One thing missing in the blogpost is in practice you see many large orgs, especially in finance, living with multiple time domains. For example, on-prem trading systems almost always use PTP or PPS for sub-microsecond timestamping, often on dedicated networks to reduce jitter (for meeting regulatory requirements like MiFID II and CAT) while the rest of their infra (in on-prem and cloud) just runs NTP for millisecond-class sync. Both protocols are fundamentally sensitive to network conditions — the mean offset may look fine, but outliers due to congestion/jitter can be very poor.
The consequence of having multiple time domains is pretty painful when you need to reconcile logs or transaction histories across systems with different sync accuracy. Millisecond NTP logs and sub-microsecond PTP logs don’t line up cleanly, so correlating events end-to-end can become guesswork rather than deterministic ordering.
If you want reliable cross-system telemetry and audit trails, you'll need a single, high-accuracy time sync approach across your whole stack.
A very clever part of the HUYGENS algorithm is that it doesn’t just sync clocks pair-wise, it leverages a natural network effect where a group of pair-wise synchronized clocks becomes transitively synchronized, helping reduce errors further without requiring specialized hardware. That’s one of the key reasons it can achieve ~100 nanoseconds of software-based sync on commodity networks.
The authors’ work forms the basis of what the team at Clockwork.io is building, enabling accurate one-way delay measurements (rather than just RTT/2) that improve latency visibility and telemetry across CPU and GPU infrastructure
I'm from the Clockwork team, thanks for listing the relevant papers.
Accurate clocks sync enables true one-way delay measurements (instead of RTT/2), this allows for edge-based network visibility. We launched Latency Sensei beta – a sensor, monitor and auditor that provides visibility into cloud deployments. The gallery has cloud fitness reports on GCP, AWS and Azure. Some interesting reports include: 1)how VM colocation impairs network bandwidth, and 2) tale of 2 cloud regions, London vs Singapore. Take a look and we'd love to get some feedback https://sensei.clockwork.io/user/gallery/
On Congestion control, an edge-based solution is coming soon. If you're interested in a private beta, email us at hello@clockwork.io
Latency Sensei is build on top of accurate clock sync, it's a powerful sensor, monitor and auditor that provides visibility into your cloud deployment.
The gallery has cloud fitness reports on GCP, AWS and Azure. Some interesting reports are 1)how VM colocation impairs network bandwidth and 2) tale of 2 cloud regions, London vs Singapore, in terms of VM placement.
we use all the sensors on the device, including compass and accelerometer. This is only possible because we built our own end-to-end mapstack for mobile.
Yeah I can back that one up - 3 out of 4 of my iPhone using friends don't understand that the phone has a OS that needs to be updated and don't remember having attached the phone to a computer with iTunes.
EggCartel, www.eggcartel.com
We're building a local mobile commerce platform to make buying and selling of used items as easy as taking picture on the phone. Office in downtown sf, here is the view from the office http://twitter.com/#!/danz/status/73505757181640704
We're looking for mobile engineers, backend engineers and generalists who can wear multiple hats. Please send me an email danz@eggcartel.com
The consequence of having multiple time domains is pretty painful when you need to reconcile logs or transaction histories across systems with different sync accuracy. Millisecond NTP logs and sub-microsecond PTP logs don’t line up cleanly, so correlating events end-to-end can become guesswork rather than deterministic ordering.
If you want reliable cross-system telemetry and audit trails, you'll need a single, high-accuracy time sync approach across your whole stack.