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by Jeremy Hansford

Operational metrics is the practice of collecting data to gather insight in order to achieve organisational goals specifically into the performance of processes. Ever since businesses have been able to harness the power of data, there has been a proliferation of tools that help you visualize large data sets in order to achieve this...

Analytics can help businesses achieve maximum ROI and deliver optimum performance. What's become more prevalent is the use of these twenty-first century skills and tools for financial institutions, especially with increasingly complex trading infrastructures and the need to respond to ever-changing regulatory compliance.



Case study: Tier 1 Bank



The Problem


Working with our partners CJC, CorellaSoft and Apogee Software we supported our client, a Tier 1 bank who was struggling to harness their internal and operational data. Their initial requirement was to gather insights from this data in two ways: externally around market data trend analysis and internally around the health of its infrastructure. The client wanted the ability to choose the types of data they wished to store and have it for use for weeks or even months. The types of insights from the infrastructure were efficiency of the CPU, update rates, the performance of their middleware and messaging servers, as well as the handling of stale records, were also required. Servers powering various parts of the infrastructure were also inconsistent in measuring certain metrics. Virtualisation and visualization requirements would assist users in diagnosing issues to aid a quick resolution. Storage costs on the bank's internal infrastructure were also a concern, despite previously being limited on what they could store on their existing MySQL database. The bank had an existing system in place with limitations on the physical amount of data it could hold and report on. The additional pressure around expensive internal infrastructure costs were also prevalent.



Challenges


In many analytics tools, potentially critical information is not available for analysis due to failings of the data management architecture which stores and manages metrics and this was present in the banks existing solution. There were also considerations about moving into the cloud, these were centred around the security of the data, safety on the network and client-side mobility. The bank did strategize a 10-year cloud migration plan, in which less intensive processes can be shifted into the cloud but at the same time retaining the key low latency processes on their own private environment. The challenge in this type of cloud migration is that legacy applications are not built for certain infrastructures. Despite being borne from necessity, it can prove difficult to obtain management buy-in and investment for IT infrastructure monitoring.



The Solution


A new Operational Analytics infrastructure was designed from scratch, but cleverly utilised existing technologies. It was also the bank's desire to have it hosted on their own private cloud. A cheaper cloud implementation could be sought due to the non-sensitive nature of the bank's operational data, so a holistic hybrid cloud-based solution was engineered. Modules were created, built on proprietary data management architecture which streamed data via a specific analytics API. The solution was not accessible via the internet and was available in a secure private environment. 24/7 support, high availability with an uptime of 99% and elastic scalability was also on the list of requirements. A platform was built in which the operational data was collected, fed into the platform and presented back to the end user via visualised user interface. This gives the end user the ability to foresee system and data outages, prevent downtime and harness intelligence about their infrastructure that would be cost-effective and provide a better experience for their internal customers overall.

Redcello platform gave our customer a highly engineered, scalable and optimised hardware infrastructure. Our platform boasted state of the art server orchestration to ensure that all those moving parts were delivering uninterrupted, high-quality data that autonomously responds to workloads in a secure manner.


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