Modern data lakes are now built on cloud storage, helping organizations leverage the scale and economics of object storage while simplifying overall data storage and analysis flow
Modern data lakes are now built on cloud storage, helping organizations leverage the scale and economics of object storage while simplifying overall data storage and analysis flow
OpenStack and Red Hat: How we learned to adapt with our customers in a maturi...OpenStack
Audience Level
All levels
Synopsis
Peter has been involved in OpenStack community since its B-release, and he has been enabling and helping customers across various industries adopt OpenStack in strategic ways. In this session, you will learn from his experience what Red Hat’s perspective is on the current state of affairs in the OpenStack community and the path we see ahead that Red Hat is putting its efforts in. OpenStack is not a product that tries to solve any one business problem in particular, but a technology that aims to be usable for many – what are the required steps to make sure that your organisation is ready for the OpenStack-based cloudification and transformation.
Speaker Bio:
Peter Jung is a Senior Business Development Manager at Red Hat where he leads the practice in the areas of Cloud, SDN/NFV and IoT across Australia and New Zealand. He is passionate about open innovation and open source software development model as the foundation for next generation society and ICT systems. Prior to Red Hat, he had various roles at Cisco and Dell for 15 years. He holds a BSEE and an MBA.
OpenStack Australia Day Melbourne 2017
https://events.aptira.com/openstack-australia-day-melbourne-2017/
An SDS (software-defined storage) refers to a software controller that is used for managing and virtualizing a physical storage for the purpose of controlling the way in which data is stored.
The Future of Cloud Software Defined Storage with Ceph: Andrew Hatfield, Red HatOpenStack
Audience: Intermediate
About: Learn how cloud storage differs to traditional storage systems and how that delivers revolutionary benefits.
Starting with an overview of how Ceph integrates tightly into OpenStack, you’ll see why 62% of OpenStack users choose Ceph, we’ll then take a peek into the very near future to see how rapidly Ceph is advancing and how you’ll be able to achieve all your childhood hopes and dreams in ways you never thought possible.
Speaker Bio: Andrew Hatfield – Practice Lead–Cloud Storage and Big Data, Red Hat
Andrew has over 20 years experience in the IT industry across APAC, specialising in Databases, Directory Systems, Groupware, Virtualisation and Storage for Enterprise and Government organisations. When not helping customers slash costs and increase agility by moving to the software-defined storage future, he’s enjoying the subtle tones of Islay Whisky and shredding pow pow on the world’s best snowboard resorts.
OpenStack Australia Day - Sydney 2016
https://events.aptira.com/openstack-australia-day-sydney-2016/
Cisco UCS Integrated Infrastructure for Big Data with CassandraDataStax Academy
With growing popularity of big data, it becomes imperative for enterprises to adopt the right platform for their workload, with efficient and user-friendly management of large scale clusters. In this session we will explore Cisco's revolutionary innovations that deliver leading-edge infrastructure, well suited for Cassandra like data base platforms, purpose built for performance and scalability. This enables our customers to unlock the intelligence in their data. Not only this provides a sustainable competitive advantage to their business, but also scales with their growing business needs.
Implementation of Dense Storage Utilizing HDDs with SSDs and PCIe Flash Acc...Red_Hat_Storage
At Red Hat Storage Day New York on 1/19/16, Red Hat partner Seagate presented on how to implement dense storage using HDDs with SSDs and PCIe flash accelerator cards.
In this presentation, Skip Levens from Quantum describes the company StorNext5 family of Appliances and Quantum Lattus Object Storage for Big Data management.
"For customers who need to retain and access hundreds of terabytes of unstructured data, Quantum Lattus Object Storage is a self-healing, self-protecting private cloud solution that enables more efficient primary storage usage, delivers extreme archive data resiliency and protection, and offers low latency disk access to archive data. Compared to RAID or tape storage, Lattus Object Storage provides the most effective solution on a cost/performance basis for active access, retention and protection of unstructured data in large archive environments."
Learn more: http://www.quantum.com/products/bigdatamanagement/index.aspx
Watch the video presentation: http://inside-bigdata.com/2013/12/12/introducing-stornext5-appliances/
Alluxio Community Office Hour
July 14, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Calvin Jia, Alluxio
Bin Fan, Alluxio
Alluxio 2.3 was just released at the end of June 2020. Calvin and Bin will go over the new features and integrations available and share learnings from the community. Any questions about the release and on-going community feature development are welcome.
In this Office Hour, we will go over:
- Glue Under Database integration
- Under Filesystem mount wizard
- Tiered Storage Enhancements
- Concurrent Metadata Sync
- Delegated Journal Backups
Red Hat Ceph Storage: Past, Present and FutureRed_Hat_Storage
Ceph is a massively scalable, open source, software-defined storage system that runs on commodity hardware. Get an update about the latest version of Red Hat Ceph Storage, including information about the newest features and use cases, with a particular focus on cloud storage and OpenStack. We’ll also explore the themes and directions for the roadmap for the next 12 months.
Home For Gypsies – Storage for NoSQL DatabasesAtish Kathpal
Video presentation: https://www.youtube.com/watch?v=QRmCr9qTL5o
Technical paper: https://www.usenix.org/conference/hotstorage17/program/presentation/kathpal
Abstract: Introduction to NoSQL DBs and CAP theorem
1. Advantages of shared storage as compared to DAS for NoSQL DBs: a) independent scaling of compute and storage b) consolidation, support of mixed workloads and predictable performance through use of flash arrays c) easier storage administration as compared to managing 100s of independent direct-attached disks in a scale-out NoSQL deployment
2. Challenges and need for integrated backup and restore in NoSQL DBs: a) cluster-consistent backups at scale in an eventually consistent system, b) storage efficiency in backups and c) ability to restore to different topologies
3. Relevance of light-weight snapshots, cloning and high-level solution directions to address challenges listed in #3
Speaker: Atish Kathpal
Acknowledgement: Priya Sehgal, Gaurav Makkar, Parag Deshmukh
A simple setup to build a private or public cloud.
A cloud at the IaaS layer is simply a cluster of hypervisors with some added storage infrastructure and software to orchestrate everything. In this presentation we show some straightfoward DELL hardware that could be purchased to build a single rack as the basic for a private or public cloud. It totals $100k and coupled with open source software: cloudstack, ceph, glusterfs, nfs etc is the basis for your cloud.
You will get a AWS compatible cloud in no-time and with limited acquisition cost.
Introducing the Hub for Data OrchestrationAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Introducing the Hub for Data Orchestration
Adit Madan, Product Manager (Alluxio)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Tachyon: An Open Source Memory-Centric Distributed Storage SystemTachyon Nexus, Inc.
Tachyon talk at Strata and Hadoop World 2015 at New York City, given by Haoyuan Li, Founder & CEO of Tachyon Nexus. If you are interested, please do not hesitate to contact us at info@tachyonnexus.com . You are welcome to visit our website ( www.tachyonnexus.com ) as well.
This presentation, delivered at CNI 2012, summarizes the lessons learned from trial audits of a several production distributed digital preservation networks. These audits were conducted using the open source SafeArchive system, which enables automated auditing of a selection of TRAC criteria related to replication and storage. An analysis of the trial audits demonstrates both the complexities of auditing modern replicated storage networks, and reveals common gaps between archival policy and practice. Recommendations for closing these gaps are discussed, as are extensions that have been added to the SafeArchive system to mitigate risks in distributed digital preservation (DDP).
OpenStack and Red Hat: How we learned to adapt with our customers in a maturi...OpenStack
Audience Level
All levels
Synopsis
Peter has been involved in OpenStack community since its B-release, and he has been enabling and helping customers across various industries adopt OpenStack in strategic ways. In this session, you will learn from his experience what Red Hat’s perspective is on the current state of affairs in the OpenStack community and the path we see ahead that Red Hat is putting its efforts in. OpenStack is not a product that tries to solve any one business problem in particular, but a technology that aims to be usable for many – what are the required steps to make sure that your organisation is ready for the OpenStack-based cloudification and transformation.
Speaker Bio:
Peter Jung is a Senior Business Development Manager at Red Hat where he leads the practice in the areas of Cloud, SDN/NFV and IoT across Australia and New Zealand. He is passionate about open innovation and open source software development model as the foundation for next generation society and ICT systems. Prior to Red Hat, he had various roles at Cisco and Dell for 15 years. He holds a BSEE and an MBA.
OpenStack Australia Day Melbourne 2017
https://events.aptira.com/openstack-australia-day-melbourne-2017/
An SDS (software-defined storage) refers to a software controller that is used for managing and virtualizing a physical storage for the purpose of controlling the way in which data is stored.
The Future of Cloud Software Defined Storage with Ceph: Andrew Hatfield, Red HatOpenStack
Audience: Intermediate
About: Learn how cloud storage differs to traditional storage systems and how that delivers revolutionary benefits.
Starting with an overview of how Ceph integrates tightly into OpenStack, you’ll see why 62% of OpenStack users choose Ceph, we’ll then take a peek into the very near future to see how rapidly Ceph is advancing and how you’ll be able to achieve all your childhood hopes and dreams in ways you never thought possible.
Speaker Bio: Andrew Hatfield – Practice Lead–Cloud Storage and Big Data, Red Hat
Andrew has over 20 years experience in the IT industry across APAC, specialising in Databases, Directory Systems, Groupware, Virtualisation and Storage for Enterprise and Government organisations. When not helping customers slash costs and increase agility by moving to the software-defined storage future, he’s enjoying the subtle tones of Islay Whisky and shredding pow pow on the world’s best snowboard resorts.
OpenStack Australia Day - Sydney 2016
https://events.aptira.com/openstack-australia-day-sydney-2016/
Cisco UCS Integrated Infrastructure for Big Data with CassandraDataStax Academy
With growing popularity of big data, it becomes imperative for enterprises to adopt the right platform for their workload, with efficient and user-friendly management of large scale clusters. In this session we will explore Cisco's revolutionary innovations that deliver leading-edge infrastructure, well suited for Cassandra like data base platforms, purpose built for performance and scalability. This enables our customers to unlock the intelligence in their data. Not only this provides a sustainable competitive advantage to their business, but also scales with their growing business needs.
Implementation of Dense Storage Utilizing HDDs with SSDs and PCIe Flash Acc...Red_Hat_Storage
At Red Hat Storage Day New York on 1/19/16, Red Hat partner Seagate presented on how to implement dense storage using HDDs with SSDs and PCIe flash accelerator cards.
In this presentation, Skip Levens from Quantum describes the company StorNext5 family of Appliances and Quantum Lattus Object Storage for Big Data management.
"For customers who need to retain and access hundreds of terabytes of unstructured data, Quantum Lattus Object Storage is a self-healing, self-protecting private cloud solution that enables more efficient primary storage usage, delivers extreme archive data resiliency and protection, and offers low latency disk access to archive data. Compared to RAID or tape storage, Lattus Object Storage provides the most effective solution on a cost/performance basis for active access, retention and protection of unstructured data in large archive environments."
Learn more: http://www.quantum.com/products/bigdatamanagement/index.aspx
Watch the video presentation: http://inside-bigdata.com/2013/12/12/introducing-stornext5-appliances/
Alluxio Community Office Hour
July 14, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Calvin Jia, Alluxio
Bin Fan, Alluxio
Alluxio 2.3 was just released at the end of June 2020. Calvin and Bin will go over the new features and integrations available and share learnings from the community. Any questions about the release and on-going community feature development are welcome.
In this Office Hour, we will go over:
- Glue Under Database integration
- Under Filesystem mount wizard
- Tiered Storage Enhancements
- Concurrent Metadata Sync
- Delegated Journal Backups
Red Hat Ceph Storage: Past, Present and FutureRed_Hat_Storage
Ceph is a massively scalable, open source, software-defined storage system that runs on commodity hardware. Get an update about the latest version of Red Hat Ceph Storage, including information about the newest features and use cases, with a particular focus on cloud storage and OpenStack. We’ll also explore the themes and directions for the roadmap for the next 12 months.
Home For Gypsies – Storage for NoSQL DatabasesAtish Kathpal
Video presentation: https://www.youtube.com/watch?v=QRmCr9qTL5o
Technical paper: https://www.usenix.org/conference/hotstorage17/program/presentation/kathpal
Abstract: Introduction to NoSQL DBs and CAP theorem
1. Advantages of shared storage as compared to DAS for NoSQL DBs: a) independent scaling of compute and storage b) consolidation, support of mixed workloads and predictable performance through use of flash arrays c) easier storage administration as compared to managing 100s of independent direct-attached disks in a scale-out NoSQL deployment
2. Challenges and need for integrated backup and restore in NoSQL DBs: a) cluster-consistent backups at scale in an eventually consistent system, b) storage efficiency in backups and c) ability to restore to different topologies
3. Relevance of light-weight snapshots, cloning and high-level solution directions to address challenges listed in #3
Speaker: Atish Kathpal
Acknowledgement: Priya Sehgal, Gaurav Makkar, Parag Deshmukh
A simple setup to build a private or public cloud.
A cloud at the IaaS layer is simply a cluster of hypervisors with some added storage infrastructure and software to orchestrate everything. In this presentation we show some straightfoward DELL hardware that could be purchased to build a single rack as the basic for a private or public cloud. It totals $100k and coupled with open source software: cloudstack, ceph, glusterfs, nfs etc is the basis for your cloud.
You will get a AWS compatible cloud in no-time and with limited acquisition cost.
Introducing the Hub for Data OrchestrationAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Introducing the Hub for Data Orchestration
Adit Madan, Product Manager (Alluxio)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Tachyon: An Open Source Memory-Centric Distributed Storage SystemTachyon Nexus, Inc.
Tachyon talk at Strata and Hadoop World 2015 at New York City, given by Haoyuan Li, Founder & CEO of Tachyon Nexus. If you are interested, please do not hesitate to contact us at info@tachyonnexus.com . You are welcome to visit our website ( www.tachyonnexus.com ) as well.
This presentation, delivered at CNI 2012, summarizes the lessons learned from trial audits of a several production distributed digital preservation networks. These audits were conducted using the open source SafeArchive system, which enables automated auditing of a selection of TRAC criteria related to replication and storage. An analysis of the trial audits demonstrates both the complexities of auditing modern replicated storage networks, and reveals common gaps between archival policy and practice. Recommendations for closing these gaps are discussed, as are extensions that have been added to the SafeArchive system to mitigate risks in distributed digital preservation (DDP).
Clustered and distributed storage with commodity hardware and open source ...Phil Cryer
An overview of the state of the Biodiversity Heritage Library's first storage cluster. It covers the basics of building a clustered and distributed storage with commodity hardware and open source software , and also details such as working software to maintain synchronization with other global partners. Presented to the Biodiversity Heritage Library Europe's Technical Architecture board at Natural History Museum, London on August 25, 2010.
Secure distributed data storage can shift the burden of maintaining a large number of files from the owner to proxy servers.
Proxy servers can convert encrypted files for the owner to encrypted files for the receiver without the necessity of knowing the content of the original files. In practice, the original files will be removed by the owner for the sake of space efficiency. Hence, the issues on confidentiality and integrity of the outsourced data must be addressed carefully. In this paper, we propose two identity-based secure distributed data storage (IBSDDS) schemes. Our schemes can capture the following properties: (1) The file owner can decide the access permission independently without the help of the private key generator (PKG).
(2) For one query, a receiver can only access one file, instead of all files of the owner.
(3) Our schemes are secure against the collusion attacks, namely even if the receiver can compromise the proxy servers, he cannot obtain the owner’s secret key.
Although the first scheme is only secure against the chosen plaintext attacks (CPA), the second scheme is secure against the chosen ciphertext attacks (CCA). To the best of our knowledge, it is the first IBSDDS schemes where an access permissions is made by the owner for an exact file and collusion attacks can be protected in the standard model.
Storage is one of the most important part of a data center, the complexity to design, build and delivering 24/forever availability service continues to increase every year. For these problems one of the best solution is a distributed filesystem (DFS) This talk describes the basic architectures of DFS and comparison among different free software solutions in order to show what makes DFS suitable for large-scale distributed environments. We explain how to use, to deploy, advantages and disadvantages, performance and layout on each solutions. We also introduce some Case Studies on implementations based on openAFS, GlusterFS and Hadoop finalized to build your own Cloud Storage.
Big Data Day LA 2016/ Hadoop/ Spark/ Kafka track - Alluxio (formerly Tachyon)...Data Con LA
Alluxio, formerly Tachyon, is a memory speed virtual distributed storage system. The Alluxio open source community is one of the fastest growing open source communities in big data history with more than 300 developers from over 100 organizations around the world. In the past year, the Alluxio project experienced a tremendous improvement in performance and scalability and was extended with key new features including tiered storage, transparent naming, and unified namespace. Alluxio now supports a wide range of under storage systems, including Amazon S3, Google Cloud Storage, Gluster, Ceph, HDFS, NFS, and OpenStack Swift. This year, our goal is to make Alluxio accessible to an even wider set of users, through our focus on security, new language bindings, and further increased stability.
This presentation outlines the different storage technology options available to cope up with the intermittent nature of the Renewable energy like wind and solar.
Distributed computing deals with hardware and software systems containing more than one processing element or storage element, concurrent processes, or multiple programs, running under a loosely or tightly controlled regime. In distributed computing a program is split up into parts that run simultaneously on multiple computers communicating over a network. Distributed computing is a form of parallel computing, but parallel computing is most commonly used to describe program parts running simultaneously on multiple processors in the same computer. Both types of processing require dividing a program into parts that can run simultaneously, but distributed programs often must deal with heterogeneous environments, network links of varying latencies, and unpredictable failures in the network or the computers.
FILE SYSTEM AND NAS: Local File Systems; Network file Systems and file servers; Shared Disk file systems; Comparison of fiber Channel and NAS.
STORAGE VIRTUALIZATION: Definition of Storage virtualization; Implementation Considerations; Storage virtualization on Block or file level; Storage virtualization on various levels of the storage Network; Symmetric and Asymmetric storage virtualization in the Network
In computing, a distributed file system (DFS) or network file system is any file system that allows access to files from multiple hosts sharing via a computer network. This makes it possible for multiple users on multiple machines to share files and storage resources.
Maginatics @ SDC 2013: Architecting An Enterprise Storage Platform Using Obje...Maginatics
How did Maginatics build a strongly consistent and secure distributed file system? Niraj Tolia, Chief Architect at Maginatics, gave this presentation on the design of MagFS at the Storage Developer Conference on September 16, 2013.
For more information about MagFS—The File System for the Cloud, visit maginatics.com or contact us directly at info@maginatics.com.
Research Paper Find a peer reviewed article in the following dat.docxaudeleypearl
Research Paper: Find a peer reviewed article in the following databases provided by the UC Library and write a 250-word paper reviewing the literature concerning Data Center Technology. Choose one of the technologies discussed in Chapter 5, Section 5.2 (Erl, 2014).
1- Virtualization -- <I prefer this one> provide some flow chat also.
2- Standardization and Modularity
3- Automation
4- Remote Operation and Management
5- High Availability
6- Security-Aware Design, Operation, and Management
7- Facilities
Etc…
You may choose any scholarly peer reviewed articles and papers.
Use the following databases for your research:
· ACM Digital Library
· IEEE/IET Electronic Library
· SAGE Premier
Section 5.2 <From here we can choose one topic)
5.2. DATA CENTER TECHNOLOGY
Grouping IT resources in close proximity with one another, rather than having them geographically dispersed, allows for
power sharing, higher efficiency in shared IT resource usage, and improved accessibility for IT personnel. These are the
advantages that naturally popularized the data center concept. Modern data centers exist as specialized IT infrastructure
Chapter 5. Cloud-Enabling Technology - Cloud Computing: Concepts, Technology & Architecture
https://www.safaribooksonline.com/library/view/cloud-computing-concepts/9780133387568/ch05.html[11/15/2017 5:49:24 PM]
used to house centralized IT resources, such as servers, databases, networking and telecommunication devices, and
software systems.
Data centers are typically comprised of the following technologies and components:
Virtualization
Data centers consist of both physical and virtualized IT resources. The physical IT resource layer refers to the facility
infrastructure that houses computing/networking systems and equipment, together with hardware systems and their
operating systems (Figure 5.7). The resource abstraction and control of the virtualization layer is comprised of operational
and management tools that are often based on virtualization platforms that abstract the physical computing and
networking IT resources as virtualized components that are easier to allocate, operate, release, monitor, and control.
Chapter 5. Cloud-Enabling Technology - Cloud Computing: Concepts, Technology & Architecture
https://www.safaribooksonline.com/library/view/cloud-computing-concepts/9780133387568/ch05.html[11/15/2017 5:49:24 PM]
Figure 5.7. The common components of a data center working together to provide virtualized IT resources
supported by physical IT resources.
Virtualization components are discussed separately in the upcoming Virtualization Technology section.
Standardization and Modularity
Data centers are built upon standardized commodity hardware and designed with modular architectures, aggregating
multiple identical building blocks of facility infrastructure and equipment to support scalability, growth, and speedy
hardware replacements. Modularity and standardization are key requirements for reducing investment and operation ...
In this presentation, we will discuss in details about challenges in managing the IT infrastructure with a focus on server sizing, storage capacity planning and internet connectivity. We will also discuss about how to set up security architecture and disaster recovery plan.
To know more about Welingkar School’s Distance Learning Program and courses offered, visit:
http://www.welingkaronline.org/distance-learning/online-mba.html
What is a Network-Attached-Storage device and how does it work?MaryJWilliams2
A network-attached storage device, or NAS for short, is a specialised type of computer designed to provide file-based data storage services to a computer network. In contrast to a standard desktop or laptop PC, which typically stores its data on an internal hard drive, a NAS device contains one or more large-capacity drives that are accessible by all devices on the network. This makes it an ideal solution for centrally storing and sharing files among multiple users. But what exactly is a NAS and how does it work then must visit :
https://stonefly.com/blog/network-attached-storage-appliance-practicality-and-usage
What is Network Attached Storage Used for?.pdfEnterprisenas
To summarize it, a NAS network storage is used for unstructured data storage. This can be surveillance videos, files, backups, snapshots, emails, etc. The network attached storage is very handy for HPC (High Performance Computing) requirements. For more information, visit : https://stonefly.com/blog/network-attached-storage-appliance-practicality-and-usage
Compare Array vs Host vs Hypervisor vs Network-Based ReplicationMaryJWilliams2
Network-based replication is a data replication technique that operates at the network layer. It involves replicating data between source and target systems over a network infrastructure. Unlike array-based or host-based replication, network-based replication is not tightly coupled to storage arrays or hosts but focuses on replicating data at the network level.
In network-based replication, data is captured and replicated at the application or file system level. It intercepts the input/output (I/O) operations at the network layer, captures the changes made to data, and replicates them to the target system. This replication method allows for the replication of specific files, folders, or even individual application transactions.
For more information visit : https://stonefly.com/blog/network-attached-storage-appliance-practicality-and-usage
Cloud Computing Mechanisms
Chapter 7 – Infrastructure
Chapter 8 – Specialized
Chapter 9 – Management
Chapter 10 – Security (Will be discussed doing the security module)
What is a mechanism?
a system of parts working together in a machine; a piece of machinery.
Learning Outcomes
Understand basic concepts and terminology relating to cloud computing
Understand virtualization technology
Cloud Characteristics mentioned in Chapter 4
The following six specific characteristics are common to the majority of cloud environments:
• on-demand usage
• ubiquitous access
• multitenancy (and resource pooling)
• elasticity
• measured usage
• resiliency
Cloud CharacteristicsCloud Mechanisms
On – Demand UsageHypervisorVirtual ServerReady-Made EnvironmentResource ReplicationRemote Administration EnvironmentResource Management SystemSLA Management SystemBilling Management SystemUbiquitous AccessLogical Network PerimeterMulti-Device Broker
Multitenancy / Resource PoolingLogical Network PerimeterHypervisorResource ReplicationResource ClusterResource Management System
ElasticityHypervisorCloud Usage MonitorAutomated Scaling ListenerResource ReplicationLoad BalancerResource Management System
Measured UsageHypervisorCloud Usage MonitorSLA MonitorPay-Per-Use MonitorAudit MonitorSLA Management SystemBilling Management System
ResiliencyHypervisorResource ReplicationFailover SystemResource ClusterRemote Management System
Cloud Infrastructure Mechanisms
Chapter 7
Cloud Infrastructure Mechanisms
7.1 Logical Network Perimeter
7.2 Virtual Server
7.3 Cloud Storage Device
7.4 Cloud Usage Monitor
7.5 Resource Replication
7.6 Ready-Made Environment
7.1 Logical Network Perimeter
Logical Network Perimeter
Defined as the isolation of a network environment from the rest of a communications network, the logical network perimeter establishes a virtual network boundary that can encompass and isolate a group of related cloud-based IT resources that may be physically distributed
This mechanism can be implemented to:
isolate IT resources in a cloud from non-authorized users
isolate IT resources in a cloud from non-users
isolate IT resources in a cloud from cloud consumers
control the bandwidth that is available to isolated IT resources
Logical Network Perimeter
Logical network perimeters are typically established via network devices that supply and control the connectivity of a data center and are commonly deployed as virtualized IT environments that include:
• Virtual Firewall – An IT resource that actively filters network traffic to and from the isolated network while controlling its interactions with the Internet.
• Virtual Network – Usually acquired through VLANs, this IT resource isolates the network environment within the data center infrastructure.
7.2 Virtual Server
Virtual Server
A virtual server is a form of virtualization software that emulates a physical server. Virtual servers are used by cloud providers to share the sa.
Research Paper Find a peer reviewed article in the following d.docxeleanorg1
Research Paper:
Find a peer reviewed article in the following databases provided by the UC Library and write a 500
-word
paper reviewing the literature concerning
Data Center Technology. Choose one of the technologies discussed in Chapter 5, Section 5.2 (Erl, 2014).
Abstract <>
Introduction <>
1-
Virtualization --
provide some flow chat also.
(Note:- But you can take anyone from 1 to 7)
2- Standardization and Modularity
3- Automation
4- Remote Operation and Management
5- High Availability
6- Security-Aware Design, Operation, and Management
7- Facilities
Etc…
======This is must
Use the following databases for your research:
· ACM Digital Library
· IEEE/IET Electronic Library
· SAGE Premier
=======
Conclusion<>
You may choose any scholarly peer reviewed articles and papers.
FYI -- PDF BOOK
Section 5.2
5.2. DATA CENTER TECHNOLOGY
Grouping IT resources in close proximity with one another, rather than having them geographically dispersed, allows for
power sharing, higher efficiency in shared IT resource usage, and improved accessibility for IT personnel. These are the
advantages that naturally popularized the data center concept. Modern data centers exist as specialized IT infrastructure
Chapter 5. Cloud-Enabling Technology - Cloud Computing: Concepts, Technology & Architecture
https://www.safaribooksonline.com/library/view/cloud-computing-concepts/9780133387568/ch05.html[11/15/2017 5:49:24 PM]
used to house centralized IT resources, such as servers, databases, networking and telecommunication devices, and
software systems.
Data centers are typically comprised of the following technologies and components:
Virtualization
Data centers consist of both physical and virtualized IT resources. The physical IT resource layer refers to the facility
infrastructure that houses computing/networking systems and equipment, together with hardware systems and their
operating systems (Figure 5.7). The resource abstraction and control of the virtualization layer is comprised of operational
and management tools that are often based on virtualization platforms that abstract the physical computing and
networking IT resources as virtualized components that are easier to allocate, operate, release, monitor, and control.
Chapter 5. Cloud-Enabling Technology - Cloud Computing: Concepts, Technology & Architecture
https://www.safaribooksonline.com/library/view/cloud-computing-concepts/9780133387568/ch05.html[11/15/2017 5:49:24 PM]
Figure 5.7.
The common components of a data center working together to provide virtualized IT resources
supported by physical IT resources.
Virtualization components are discussed separately in the upcoming
Virtualization Technology
section.
Standardization and Modularity
Data centers are built upon standardized commodity hardware and designed with modular architectures, aggregating
multiple identical building blocks of facility infrastructure and equipment to support scalability, gro.
Similar to Survey of distributed storage system (20)
Some key value stores using log-structureZhichao Liang
This slides presents three key-value stores using log-structure, includes Riak, RethinkDB, LevelDB. BTW, i state that RethinkDB employs append-only B-tree and that is an estimate made by combining guessing wih reasoning!
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
4. Background As more and more digital devices(e.g. PC, laptop, ipad and smart phone) connect to the Internet, massive amount of new data are created on the web There were 5 exabytes of data online in 2002, which had risen to 281 exabytes in 2009, and the online data growth rate is rising faster than Moore's Law Then, how to store and manage these massive data effectively and efficiently ? An natural approach: Distributed Storage System!
5. Traditional Storage Architecture Direct Attached Storage(DAS) - huge management burden - limited number of connected host - severely limited data sharing Fabric Attached Storage - central system serves data to connected hosts - hosts and devices interconnected through Ethernet or Fibre Channel - NAS & SAN
6. FAS Implementations Network Attached Storage(NAS) - file-based storage architecture - data sharing across platforms - file sever can be the bottleneck Storage Area Networks(SAN) - scalable performance, high capacity - limited ability of sharing data - unreliable security Since the traditional storage architectures can not satisfy the emerging requirement well, novel approaches need to be proposed !
8. Storage Virtualization Definitions of storage virtualization by SNIA - the act of abstracting, hiding, or isolating the internal functions of a storage (sub)system or service from applications, computer servers, or general network resources for the purposes of enabling application and network independent management of storage or data - The application of virtualization to storage services or devices for the purpose of aggregating, hiding complexity, or adding new capabilities to lower-level storage resources Simply speaking, storage virtualization aggregates storage components, such as disks, controllers, and storage networks, in a coordinated way to share them more efficiently among the applications it serves!
9. Charactristics of ideal solution A good storage virtualization solution should: Enhance the storage resources it is virtualizing through the aggregation of services to increase the return of existing assets Not add another level of complexity in configuration and management Improve performance rather than act as a bottleneck in order for it to be scalable. Scalability is the capability of a system to maintain performance linearly as new resources (typically hardware) are added Provide secure multi-tenancy so that users and data can share virtual resources without exposure to other users’ bad behavior or mistakes Not be proprietary, but virtualize other vendor storage in the same way as its own storage to make the management seamless.
10. Types of Storage Virtualization Modern storage virtualization technologies can be implemented in three layers of the infrastructure In the server, some of the earliest forms of storage virtualization came from within the server’s operating systems In the storage network, network-based storage virtualization embeds the intelligence of managing the storage resources in the network layer In the storage controller, controller-based storage virtualization allows external storage to appear as if it’s internal
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12. It does not require additional hardware in the storage infrastructure, and works with any devices that can be seen by the operating system.
13. Although it helps maximize the efficiency and resilience of storage resources, it’s optimized on a per-server basis only.
14. The task of mirroring, striping, and calculating parity requires additional processing, taking valuable CPU and memory resources away from the application.
15. Since every operating system implements file systems and volume management in different ways, organizations with multiple IT vendors need to maintain different skill sets and processes, with higher costs.
19. The virtualization devices are typically servers running system software and requiring as much maintenance as a regular server.
20. The I/O can suffer from latency, impacting performance and scalability due to the multiple steps required to complete the request, and limited to the amount of memory and CPU available in the appliance nodes.
21. Decoupling the virtualization from the storage once it has been implemented is impossible because all the meta-data resides in the appliance, thereby making it proprietary.
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23. Complexity is reduced as it needs no additional hardware to extend the benefits of virtualization. In many cases the requirement for SAN hardware is greatly reduced.
26. Interoperability issues are reduced as the virtualized controller mimics a server connection to external storage.Although a few downsides to controller-based virtualization exist, the advantages not only far outweigh them but they also address most of the deficiencies found in server- and network based approaches.
28. Motivation of Object Storage Improved device and data sharing - platform-dependent metadata moved to device Improved scalability & security - devices directly handle client requests - object security Improved performance - data types can be differentiated at the device Improved storage management - self-managed, policy-driven storage - storage devices become more autonomous
29. Objects in Storage The root object -- The OSD itself User object -- Created by SCSI commands from the application or client Collection object -- A group of user objects, such as all .mp3 Partition object -- Containers that share common security and space managementcharacteristics P4 P3 P2 OSD P1 Root Object (one per device) Partition Objects U1 User Data Collection Objects Metadata Attributes User Objects(for user data) Object ID
30. Object Storage Device Two changes - Object-based storage offloads the storage component to the storage device - The device interface changes from blocks to objects Applications Applications System call interface System call interface File system user component File system user component File system storage component Object interface File system storage component Block interface Block I/O manager Block I/O manager Storage device Storage device Traditional model OSD model
31. Object Storage Architecture Summary of OSD Key Benefits ■ Better data sharing – Using objects means less metadata to keep coherent, which makes it possible to share the data across different platforms. ■ Better security – Unlike blocks, objects can protect themselves and authorize each I/O. ■ More intelligence – Object attributes help the storage devices learn about its users, the applications and the workloads. This leads to a variety of improvements, such as better data management through caching. Active disks can be implemented on OSDs to implement database filters. An intelligent OSD can also continuously reorganize the data, manage its own backups and deal with failures.
32. Lustre Lustre (Linux + Cluster) - first open sourced system with object storage - a massively parallel distributed file system - consist of clients, MDS and OST - used by fifteen of the top 30 supercomputers in the world A single metadata server (MDS) that has a single metadata target (MDT) per Lustrefilesystem that stores namespace metadata, such as filenames, directories, access permissions, and file layout. Client(s)that access and use the data, concurrent and coherent read and write access to the files are allowed One or more object storage servers (OSSes) that store file data on one or more object storage targets (OSTs)
33. Ceph Ceph is a distributed file system that provides excellent performance, reliability, and scalability based on object storage devices Metadata Cluster store the cluster map and control the data placement, higher-level POSIX functions (such as open, close, and rename) are managed.
34. Panasas Panasas (Panasas, Inc.) - consist of OSD, Panasas File System, MDS - claim to be the world's fastest HPC storage system
36. Distributed File System A distributed file system or network file system is any file system that allows access to files from multiple hosts sharing via a computer network(Wikipedia) The history - 1st generation(1980s): NFS, AFS - 2nd generation(1990~1995): Tiger Shark, Slice File System - 3rd generation(1995~2000): Global File System, General Parallel File System, DiFFs, CXFS, HighRoad - 4th generation(2000~now): Lustre, GFSm, GlusterFS, HDFS Performance Scalability Reliability Availability Fault-tolerant
37. Google File System(GFS) GFS is a scalable distributed file system for large distributed data-intensive application in Google Beyond the traditional choices - normal component failures - huge files by traditional standards - appending new data rather than overwriting - co-designing the application and file system API GFS Interface - create, delete, open, close, read, write - snapshot & record append Master maintains all file system metadata, such as namespace, access control information, mapping from files to chunks and the location of chunks Clients interact with the master for metadata operations, but all data-bearing communication goes directly to the chunkservers Files are divided into fix-size(64MB) chunks, and each chunk is identified by immutable and global unique 64 bit chunk handle. Chunkservers store chunks on local disks as Linux files. In addition, each chunk is replicated on multiple chunkservers, in default, 3 replicas.
38. The client sends a write request to the primary once all the replicas have acknowledged receiving the data. The primary assigns consecutive serial numbers to all the mutations it receives and applies the mutation to its own local state in serial number order. Write Control and Data Flow The client asks the master which chunkserver holds the current lease for the chunk and the locations of the other replicas. If no one has, the master grants one to a replica it chooses. Error cases: Failed at the primary, it would not have been assigned a serial number and forwarded; Succeeded at primary and an arbitrary subset of the secondary replicas. The client code handles such errors by retrying the failed mutation. The primary forwards the write request to secondary replicas The client pushes the data to all replicas in any order. The master replies with the identity of primary and the locations of the other replicas. The client caches the information. The primary replies to the client. The secondaries all reply to the primary indicating that they have completed the operation.
39. Hadoop Distributed File System (HDFS) NameNode, a master server that manages the file system namespace and regulates access to files by clients. The Hadoop Distributed File System (HDFS) is an open source implementation of GFS DataNodes, manage storage attached to the nodes that they run on A file is split into one or more blocks and these blocks are stored in a set of DataNodes
40. Taobao File System Taobao File System(TFS) is a distributed file system optimized for the management of massive small files(1MB), such as pictures and descriptions of commodity Application/Client: access the name server & data server through TFSClient Name Sever: store metadata, monitor data server through heartbeat message, control IO balance, and data location info such <block id, data server> Data Sever: store application data, load blance, redundant backup
41.
42. effective distribution of data, file distribution is intelligently handled using elastic hash
43.
44. Sheepdog Automatically detect removed nodes Sheepdog is a distributed storage system for QEMU/KVM - amazon EBS-like volume pool - highly scalable, available and reliable - support for advanced volume management - not general file system, API is designed specific to QEMU Zero configuration about cluster nodes Automatically detect added nodes
45. Sheepdog Volumes are divided into 4 MB objects and each object is identified by globally unique 64 bit id, and replicated to multiple nodes Consistent hashing is used to decide which node to store objects. Each node is also placed on the ring.Addition or removal of nodes does not significantly change the mapping of objects
46. Reference [1] A. D. Luca and M. Bhide. Storage virtualization for dummies, Hitachi Data Systems Edition. Wiley Publishing, 2010. [2] S. Ghemawat, H. Gobioff, and S.-T. Leung. The google file system. In Proceedings of the 19th ACM Symposium on Operating Systems Principles 2003, SOSP 2003, Bolton Landing, NY, USA, October 19-22, 2003. [3] R. MacManus. The coming data explosion. Available: http://www.readwriteweb.com/archives/the_coming_data_explosion.php, 2010.
47. Reference (cont.) [4] Intel white paper: Object-based storage, the next wave of storage technology and devices, 2003. [5] M. Mesnier, G. R. Ganger and E. Riedel. Object-based storage. IEEE Communications Magazine, August 2003, 84-89. [6] Lustre. Available: http://wiki.lustre.org/index.php, 2010. [7] Panasas. Available: http://www.panasas.com/. [8] Hadoop. Available: http://hadoop.apache.org/. [9] tfs. Available: http://code.taobao.org/trac/tfs/wiki/intro. [10] GlusterFS. Available: http://www.gluster.org/.
48. Reference (cont.) [11] Sheep dog. Available: http://www.osrg.net/sheepdog/. [12] Ceph. Available: http://ceph.newdream.net/. [13] S. A. Weil, S. A. Brandt, E. L. Miller, D. D. E. Long. Ceph: A Scalable, High-Performance Distributed File System. In Proceedings of 7th Symposium on Operating Systems Design and Implementation (OSDI '06), November 6-8, Seattle, WA, USA. [14] Gluster Whitepaper: Gluster file system architecture.