OpenStack private cloud bring flexibility and agility to respond to opportunities and changes in the financial industry. However, workload patterns in finance, including investment banks, hedge funds, proprietary trading firms, insurance and retail banking, present challenges in private cloud operations.
- Variable and time-dependent workload wasting resources during idle periods
- Hardware allocated for DR (disaster recovery) sitting mostly idle (waiting for disaster to happen!)
- Hardware faults incurring down time, impacting business
- Adoption of DevOps model require supporting tools to enable clear segmentation of roles of Service Provider and Service Users
- Service Users expect computing resources to be available on demand, at an instant
- The infrastructure operations team is under ever greater pressure to ensure that data centers are reliable and efficient
- The infrastructure operations team is concerned about providing the computing service at a competitive cost
- FishOS optimizes away idle powered-on servers, by enabling efficient utilization of cloud resources, in real-time
- FishOS mitigates downtime without unnecessary idle servers, by dynamically handling live migration of workload away from faults, while scaling to manage multiple data centers as one
- FishOS increases reliability by preemptively migrating workload away from imminent hardware faults
- Data center operations team easily extend on FishOS, using familiar tools, with zero learning curve
- FishOS enables rapid provision of Service Users’ requests, in an optimal manner, scaling to entire facility and multiple facilities
- FishOS lowers data center OpEx, enabling data center operations team to be more competitive
- With clear segmentation of roles of Service Provider and Service User, implementation of private cloud to support adoption of DevOps operating model is easy using FishOS
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Further examples of FishOS application in finance
Dynamically balance resources for risk computations: In addition to periodic (daily, weekly, monthly, quarterly) nature of risk computations, each component of the computation steps also demand resources at varying times. FishOS ensures right-allocation of computational resources at all times — automatically!
Efficient fixed income computations demand computational resources at variable times. FishOS ensures high performance by guaranteeing balanced computational resources — in real-time!
Static Data and Referential Data
The two major parts of Static Data and Referential Data services:
- Data loading, matching and cleaning
- Data serving
require resources to be right-allocated at all times, in order to be competitive, without unnecessary over-engineering — FishOS automates this!