On-demand computing lets businesses use cloud-based resources like computing power, storage, and memory on a pay-as-you-go basis. Instead of buying expensive hardware upfront, companies only pay for what they use, making it flexible and cost-efficient. This model is especially useful in industries like trading, where speed, scalability, and reliability are critical. Trading firms use on-demand computing to handle massive data, run automated systems, and quickly adjust to market changes. Key benefits include real-time resource scaling, usage-based pricing, and improved system performance.
For example, companies like Hudson River Trading leverage cloud solutions to dynamically allocate resources, while platforms like QuantVPS offer ultra-low latency services tailored for traders. This approach reduces costs, enhances performance, and ensures reliable access to critical systems, even during high-demand periods.
What is Cloud Computing? | Amazon Web Services
How On-Demand Computing Works in Trading
On-demand computing in trading revolves around three core principles: dynamic resource allocation, pay-as-you-go pricing, and real-time scaling. Together, these mechanisms enable trading firms to operate with agility, efficiency, and cost-effectiveness.
Cloud-Based Resource Allocation
Cloud-based resource allocation eliminates the need for hefty upfront investments in hardware while addressing concerns about having sufficient computing power during volatile market conditions. Instead of managing physical servers, traders can access computing resources over the internet as needed. A dynamic workload scheduler monitors current demand, reallocating resources to prioritize live trading tasks while supporting activities like backtesting.
Take the example of Hudson River Trading (HRT) partnering with Google Cloud in August 2024. Using Google Cloud‘s Dynamic Workload Scheduler, HRT managed its operations more efficiently by dynamically redistributing AI chips and utilizing Spot Virtual Machines for non-critical tasks. This approach allowed them to tap into unused cloud capacity for activities like workload analysis. Kenny Mullican, CIO at Paragon Films, highlighted the advantages:
"Google Cloud’s scalable infrastructure is a game-changer for HRT, offering it the ability to adjust its computing resources on the fly to meet the specific demands of its research and trading activities."
This system ensures that trading firms can instantly access enterprise-level computing power, whether for running complex quantitative models or storing vast amounts of market data. The dynamic allocation model also aligns with a pricing structure that charges only for the resources actually used.
Pay-as-You-Go Pricing
Building on dynamic resource allocation, the pay-as-you-go (PAYG) pricing model ensures that costs are directly tied to usage. Under PAYG, traders only pay for the computing resources they consume. This can be implemented through consumption-based pricing – where fees depend on transactions processed, data stored, or bandwidth used – or through credit-based systems, allowing pre-purchased credits to be exchanged for services.
Interestingly, businesses adopting usage-based pricing have seen a 29.9% year-over-year revenue growth, outpacing the SaaS average of 21.7%. For trading firms, this model offers improved cost management and the flexibility to scale operations in response to market fluctuations. For instance, Amazon Web Services charges by the hour or second for EC2 virtual servers, while Stripe‘s transaction model – 2.9% plus $0.30 per transaction – demonstrates how costs can align with actual business activity.
Scaling Resources Up and Down
Real-time scaling allows trading systems to adapt quickly to changing market demands and adjust backtesting processes efficiently. However, research shows that 68% of organizations rarely modify their pipeline deployments in response to cloud provider pricing updates, resulting in inefficiencies.
Automated scaling tools address this by monitoring key performance indicators like response time and CPU usage. These tools, often managed through containerized microservices with platforms like Kubernetes, ensure consistent performance during demand surges. Vikas Srivastava, Chief Revenue Officer at Integral, emphasized:
"The ability to scale up and down based on specific needs at a certain time makes cloud computing an essential tool for modern FX trading operations."
Tim Carmody, Chief Technology Officer at IPC Systems, also noted:
"At its core, cloud computing delivers a more flexible and scalable computing resource capability, particularly if accessed through an on-demand, pay-as-you-go, ‘as a service’ model."
This capacity for real-time scaling is crucial for maintaining high-performance trading operations, especially in a fast-paced and unpredictable market environment.
Benefits for Trading Infrastructure
With its ability to manage resources dynamically, on-demand computing offers clear, measurable advantages for trading infrastructure. These benefits directly address the challenges traders face in today’s high-speed financial markets, enhancing performance, reliability, and accessibility.
Better Performance
On-demand computing provides the speed and capacity that modern automated trading systems demand. By leveraging advanced cloud infrastructure, traders can scale computing resources up or down based on real-time performance needs.
Automated systems shine in speed and efficiency. They can execute trades in just 0.001 seconds, analyze over 100 technical indicators, and process more than 1,000 market scenarios per second. This enables faster, more reliable decision-making and reduces impulsive trades by 85% compared to manual methods.
A practical example is Proof Trading, which demonstrates the power of such technology. Their platform processes actions in about 200 microseconds (90th-percentile round-trip latency between their sequencer and the OMS/Algo engine). In some cases, their components can handle messages in as little as 100 nanoseconds.
"In general, when someone quotes a high throughput number for their system, (e.g. 6 million messages/second), your first response should be ‘what is the average message/packet size?’"
Server-side execution further boosts performance by allowing algorithms to run directly on the provider’s infrastructure. This minimizes latency and ensures trades are executed exactly as programmed. These performance improvements naturally contribute to greater system reliability.
Higher Reliability
Cloud-based systems offer unmatched reliability through redundant systems and automatic failover mechanisms. Major cloud providers maintain extensive networks of data centers, monitored and maintained by skilled engineers around the clock, ensuring continuous service.
With information and applications distributed across multiple servers, cloud hosting reduces the risk of data loss and downtime. Built-in disaster recovery features, such as geographic failover, provide an additional layer of protection that traditional systems often lack.
Routine updates, patches, and hardware maintenance are handled by the cloud provider, freeing internal IT teams to focus on higher-value tasks. These operational benefits are complemented by the flexibility of remote access.
Access from Anywhere
On-demand computing makes it possible to access trading systems from virtually any location with an internet connection, allowing traders to operate seamlessly across time zones. Currently, 93% of exchanges, trading systems, and data providers offer cloud-based services, and 90% of buy-side firms rely on cloud-deployed market data.
Through internet-based access, traders can monitor and manage their systems remotely, with automated tools providing 300% more market coverage compared to manual monitoring.
"In general, when someone quotes a high throughput number for their system, (e.g. 6 million messages/second), your first response should be ‘what is the average message/packet size?’"
This level of access ensures traders can respond to market volatility or unexpected events, even outside regular business hours, maintaining operational flexibility and reducing downtime.
sbb-itb-7b80ef7
QuantVPS: On-Demand Computing for Trading
QuantVPS provides futures and forex traders with a cutting-edge solution for on-demand computing. Its cloud-based VPS is specifically designed for automated trading, offering unmatched speed, dependability, and scalability. By positioning servers near major exchanges, QuantVPS tackles common issues like latency and system downtime, bringing the principles of on-demand computing to life in the trading world.
QuantVPS Features
QuantVPS is engineered for performance, delivering ultra-low latency of less than 0.52 milliseconds to the CME Group through its strategically located servers in Chicago. With a 99.99% uptime SLA, supported by redundant systems and round-the-clock monitoring, traders can rely on uninterrupted operations. Every server is powered by premium AMD EPYC processors and NVMe storage for top-tier performance.
The platform also prioritizes security, offering enterprise-grade protection with DDoS safeguards and advanced firewalls. For traders who prefer a multi-monitor setup, QuantVPS has plans that support up to six monitors through Remote Desktop Protocol (RDP). It’s compatible with leading futures and forex trading platforms like NinjaTrader, Sierra Chart, TradeStation, Quantower, Tradovate, and MetaTrader 4/5, with pre-installed software and optimized configurations to minimize setup time. Plus, 24/7 expert support is available to assist with setup, performance tuning, and troubleshooting.
These robust features are paired with competitive pricing plans designed to meet the diverse needs of traders.
Pricing Plans for Traders
QuantVPS offers four pricing tiers, all of which include Windows Server 2022, unmetered bandwidth, and ultra-low latency connectivity.
| Plan | Monthly Price | Annual Price | Cores | RAM | Storage | Best For |
|---|---|---|---|---|---|---|
| VPS Lite | $59 | $41.30 | 4 AMD EPYC | 8GB DDR4 | 70GB NVMe | 1–2 charts |
| VPS Pro | $99 | $69.33 | 6 AMD EPYC | 16GB DDR4 | 150GB NVMe | 3–5 charts |
| VPS Ultra | $199 | $139.17 | 24 AMD EPYC | 64GB DDR4 | 500GB NVMe | 5–7 charts |
| Dedicated Server | $299 | $209.08 | 16+ cores | 128GB RAM | 2TB+ storage | 7+ charts |
Annual billing offers substantial savings, with discounts ranging from 30% to 43%. The VPS Lite plan is ideal for individual traders just getting started, while the Dedicated Server plan caters to large-scale operations and proprietary trading firms managing multiple strategies. Additionally, through a partnership with CrossTrade, qualified traders can access exclusive pricing starting at $35 per month.
Traders frequently praise QuantVPS for its value. Eric Gonzalez shared his experience: "QuantVPS has changed my perspective on how crucial a proper VPS is for consistent day trading profits." He uses QuantVPS to manage multiple strategies on Interactive Brokers.
Built for US-Based Traders
QuantVPS is designed with US traders in mind, ensuring compliance and connectivity tailored to the local market. With strategic data center placement, including a facility in Chicago offering direct connectivity to the CME Group, the platform meets the high standards required by US-based traders. It also incorporates measures to align with regulatory requirements and the strict latency and uptime standards often demanded by proprietary trading firms.
Timothy Young, another satisfied user, highlighted the benefits: "QuantVPS has reduced so much stress in my daily trading routine… Their servers are always up, the latency is super low, and the server doesn’t choke when I open multiple chart windows". With a 4.7/5 rating on Trustpilot from 262 reviews, QuantVPS has become a trusted choice for traders in the US looking to leverage on-demand computing for their trading activities.
How to Implement On-Demand Computing
Implementing on-demand computing for trading requires careful preparation to fully benefit from its performance and scalability. Success hinges on having the right infrastructure, selecting a suitable provider, and managing resources effectively.
What You Need Before Starting
Before diving into on-demand computing, ensure you have a stable and fast internet connection – preferably a wired Ethernet setup. Your development environment should meet the technical requirements of your trading platform, whether that’s MetaTrader 4, NinjaTrader, or TradeStation. Programming languages like Python, C++, or Java are commonly used, so make sure you’re equipped to work with them. A well-organized workspace, such as a multi-monitor setup, can also enhance focus and reduce the likelihood of errors.
Regulatory compliance is another critical factor, especially if you’re running automated strategies or handling client funds. As the U.S. Securities and Exchange Commission notes:
"Electronic trading and algorithmic trading are both widespread and integral to the operation of our capital markets."
Access to high-quality historical and real-time market data is essential for accurate backtesting and smooth trade execution. Once these prerequisites are in place, the next step is choosing the right VPS provider.
How to Choose a VPS Provider
When selecting a VPS provider, low latency should be a top priority. Servers located near your broker’s facilities can significantly reduce delays. Look for providers that guarantee at least 99.9% uptime and offer pre-configured environments for trading platforms.
For example, MetaTrader 5 VPS reports latency of less than five milliseconds for 82% of brokerage servers, while trading from a home PC can result in delays exceeding 200 milliseconds.
Assess the provider’s hardware capabilities, including RAM, processing power, disk I/O, and network bandwidth, to ensure they align with your trading requirements. Security is equally important – verify that the provider offers data encryption, regular backups, and robust firewall protection. It’s also a good idea to test their customer support to ensure reliability.
Finally, decide between a managed VPS service, where the provider takes care of maintenance, or an unmanaged VPS, which gives you more control but requires technical expertise. Once your VPS is set up, focus on managing costs effectively.
Managing Costs
To keep expenses under control, start by tailoring your resources to your actual usage. Monitor metrics like CPU, RAM, and disk I/O, and enable auto-scaling during peak trading hours. Many providers offer discounts for long-term commitments – Google Cloud’s Committed Use Discounts, for instance, can save you 57–70%, while AWS and Microsoft Azure offer up to 72% savings on three-year contracts.
Another cost-saving measure is implementing tiered storage for historical data. Archive older, less frequently accessed backtesting data to cheaper storage options, and delete unnecessary snapshots. Setting up budget alerts with spending thresholds can also help you catch unexpected cost spikes before they impact your bottom line.
Conclusion
On-demand computing has reshaped trading infrastructure by delivering the scalability, performance, and reliability that modern trading demands. Moving away from traditional on-premises systems, cloud-based solutions give traders the ability to adjust resources in real-time based on market conditions, all while cutting capital expenses through flexible pay-as-you-go pricing models.
The numbers speak for themselves: 65% of respondents highlight scalability as the top advantage, while 18% point to reduced capital costs as a key benefit. Meanwhile, algorithmic trading has grown significantly, now making up 60% of global equity trading volume compared to 46% in 2016. These figures reflect a clear industry-wide shift toward cloud-powered trading solutions.
QuantVPS exemplifies this transition with its ultra-low latency of 0.52ms to CME and an impressive 99.999% uptime guarantee. Designed specifically for futures trading, it offers seamless compatibility with major platforms like NinjaTrader and MetaTrader, backed by 24/7 expert support. Whether you’re an individual trader or part of a prop firm, this platform provides the tools to enhance trading efficiency and unlock meaningful financial benefits.
The potential savings are staggering. Fortune 500 financial institutions could save between $60 and $80 billion by embracing cloud solutions. Beyond cost reductions, the performance improvements and operational flexibility make on-demand computing more than just a technical upgrade – it’s a strategic advantage.
Whether you’re automating strategies, running backtests, or managing multiple accounts, on-demand computing offers a scalable, reliable, and cost-efficient foundation. The key to success lies in choosing a provider that delivers the performance, security, and support tailored to your trading needs.
FAQs
How does on-demand computing improve the performance and reliability of automated trading systems?
On-demand computing transforms automated trading systems by offering resources that adjust dynamically to shifting market conditions. This adaptability ensures quicker data processing, minimizes latency, and keeps operations running smoothly – even during intense trading periods. In high-speed trading, every millisecond counts, and these capabilities make a real difference.
It also boosts system reliability, ensuring high availability and reducing downtime. This means your trading algorithms can execute trades consistently, without interruptions, even when demand spikes. Such reliability is crucial for maintaining precision and efficiency in automated trading processes.
What should trading firms consider when choosing a VPS provider for on-demand computing?
When choosing a VPS provider for on-demand computing, trading firms need to prioritize several important aspects to achieve the best performance. One of the top considerations is proximity to financial hubs, as this helps reduce latency – an essential factor for automated trading systems. Opting for a VPS provider with servers close to major broker data centers can significantly cut down delays in executing trades.
Equally important are factors like reliable uptime, which ensures uninterrupted operations, and robust security measures to safeguard sensitive trading data. Firms should also look for scalable resources that can adapt to fluctuating workloads. Additionally, having access to responsive and knowledgeable technical support can make a big difference when issues arise. Lastly, evaluate the provider’s pricing structure, ensuring it fits within your firm’s budget while still delivering the performance you need.
How can trading firms optimize costs when using on-demand computing services?
Trading firms can keep costs in check by smartly managing on-demand computing resources. The first step? Match your resources to actual workload needs. This means avoiding overpaying for capacity you don’t use. Pay-as-you-go models are a great fit here, letting you pay only for what you need without locking into long-term agreements.
To take it further, tap into cloud cost management tools. These tools can help track usage, highlight inefficiencies, and cut out waste. Regularly reviewing and adjusting resource allocation ensures you’re scaling up or down based on demand. By combining these tactics, firms can strike a balance between top-notch performance and staying within budget.
