Using the cloud to drive down scale-up costs
Post-trade processing businesses can create sustainable margins by developing the capability to rapidly scale on public cloud-native platforms to accommodate fluctuating trading volumes. A cloud-native platform allows them to balance the unit capacity and scale-up cost through the following architectural strategies.
Granular control: Developing a platform on a microservices-based architecture allows the granular control of costs by scaling only the bottlenecked services. This granularity comes at a cost of increased internal communication overheads and needs to be factored while designing the platform.
Leverage usage profile: Public cloud providers extend pricing options and promotions that customers can leverage based on their usage profiles to reduce their costs. For example, on AWS (Amazon Web Services), customers can reserve capacity (processing and/or storage) for long term usage, resulting in substantial savings. They can even sell their unused reserved compute instances on AWS EC2 Reserved Instance Marketplace. For known usage patterns, computing resources can be scheduled to operate, again at a lower price. AWS also provides a spot pricing model for computing resources, where prices vary according to supply and demand. Based on their usage profile, post-trade processing providers can build a fleet of reserved, on-demand and spot compute and storage infrastructure on which their applications can scale while optimising their cost as well.
Serverless Hosting: Serverless hosting on the public cloud, for example, AWS Lambda, offers an additional dimension of flexibility and economy. For services with low to moderate usage, serverless hosting can provide considerable cost saving as pricing is purely usage-based without any reservation or hosting costs. Further, a microservices implementation allows choosing feasible hosting options which offer opportunities for cost optimisations. For example, functionality exposing RESTful APIs for data access, manual data update and report generation may be hosted on serverless. Conversely, trade workflow services exchanging high volume trade messages and events asynchronously may be hosted on a containerised platform over compute instances.
In a nutshell, elastic scalability on public cloud, flexible pricing and hosting options coupled with a microservices architecture present substantial cost optimisation opportunities for post-trade processing systems. All these drive down the scale-up costs. To improve margins further, unit capacity can be stretched through computational, storage and communications efficiencies.
Migrating to a cloud-native platform
Migrating to the cloud remains risky and expensive despite its advantages. According to the Flexera 2020 State of the Cloud Report, most organisations migrating to the cloud are over budget by 23% and waste 30% of that spend. An earlier report suggests that 75% of cloud migrations take over a year with a majority taking 2 years or more.
High costs, long delays and failure to meet migration objectives can result in abandoned or stalled cloud migrations. This leads to wasted spending along with a fragmented IT organisation and an operationally complex and expensive technology estate. Successful cloud migrations require an objective and flexible strategy.
One approach which firms can take to migrate to the cloud is by rehosting legacy systems. This may not be possible where the legacy technology stack is not supported on the cloud or if there is a tight coupling with on-premise services. The benefits of simply rehosting are limited, but they offer an alternate and early mobilisation for re-architecting the services.
Rehosting can therefore be treated as the first stage in the overall cloud migration programme. Through rehosting, cloud migrated applications can not only continue generating revenue but also provide opportunities for fine-tuning and right-sizing the resources for margin improvements. Further refinement is possible by incrementally re-architecting with microservices-based architecture and by reducing the dependency of on-prem services, which can be decommissioned to achieve additional cost improvements.
Firms should pursue an incremental capability driven re-architecture and migration approach to simplify the operating model. This approach helps identify unused or rarely used capabilities and features that can be decommissioned, thus lowering development and operating costs. Where rehosting is not possible, this becomes the starting point of the migration journey.
A mature DevOps practice will deliver additional returns for cloud migration initiatives. By optimising the 4-key Accelerate metrics, we can achieve higher efficiency and economy for promoting changes through the delivery pipeline. ‘Accelerate metrics’ measure lead time, the change failure rate, the deployment frequency and the mean time to recover (MTTR).