All posts by Clockwork Team

In the race to build bigger and more powerful AI systems, organizations are discovering that simply adding more GPUs isn’t the golden ticket to faster results. While GPU clusters with thousands—or even hundreds of thousands—of chips offer unparalleled computational power, they also introduce a formidable challenge: synchronization and checkpointing. This blog explores why checkpointing is critical for AI training, why it becomes exponentially more challenging as GPU clusters grow, and how Clockwork’s innovative solution transforms this bottleneck into an opportunity for efficiency and cost savings. Why is Checkpointing a Requirement for AI Training? Training a modern AI model relies on […]

AI at velocity. Made simple in 100% software. Artificial intelligence (AI) is reshaping industries at an unprecedented pace. But with this rapid growth comes immense pressure on the networks that support it. From CPU clouds to sprawling GPU clusters, the infrastructure powering AI workloads is under constant strain. Network bottlenecks, interruptions, and inefficiencies are more than annoyances—they’re costly barriers to innovation How do we move beyond these challenges to build networks that are ready for the AI workloads of today and tomorrow? Let’s dive into what makes a network truly “AI-ready” and how innovations like Clockwork’s software-based solutions are rewriting […]

According to a study by Insight Partners and the MIT Center for Information Systems Research (CISR), businesses in the top quartile of “real-time-ness” significantly outperform their peers: 62% higher revenue growth 97% higher profit margins These organizations also demonstrate improvements in operations: Innovation: 20% better Operational efficiency: 22% better Risk management: 17% better These findings emphasize the importance of becoming a real-time business. Operating in real time isn’t just about speed—it’s about aligning agility with scale, accuracy, and innovation. Notably, these profit margins weren’t achieved by being agile at any cost. Building a real-time business must also account for cost […]

Introduction In the ultra-competitive worlds of crypto arbitrage and high-frequency trading (HFT), every microsecond counts. Your algorithms are in a constant race against competitors to capitalize on fleeting opportunities. A mere microsecond delay can mean the difference between a profitable trade and a missed opportunity—or worse, a loss due to being outpaced by faster traders. The Challenge As a crypto arbitrageur, your strategies involve exploiting price discrepancies across multiple exchanges. Your algorithms gather information from two or more exchanges to execute contracts that ideally settle for a net gain. However, you’re not alone in this endeavor; competing algorithms are simultaneously […]

In today’s digital world, we all expect apps to work quickly and seamlessly, no lag, no waiting—just a smooth, efficient experience. For site reliability engineers (SREs) and data platform engineers, this is more than just a goal; it’s essential. These teams are tasked with making sure applications, databases, and systems perform well, meeting strict Service Level Objectives (SLOs) for latency and uptime. But keeping applications responsive and reliable can be a challenge, especially when those applications run in Kubernetes clusters. Kubernetes has become a go-to solution for containerizing and managing applications, and for good reason—it’s flexible and can handle scaling […]

Precision Timing—A Game Changer for Real-Time Applications In a digital ecosystem where milliseconds matter, precise timestamping isn’t just a nice-to-have; it’s a necessity. Whether you’re managing a high-frequency trading platform, handling critical telecom infrastructure, responding to cybersecurity incidents, or operating latency-sensitive applications, the accuracy of your event timestamps can make or break your performance or limit your ability to consistently meet legal mandates requiring high precision time synchronization. Yet, synchronizing clocks across geographically dispersed locations has long been a costly, complex, and infrastructure-heavy challenge. Let’s dive into why exact time synchronization matters, the limitations of traditional methods, and how Clockwork […]

Let’s face it—cloud services are fantastic. They empower you to build scalable, resilient applications leveraging virtualized compute instances, Kubernetes, and cloud databases. But what happens when those apps start to feel sluggish, unresponsive, or underperforming for no obvious reason? You’ve checked CPU, memory, and disk I/O, and everything seems fine. So what’s the deal?

The hidden culprit could be network throttling by your cloud provider, impacting latency, errors, traffic, and saturation—the four golden signals of system reliability.

In today’s fast-paced world, a seamless digital experience can make or break your business. When customers interact with your applications, they expect instantaneous responses consistently. Any lag or delay can lead to frustration, diminished satisfaction, and ultimately, a loss of business. Accurate, real-time data on network performance isn’t a “nice-to-have”—it’s essential. Let’s dive into why this matters and can now be realized cost-effectively for any real-world scenario utilizing distributed workloads.

Recently, the Clockwork team sponsored both Google Cloud Next ‘24 and Cisco Live in Las Vegas. We had the pleasure of talking to hundreds of people who stopped by our booth to chat about their challenges managing hybrid, multi-cloud networks, and discuss Cloud Deluxe, Clockwork’s congestion control solution. One challenge we heard repeatedly was the need for Quality of Service (QoS) to address performance degradation when primary workloads are disrupted by resource contention from concurrent tasks like backups, observability, and security processes. If this resonates with you, we’d love to learn more in this quick survey. Clockwork’s Bandwidth Slicer addresses […]