Online Spatial Delivery System Management in Cloud Computing

Question: Discuss about the Online Spatial Delivery System for Management in Cloud Computing. Answer: Introduction Online Spatial Delivery System (OSDS) is based on the cloud model Platform as a Service (PaaS) ("What is SPI model (SaaS, PaaS, IaaS)? - Definition from WhatIs.com", 2016). There are a lot many entities that are involved in the implementation and migration of OSDS to cloud such as remote administration, resource management, SLA management, application resilience, backup and disaster recovery. Each of these processes plays an important role in the entire project and needs to be taken seriously and executed with perfection. Remote Administration Remote Administration is the process of controlling a computer from a remote location (cbigconsulting.com, 2016). OSDS will be migrated to a cloud provider and it would have a single or multiple administrators which may or may not belong to a single location. DSI is a huge department and is expanded to a large geographical area. With the applicability of cloud computing in its structure, it would be possible to easily access the information from a remote location and hence, administration would also be allowed from anywhere and at any time. For OSDS, it would be advantageous for the following reasons: Increased efficiency Remote administration would allow increased efficiency and would also save costs. Manual tracking and compiling could be avoided and the resources can be utilized elsewhere. Proactive maintenance Common irregularities and errors can be detected at all the time and an immediate action can be taken. It would help in minimizing the downtime and the impact of any attack. Gain essential insights Remote monitoring and administration would allow gaining an insight to the details of the network and areas that would require improvements. Minimal business interruption Network and other issues can be fixed in a quick turnaround time and it would cause minimal impact to the loss in business. Availability and reliability of the service would surely increase by a good percentage. Resource Management Resource Management is another key area for DSI that needs to be effectively managed in OSDS. There are a number of key resources that may be involved in the OSDS project for DSI. Resource Management Structure in OSDS DSI There are a set of questions that need to be answered to have an efficient resource management strategy in place. Does DSI have a resource tagging startegy? Is there an internal resource management system in place for OSDS and is it linked with the overal DSI model? Is there a policy to identify and allocate the resources correctly? Is there sufficient metadata and service specific instances for the resources? (s3.amazonaws.com, 2016) There are a number of advantages for resource management as: There would be a complete visbility of resource utilization. There would a minimal reliance on the manual processes for resource tracking with automated and searchable resource profiles. Efficiency and productivity would also be increased with the help of an automated resource management process. Centralized resource management and deployment would be extremely useful for DSI to keep a track of resources through an automated system (Netsuite.com, 2016). SLA Management SLA stands for Service Level Agreement which is a written contract between the two parties as the service provider and the end user. SLA in the case of OSDS would be signed between the cloud provider and DSI. Levels of SLA in SLA Management OSDS is based on cloud computing which makes use of shared resources. The primary level in this case is Service based SLA (Bose et al., 2011). SLA management for OSDS would be based upon the following: Service deisgn negotiated and agreed with the cloud provider Supply management process for supply of the services Roles and responsibilities of all the resources such as project owner, manager and various teams involved Service agreement record holding any of the management related and relevant information Service catalog providing the service description, cost and schedule constraints High level process flow chart covering critical success factors and processes Performance indicators (mitsm.de, 2016) Application Resilience OSDS has a list of High Availability (HA) requirements and specifications. There are a number of stepping stones to infrastructure that would help DSI to meet these requirements in a cost effective manner. An effective strategy to maintain and manage all the HA requirements would include redundancy of instances, incorporation of multiple availability zones in a particular region, load balancing, auto scaling, accurate monitoring and data recovery in a region. It is required to ensure that all the critical areas and single points of failures should be carefully assessed. The strategy would not only focus upon the measures to cover every single component and its recoverability but also the methods to ensure that the application is quickly recovered. The strategy would include the following: Design of a fault tolerant application in the cloud to ensure complete availability and reliabilty of the service Use of best practices Storage and backup options Cloud architecture Data Storage and Backup OSDS would deal with huge chunks of data on a day to day basis. The use of Big Data tools would be applicable to manage this data with the help of certain tools. Two of these tools and strategies have been decscribed below: Hadoop Hadoop is an open source tool that is used to store, back-up and manage Big Data. It is written in JAVA and comes with a number of different advantages. Hadoop is extremely scalable in nature and enables businesses to run applications on thousands of nodes involving thousands of terabytes of data. It is also very cost-effective storage solution as compared to the other techniques. It is based on distributed file systems which makes it fast and flexible in nature. Fault tolerance is another feature that comes handy with Hadoop (ITProPortal, 2013). Hyperscale Storage Architecture It makes use of Direct-attached storage (DAS) which are used to power Big Data analytics environments. If a component suffers a breakdown the workload fails over to another node and the entire unit is replaced rather than just the component within. Added to this is the capability to link via APIs to Hadoop and other big data analytics engines that allow data to be interrogated where it resides. Hyperscale is used to easily store and manage the Big Data across several different environments (ComputerWeekly, 2016). Disaster Recovery OSDS makes use of cloud computing which in turn is based on virtualization. The approach that is followed in such a case is entirely different as compared to the standard approach. In case of virtualization, All the components of the system that is whole of the server along with the operating system, applications, every chunk of data and all of the patches are bundled on a single software or on a virtual server. It is possible to bring the whole of the virtual server in just a few minutes or a very short span of time. Virtual server is not dependent on the hardware in any manner and it thus, allows the possibility to transfer from one data center to another data center with extreme ease. Reloading of each component would not be necessary. Recovery time in case of disaster recovery is also reduced by a great margin. With the huge change that is seen in the IT disaster recivery when the cloud computing is involved, network replication becomes the critical path. With fast server recovery at an offsite data center, the critical path for a disaster recovery operation is replicating the production network at the DR site including IP address mapping, firewall rules VLAN configuration (Onlinetech.com, 2016). Conclusions Opportunities and Risks OSDS for DSI is based on the Paas model of cloud computing. Remote administration and efficient resource management would lead to increase in productivity and efficiency and would also help in the cost savings. SLA management in OSDS would primarily be service level SLA and would comprise of the service design along with the roles and responsibilities, performance indicators and a lot of information. Application resilience would focus upon the high availability requirements. The options for backup and disaster recovery have been suggested through the Big Data tools such as Hadoop and Hyperscale. There are a lot many risks that are involved with OSDS which revolve around data protection and information security. Shared access, increased cost and time, authentication and access control, unauthorized access along with the legislation and regulatory information are some of the risks that are involved with the cloud computing model in OSDS ("Risks of cloud computing | Queensland Governmen t", 2016). References Bose, S., Pasala, A., Ramanujam A, D., Murthy, S. and Malaiyandisamy, G. (2011). SLA Management in Cloud Computing: A Service Provider's Perspective. Cloud Computing, pp.413-436. cbigconsulting.com,. (2016). Retrieved 20 May 2016, from https://www.cbigconsulting.com/wp-content/uploads/2013/01/Advantages-of-Remote-Administration.pdf Big data storage choices. (2016). ComputerWeekly. Retrieved 20 May 2016, from https://www.computerweekly.com/feature/Big-data-storage-choices itportal.com,. (2016). Retrieved 20 May 2016, from https://://www.itproportal.com/2013/12/20/big-data-5-major-advantages-of-hadoop Service Level Agreement Management. (2016). Mitsm.de. Retrieved 20 May 2016, from https://www.mitsm.de/service-level-agreement-management-en Resource Management, Resource Utilization, Resource Management System - NetSuite. (2016). Netsuite.com. Retrieved 20 May 2016, from https://www.netsuite.com/portal/products/srp/resource-management.shtml Benefits of Disaster Recovery in Cloud Computing. (2016). Onlinetech.com. Retrieved 20 May 2016, from https://www.onlinetech.com/resources/references/benefits-of-disaster-recovery-in-cloud-computing s3.amazonaws.com,. (2016). Retrieved 20 May 2016, from https://s3.amazonaws.com/awsmedia/AWS_Operational_Checklists.pdf Risks of cloud computing | Queensland Government. (2016). Business.qld.gov.au. Retrieved 20 May 2016, from https://www.business.qld.gov.au/business/running/technology-for-business/cloud-computing-business/cloud-computing-risks What is SPI model (SaaS, PaaS, IaaS)? - Definition from WhatIs.com. (2016). SearchCloudComputing. Retrieved 20 May 2016, from https://searchcloudcomputing.techtarget.com/definition/SPI-model