Figure 8.11 NOTE To modify the specification, select Override Specification Values. ii. Select Sysprep Answer File, to upload a Sysprep file or use one that exists for a custom specification on the Provider where the template resides. To upload a file, click Browse to find the file, and then upload. To use an answer file in Customization Specification, click on the item. The answer file will automatically upload for viewing. You cannot make modifications to it. 9. For Linux provisioning: i. Under Credentials, enter a Root Password for the root user to access the instance. ii. Enter an IP Address Information for the instance. Leave as DHCP for automatic IP assignment from the provider. iii. Enter any DNS information for the instance if necessary. iv. Select Customize Template for additional instance configuration. Select from the Kickstart or Cloud-Init customization templates stored on your appliance. 10. Click the Schedule tab to select when provisioning begins. i. In Schedule Info, select when to start provisioning. If you select Schedule, you will be prompted to enter a date and time. Select Stateless if you do not want the files deleted after the provision completes. A stateless provision does not write to the disk so it requires the PXE files on the next boot. ii. In Lifespan, select to power on the virtual machines after they are created, and to set a retirement date. If you select a retirement period, you will be prompted for when you 150 CU IDOL SELF LEARNING MATERIAL (SLM)
want a retirement Figure 8.12 Schedule 11. Click Submit. The provisioning request is distributed for approval. For the provisioning to start, a user with the administrator, approver, or super administrator account role should approve the request. The administrator and super administrator roles may also edit, delete, and deny the requests. you may be able to see all provisioning requests wherever you're either the requester or the authority. After submission, the appliance assigns every provision request missive of invitation ID. If a mistake happens throughout the approval or provisioning method, use this ID to find the request within the appliance logs. The Request ID consists of the region related to the request followed by the request range. As regions outline a spread of 1 trillion info IDs, this range may be many digits long. Request ID Format Request 99 in region 123 results in Request ID 123000000000099. 151 CU IDOL SELF LEARNING MATERIAL (SLM)
2. Clone a virtual machine Virtual Machines can be cloned in other providers as well. 1. Navigate to Infrastructure → Virtual Machines, and check the virtual machine you want to clone. 2. Click (Lifecycle), and then (Clone selected item). 3. Fill in the options as shown in To Provision from a template using the provided dialogs. Be sure to check the Catalog Tab. 4. Schedule the request on the Schedule tab. 5. Click Submit. 1. Publish a virtual machine to a template 2. Navigate to Infrastructure → Virtual Machines, and check the virtual machine you want to publish as a template. 3. Click (Lifecycle), and then (Publish selected VM to a Template). 4. Fill in the options as shown in To Provision from a template using the provided dialogs. Be sure to check the Catalog tab. 5. Schedule the request on the Schedule tab. 6. Click Submit. 8.8 LOAD BALANCING Traditional load balancing solutions believe in proprietary hardware housed during a data centre, and they need a team of sophisticated IT personnel to put in, tune, and maintain the system. Only large companies with big IT budgets can reap the advantages of improved performance and reliability. In the age of cloud computing, hardware-based solutions have another serious drawback: they don’t support cloud load balancing, because cloud 152 CU IDOL SELF LEARNING MATERIAL (SLM)
infrastructure vendors typically don’t allow customer or proprietary hardware in their environment. Fortunately, software-based cloud load balancers can deliver the performance and reliability benefits of hardware-based solutions at a much lower cost. As they run on commodity hardware, they’re affordable even for smaller companies. They are ideal for cloud load balancing as they will run within the cloud like all other software applications. There are certain parameters for measuring the efficiency of the load balancing algorithm in cloud computing environment. • Fault Tolerance • Throughput • Adaptability • Response Time • Energy Consumption • Migration Time • Associated Cost There are two types of load balancing algorithms, mainly. They are: 1) Static Algorithm – In this, traffic is divided evenly among the servers. Static algorithm is known to be proper in the system which has low variation in load. 2) Dynamic Algorithm – Here, the lightest server in the whole network or system is searched and preferred for balancing a load. Why Cloud Providers Need Load Balancing The effective use of cloud load balancing helps ensure business continuity. The noteworthy features and main objectives of using load balancers are to effectively maintain system firmness, facilitate system performance and protection against system failures. 153 CU IDOL SELF LEARNING MATERIAL (SLM)
The speed of scaling in the cloud means how effectively companies can handle traffic without downgrading the performance by putting a cloud load balancer ahead of a gaggle of application instances, which may quickly auto scale in reaction to the extent of demand. Cloud Load Balancing was introduced for various reasons. One of them is to better the speed and performance of every single device and the other is to keep saving individual devices from hitting their threshold by dropping down their performance. Cloud load balancing helps other companies to give high level of performance at a lower cost as compared to that offered by traditional on-premises load balancing technology. Cloud load balancing takes advantage of the cloud’s scalability and agility to satisfy rerouted workload demands and to enhance overall availability. Additionally, when it comes to workload and traffic distribution, cloud load balancing technology succeeds immensely to provide health checks for cloud applications. How Cloud Load Balancing Helps As you are involved in the continuous process of delivering more services through your cloud infrastructure, it is expected that you’d experience an exponential increase in traffic from the clients. You also, need to stay alert and ready for the occasional spikes and seasonal surge in demand. In order to scale your infrastructure to support the increasing demand as well as maintain acceptable levels of responsiveness and availability, you need to ensure that you incorporate load balancing into your cloud endeavours. Some of the benefits of cloud load balancing are: • Increased Scalability – The usage of efficient load balancers enables you to easily match up the increased user traffic and also, distribute it among several servers or various network devices. • High Performing Applications – Organizations are able to make their client applications work faster and provide improved performances, that too at potentially lower costs. • Ability to Handle Traffic Surges – If you are using cloud load balancers, no need to worry about traffic surges. With the help of load balancing requests can be wisely 154 CU IDOL SELF LEARNING MATERIAL (SLM)
distributed among different servers for generating maximum results in less response time. • Flexibility – If the workload is distributed among various servers or network units, even if one node fails the burden can be shifted to another active node. Load balancing easily manages application traffic with increased redundancy and scalability. • Reliability – If in case a cloud resource crashes, the cloud load balancer is effective in directing traffic away from the resource to resources hosted elsewhere in a business’ cloud environment. • Cost Effectiveness – Cloud load balancers are able to deliver the performance and reliability benefits of hardware-based solutions at a much lower total cost of ownership. Since they run on the cloud, they are affordable even for smaller companies. Cloud Service Providers There are many cloud service providers that offer cloud load balancing technologies, such as Amazon Web Services (AWS), Google Cloud, Microsoft Azure etc. AWS offers Elastic Load Balancing, in which you distribute workloads and traffic among EC2 instances. Google Cloud Platform offers load balancing for its infrastructure as a service. Google Compute Engine distributes network traffic between VM instances. Microsoft Azure’s Traffic Manager distributes traffic in its cloud services across multiple data centres. The users of Cloud load balancing include companies with large-scale applications that need high availability and performance, but any organization can achieve benefits from the cloud technology. The Rise of Load Balancing in Cloud Computing The benefits of cloud load balancing arise from the scalable and global nature of the cloud itself. The ease and speed of scaling in the cloud primarily means that enterprises and organizations can handle traffic surges without deteriorating performance by placing a cloud load balancer in front of a group of application instances, which can quickly auto scale in reaction to the level of demand. Cloud load balancing enables companies to achieve high performance levels for potentially reduced expenses than the traditional on-premises load 155 CU IDOL SELF LEARNING MATERIAL (SLM)
balancing technology. It makes use of the advantage of cloud’s scalability and agility to meet rerouted workload demands and to improve overall availability. 1. Cloud load reconciliation is outlined because the methodology of cacophonous workloads and computing properties in an exceedingly cloud computing. It permits enterprise to manage employment demands or application demands by distributing resources among various computers, networks or servers. Cloud load reconciliation includes holding the circulation of employment traffic and demands that exist over the net. 2. As the traffic on the net growing speedily, that is concerning 100% annually of this traffic. Hence, the employment on the server growing therefore quick that ends up in the overloading of servers chiefly for in style net server. There are 2 elementary solutions to beat the matter of overloading on the servers- 3. First could be a single-server answer within which the server is upgraded to the next performance server. However, the new server might also be full before long, exigent another upgrade. Moreover, the upgrading method is arduous and big-ticket. 4. Second could be a multiple-server answer within which an ascendible service system on a cluster of servers is made. That’s why it's additional price effective similarly as additional ascendible to make a server cluster system for network services. 5. Load reconciliation is helpful with virtually any variety of service, like HTTP, SMTP, DNS, FTP, and POP/IMAP. It additionally rises responsibleness through redundancy. The reconciliation service is provided by a frenzied hardware device or program. Cloud-based servers farms will attain additional precise measurability and handiness victimisation server load reconciliation. 6. Load reconciliation solutions are often classified into 2 varieties – 1. Software-based load balancers: Software-based load balancers run on normal hardware (desktop, PCs) and normal operative systems. 2. Hardware-based load balancer: Hardware-based load balancers are dedicated boxes that embody Application Specific Integrated Circuits (ASICs) tailored for a selected use. ASICs permits high speed promoting of network traffic and are ofttimes used for transport- 156 CU IDOL SELF LEARNING MATERIAL (SLM)
level load reconciliation as a result of hardware-based load reconciliation is quicker as compared to computer code answer. Major Examples of Load Balancers – 1. Direct Routing Requesting Dispatching Technique: This approach of request dispatching is like to the one implemented in IBM’s Net Dispatcher. A real server and load balancer share the virtual IP address. In this, load balancer takes an interface constructed with the virtual IP address that accepts request packets and it directly routes the packet to the selected servers. 2. Dispatcher-Based Load Balancing Cluster: A dispatcher does smart load balancing by utilizing server availability, workload, capability and other user-defined criteria to regulate where to send a TCP/IP request. The dispatcher module of a load balancer can split HTTP requests among various nodes in a cluster. The dispatcher splits the load among many servers in a cluster so the services of various nodes seem like a virtual service on an only IP address; consumers interrelate as if it were a solo server, without having information about the back-end infrastructure. 3. Linux Virtual Load Balancer: It is an opensource enhanced load balancing solution used to build extremely scalable and extremely available network services such as HTTP, POP3, FTP, SMTP, media and caching and Voice Over Internet Protocol (VoIP). It is simple and powerful product made for load balancing and fail-over. The load balancer itself is the primary entry point of server cluster systems and can execute Internet Protocol Virtual Server (IPVS), which implements transport-layer load balancing in the Linux kernel also known as Layer-4switching. 8.9 SUMMARY • Cloud Computing is an internet-based network technology that shared a rapid growth in the advances of communication technology by providing service to customers of various requirements with the aid of online computing resources. It has provisions of both hardware and software applications along with software development platforms and testing tools as resources. Such a resource delivery is accomplished with the help of services. While as the former comes under category of Infrastructure as a service (IaaS) cloud, the latter two comes under headings of Software as a service (SaaS) 157 CU IDOL SELF LEARNING MATERIAL (SLM)
cloud and platform as a service (PaaS) cloud respectively. The cloud computing is an on-demand network enabled computing model that share resources as services billed on pay-as-you-go (PAYG) plan. • Some of the giant players in given technology are Amazon, Microsoft, Google, SAP, Oracle, VMware, Sales force, IBM and others. Majority of these cloud providers are high- tech IT organizations. The cloud computing model is viewed under two different headings. The first one is the service delivery model, which defines the type of the service offered by a typical cloud provider. Based on this aspect, there are popularly following three important service models SaaS, PaaS and IaaS. The other aspect of cloud computing model is viewed on its scale of use, affiliation, ownership, size and access. • The official ‘National Institute of Standards and Technology’ (NIST) definition for cloud computing outlines four cloud deployment models. A cloud computing model is efficient if its resources are utilized in best possible way and such an efficient utilization can be achieved by employing and maintaining proper management of cloud resources. Resource management is achieved by adopting robust resource scheduling, allocation and powerful resource scalability techniques. These resource s are provided to customers in the form of Virtual Machines (VM) through a process known as virtualization that makes use of an entity (software, hardware or both) known as hypervisor. • The greatest advantage of cloud computing is that a single user physical machine is transformed into a multiuser virtual machine. The Cloud Service Provider (CSP) plays a crucial role in service delivery to users and is a complex task with given available virtual resources. 8.10 KEY WORDS/ABBREVIATIONS • Container – A container a virtualization instance in which the kernel of an operating system allows for multiple isolated user-space instances • Content Delivery Network (CDN) – A content delivery network (CDN) is a network of distributed services that deliver content to a user based on the user’s geographic proximity to servers. CDNs allow speedy content delivery for websites with high traffic volume or large geographic reach. 158 CU IDOL SELF LEARNING MATERIAL (SLM)
• Hypervisor – A hypervisor or virtual machine monitor (VMM) is a piece of software that allows physical devices to share their resources among virtual machines (VMs) running on top of that physical hardware. The hypervisor creates, runs and manages VMs. • Amazon Web Services (AWS) – Amazon Web Services is a suite of cloud computing services that make a comprehensive cloud platform offered by Amazon.com. • Customer Relationship Management (CRM) – Customer Relationship Management (CRM) applications allow a business to manage relationships with current and future customers by providing the business with tools to manage sales, customer service, and technical support roles. SaaS CRM applications, such as Salesforce.com, are very popular. 8.11 LEARNING ACTIVITY 1. Why virtualization is important aspects in Cloud Computing. ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ 2. Draw a framework to analyse the various virtualization Techniques ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ 8.12 UNIT END QUESTIONS (MCQ AND DESCRIPTIVE) A. Descriptive Questions 1. Explain virtualization. 2. Discuss Virtualization Techniques. 3. State the Pros and cons of Virtualization. 4. How do we perform the Virtual Machine provisioning? Explain. 5. Define Load Balancing. B. Multiple Choice Questions 159 CU IDOL SELF LEARNING MATERIAL (SLM)
1. Microsoft offers a________calculator for the Windows Azure Platform. a) TCO b) TOC c) OCT d) All of the mentioned 2. The connection between storage and Microsoft’s Content Delivery Network is stated to be at least_____ percent uptime. a) 90 b) 95 c) 99.9 d) None of the mentioned 3. Which of the following aims to deploy methods for measuring various aspects of cloud performance in a standard way? a) RIM b) SIM c) SMI d) All of the mentioned 4. Which of the following is not the feature of Network management systems? a) Accounting b) Security c) Performance d) None of the mentioned 5. ____ _______is a framework tool for managing cloud infrastructure. 160 a) IBM Tivoli Service Automation Manager b) Microsoft Tivoli Service Automation Manager c) Google Service Automation Manager d) Windows Live Hotmail CU IDOL SELF LEARNING MATERIAL (SLM)
Answer 1. a 2. c 3. c 4. d 5. a 8.13 REFERENCES • https://arpitapatel.files.wordpress.com/2014/10/cloud-computing-bible1.pdf • Mastering Cloud Computing by Rajkumar Buyya • https://ramslaw.files.wordpress.com/2016/07/0124114547cloud.pdfBuyya Rajkumar, Vecchiola Christian, ThamaraiSelvi S. (2013). Mastering Cloud Computing. New Delhi: Tata McGraw-Hill. • Jayaswal K., Kallakuruchi J., Houde D.J., Shah D. (2014). Cloud Computing: Black Book. New Delhi: Dreamtech Press. • Buyya Rajkumar, Broberg James, Goscinski A.M., Wile (Editors). (2011). Cloud Computing: Principles and Paradigm. NewJersey: John Willy & Sons Inc. • Microsoft Documents: https://docs.microsoft.com/en-us/azure/ • https://channel9.msdn.com/Azure • Gens, Frank. (2008-09-23) “Defining ‘Cloud Services’ and ‘Cloud Computing’,” IDC Exchange. Archived 2010-07-22 at the Way back Machine • Henderson, Tom and Allen, Brendan. (2010-12-20) “Private clouds: Not for the faint of heart”, Network World. • Whitehead, Richard. (2010-04-19) “A Guide to Managing Private Clouds,” Industry Perspectives. • Sullivan, Dan. (2011–02) “Hybrid cloud management tools and strategies,” SearchCloudComputing.com • \"Definition: Cloud management\", ITBusinessEdge/Webopedia • S. Garcia-Gomez; et al. (2012). \"Challenges for the comprehensive management of Cloud Services in a PaaS framework\". Scalable Computing: Practice and Experience. Scientific International Journal for Parallel and Distributed Computing. 13 (3): 201– 213. • \"A Guidance Framework for Selecting Cloud Management Platforms and Tools\". www.gartner.com. Retrieved 2018-11-26. 161 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 9: TRAFFIC MANAGER Structure 9.0. Learning Objectives 9.1. Introduction 9.2. Traffic Manager 9.3. Increase application availability 9.4. How clients connect using Traffic Manager 9.5. Benefits 9.6. Managing traffic between datacenters 9.7. Summary 9.8. Key Words/Abbreviations 9.9. Learning Activity 9.10. Unit End Questions (MCQ and Descriptive) 9.11.References 9.0 LEARNING OBJECTIVES At the end of the unit learner will able to understand and have knowledge of following aspects Traffic Manager: • Definition of Traffic Manager • Pros of traffic Manager • Connection with the help of Traffic Manager 9.1 INTRODUCTION Traffic Manager uses DNS to direct consumer requests to the foremost acceptable service end supported a traffic-routing technique and therefore the health of the endpoints. associate degree end is any Internet-facing service hosted within or outside of Azure. Traffic Manager provides a variety of traffic-routing ways and end observance choices to suit completely different application wants and automatic failover models. Traffic Manager is resilient to failure, together with the failure of a complete Azure region. 162 CU IDOL SELF LEARNING MATERIAL (SLM)
Azure Traffic Manager permits you to manage the distribution of traffic across your application endpoints. Associate degree end is any Internet-facing service hosted within or outside of Azure. Traffic Manager provides 2 key benefits: • Distribution of traffic per one amongst many traffic-routing ways • Continuous observance of end health and automatic failover once endpoints fail When a consumer tries to attach to a service, it should initial resolve the DNS name of the service to associate degree science address. The consumer then connects thereto science address to access the service. The most vital purpose to grasp is that Traffic Manager works at the DNS level. Traffic Manager uses DNS to direct shoppers to specific service endpoints supported the foundations of the traffic-routing technique. Shoppers hook up with the chosen end directly. Traffic Manager isn't a proxy or an entry. Traffic Manager doesn't see the traffic passing between the consumer and therefore the service. 9.2 TRAFFIC MANAGER Traffic manager operates at the DNS level it allows you to point your domain name to traffic manager with a CNAME record, and have traffic manager redirect the request the correct endpoint based on whatever mode you’re using. Traffic manager has three modes of operation, which are Priority, Weighted and Performance. Let’s run through each option. The priority option is better known as failover. It works by directing all requests t o a primary endpoint unless that endpoint is down, and then it directs to a secondary endpoint. It’s common to have a backup of an environment in case of failure. That’s where the priority method comes in handy. 163 CU IDOL SELF LEARNING MATERIAL (SLM)
The way it works is that you specify a list of endpoints in priority order, and traffic manager will send traffic to the highest priority endpoint that’s available. If you’re thinking about high availability, especially cross-region availability, this is a fantastic option. The next mode is weighted, which is similar to round robin in that the intent is to evenly distribute requests. So, requests are evenly distributed across the different endpoints at random, however the chance of any given endpoint being selected is based on weighted values that you define for each endpoint. If you want an even distribution, then assign equal weights to all the endpoints. Being able to change the weights gives a lot of flexibility! And it’s a great way to perform canary deployments, as well as application migrations. The final mode is performance mode, and this is where you have geographically separated endpoints, and traffic manager will select the best one per request based on latency. By having your endpoints cross region, and using performance-based routing you can ensure that your end-users are getting the best user experience possible, because they’ll be directed to the endpoint with the lowest latency, for them. This tends to be the “closest” endpoint, however it’s not a rule. Traffic Manager offers the following features: 9.3 INCREASE APPLICATION AVAILABILITY Traffic Manager delivers high availability for your critical applications by monitoring your endpoints and providing automatic failover when an endpoint goes down. Improve application performance Azure allows you to run cloud services or websites in datacentres located around the world. Traffic Manager improves application responsiveness by directing traffic to the endpoint with the lowest network latency for the client. Perform service maintenance without downtime You can perform planned maintenance operations on your applications without downtime. Traffic Manager can direct traffic to alternative endpoints while the maintenance is in progress. 164 CU IDOL SELF LEARNING MATERIAL (SLM)
Combine hybrid applications Traffic Manager supports external, non-Azure endpoints enabling it to be used with hybrid cloud and on-premises deployments, including the \"burst-to-cloud,\" \"migrate-to-cloud,\" and \"failover-to-cloud\" scenarios. Distribute traffic for complex deployments Using nested Traffic Manager Profiles, multiple traffic-routing methods can be combined to create sophisticated and flexible rules to scale to the needs of larger, more complex deployments. 9.4 HOW CLIENTS CONNECT USING TRAFFIC MANAGER Continuing from the previous example, when a client requests the page https://partners.contoso.com/login.aspx, the client performs the following steps to resolve the DNS name and establish a connection: Figure 9.1 clients connect using Traffic Manager 1. The client sends a DNS query to its configured recursive DNS service to resolve the name 'partners.contoso.com'. A recursive DNS service, sometimes called a 'local DNS' service, does not host DNS domains directly. Rather, the client off-loads the work of 165 CU IDOL SELF LEARNING MATERIAL (SLM)
contacting the various authoritative DNS services across the Internet needed to resolve a DNS name. 2. To resolve the DNS name, the recursive DNS service finds the name servers for the 'contoso.com' domain. It then contacts those name servers to request the 'partners.contoso.com' DNS record. The contoso.com DNS servers return the CNAME record that points to contoso.trafficmanager.net. 3. Next, the recursive DNS service finds the name servers for the 'trafficmanager.net' domain, which are provided by the Azure Traffic Manager service. It then sends a request for the 'contoso.trafficmanager.net' DNS record to those DNS servers. 4. The Traffic Manager name servers receive the request. They choose an endpoint based on: • The configured state of each endpoint (disabled endpoints are not returned) • The current health of each endpoint, as determined by the Traffic Manager Health checks. For more information, see Traffic Manager Endpoint Monitoring. • The chosen traffic-routing method. For more information, see Traffic Manager Routing Methods. 5. The chosen endpoint is returned as another DNS CNAME record. In this case, let us suppose contoso-eu.cloudapp.net is returned. 6. Next, the recursive DNS service finds the name servers for the 'cloudapp.net' domain. It contacts those name servers to request the 'contoso-eu.cloudapp.net' DNS record. A DNS 'A' record containing the IP address of the EU-based service endpoint is returned. 7. The recursive DNS service consolidates the results and returns a single DNS response to the client. 8. The client receives the DNS results and connects to the given IP address. The client connects to the application service endpoint directly, not through Traffic Manager. Since it is an HTTPS endpoint, the client performs the necessary SSL/TLS handshake, and then makes an HTTP GET request for the '/login.aspx' page. 166 CU IDOL SELF LEARNING MATERIAL (SLM)
The recursive DNS service caches the DNS responses it receives. The DNS resolver on the client device also caches the result. Caching enables subsequent DNS queries to be answered more quickly by using data from the cache rather than querying other name servers. The duration of the cache is determined by the 'time-to-live' (TTL) property of each DNS record. Shorter values result in faster cache expiry and thus more round-trips to the Traffic Manager Name servers. Longer values mean that it can take longer to direct traffic away from a failed endpoint. Traffic Manager allows you to configure the TTL used in Traffic Manager DNS responses to be as low as 0 seconds and as high as 2,147,483,647 seconds (the maximum range compliant with RFC-1035), enabling you to choose the value that best balances the needs of your application. 9.5 BENEFITS The Traffic Manager comes with many benefits for the user: • Increase Performance: Can increase the performance of your application that includes faster page loading and better user experience. This applies to the serving of users with the hosted service closest to them. • High Availability: You can use the Traffic Manager to improve application availability by enabling automatic customer traffic fail-over scenarios in the event of issues with one of your application instances. • No Downtime Required for Upgrade / Maintenance: Once you have configured the Traffic Manager, you don’t need downtime for application maintenance, patch purgation or completely new package deployment. • Quick Setup: It’s very easy to configure Azure Traffic Manager on Windows Azure portal. If you have already hosted your application on Windows Azure (a cloud service, Azure website), you can easily configure this Traffic Manager with a simple procedure (setting routing policy). 9.6 MANAGING TRAFFIC BETWEEN DATA CENTERS Datacentres give cost-efficient and versatile access to scalable cipher and storage resources necessary for today’s cloud computing wants. A typical datacentre is created from thousands 167 CU IDOL SELF LEARNING MATERIAL (SLM)
of servers connected with an outsized network and typically managed by one operator. to produce quality access to the range of applications and services hosted on datacentres and maximize performance, it deems necessary to use datacentre networks effectively and with efficiency. Datacentre traffic is commonly a mixture of many categories with totally different priorities and needs. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. to the present finish, custom transport protocols and traffic management techniques are developed to enhance datacentre network performance IV. DATACENTER control MANAGEMENT To enforce control, some level of coordination is required across the network components. In general, control will vary from totally distributed to utterly centralized. Here we tend to review the 3 main approaches utilized in the literature particularly distributed, centralized or hybrid. Table III provides a summary of control management schemes. A. Distributed Most congestion management schemes coordinate in an exceedingly distributed means because it is additional reliable and scalable. A distributed theme is also enforced as a part of the end-hosts, switches, or both. Some recent distributed control schemes styles that may be totally accomplished victimization end-hosts square measure sometimes most popular over ones that require changes within the default network functions or demand further options at the switches like custom priority queues, in-network rate negotiation and allocation complicated calculations in switches, or per flow state data. End- host implementations square measure sometimes additional scalable since each server handles its own traffic. Therefore, standard transport protocols deem this sort of implementation like. Some samples of this approach embrace RCP [Expedites, and Racks. RCP and PDQ perform in-network rate allocation and assignment by permitting switches and end-hosts to speak victimization custom headers, CONGA gets facilitate from switches to perform flow let primarily based load reconciliation in leaf-spine topologies, Expedites performs flow primarily based load reconciliation by implementing custom Layer a pair of headers and localized observation of congestion at the switches, and Racks uses Tour switches as suggests that to share congestion data among several flows between identical supply and destination racks to assist them converge quicker to correct transmission rates. To implement advanced in-network options, changes to the network components can be necessary and switches might have to try to further computations or support new options. 168 CU IDOL SELF LEARNING MATERIAL (SLM)
B. Centralized In centralized schemes a central unit coordinates transmission within the network to avoid congestion. The central unit has access to a world read of configuration and resources, state data of switches, and end-host demands. These embrace flow sizes, deadlines and priorities still as queuing standing of switches and link capacities. computer hardware will proactively apportion resources temporally and spatially (several slots of your time and totally different links) and arrange transmissions in an exceedingly means that optimizes the performance and minimizes contentions. To more increase performance, this entity will translate the planning downside into associate degree improvement downside with resource constraints the answer to which might be approximated victimization quick heuristics. for big networks, computer hardware effectiveness depends on its process capability and communication latency to end-hosts. TDMA, Fantasied Flow Tune square measure samples of a centrally coordinated network. TDMA divides timeline into rounds throughout that it collects end-host demands. every spherical is split into fastened sized slots throughout that hosts will communicate in an exceedingly contention-less manner C. Hybrid employing a hybrid system might give the responsibleness and measurability of distributed management and performance gains obtained from world network management. A general hybrid approach is to own distributed management that's power-assisted by centrally calculated parameters. samples of this approach embrace OTCP lying rosid dicot genus and driver. OTCP uses a central controller to watch and collect measurements on link latencies and their queuing extent victimization ways provided by package outlined Networking (SDN) 9.7 SUMMARY • Microsoft Azure Traffic Manager allows users to manage the user traffic distribution of various service endpoints that are located in data centres around the world. The service endpoints, which are supported by the Azure Traffic Manager, incorporate cloud services, Web Apps, and Azure VMs. • Users can use the Azure Traffic Manager, as well as the non-Azure external endpoints as well. AZURE Traffic Manager utilizes the DNS (Domain Name System) in order to direct the client requests through the most suitable endpoint by applying the traffic- routing method. • The Traffic Manager offers several endpoint monitoring alternatives and traffic- routing methodologies to suit unique application requirements with auto-failover 169 CU IDOL SELF LEARNING MATERIAL (SLM)
models. Azure Traffic Manager is robust and resilient to failures, which also includes the failures of the whole Azure region. 9.8 KEY WORDS/ABBREVIATIONS • Vertical Cloud – A vertical cloud is a cloud computing solution that is built or optimized for a specific business vertical such as manufacturing, financial services, or healthcare. • Virtual Desktop Infrastructure (VDI) – Virtual desktop infrastructure (VDI) is a desktop operating system hosted within a virtual machine. • Shared Resources – Shared Resources, also known as network resources, are computing resources that can be accessed remotely through a network, such as a Local Area Network (LAN) or the internet. • On-Premise – On Premise technology is software or infrastructure that is run on computers on the premises (in the building) of the person or organization using the software or infrastructure. • Open Source – Open Source is a development model in which a product’s source code is made openly available to the public. Open source products promote collaborative community development and rapid prototyping. 9.9 LEARNING ACTIVITY 1. How Traffic is managed between data centres? ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ 2. Discuss how Data centre play important role in managing Data. ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ 9.10 UNIT END QUESTIONS (MCQ AND DESCRIPTIVE) A. Descriptive Questions 170 CU IDOL SELF LEARNING MATERIAL (SLM)
1. Explain, how client connects using Traffic Manager? 2. Discuss Traffic Manager. 3. Outline benefits of Azure Traffic Manager. 4. Describe how Azure Traffic Manager helps managing traffic between datacentres. B. Multiple Choice Questions 1. Which of the following “cloudily” characteristics that cloud management service must have? a) Billing is on a pay-as-you-go basis b) The management service is extremely scalable c) The management service is ubiquitous d) All of the mentioned 2. How many categories need to be monitored for entire cloud computing? a) 1 b) 2 c) 4 d) 6 3. Which of the following is a standard protocol for network monitoring and discovery? a) SNMP b) CMDB c) WMI d) All of the mentioned 4. Which of the following service provider provides the least amount of built in security? a) SaaS b) PaaS c) IaaS d) All of the mentioned 171 CU IDOL SELF LEARNING MATERIAL (SLM)
5. Which of the following services that need to be negotiated in Service Level Agreements? a) Logging b) Auditing c) Regulatory compliance d) All of the mentioned Answer 1. d 2. d 3. d 4. c 5. d 9.11 REFERENCES • Buyya Rajkumar, Vecchiola Christian, ThamaraiSelvi S. (2013). Mastering Cloud Computing. New Delhi: Tata McGraw-Hill. • Jayaswal K., Kallakuruchi J., Houde D.J., Shah D. (2014). Cloud Computing: Black Book. New Delhi: Dreamtech Press. • Buyya Rajkumar, Broberg James, Goscinski A.M., Wile (Editors). (2011). Cloud Computing: Principles and Paradigm. New Jersey: John Willy & Sons Inc. • Microsoft Documents: https://docs.microsoft.com/en-us/azure/ • https://channel9.msdn.com/Azure • Linthicum, David. (2011-04-27) “How to integrate with the cloud”, InfoWorld: Cloud Computing, April 27, 2011. • Semple, Bryan. (2011-07-14) “Five Capacity Management Challenges for Private Clouds,” Cloud Computing Journal. • Magalhaes, Deborah et al. (2015-09-19) “Workload modelling for resource usage analysis and simulation in cloud computing,” Computers & Electrical Engineering • Golden, Barnard. (2010-11-05) “Cloud Computing: Why You Can't Ignore Chargeback,” CIO.com. • Rigsby, Josette. (2011-08-30) “IBM Offers New Hybrid Cloud Solution Using Cast Iron, Tivoli,” CMS Wire. • Mike Edwards, Pritam Gawade, John Leung, Bill McDonald, Karolyn Schalk, Karl Scott, Bill Van Order, Steven Woodward (2017). \"Practical Guide to Cloud Management Platforms\". Cloud Standards Customer Council. • Fellows, William (June 2018). \"451 Research Cloud Management Market Map\". 451 Research Report Excerpt. 172 CU IDOL SELF LEARNING MATERIAL (SLM)
• \"Cloud Computing\". www.gartner.com. Retrieved 28 May 2015. • Gamal, Selim; Rowayda A. Sadek; Hend Taha (January 2014). \"An Efficient Cloud Service Broker Algorithm\". International Journal of Advancements in Computing Technology. 6 173 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 10: DATA MANAGEMENT Structure 10.0.Learning Objectives 10.1.Introduction 10.2.Data management strategy in cloud computing 10.3.Challenges with data 10.4. Data centers 10.5. Storage of data and databases 10.6. Data Privacy and Security Issues at different level. 10.7.Summary 10.8.Key Words/Abbreviations 10.9.Learning Activity 10.10. Unit End Questions (MCQ and Descriptive) 10.11. References 10.0 LEARNING OBJECTIVES At the end of the unit learner will able to learn and have knowledge of following aspects Data Management: • Learning of Data Management • Introduction to Data Centres • Security Issues at Data Management • Knowledge of Storage of Data Base 10.1 INTRODUCTION Traffic Manager uses DNS to direct consumer requests to the foremost acceptable service end supported a traffic-routing technique and therefore the health of the endpoints. associate degree end is any Internet-facing service hosted within or outside of Azure. Traffic Manager provides a variety of traffic-routing ways and end observance choices to suit completely different application wants and automatic failover models. Traffic Manager is resilient to failure, together with the failure of a complete Azure region. 174 CU IDOL SELF LEARNING MATERIAL (SLM)
Azure Traffic Manager permits you to manage the distribution of traffic across your application endpoints. associate degree end is any Internet-facing service hosted within or outside of Azure. Traffic Manager provides 2 key benefits: • Distribution of traffic per one amongst many traffic-routing ways • Continuous observance of end health and automatic failover once endpoints fail When a consumer tries to attach to a service, it should initial resolve the DNS name of the service to associate degree science address. The consumer then connects thereto science address to access the service. The most vital purpose to grasp is that Traffic Manager works at the DNS level. Traffic Manager uses DNS to direct shoppers to specific service endpoints supported the foundations of the traffic-routing technique. shoppers hook up with the chosen end directly. Traffic Manager isn't a proxy or an entry. Traffic Manager doesn't see the traffic passing between the consumer and therefore the service 10.2 DATA MANAGEMENT STRATEGY IN CLOUD COMPUTING Data migration to the cloud is the real deal that requires a holistic approach. This process is oftentimes hard. Therefore, it is the primary objectives of your business that should dictate your strategy in the first place. Positive changes are incremental and no miracle will happen once you start, not to mention the fact that data management is continuous and must be constantly monitored after the strategic planning is done. Figure 10.1 Data management strategy in cloud computing 175 CU IDOL SELF LEARNING MATERIAL (SLM)
One of the most undesirable effects of the wrong data management strategy that everybody stands a hazard to experience is a substantial increase in costs. Due to the growing complexity of cloud-driven environments, enterprises expenditures can be unreasonably high. Nonetheless, you can control a budgeting process and do not have to spend as much as one used to when there was a need for costly servers and systems. Accordingly, developing an effective strategy to minimize the number of obstacles you might face by considering its key elements is critical for you. These aspects are the following: 1. A systematic approach to data security. Overcoming and preventing security challenges should be a data management system’s primary concern. Firewalls, data encryption, and data exposure are some possible protective measures. More stringent control is needed for ensuring security in the cloud. Thus, data governance must be standardized within your enterprise for your data to be secured at rest, in flight or when going outside the production environment. Make sure you have considered and employed all possible security cloud services that can help you detect and respond to threats and actual leakages. Then, it will be easier to comply with existing data management policies. 2. Tiers optimization for specific workloads. Tiering is, in the first place, meant to add efficiency to your data management strategy, derive value from and add value to your data. With the tiered storage, frequently accessed objects will be stored in higher-performing storage pools while the more rarely accessed data objects whose volume is bigger will be stored in larger-capacity storage pools. Besides, your data will be structured, which means lower latency. 3. Flexibility in managing multi-structured data. Multi-structured data make up separate sets of data managed and stored in multiple formats. So, it is easy to overspend on storage and analytics. Nevertheless, it is the unified data management that affords flexibility, operational and cost efficiency in your cloud data analytics. 176 CU IDOL SELF LEARNING MATERIAL (SLM)
10.3 CLOUD DATA MANAGEMENT MISTAKES TO AVOID Now that we have highlighted three pillars that your data migration strategy must rest upon, it is time to define data management challenges in cloud computing and the potential risk factors that may hinder your efforts. Figure 10.2 Cloud data management mistakes to avoid 1. No corporate policy. Any strategic initiative, especially the one that is process-centric, has to comply with the corresponding policies and standards. Essentially, data management is the tactical execution thereof and a good idea here is to consolidate as many entities as possible into one system. Then, one will not only be able to manage data at lower costs but will also do it more securely. Data that is kept separately and managed in several different ways within one organization can be easy to access and control can be provided at the insufficient quality. Centralized and consistent policies will result in making more right decisions and fewer mistakes. 2. Moving all your data to the cloud. Despite all those great things about cloud computing, enterprises should never forget about the local file servers, domain controllers and the value they add to your solution. Data -driven decisions can still be made without driving all you have to the cloud. First, one has to think over what information can stay in an on-premise server and what should go to a cloud server for further processing. 3. Limited structure. 177 CU IDOL SELF LEARNING MATERIAL (SLM)
Data must be structured. When it is organized, it is accessible and you do not have to waste your time on searching. Thus, proper classification and strict formats for document names are essential. 10.4 BEST PRACTICES FOR DATA MANAGEMENT IN CLOUD COMPUTING If there are core principles that lay the foundation for the strategic management of data in the cloud and certain pitfalls to avoid, then there must be methods and techniques that are, if compared with the traditional ones, aimed at the operational excellence and overall improvement of your experience. Figure 10.3 Best practices for data management in cloud computing 1. Ensure a sophisticated infrastructure. Everything will work smoothly and efficiently if there is a possibility to choose whether you want to move data to on-prem storages, to the cloud, or across different clouds. The cloud is not the only destination of a mass data migration. The structure has to be sophisticated yet this whole system should have centralized management. 2. Choose your cloud data management platform. Platforms like this are used for control, monitoring and other relevant cloud activities. Modern enterprises tend to constantly change their IT environments by making them larger and more complex. If you do provide such an infrastructure managing different types of data across various cloud computing services and local servers, then selecting a single platform is highly recommended. This platform approach will help you maintain a certain level of consistency and reduce bottlenecks. Besides you can opt for a platform that is native, cloud provider-specific, or available from a third-party vendor. 178 CU IDOL SELF LEARNING MATERIAL (SLM)
3. Leverage the Cloud Data Management Interface. It is a generally accepted standard of interface’s functioning which allows enterprises to manage data elements increasing the system’s interoperability. Accommodation of requirements from multiple vendors instead of using the storage system with a unique interface might be challenging, so the deployment of CDMI compatible systems is the right thing to do. 4. Create a framework for cloud management first. Before moving data to the cloud, make sure there is a solid framework. Upon having one established, it will be easier for an enterprise to say how to best manage its cloud resources. Migration of systems to more capable platforms is a natural process, but it has to be a conscious and informed decision. 10.5 CHALLENGES WITH DATA Challenge 1: DDoS attacks As more and more businesses and operations move to the cloud, cloud providers are becoming a bigger target for malicious attacks. Distributed denial of service (DDoS) attacks is more common than ever before. Verisign reported IT services, cloud and SaaS was the most frequently targeted industry during the first quarter of 2015. A DDoS attack is designed to overwhelm website servers so it can no longer respond to legitimate user requests. If a DDoS attack is successful, it renders a website useless for hours, or even days. This can result in a loss of revenue, customer trust and brand authority. Complementing cloud services with DDoS protection is no longer just good idea for the enterprise; it’s a necessity. Websites and web-based applications are core components of 21st century business and require state-of-the-art security. Challenge 2: Data breaches Known data breaches in the U.S. hit a record-high of 738 in 2014, according to the Identity Theft Research Centre, and hacking was (by far) the number one cause. That’s an incredible statistic and only emphasizes the growing challenge to secure sensitive data. Traditionally, IT professionals have had great control over the network infrastructure and physical hardware (firewalls, etc.) securing proprietary data. In the cloud (in private, public 179 CU IDOL SELF LEARNING MATERIAL (SLM)
and hybrid scenarios), some of those controls are relinquished to a trusted partner. Choosing the right vendor, with a strong record of security, is vital to overcoming this challenge. Challenge 3: Data loss When business critical information is moved into the cloud, it’s understandable to be concerned with its security. Losing data from the cloud, either though accidental deletion, malicious tampering (i.e. DDoS) or an act of nature brings down a cloud service provider, could be disastrous for an enterprise business. Often a DDoS attack is only a diversion for a greater threat, such as an attempt to steal or delete data. To face this challenge, it’s imperative to ensure there is a disaster recovery process in place, as well as an integrated system to mitigate malicious attacks. In addition, protecting every network layer, including the application layer (layer 7), should be built-in to a cloud security solution. Challenge 4: Insecure access points One of the great benefits of the cloud is it can be accessed from anywhere and from any device. But what if the interfaces and APIs users interact with aren’t secure? Hackers can find these types of vulnerabilities and exploit them. A behavioural web application firewall examines HTTP requests to a website to ensure it is legitimate traffic. This always-on device helps protect web applications from security breaches. Challenge 5: Notifications and alerts Awareness and proper communication of security threats is a cornerstone of network security and the same goes for cloud security. Alerting the appropriate website or application managers as soon as a threat is identified should be part of a thorough security plan. Speedy mitigation of a threat relies on clear and prompt communication so steps can be taken by the proper entities and impact of the threat minimized. Final Thoughts 180 CU IDOL SELF LEARNING MATERIAL (SLM)
Cloud security challenges are not insurmountable. With the right partners, technology and forethought, enterprises can leverage the benefits of cloud technology. 10.6 DATA CENTERS Data centers are simply centralized locations where computing and networking equipment is concentrated for the purpose of collecting, storing, processing, distributing or allowing access to large amounts of data. They have existed in one form or another since the advent of computers. In the days of the room-sized behemoths that were our early computers, a data center might have had one supercomputer. As equipment got smaller and cheaper, and data processing needs began to increase -- and they have increased exponentially -- we started networking multiple servers (the industrial counterparts to our home computers) together to increase processing power. We connect them to communication networks so that people can access them, or the information on them, remotely. Large numbers of these clustered servers and related equipment can be housed in a room, an entire building or groups of buildings. Today's data center is likely to have thousands of very powerful and very small servers running 24/7. Because of their high concentrations of servers, often stacked in racks that are placed in rows, data centers are sometimes referred to a server farm. They provide important services such as data storage, backup and recovery, data management and networking. These centers can store and serve up Web sites, run e-mail and instant messaging (IM) services, provide cloud storage and applications, enable e-commerce transactions, power online gaming communities and do a host of other things that require the wholesale crunching of zeroes and ones. Just about every business and government entity either needs its own data center or needs access to someone else's. Some build and maintain them in-house, some rent servers at co- location facilities (also called colos) and some use public cloud-based services at hosts like Amazon, Microsoft, Sony and Google. The colos and the other huge data centers began to spring up in the late 1990s and early 2000s, sometime after Internet usage went mainstream. The data centers of some large companies are spaced all over the planet to serve the constant need for access to massive 181 CU IDOL SELF LEARNING MATERIAL (SLM)
amounts of information. There are reportedly more than 3 million data centers of various shapes and sizes in the world today Why do we need data centres? The idea that cloud computing means data isn’t stored on computer hardware isn’t accurate. Your data may not be on your local machine, but it has to be housed on physical drives somewhere -- in a data centre. The idea that cloud computing means data isn’t stored on computer hardware isn’t accurate. Your data may not be on your local machine, but it has to be housed on physical drives somewhere -- in a data centre. Despite the fact that hardware is constantly getting smaller, faster and more powerful, we are an increasingly data-hungry species, and the demand for processing power, storage space and information in general is growing and constantly threatening to outstrip companies' abilities to deliver. Any entity that generates or uses data has the need for data centres on some level, including government agencies, educational bodies, telecommunications companies, financial institutions, retailers of all sizes, and the purveyors of online information and social networking services such as Google and Facebook. Lack of fast and reliable access to data can mean an inability to provide vital services or loss of customer satisfaction and revenue. A study by International Data Corporation for EMC estimated that 1.8 trillion gigabytes (GB), or around 1.8 zettabytes (ZB), of digital information was created in 2011 [sources: Glanz, EMC, Phneah]. The amount of data in 2012 was approximately 2.8 ZB and is expected to rise to 40 ZB by the year 2020 [sources: Courtney, Digital Science Series, EMC]. All of this media has to be stored somewhere. And these days, more and more things are also moving into the cloud, meaning that rather than running or storing them on our own home or work computers, we are accessing them via the host servers of cloud providers. Many companies are also moving their professional applications to cloud services to cut back on the cost of running their own centralized computing networks and servers. The cloud doesn't mean that the applications and data are not housed on computing hardware. It just means that someone else maintains the hardware and software at remote locations 182 CU IDOL SELF LEARNING MATERIAL (SLM)
where the clients and their customers can access them via the Internet. And those locations are data centres. 10.7 STORAGE OF DATA AND DATABASES A cloud database is a database that typically runs on a cloud computing platform, and access to the database is provided as-a-service. Database services take care of scalability and high availability of the database. Database services make the underlying software-stack transparent to the user There are two primary methods to run a database in a cloud: Virtual machine image Cloud platforms allow users to purchase virtual-machine instances for a limited time, and one can run a database on such virtual machines. Users can either upload their own machine image with a database installed on it, or use ready-made machine images that already include an optimized installation of a database. Database-as-a-service (DBaaS) With a database as a service model, application owners do not have to install and maintain the database themselves. Instead, the database service provider takes responsibility for installing and maintaining the database, and application owners are charged according to their usage of the service. This is a type of SaaS - Software asa Service. Architecture and common characteristics Most database services offer web-based consoles, which the end user can use to provision and configure database instances. Database services consist of a database-manager component, which controls the underlying database instances using a service API. The service API is exposed to the end user, and permits users to perform maintenance and scaling operations on their database instances. Underlying software-stack stack typically includes the operating system, the database and third-party software used to manage the database. The service provider is responsible for 183 CU IDOL SELF LEARNING MATERIAL (SLM)
installing, patching and updating the underlying software stack and ensuring the overall health and performance of the database. Scalability features differ between vendors – some offer auto-scaling, others enable the user to scale up using an API, but do not scale automatically. There is typically a commitment for a certain level of high availability (e.g. 99.9% or 99.99%). This is achieved by replicating data and failing instances over to other database instances. Data model The design and development of typical systems utilize data management and relational databases as their key building blocks. Advanced queries expressed in SQL work well with the strict relationships that are imposed on information by relational databases. However, relational database technology was not initially designed or developed for use over distributed systems. This issue has been addressed with the addition of clustering enhancements to the relational databases, although some basic tasks require complex and expensive protocols, such as with data synchronization. Modern relational databases have shown poor performance on data-intensive systems; therefore, the idea of NoSQL has been utilized within database management systems for cloud-based systems. Within NoSQL implemented storage, there are no requirements for fixed table schemas, and the use of join operations is avoided. \"The NoSQL databases have proven to provide efficient horizontal scalability, good performance, and ease of assembly into cloud applications. “Data models relying on simplified relay algorithms have also been employed in data-intensive cloud mapping applications unique to virtual frameworks. It is also important to differentiate between cloud databases which are relational as oppo sed to non-relational or NoSQL. SQL databases Are one type of database which can run in the cloud, either in a virtual machine or as a service, depending on the vendor. While SQL databases are easily vertically scalable, 184 CU IDOL SELF LEARNING MATERIAL (SLM)
horizontal scalability poses a challenge, that cloud database services based on SQL have started to address. NoSQL databases are another type of database which can run in the cloud. NoSQL databases are built to service heavy read/write loads and can scale up and down easily, and therefore they are more natively suited to running in the cloud. However, most contemporary applications are built around an SQL data model, so working with NoSQL databases often requires a complete rewrite of application code. Some SQL databases have developed NoSQL capabilities including JSON, binary JSON (e.g. BSON or similar variants), and key-value store data types. A multi-model database with relational and non-relational capabilities provides a standard SQL interface to users and applications and thus facilitates the usage of such databases for contemporary applications built around an SQL data model. Native multi-model databases support multiple data models with one core and a unified query language to access all data models. 10.8 DATA PRIVACY AND SECURITY ISSUES AT DIFFERENT LEVEL. With the increase in data volumes, data handling has become the talk of the town. As companies begin to move to the cloud, there is a higher emphasis ensuring everything is safe and secure, and that there is no risk of data hacking or breaches. Since the cloud allows people to work without hardware and software investments, users can gain flexibility and data agility. However, since the Cloud is often shared between a lot of users, security becomes an immediate concern for Cloud owners. Security Issues Within the Cloud Cloud vendors provide a layer of security to user’s data. However, it is still not enough since the confidentiality of data can often be at risk. There are various types of attacks, which range from password guessing attacks and man-in-the-middle attacks to insider attacks, shoulder surfing attacks, and phishing attacks. Here is a list of the security challenges which are present within the cloud: 185 CU IDOL SELF LEARNING MATERIAL (SLM)
Data Protection and Misuse: When different organizations use the cloud to store their data, there is often a risk of data misuse. To avoid this risk, there is an imminent need to secure the data repositories. To achieve this task, one can use authentication and restrict access control for the cloud’s data. Locality: Within the cloud world, data is often distributed over a series of regions; it is quite challenging to find the exact location of the data storage. However, as data is moved from one country to another, the rules governing the data storage also change; this brings compliance issues and data privacy laws into the picture, which pertain to the storage of data within the cloud. As a cloud service provider, the service provider has to inform the users of their data storage laws, and the exact location of the data storage server. Integrity: The system needs to be rigged in such a manner so to provide security and access restrictions. In other words, data access should lie with authorized personnel only. In a cloud environment, data integrity should be maintained at all times to avoid any inherent data loss. Apart from restricting access, the permissions to make changes to the data should be limited to specific people, so that there is no widespread access problem at a later stage. Access: Data security policies concerning the access and control of data are essential in the long run. Authorized data owners are required to give part access to individuals so that everyone gets only the required access for parts of the data stored within the data mart. By controlling and restricting access, there is a lot of control and data security which can be levied to ensure maximums security for the stored data. Confidentiality: There is a lot of sensitive data which might be stored in the cloud. This data has to have extra layers of security on it to reduce the chances of breaches and phishing attacks; this can be done by the service provider, as well as the organization. However, as a precaution, data confidentiality should be of utmost priority for sensitive material. Breaches: Breaches within the cloud are not unheard. Hackers can breach security parameters within the cloud, and steal the data which might otherwise be considered confidential for organizations. On the contrary, a breach can be an internal attack, so organizations need to lay particular emphasis in tracking employee actions to avoid any unwanted attacks on stored data. 186 CU IDOL SELF LEARNING MATERIAL (SLM)
Storage: For organizations, the data is being stored and made available virtually. However, for service providers, it is necessary to store the data in physical infrastructures, which makes the data vulnerable and conducive to physical attacks. These are some of the security issues which come as a part of the cloud environment. However, these are not exactly difficult to overcome, especially with the available levels of technological resources these days. There is a lot of emphasis on ensuring maximum security for the stored data so that it complies with the rules and regulations, as well as the organization’s internal compliance policies. 10.9 SUMMARY Data is born around us to evolve every second. This process promises the ability to return anywhere, anytime but the information must also be protected properly with the help of the right data management solution. Some people may experience difficulties in deciding how to start working in the cloud or fail to recognize those promised benefits while on their way. Although the cloud does not come with an instruction manual, it can work for you and your business, anyway. All you need is to have your data managed well. Businesses used to have centralized on-premise data warehouses where information was safe. Yet, as time went by, it became harder to maintain them; highly skilled manpower and greater maintenance fees are needed now. So, now, in our cloud age, when people are willing to access their data easily, an innovative management solution is what can help extract the full value of data to put it to good use. Management methods applied to data that is stored in the cloud differ from the traditional ones since cloud data analytics has to meet the requirements of enhanced cloud data security and integrity. Data management has been rapidly evolving from outdated, locally-hosted storage systems to a much more versatile and reliable cloud data management module. Although local data storage was the industry standard for some time, this preference is changing as businesses become aware of new developments in cloud storage technology. Over the next few years, more and more companies will migrate to the cloud as their preferred method of data management. Data will play an increasingly important role in the ability of organizations to stay competitive in their respective fields. This projection further 187 CU IDOL SELF LEARNING MATERIAL (SLM)
emphasizes the need to achieve and maintain an efficient data management structure that will allow a company to keep pace with a fast-paced and constantly evolving business landscape. 10.10 KEY WORDS/ABBREVIATIONS • Multi-Cloud – A multi-cloud strategy is the concurrent use of separate cloud service providers for different infrastructure, platform, or software needs. • Multi-Tenancy – Multi-Tenancy is a mode of operation for software in which multiple instances of one or many applications run in a shared environment • Micro services – is a way of designing applications in which complex applications are built out of a suite of small, independently deployable services • Linux – Linux is an open-source operating system, built on Unix that is used for the majority of cloud services. • Load Balancing – The process of distributing computing workloads across multiple resources, such as servers. 10.11 LEARNING ACTIVITY 1. Discuss various challenged faced to secure the data. ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ 2. Draw a list of different threats to Data in Network. ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ ___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ 10.12 UNIT END QUESTIONS (MCQ AND DESCRIPTIVE) A. Descriptive Questions 1. What is Datacentre? 2. Explain the challenges faced to manage data. 3. Discuss the Storage of data and databases. 4. Outline various Data Privacy and Security Issues in cloud computing. 188 CU IDOL SELF LEARNING MATERIAL (SLM)
B. Multiple Choice Questions 1. Which of the following area of cloud computing is uniquely troublesome? a) Auditing b) Data integrity c) e-Discovery for legal compliance d) All of the mentioned 2. Which of the following is the operational domain of CSA? a) Scalability b) Portability and interoperability c) Flexibility d) None of the mentioned 3. Which of the following is considered an essential element in cloud computing by CSA? a) Multi-tenancy b) Identity and access management c) Virtualization d) All of the mentioned 4. Which of the following is used for Web performance management and load testing? a) VMware Hyperic b) Webmetrics c) Univa UD d) Tapinsystems 5. Which of the following is application and infrastructure management software for hybrid multi-clouds? a) VMware Hyperic b) Webmetrics c) Univa UD 189 CU IDOL SELF LEARNING MATERIAL (SLM)
d) Tapinsystems Answer 1. d 2. b 3. a 4. b 5. c 10.13 REFERENCES • Buyya Rajkumar, Vecchiola Christian, ThamaraiSelvi S. (2013). Mastering Cloud Computing. New Delhi: Tata McGraw-Hill. • Jayaswal K., Kallakuruchi J., Houde D.J., Shah D. (2014). Cloud Computing: Black Book. New Delhi: Dreamtech Press. • Buyya Rajkumar, Broberg James, Goscinski A.M., Wile (Editors). (2011). Cloud Computing: Principles and Paradigm. New Jersey: John Willy & Sons Inc. • Microsoft Documents: https://docs.microsoft.com/en-us/azure/ • https://channel9.msdn.com/Azure • Hamlen, K. Kantarcioglu, M. Khan, L. Thuraisingham, B. (2010). Security Issues for Cloud Computing. International Journal of Information Security and Privacy, 4(2), 36-48. • Levina, N., and Vaast, E. (2005). The emergence of boundary spanning competence in practice: Implications for implementation and use of information systems. MIS Quarterly, 29(2), 335–363. • Ravishankar, M.N.; Pan, S.L.; and Leisner, D.E. (2011). Examining the strategic alignment and implementation success of a KMS: A subculture-based multilevel analysis. Information Systems Research, 22(1), 39–59. • Tiwana, A (2012), Novelty-knowledge alignment: A theory of design convergence in systems development. Journal of Management Information Systems, 29(1) 15–52. • RizwanMian, Patrick Martin (2012). Executing data-intensive workloads in a Cloud.ACM International Symposium on Cluster 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. • Yingjie Shi, XiaofengMeng, Jing Zhao, Xiangmei Hu, Bingbing Liu and HaipingWang (2010). Benchmarking Cloud-based Data Management Systems.CloudDB’10, Toronto, Ontario, Canada. ACM 978-1-4503-0380-4/10/10 190 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 11: CLOUD STORAGE Structure 11.0.Learning Objectives 11.1.Introduction 11.2.Cloud storage 11.3.Storage account 11.4.Storage Replications: LRS, ZRS, GRS, RAGRS 11.5.Types of storage: blob, file, table, queue. 11.6. Summary 11.7. Key Words/Abbreviations 11.8.Learning Activity 11.9. Unit End Questions (MCQ and Descriptive) 11.10. References 11.0 LEARNING OBJECTIVES At the end of the unit learner will able to learn and have knowledge of following aspects Cloud Storage and Storage Account: • Definition of Cloud Storage • Introduction to Storage Account • Knowledge of Storage Replications • Life cycle of Virtual Machine 11.1 INTRODUCTION Cloud storage relies on extremely virtualized infrastructure and is like broader cloud computing in terms of accessible interfaces, near-instant physical property and measurability, multi-tenancy, and metered resources. Cloud storage services will be utilised from associate off-premises service (Amazon S3) or deployed on-premises (ViON capability Services). Cloud storage usually refers to a hosted object storage service, however the term has broadened to incorporate alternative styles of knowledge storage that square measure currently offered as a service, like block storage. 191 CU IDOL SELF LEARNING MATERIAL (SLM)
Object storage services like Amazon S3, Oracle Cloud Storage and Microsoft Azure Storage, object storage package like Openstack Swift, object storage systems like EMC Atmos, EMC ECS and Hitachi Content Platform, and distributed storage analysis comes like OceanStore and VISION Cloud square measure all samples of storage which will be hosted and deployed with cloud storage characteristics. Cloud storage is: • Made up of many distributed resources, but still acts as one, either in a federated or a cooperative storage cloud architecture • Highly fault tolerant through redundancy and distribution of data • Highly durable through the creation of versioned copies • Typically, eventually consistent with regard to data replicas 11.2 CLOUD STORAGE Cloud storage is a cloud computing model that stores data on the Internet through a cloud computing provider who manages and operates data storage as a service. It’s delivered on demand with just-in-time capacity and costs, and eliminates buying and managing your own data storage infrastructure. This gives you agility, global scale and durability, with “anytime, anywhere” data access. Cloud storage is a model of computer data storage in which the digital data is stored in logical pools, said to be on \"the cloud\". The physical storage spans multiple servers (sometimes in multiple locations), and the physical environment is typically owned and managed by a hosting company. These cloud storage providers are responsible for keeping the data available and accessible, and the physical environment protected and running. People and organizations buy or lease storage capacity from the providers to store user, organization, or application data. Cloud storage services may be accessed through a collocated cloud computing service, a web service application programming interface (API) or by applications that utilize the API, such as cloud desktop storage, a cloud storage gateway or Web-based content management systems. 192 CU IDOL SELF LEARNING MATERIAL (SLM)
Cloud storage is purchased from a third-party cloud vendor who owns and operates data storage capacity and delivers it over the Internet in a pay-as-you-go model. These cloud storage vendors manage capacity, security and durability to make data accessible to your applications all around the world. Applications access cloud storage through traditional storage protocols or directly via an API. Many vendors offer complementary services designed to help collect, manage, secure and analyse data at massive scale. 11.3 STORAGE ACCOUNT An Azure storage account contains all of your Azure Storage data objects: blobs, files, queues, tables, and disks. The storage account provides a unique namespace for your Azure Storage data that is accessible from anywhere in the world over HTTP or HTTPS. Data in your Azure storage account is durable and highly available, secure, and massively scalable. Azure Storage features These features apply to all Azure Storage offerings: Durability Azure Storage data is replicated multiple times across regions. There are four ways you can make sure data is stored redundantly: Locally Redundant Storage (LRS), Zone-Redundant Storage (ZNS), Geo-redundant Storage (GRS), and Read Access Geo-Redundant Storage (RA-GRS). Using LRS, three copies of all data are maintained in a single facility within a single region. With ZRS, three copies of your data will be stored in multiple facilities of two or three regions. Obviously, this will achieve greater durability than LRS. For GRS, six copies of data are stored across two regions, with three copies in a so-called primary region, and the rest in a secondary region, usually geographically distant from your primary region. In case of primary region failure, the secondary region is used as part of a fail-over mechanism. RA- GRS data will be stored just like GRS, except that you get read-only access to the secondary region. 193 CU IDOL SELF LEARNING MATERIAL (SLM)
Geo-redundant Storage (GRS) and Read Access Geo-Redundant Storage (RA-GRS) provide the highest level of durability, but at a higher cost. GRS is the default storage redundancy mode. In case you need to switch from LRS to GRS or to RA-GRS, an additional one-time data transfer cost will be applied. But if you chose ZRS, you cannot subsequently change to any other redundancy mode. High Availability With such durable features, storage services will automatically be highly available. If you chose GRS or RA-GRS, your data collocated will be replicated in multiple facilities across multiple regions. Any catastrophic failure of one data centre will not result in permanent data loss. Scalability Data is automatically scaled out and load-balanced to meet peak demands. Azure Storage provides a global namespace to access data from anywhere. Security Azure Storage relies on a Shared Key model for authentication security. Access can be further restricted through the use of a shared access signature (SAS). SAS is a token that can be appended to a URI, defining specific permissions for a specified period of time. With SAS, you can access standard stores like Blob, Table, Queue, and File. You can also provide anonymous access, although that it is generally not recommended. 11.4 STORAGE REPLICATIONS: LRS, ZRS, GRS, RAGRS Azure Storage is a managed data storage service in Microsoft Azure cloud which is highly redundant and protected from any kind of failure as it provides different level of data replication and redundancy. Azure Storage Replication Mechanism: 1. Locally Redundant Storage (LRS): LRS synchronously replicates data three times within a single physical datacentre in a region, provides protection against server rack or storage cluster failure but can’t sustain Datacentre level (Availability Zone level also) failure. Provides at least 99.999999999% (11 nines) 194 CU IDOL SELF LEARNING MATERIAL (SLM)
durability of the data. Figure 11.1 Azure Storage Replication Mechanism: 2. Zone Redundant Storage (ZRS): With ZRS, data is replicated synchronously across three Availability Zones (AZs) in an Azure region which means even if one of the AZ completely fails, we can still continue to read and write the data without any interruption or data loss as each Availability Zone is an independent physical location within an Azure region, however this can’t sustain if the complete Azure region is impacted due to any unexpected failure. ZRS provides at least 99.9999999999% (12 9’s) durability of the data. Figure 11.2 Zone Redundant Storage (ZRS): 195 CU IDOL SELF LEARNING MATERIAL (SLM)
3. Geo Redundant Storage (GRS): With GRS, first data is replicated synchronously three times within a single physical datacentre in the primary Azure region using LRS mechanism. It then replicates your data asynchronously to a single physical location in the secondary Azure region. After the data replicated to the secondary location, it’s also replicated within that location using LRS.GRS protects against region level disasters and provides at least 99.99999999999999% (16 9’s) durability of the data. Figure 11.3 Geo Redundant Storage (GRS): 4. Geo Zone Redundant Storage (GZRS): With GZRS, data is replicated across three Azure availability zones in the primary region and is also replicated to a secondary geographic region for protection from region level disasters. GZRS provides at least 99.99999999999999% (16 9’s) durability of the data. The key difference between GRS and GZRS is how data is replicated in the primary region. Within the secondary location, data is always replicated synchronously three times using LRS. The main difference between GRS and GZRS replication is basically how the data is replicated in the primary region, data in secondary Azure region is always replicated three times using LRS. 196 CU IDOL SELF LEARNING MATERIAL (SLM)
Figure 11.4 Geo Zone Redundant Storage (GZRS): Note: Your application or client can’t read or write in secondary Azure region with GRS or GZRS replication unless there is a failover to the secondary region. If you would like read access to secondary Azure region then you configure your storage account to use read-access geo-redundant storage (RA-GRS) or read-access geo-zone-redundant storage (RA-GZRS). If primary Azure region where Storage Account resides goes unavailable due to any unplanned or planned events we can manually perform the failover to secondary region, once failover is completed, the secondary region becomes the primary region and we can again read and write data. 11.5 TYPES OF STORAGE: BLOB, FILE, TABLE, QUEUE. Azure Storage offers several types of storage accounts. Each type supports different features and has its own pricing model. Consider these differences before you create a storage account to determine the type of account that is best for your applications. The types of storage accounts are: With an Azure Storage account, you can choose from two kinds of storage services: Standard Storage which includes Blob, Table, Queue, and File storage types, and Premium Storage – 197 CU IDOL SELF LEARNING MATERIAL (SLM)
Azure VM disks. Figure 11.5 Type of storage Standard Storage account With a Standard Storage Account, a user gets access to Blob Storage, Table Storage, File Storage, and Queue storage. Let’s explain those just a bit better. Azure Blob Storage Blog Storage is basically storage for unstructured data that can include pictures, videos, music files, documents, raw data, and log data…along with their meta-data. Blobs are stored in a directory-like structure called a “container”. If you are familiar with AWS S3, containers work much the same way as S3 buckets. You can store any number of blob files up to a total size of 500 TB and, like S3, you can also apply security policies. Blob storage can also be used for data or device backup. Blob Storage service comes with three types of blobs: block blobs, append blobs and page blobs. You can use block blobs for documents, image files, and video file storage. Append blobs are similar to block blobs, but are more often used for append operations like logging. Page blobs are used for objects meant for frequent read-write operations. Page blobs are therefore used in Azure VMs to store OS and data disks. To access a blob from storage, the URI should be: • http://<storage-account-name>. blob.core.windows.net/<container-name>/<blob- name> 198 CU IDOL SELF LEARNING MATERIAL (SLM)
For example, to access a movie called RIO from the BlueSky container of an account called Carlos, request: • http://carlos.blob.core.windows.net/ BlueSky/RIO.avi Note that container names are always in lower case. Azure Table Storage Table storage, as the name indicates, is preferred for tabular data, which is ideal for key-value NoSQL data storage. Table Storage is massively scalable and extremely easy to use. Like other NoSQL data stores, it is schema-less and accessed via a REST API. A query to table storage might look like this: • http://<storage account>. table.core.windows.net/<table> Azure File Storage Azure File Storage is meant for legacy applications. Azure VMs and services share their data via mounted file shares, while on-premise applications access the files using the File Service REST API. Azure File Storage offers file shares in the cloud using the standard SMB protocol and supports both SMB 3.0 and SMB 2.1. Azure Queue Storage The Queue Storage service is used to exchange messages between components either in the cloud or on-premise (compare to Amazon’s SQS). You can store large numbers of messages to be shared between independent components of applications and communicated asynchronously via HTTP or HTTPS. Typical use cases of Queue Storage include processing backlog messages or exchanging messages between Azure Web roles and Worker roles. A query to Queue Storage might look like this: • http://<account>. queue.core.windows.net/<file_to_download> 199 CU IDOL SELF LEARNING MATERIAL (SLM)
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