analytical Compute Grid (ACG) Features
• Host ever growing set of data
• Quick data collection and retrieval
• Rapid scalability
• Ease of maintenance
• Provide standard data access API
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3
4. Analytical Compute Grid (ACG) Features
• Ability to provide variety of storage types:
• Columnar
• Relational
• HDFS
• Enable users to select optimal storage
type for information collected
• Leverage Rackspace® Private Cloud
powered by OpenStack® and open
source technology
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4
10. ACG on Rackspace® Private Cloud powered by OpenStack®
Node
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10
11. ACG on Rackspace® Private Cloud powered by OpenStack®
Node
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11
12. ACG on Rackspace® Private Cloud powered by OpenStack®
Node
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12
13. ACG on Rackspace® Private Cloud powered by OpenStack®
Node
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13
14. ACG on Rackspace® Private Cloud powered by OpenStack®
Controller
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15. ACG on Rackspace® Private Cloud powered by OpenStack®
Controller
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16. ACG on Rackspace® Private Cloud powered by OpenStack®
Controller
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16
17. ACG on Rackspace® Private Cloud powered by OpenStack®
API
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17
18. ACG on Rackspace® Private
Cloud powered by OpenStack®
Indexing Structure
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18
19. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure:
• Resides on a set of Rackspace® Private Cloud powered by
OpenStack® instances
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19
20. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure:
• Resides on a set of Rackspace® Private Cloud powered by
OpenStack® instances
• It is a set of pointers ultimately addressing database entities
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20
21. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure:
• Resides on a set of Rackspace® Private Cloud powered by
OpenStack® instances
• It is a set of pointers ultimately addressing database entities
• ACG Controller manages Indexing Structure
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21
22. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure:
• Resides on a set of Rackspace® Private Cloud powered by
OpenStack® instances
• It is a set of pointers ultimately addressing database entities
• ACG Controller manages Indexing Structure
• Dynamically expands vertically and horizontally to address a
growing data set
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22
23. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure Enables:
• Distribution of data bases across many instances
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23
24. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure Enables:
• Distribution of data bases across many instances
• Splitting large data sets across many instances
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24
25. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure Enables:
• Distribution of data bases across many instances
• Splitting large data sets across many instances
• Parallelization of large data set queries
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25
26. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure Enables:
• Distribution of data bases across many instances
• Splitting large data sets across many instances
• Parallelization of large data set queries
• Deploying data stores with optimal configuration, minimizing
maintenance
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26
27. ACG on Rackspace® Private Cloud powered by OpenStack®
Indexing Structure
• ACG Indexing Structure Enables:
• Distribution of data bases across many instances
• Splitting large data sets across many instances
• Parallelization of large data set queries
• Deploying data stores with optimal configuration, minimizing
maintenance
• Accessing data residing in
variety of storage types via
uniform interface
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27
28. ACG on Rackspace® Private Cloud powered by OpenStack®
Sorter & Aggregator
• ACG Sorter & Aggregator Enables:
• Joining the results from multiple ACG nodes
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28
29. ACG on Rackspace® Private Cloud powered by OpenStack®
Sorter & Aggregator
• ACG Sorter & Aggregator Enables:
• Joining the results from multiple ACG nodes
• Result sorting and aggregation
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29
30. ACG on Rackspace® Private Cloud powered by OpenStack®
Sorter & Aggregator
• ACG Sorter & Aggregator Enables:
• Joining the results from multiple ACG nodes
• Result sorting and aggregation
• Together with temporary segment it will support
joining heterogeneous data sets
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30
31. ACG on Rackspace® Private
Cloud powered by OpenStack®
Quality Attributes
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31
32. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes - Performance
Rackspace® Private Cloud ACG
powered by OpenStack®
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32
33. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes - Performance
Rackspace® Private Cloud ACG
powered by OpenStack®
Creates ACG node in 30 seconds
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33
34. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes - Performance
Rackspace® Private Cloud ACG
powered by OpenStack®
Creates ACG node in 30 seconds
Creates ACG nodes concurrently
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34
35. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes - Performance
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size resulting
Creates ACG node in 30 seconds in:
Creates ACG nodes concurrently
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35
36. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes - Performance
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size resulting
Creates ACG node in 30 seconds in: Quick data distribution
Creates ACG nodes concurrently
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36
37. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes - Performance
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size resulting
Creates ACG node in 30 seconds in: Quick data distribution
Creates ACG nodes concurrently Query parallelization
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37
38. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes - Performance
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size resulting
Creates ACG node in 30 seconds in: Quick data distribution
Creates ACG nodes concurrently Query parallelization
Fast data retrieval
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38
39. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Scalability
Rackspace® Private Cloud ACG
powered by OpenStack®
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39
40. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Scalability
Rackspace® Private Cloud ACG
powered by OpenStack®
Quick and concurrent ACG node
creation
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40
41. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Scalability
Rackspace® Private Cloud ACG
powered by OpenStack®
Quick and concurrent ACG node
creation
Ability to re-size existing nodes
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41
42. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Scalability
Rackspace® Private Cloud ACG
powered by OpenStack®
Quick and concurrent ACG node
creation
Ability to re-size existing nodes
Ability to remove nodes
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42
43. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Scalability
Rackspace® Private Cloud ACG
powered by OpenStack® Indexing structure and controlled
Quick and concurrent ACG node data set size allow ACG to
creation stabilize quickly as it expands or
Ability to re-size existing nodes contracts
Ability to remove nodes
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43
44. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Availability
Rackspace® Private Cloud ACG
powered by OpenStack®
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44
45. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Availability
Rackspace® Private Cloud ACG
powered by OpenStack®
Rapidly replace failed ACG nodes
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45
46. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Availability
Rackspace® Private Cloud ACG
powered by OpenStack® Deploys data store native
Rapidly replace failed ACG nodes availability mechanisms
(replication, data distribution…)
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46
47. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack®
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47
48. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack®
Adding ACG nodes expands:
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48
50. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack®
Adding ACG nodes expands:
Storage capacity
CPU power
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50
51. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack®
Adding ACG nodes expands:
Storage capacity
CPU power
RAM
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51
52. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack®
Adding ACG nodes expands:
Storage capacity
CPU power
RAM
No DBA or system administrators
activity required
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53. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size enables:
Adding ACG nodes expands:
Storage capacity
CPU power
RAM
No DBA or system administrators
activity required
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54. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size enables:
Adding ACG nodes expands: Optimal and stable data store
Storage capacity configuration
CPU power
RAM
No DBA or system administrators
activity required
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55. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size enables:
Adding ACG nodes expands: Optimal and stable data store
Storage capacity configuration
CPU power Reducing demand for managing
RAM data store objects
No DBA or system administrators
activity required
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56. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Maintainability
Rackspace® Private Cloud ACG
powered by OpenStack® Controlled data set size enables:
Adding ACG nodes expands: Optimal and stable data store
Storage capacity configuration
CPU power Reducing demand for managing
RAM data store objects
No DBA or system administrators Stable query execution plans
activity required
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57. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Flexibility
ACG
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58. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Flexibility
ACG
Variety of storage types:
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59. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Flexibility
ACG
Variety of storage types:
Columnar – Cassandra : time series data
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60. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Flexibility
ACG
Variety of storage types:
Columnar – Cassandra : time series data
Relational – PostgreSQL : relational data
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61. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Flexibility
ACG
Variety of storage types:
Columnar – Cassandra : time series data
Relational – PostgreSQL : relational data
HDFS – Hadoop : un-structured data
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62. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Flexibility
ACG
Variety of storage types: Ability to select optimal storage
Columnar – Cassandra : time series data type for individual use case
Relational – PostgreSQL : relational data
HDFS – Hadoop : un-structured data
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63. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Usability
ACG
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64. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Usability
ACG
Standard interfaces:
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65. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Usability
ACG
Standard interfaces:
SQL language
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66. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Usability
ACG
Standard interfaces:
SQL language
JDBC API
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67. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Usability
ACG
Standard interfaces:
SQL language
JDBC API
Data store native calls
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68. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Usability
ACG
Standard interfaces: Native bulk loader utility
SQL language
JDBC API
Data store native calls
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69. ACG on Rackspace® Private Cloud powered by OpenStack®
Quality Attributes – Usability
ACG
Standard interfaces: Native bulk loader utility
SQL language
JDBC API ACG will support joining
Data store native calls heterogeneous data sets
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70. ACG on Rackspace® Private
Cloud powered by OpenStack®
Rackspace Use Case
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71. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case
• Subject:
• Complex availability calculation sourcing 3
months of monitoring data and creating 1 billion
records in initial calculation
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72. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case
• Environment 1
• Data Warehouse Microsoft SQL server database
• SSIS data loading
• SQL server with 24 CPUs and 250GB RAM was
dedicated to the initial calculation
• SQL server stored procedure performed the
calculation
• Source and result are stored in traditional data
warehouse structure
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73. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case
• Environment 2
• In 30 seconds, ACG Node Manager instantiated
new columnar data store consisting of 4
Cassandra nodes, and registered it in ACG
Indexing Structure
• Each ACG node has 2CPUs and 8GB RAM
• Informatica data loading
• Calculation developed in Java
• Source and result are stored in columnar
structure suitable for time series data
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74. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case - Result
• Calculation Duration
•Microsoft SQL Server lasted 5 days
•ACG calculation completed in 3.5 hours
• Storage Size
• Microsoft SQL server 500GB
•ACG 20 GB
• Complexity of the calculation
•Columnar data store is optimal for time series data.
Sourcing from columnar data store resulted in relatively
simple Java calculation process comparing to SQL
server stored procedure
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75. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case - Conclusion
• Selecting optimal data store for use case resulted in:
• Substantial performance improvement
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76. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case - Conclusion
• Selecting optimal data store for use case resulted in:
• Substantial performance improvement
• Reduced storage demand
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77. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case - Conclusion
• Selecting optimal data store for use case resulted in:
• Substantial performance improvement
• Reduced storage demand
•Simplified processes
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78. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case - Conclusion
• Selecting optimal data store for use case resulted in:
• Substantial performance improvement
• Reduced storage demand
•Simplified processes
•Ability to process terabytes of data per day close to
real-time and on-demand
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79. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case - Conclusion
• Selecting optimal data store for use case resulted in:
• Substantial performance improvement
• Reduced storage demand
•Simplified processes
•Ability to process terabytes of data per day close to
real-time and on-demand
•Improved trending and reporting:
• enhances support capabilities
• improved Rackspace customer experience
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80. ACG on Rackspace® Private Cloud powered by OpenStack®
Rackspace Use Case - Conclusion
• Selecting optimal data store for use case resulted in:
• Substantial performance improvement
• Reduced storage demand
• Simplified processes
• Ability to process terabytes of data per day close to
real-time and on-demand
• Improved trending and reporting:
• enhances support capabilities
• improved Rackspace customer experience
• Significant cost reduction
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