There were four cases identified as potential candidates for cloud implementations within Fortum. These cases were application testing, application development, disaster recovery and simulation processes. Only one of these, application development, was tested during this research as the scope is more focused on the template itself. There is growing interest toward cloud computing, especially toward simulation and optimization, in the Fortum trading environment. A project, which extends this thesis, will be initialized during the January of 2015.
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In addition to further research, a proof of concept will be initiated during the 2015 spring to evaluate a chosen cloud vendor and to get personnel familiarized with the cloud. This proof of concept could provide additional information on cloud costs, but also services that could be leveraged within the trading environment. As stated in 5.1, it is safer to test the cloud before any implementations.
The template will evolve along the additional research and will likely build up to be usable even outside the trading environment. It would be interesting to create a template, which is accepted widely within Fortum. The current solution is far from that, as it is merely an overview of the higher level phases and steps, which could be conducted in the Fortum trading environment to reach the cloud with any process. With additional study on corpo-rate level principles and service needs, the template could be extended to take into account the requirements for a widely recognized cloud implementation template at Fortum.
In the near future, cloud could be utilized at Fortum for small tasks to evaluate if the tech-nology can be leveraged for all of the benefits found out during this research. Small, suc-cessful projects and co-operation with the infrastructure provider could enable the possibil-ity to build a private cloud within Fortum data centers to use cloud on a larger scale and release the users of their concerns with security. Moreover, a private cloud platform would simplify moving traditional processes to the cloud and some of the steps of the cloud im-plementation template can be phased out, such as extensive piloting, to make moving to the cloud faster.
The future of cloud computing is bright and growing fast as forecasted by IDC (2014).
According to Malik (2014), the cloud has not yet reached its peak as it is just slowly be-coming a natural part of the society. It has already enabled huge things to happen due to a virtually endless computing capacity, and only time will tell what the possibilities of scale can achieve during the next few years. In addition, the abstraction of infrastructure will remove certain IT responsibilities from companies and allow for more innovation and ex-perimentation with new resources.
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7 SUMMARY
The goal of this research was to build a step by step cloud implementation template for the Fortum trading environment. This template will be followed when attempting to utilize the cloud for a task, an application or a process. A literature review on recent studies was completed to collect information on cloud technology and the trading environment. The acquired information was analyzed and applied to build the end result presented in figure 22.
The template provides Fortum the capabilities to approach cloud implementation projects by dividing the process into six phases. These phases include several steps for further de-fining the implementation challenges found from past research and trading cloud case stud-ies. The benefits of the template translate to a structured approach to cloud computing im-plementations within the Fortum trading environment.
To build the template, the research problem was specified with three research questions.
Each of these questions were answered successfully. The first question was to answer what cloud computing is and what can it be used for. This question was answered by studying relevant past researches and by investigating cloud service providers. Due to the fast mov-ing nature of computer sciences, the literature review was done on studies from the year 2009 to the year 2014 in order to include as recent information as possible.
The second question was to define, which trading applications or processes could benefit from cloud computing. Trading environment was studied by interviewing Fortum trading IT personnel and reviewing cloud implementations in financial services and the energy industry. The case study results point toward cautious implementations of processes, which do not have strong dependencies to the rest of the trading environment. Security is seen as one of the main issues of cloud computing for the trading environment, due to confidential decision making data. This is driving financial companies to building internal cloud solu-tions or utilizing the cloud for processes that do not involve confidential data.
The third question to be answered, before building the template, was how to migrate from a traditional environment to the cloud environment. The findings proved that heavy em-phasis is put on the initial steps of planning what the requirements for the implementation
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are. The initial decisions would then further guide the remainder of the process through piloting to the eventual deployment to production.
Technical development details were scoped out of the project as the main goal was to build a high level template for cloud implementation. To support the template, a validation was conducted by selecting a potential cloud candidate from the Fortum trading environment, and by processing the template for that particular candidate. This validation process was completed successfully with the assistance of Fortum experts and the end results were ac-cepted by the company. In addition to the validation, a cost comparison between a tradi-tional computing environment and several cloud vendors was conducted to initiate a busi-ness case. The cost comparison proved cloud computing to likely bring cost savings to the organization.
Cloud study will be continued in the future at Fortum. This research was the initial spark needed to raise the interest of Fortum employees toward the cloud. The trading personnel are eager to see this project going forward and bringing modern possibilities to the envi-ronment. The first steps of further cloud study at Fortum are testing the template with more potential cloud candidates and conducting a proof of concept before starting on an actual implementation case in the near future.
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APPENDICES
APPENDIX 1. Energy trading and risk management system interview (7.11.2014) with Harri Halminen, System Manager
What is the general purpose of this business process or application?
This system is a backend system for finance trades. It is involved in the life-cycle of the electricity trades here at Fortum. Traders place the trade and the information gets brought to the system via a market data system. This is used by risk control to manage risk calculations and back office for invoicing. The users have to make sure that the trades appear in the system. They come mainly from Nord Pool OMX, but there are other sources.
Back office also has a responsibility to ensure at the end of the day that every trade that exists in the trade reports, also exist in the system. There are also some quite new rules involving European Market Infrastructure Regulation (EMIR) that some trades have to be sent to them by the buyer and the seller, to make sure the trade in-formation matches.
Over the counter (OTC) trades, 1-on-1 trades, money go directly between individu-als and there is individu-also a lot of confirming involved. This is mainly done by an auto-matic script in the end of the day that sends invoices and confirmations to the coun-ter party via email. The invoices are processed overnight.
Cash flows are also sent to FINA (corporate accounting system). This also involves a highly complex automatic process caused by countless rules and regulations.
The bottom line is: a lot of data goes into the system database, and all of the data has to match everywhere.
Which applications are reliant on this process or application?
A financial electricity reporting tool, which exists for a single calculation, is reliant on this system. These two are very closely integrated, but the financial electricity tool is seen as a separate entity. The reporting tool gets all its trade data from the energy trading and risk management system. (continues)
APPENDIX 1. (continued)
Vice versa, which applications does this one rely on?
This system gets all price information from an external system. A corporate appli-cation provides the external system information on currency exchange rates and in-terests, which are used by this system. All of the trading platforms used in Fortum’s trading floor, including trading workstations, broker software, secure phone lines and countless excel tools feed data into to this system. Basically, the IT integration around the system is quite delicate as Excel tools are easy to break.
Who are the primary stakeholders?
The system is used by risk control, back office and traders.
What is the role of IT regarding this process? What about the supplier?
IT is responsible of managing the access rights and support for this tool. IT is gen-erally not responsible of daily activities, but there are constant change requests and incidents that demand attention from the IT staff.
Supplier SLA states that they should assist with various incidents. There is also the possibility to purchase consulting from the supplier, but this is an expensive en-deavor as the supplier staff is located outside of Finland. All expenses should be covered if they were to come to Finland.
What kinds of resources are needed? Are there load peaks?
There are three environments for running the system: production, test and devel-opment.
The production environment has three (3) physical Windows machines for graph-ical user interface (GUI), three (3) physgraph-ical Windows application servers and two (2) UNIX database servers that are linked with a market analyzer as it has produc-tion Oracle database on the same computers.
The development and test environment have a single database cluster which is also shared with the market analyzer’s test environment. Development and test also both have four (4) virtual machines where one (1) is dedicated to GUI and three (3) to application, to basically replicate the production environment. (continues)
APPENDIX 1. (continued)
Is the data handled highly confidential? Are there location restrictions?
Trade data is confidential overall. There are a few very, very confidential price forecasts sent from market analyzer to this system which should never be visible outside of the trading floor. Even the suppliers are not given exact data dumps (a data dump is basically a copy-paste of all the data in some database to another).
They are handed some data to work with while they develop new things. The
They are handed some data to work with while they develop new things. The