On March 17-18, 2025, Kraken announced a groundbreaking colocation service partnership with Beeks Exchange Cloud, bringing institutional-grade, ultra-low-latency trading infrastructure to cryptocurrency markets for the first time. For advanced traders seeking sub-millisecond execution times, this development opens a new chapter in crypto trading infrastructure. This tutorial walks you through the concepts, prerequisites, and practical steps for leveraging colocation services in your cryptocurrency trading operations.
The Objective
Colocation in financial markets refers to the practice of placing your trading servers physically close to an exchange’s matching engine — ideally in the same data center. In traditional finance, firms like Citadel, Jump Trading, and Virtu spend millions on colocation to gain microsecond advantages in price discovery and order execution. Kraken’s partnership with Beeks brings this capability to crypto for the first time, promising sub-millisecond latency for traders connecting from major European hubs like London.
The objective is straightforward: reduce the time between your trading signal and your order reaching the exchange’s order book. In a market where Bitcoin trades at $82,718 with 24-hour volumes exceeding $24 billion, even a few milliseconds of latency can mean the difference between catching a price movement and missing it entirely. For arbitrage strategies, market-making operations, and high-frequency trading, colocation is not a luxury — it is a requirement.
Prerequisites
Before setting up colocation infrastructure, you need several components in place. First, a funded Kraken account with API access enabled. You will need to generate API keys with trading permissions and configure IP whitelisting for security. Second, a trading algorithm or strategy that is optimized for low-latency execution. Colocation amplifies both good and bad strategies — a faster bad strategy still loses money, just faster.
Third, familiarity with WebSocket and FIX protocol connections. Kraken’s colocation service supports both, and understanding how to establish persistent connections with minimal overhead is critical. Fourth, a budget for infrastructure. While Kraken and Beeks have emphasized accessibility and fairness in pricing, colocation services involve renting cloud compute from Beeks’ Exchange Cloud platform or installing physical hardware at Kraken’s European data center.
Fifth, risk management infrastructure. Low-latency trading amplifies risk as much as it amplifies opportunity. You need automated circuit breakers, position limits, and loss thresholds that can operate at machine speed without human intervention.
Step-by-Step Walkthrough
Step 1: Evaluate your current latency. Before investing in colocation, measure your existing round-trip times to Kraken’s API endpoints. Use tools like ping, traceroute, and Kraken’s own API status page to establish a baseline. If your current latency is under 50 milliseconds and your strategy does not depend on microsecond advantages, colocation may not provide significant benefits.
Step 2: Register with Beeks Exchange Cloud. Visit the Beeks website and create an account for their Exchange Cloud service. Select the data center location that corresponds to Kraken’s European infrastructure. Beeks offers both virtual machines and bare-metal servers, with the latter providing the lowest and most consistent latency.
Step 3: Deploy your trading stack on the colocation server. This typically involves a Linux-based server running your trading algorithm, a market data handler that subscribes to Kraken’s WebSocket feeds, and an order management system that connects to Kraken’s trading API. Use lightweight frameworks optimized for speed — C++ and Rust are preferred over Python for latency-critical components.
Step 4: Optimize your network configuration. Disable Nagle’s algorithm (TCP_NODELAY) to prevent packet batching delays. Use kernel bypass techniques like DPDK or io_uring for ultra-fast packet processing. Configure your network interface card to use multiple queues and distribute interrupts across CPU cores.
Step 5: Implement monitoring and alerting. Deploy real-time latency monitoring that tracks the time from market data receipt to order submission. Set alerts for latency spikes, connection drops, and error rates. Kraken’s colocation service is designed for reliability, but any infrastructure can experience issues, and you need to detect and respond to problems within milliseconds.
Step 6: Test thoroughly in a simulated environment before going live. Use Kraken’s sandbox or testnet environment to validate your trading infrastructure. Simulate high-volume scenarios, network interruptions, and failover conditions. Only deploy to production after achieving consistent, reliable performance in testing.
Troubleshooting
Common issues with low-latency trading infrastructure include jitter (inconsistent latency), which is often caused by operating system scheduling. Pin your trading process to dedicated CPU cores using taskset or cgroups to prevent the OS from migrating your process between cores. Disable CPU frequency scaling and turbo boost for more consistent performance.
Network congestion is another frequent problem. Even on a dedicated colocation server, background processes can generate network traffic that competes with your trading data. Strip your server installation to the minimum required services and disable all unnecessary network activity.
API rate limits can also cause unexpected behavior. Kraken’s API has specific rate limits that vary by endpoint and account tier. Monitor your API usage carefully and implement request queuing to stay within limits. Colocation reduces network latency but does not change the exchange’s rate limiting policies.
Mastering the Skill
Colocation is the beginning of professional-grade trading infrastructure, not the end. As you become comfortable with low-latency execution, explore advanced topics like cross-exchange arbitrage infrastructure, where you maintain colocation connections to multiple exchanges simultaneously. Investigate FPGA (Field Programmable Gate Array) acceleration for order book processing, which can reduce latency to nanosecond levels.
Kraken’s colocation service represents a significant step in the maturation of cryptocurrency markets. By making institutional-grade infrastructure accessible to individual traders, Kraken and Beeks are leveling the playing field and pushing the entire industry toward the performance standards of traditional finance. For traders willing to invest the time and resources, the opportunity to compete on speed has never been more accessible. The race is on.
Disclaimer: This article is for educational purposes only and does not constitute financial or trading advice. Trading cryptocurrency involves significant risk. Always test thoroughly before deploying any trading strategy with real funds.
the real bottleneck isnt latency its liquidity. you can have sub-ms execution but if the order book is thin on kraken vs binance it doesnt matter
cable_management liquidity argument is the real issue. kraken BTC order book depth is a fraction of binance. sub-ms execution on thin books just means you slip faster
sub-millisecond execution sounds great until you see the colo fees. kraken is targeting the jump/citadel crowd, not regular traders
sub-millisecond for crypto is laughable when tradfi is measuring in nanoseconds. the gap is enormous
sub-millisecond in crypto vs nanoseconds in tradfi. the gap is closing but honestly most crypto volume is still retail flow that does not care about latency at all
institutional money will pay whatever the colo fee is. were talking about funds that spend 8 figures on data infrastructure already. crypto is just catching up to what tradfi did in 2010
quantbro_ institutional money will pay whatever, exactly. this colo service is not for retail. kraken wants jump and wintermute as clients. your 0.1 ETH market buy does not need sub-millisecond
fpga_ron_ exactly right. this whole colo push is kraken chasing wintermute and jump as clients. retail traders thinking theyll benefit are delusional
fpga_ron_ your 0.1 ETH market buy line is dead on. kraken built this for wintermute and jump. retail thinking theyll benefit from sub-ms execution are dreaming
colo_realist_ kraken built this for wintermute and jump. retail thinking they will benefit from sub-ms execution on a thin order book are dreaming
beeks exchange cloud has been solid in traditional markets for years. bringing that to crypto is actually a big deal for institutional flow
^ yeah but how many crypto exchanges even have matching engines fast enough to benefit from colo? most still run on aws
crypto matching engines on AWS is exactly the problem. most exchanges are running cloud infrastructure pretending to be low latency
crypto matching engines on AWS is the dirty secret of this industry. beeks colocating next to kraken means nothing if the order book is still processed in us-east-1
Soren L. matching engines running on AWS while marketing sub-ms colo is the most crypto thing ever. the gap between the pitch and the infrastructure is wild
Heiko F. AWS jitter is the real killer. you can colocate next to the matching engine but if the matching engine itself runs on cloud infra the latency floor is set by AWS not your cable length
beeks has been doing this for equities since like 2015. the fact that crypto is only now getting colo tells you how far behind the infrastructure still is compared to traditional markets
the real question is whether retail will ever get access or if this stays institutional-only. reading between the lines it sounds like minimums will be steep
Kraken order book depth is the real bottleneck here. sub-ms colo on a thin book just means your market order slips faster
Yannick P. exactly. sub-ms to kraken is pointless when their BTC book has $200k of depth at the top. you hit it with a 5 ETH market order and price moves 30 bps
Kraken’s colocation service is a game changer for serious traders
Sub-millisecond execution matters when you’re doing high-frequency crypto trading
beeks colocating next to kraken matching engine is pointless if the order book runs on AWS. you get sub-ms to the server but the server itself adds 40ms of cloud jitter
us_east_1_ghost spot on. you get sub-ms to the matching engine but the engine itself adds 40ms of AWS jitter. marketing vs reality gap is huge
us_east_1_ghost colocating next to the matching engine is pointless if the engine runs on AWS. you get sub-ms to the server but the server adds 40ms of cloud jitter