The people who know the most about computers consider it nothing short of a miracle they actually work at all. A new enterprise startup called Clockwork wants to fix an old, fundamental problem with computer networks — their failure to keep very accurate time.
Its mission is to bring nanosecond clock-synchronization accuracy into distributed systems to empower time-sensitive applications used in cryptocurrency and stock trading, mobile banking, online gaming, database design and other industries.
“If you look at cloud computing, the big idea in the first decade of the century was virtualization,” Clockwork co-founder and CEO Balaji Prabhakar said. “The next decade was all big data, crunching large amounts of data. What we believe is that this decade is going to move on time, timeliness, deadlines, real-time control: things to do with more time sensitivity.”
Latency Sensei is Clockwork’s new network latency sensor for cloud, hybrid and on-premises data-center environments. Underpinned by the company’s clock synchronization technology, the software measures one-way network delays and helps customers detect bottlenecks, hiccups and underperforming virtual machines to optimize application performance.
Company executives say Latency Sensei’s sensor cuts through the “fog of virtualization” to give DevOps engineers visibility into their networks’ underlying infrastructure.
A Latency Sensei audit.Image: Clockwork
“When you go to the cloud and rent some virtual machines, you're in a bubble,” Prabhakar said. “You don't know what hardware you're running on, you don't know whether two virtual machines are in the same rack of servers or are they across each other in the data center. And when you don't know, you can't tell how much time was spent in the network. ”
Latency Sensei promises to solve this problem, determining as precisely as possible how long it takes for a packet or any piece of data to go from one node in a network to another node.
“For 50 years … in networking, we've never really managed to measure one-way delays accurately, because we don't have accurate clocks,” Prabhakar said, referring to unsynchronized network clocks. “All we've done historically is to say, ‘The time from here to there is half the time it takes to go from here to there and coming back.’”
That roundtrip time approach isn’t adequate to determine where a delay is happening, because it doesn’t distinguish between forward congestion and reverse congestion that can be picked up with accurate one-way times, he said.
“It doesn't work in the modern era where the time you spend on the wire is very small in data centers, and any congestion is really what's slowing you down,” Prabhakar said. “You're missing that information. It's a very powerful tool. After timestamps are taken, probably the first use would be to measure all the delays so you can tell whether a job is stuck in the network or it's stuck in the computer.”
Cryptocurrency trader Collect Trading and an undisclosed multinational financial services company are among early customers for Latency Sensei.
The Clock Sync software
Clockwork launched in 2018 to commercialize clock synchronization research conducted at Stanford University under the supervision of Prabhakar and VMware co-founder Mendel Rosenblum, who serves as Clockwork’s chief scientist. Prabhakar currently is on leave from Stanford, where he’s the VMware Founders Professor of Computer Science and an electrical engineering faculty member.
Latency Sensei’s underlying time-synchronization technology comes from Clockwork’s first software product, Clock Sync, which synchronizes clocks in computers at extremely high levels of accuracy: single-digit nanosecond accuracy for hardware timestamps and within hundreds of nanoseconds for software timestamps, according to the company.
The Clock Sync software launched for private data centers in March 2019 and for public clouds a year later. It can scale to thousands or tens of thousands of nodes.
Accurate clock synchronization is an old problem, and the jittery nature of networks connecting the clocks in servers makes it hard to resolve, because the networks could add random delays to packets exchanged by the clocks, according to Prabhakar.
Latency Sensei checks for any lag time and diagnoses where it occurs.Image: Clockwork
“The network is kind of the enemy in this equation,” he said. “The approach taken was to synchronize the switches in the network with the reference clock and use the network to convey time. This is a hardware-based way of doing it – expensive and hard to scale.”
Clockwork came up with a software approach that doesn’t require a network upgrade.
“The way we went about it was to not touch the network, but make it more of a signal processing, machine learning-type approach, by just cleaning up the timestamps that we get from all the random delay noise added by the network,” Prabhakar explained. “We treat the network like a black box and make clock synchronization an application service. This makes us scalable and accurate. Could this have been done 30 years ago or 25 years ago, probably not — not the way we've done it, because the ML technology that we needed wasn't around.”
Wells Fargo, the Royal Bank of Canada, Nasdaq and eBay are among customers using Clock Sync.
“The financial industry and gaming are similar in terms of the fairness problem,” Prabhakar said. “When two different traders are placing trades, you want to make sure that the trades are executed in the order in which the traders place them and not in a different order, which can happen if the wires are not all the same length. The same thing happens in multiplayer games.”
Clockwork announced $21 million in venture funding last month, a series A round led by New Enterprise Associates (NEA). The company is focused on increasing the speed of adoption for Latency Sensei and Clock Sync and building other products atop its clock synchronization system, including one to reduce latency.
“Having computers synchronized is a really powerful thing,” said Greg Papadopoulos, an NEA partner and the former chief technology officer at Sun Microsystems. “I can tell you almost assuredly that we will also be investing aggressively in the next [funding] round, too. There's just so much promise here. It is really something that you don't get to see that often … where you can take such a fundamental idea that can transform an area and, at the same time, you're not really sure what that means. It's really going to be the story of how we taught computers to keep time.”
