How Precision Time Protocol is being deployed at Meta

Implementing Precision Time Protocol (PTP) at Meta permits us to synchronize the methods that drive our services right down to nanosecond precision. PTP’s predecessor, Community Time Protocol (NTP), offered us with millisecond precision, however as we scale to extra superior methods on our option to constructing the subsequent computing platform, the metaverse and AI, we have to be sure that our servers are preserving time as precisely and exactly as potential. With PTP in place, we’ll be capable of improve Meta’s applied sciences and applications — from communications and productiveness to leisure, privateness, and safety — for everybody, throughout time zones and all over the world.
The journey to PTP has been years lengthy, as we’ve needed to rethink how each the timekeeping {hardware} and software program function inside our servers and information facilities.
We’re sharing a deep technical dive into our PTP migration and our improvements which have made it potential
The case for PTP
Earlier than we dive into the PTP structure, let’s discover a easy use case for very correct timing, for the sake of illustration.
Think about a scenario during which a consumer writes information and instantly tries to learn it. In giant distributed methods, likelihood is excessive that the write and the learn will land on totally different back-end nodes.
If the learn is hitting a distant reproduction that doesn’t but have the most recent replace, there’s a probability the consumer won’t see their very own write:

That is annoying on the very least, however extra essential is that that is violating a linearizability assure that permits for interplay with a distributed system in the identical approach as with a single server.
The everyday option to resolve that is to subject a number of reads to totally different replicas and anticipate a quorum resolution. This not solely consumes additional assets but in addition considerably delays the learn due to the lengthy community round-trip delay.
Including exact and dependable timestamps on a again finish and replicas permits us to easily wait till the reproduction catches up with the learn timestamp:

This not solely hurries up the learn but in addition saves tons of compute energy.
A vital situation for this design to work is that every one clocks be in sync or that the offset between a clock and the supply of time be identified. The offset, nonetheless, modifications due to fixed correction, drifting, or easy temperature variations. For that goal, we use the notion of a Window of Uncertainty (WOU), the place we are able to say with a excessive chance the place the offset is. On this explicit instance, the learn must be blocked till the learn timestamp plus WOU.
One might argue that we don’t really want PTP for that. NTP will do exactly high-quality. Nicely, we thought that too. However experiments we ran evaluating our state-of-the-art NTP implementation and an early model of PTP confirmed a roughly 100x efficiency distinction:

There are a number of extra use circumstances, together with occasion tracing, cache invalidation, privateness violation detection enhancements, latency compensation within the metaverse, and simultaneous execution in AI, a lot of which is able to tremendously scale back {hardware} capability necessities. This can hold us busy for years forward.
Now that we’re on the identical web page, let’s see how we deployed PTP at Meta scale.
The PTP structure

After a number of reliability and operational opinions, we landed on a design that may be break up into three most important elements: the PTP rack, the community, and the consumer.
Buckle up — we’re going for a deep dive.
The PTP rack
This homes the {hardware} and software program that serves time to purchasers; the rack consists of a number of vital elements, every of which has been fastidiously chosen and examined.
The antenna
The GNSS antenna is well one of many least appreciated elements. However that is the place the place time originates, not less than on Earth.
We’re striving for nanosecond accuracy. And if the GNSS receiver can’t precisely decide the place, it will be unable to calculate time. We’ve got to strongly contemplate the signal-to-noise ratio (SNR). A low-quality antenna or obstruction to the open sky can lead to a excessive 3D location normal deviation error. For time to be decided extraordinarily precisely, GNSS receivers ought to enter a so-called time mode, which usually requires a <10m 3D error.
It’s completely important to make sure an open sky and set up a strong stationary antenna. We additionally get to get pleasure from some lovely views:

Whereas we have been testing totally different antenna options, a comparatively new GNSS-over-fiber know-how received our consideration. It’s free from virtually all disadvantages — it doesn’t conduct electrical energy as a result of it’s powered by a laser by way of optical fiber, and the sign can journey a number of kilometers with out amplifiers.
Contained in the constructing, it could use pre-existing structured fiber and LC patch panels, which considerably simplifies the distribution of the sign. As well as, the sign delays for optical fiber are nicely outlined at roughly 4.9ns per meter. The one factor left is the delay launched by the direct RF to laser modulation and the optical splitters, that are round 45ns per field.

By conducting exams, we confirmed that the end-to-end antenna delay is deterministic (usually about a number of hundred nanoseconds) and may simply be compensated on the Time Equipment aspect.
Time Equipment
The Time Equipment is the guts of the timing infrastructure. That is the place time originates from the information middle infrastructure perspective. In 2021, we revealed an article explaining why we developed a brand new Time Equipment and why present options wouldn’t reduce it.
However this was principally within the context of NTP. PTP, alternatively, brings even larger necessities and tighter constraints. Most significantly, we made a dedication to reliably assist as much as 1 million purchasers per equipment with out hurting accuracy and precision. To realize this, we took a vital have a look at lots of the conventional elements of the Time Equipment and thought actually laborious about their reliability and variety.
The Time Card

To guard our infrastructure from a vital bug or a malicious assault,we determined to begin diversification from the supply of time — the Time Card. Final time, we spoke loads concerning the Time Card design and some great benefits of an FPGA-based resolution. Below the Open Compute Challenge (OCP), we’re collaborating with distributors corresponding to Orolia, Meinberg, Nvidia, Intel, Broadcom, and ADVA, that are all implementing their very own time playing cards, matching the OCP specification.
Oscillatord
The Time Card is a vital element that requires particular configuration and monitoring. For this goal, we labored with Orolia to develop a disciplining software, referred to as oscillatord, for various flavors of the Time Playing cards. This has turn out to be the default software for:
- GNSS receiver configuration: setting the default config, and adjusting particular parameters like antenna delay compensation. It additionally permits the disabling of any variety of GNSS constellations to simulate a holdover state of affairs.
- GNSS receiver monitoring: reporting variety of satellites, GNSS high quality, availability of various constellations, antenna standing, leap second, and so forth.
- Atomic clock configuration: Totally different atomic clocks require totally different configuration and sequence of occasions. For instance, it helps SA53 TAU configuration for quick disciplining, and with mRO-50, it helps a temperature-to-frequency relation desk.
- Atomic clock monitoring: Parameters corresponding to a laser temperature and lock should be monitored completely, and quick selections should be made when the values are outdoors of operational vary.
Successfully, the information exported from oscillatord permits us to resolve whether or not the Time Equipment ought to take visitors or must be drained.
Community card
Our final aim is to make protocols corresponding to PTP propagate over the packet community. And if the Time Card is the beating coronary heart of the Time Equipment, the community card is the face. Each time-sensitive PTP packet will get {hardware} timestamped by the NIC. This implies the PTP {Hardware} Clock (PHC) of the NIC should be precisely disciplined.
If we merely copy the clock values from Time Card to the NIC, utilizing the phc2sys or the same software, the accuracy won’t be practically sufficient. In actual fact, our experiments present that we’d simply lose ~1–2 microseconds whereas going by PCIe, CPU, NUMA, and so forth. The efficiency of synchronization over PCIe bus will dramatically enhance with the rising Precision Time Measurement (PTM) know-how, as the event and assist for varied peripherals with this functionality is in progress.
For our utility, since we use NICs with PPS-in capabilities, we employed ts2phc, which copies clock values at first after which aligns the clock edges based mostly on a pulse per second (PPS) sign. This requires an extra cable between the PPS output of the Time Card and the PPS enter of the NIC, as proven within the image beneath.

We continually monitor offset and ensure it by no means goes out of a ±50ns window between the Time Card and the NIC:

We additionally monitor the PPS-out interface of the NIC to behave as a fail-safe and be sure that we truly know what’s occurring with the PHC on the NIC.
ptp4u
Whereas evaluating totally different preexisting PTP server implementations, we skilled scalability points with each open supply and closed proprietary options, together with the FPGA-accelerated PTP servers we evaluated. At greatest, we might get round 50K purchasers per server. At our scale, this implies we must deploy many racks full of those gadgets.
Since PTP’s secret sauce is the usage of {hardware} timestamps, the server implementation doesn’t should be a extremely optimized C program and even an FPGA-accelerated equipment.
We carried out a scalable PTPv2 unicast PTP server in Go, which we named ptp4u, and open-sourced it on GitHub. With some minor optimizations, we have been capable of assist over 1 million concurrent purchasers per gadget, which was independently verified by an IEEE 1588v2 licensed gadget.
This was potential by the straightforward however elegant use of channels in Go that allowed us to cross subscriptions round between a number of highly effective employees.
As a result of ptp4u runs as a course of on a Linux machine, we robotically get all the advantages, like IPv6 assist, firewall, and so forth., without cost.
c4u
The ptp4u server has many configuration choices, permitting it to cross dynamically altering parameters corresponding to PTP Clock Accuracy, PTP Clock Class, and a UTC offset — that’s at present set to 37 seconds (we’re wanting ahead this changing into a continuing) — right down to purchasers.
With a purpose to regularly generate these parameters, we carried out a separate service referred to as c4u, which continually displays a number of sources of knowledge and compiles the lively config for ptp4u:

This offers us flexibility and reactivity if the surroundings modifications. For instance, if we lose the GNSS sign on one of many Time Home equipment, we’ll swap the ClockClass to HOLDOVER and purchasers will instantly migrate away from it. It’s also calculating ClockAccuracy from many various sources, corresponding to ts2phc synchronization high quality, atomic clock standing, and so forth.
We calculate the UTC offset worth based mostly on the content material of the tzdata package deal as a result of we cross Worldwide Atomic Time (TAI) right down to the purchasers.
Calnex Sentinel
We needed to verify our Time Home equipment are continually and independently assessed by a well-established licensed monitoring gadget. Fortunately, we’ve already made a number of progress within the NTP area with Calnex, and we have been ready to use the same strategy to PTP.
We collaborated with Calnex to take their area gadget and repurpose it for information middle use, which concerned altering the bodily type issue and including assist for options corresponding to IPv6.

We join the Time Equipment NIC PPS-out to the Calnex Sentinel, which permits us to watch the PHC of the NIC with nanosecond accuracy.
We’ll discover monitoring in nice element in “How we monitor the PTP structure,” beneath.
The PTP community
PTP protocol
The PTP protocol helps the usage of each unicast and multicast modes for the transmission of PTP messages. For big information middle deployments, unicast is most popular over multicast as a result of it considerably simplifies community design and software program necessities.
Let’s check out a typical PTP unicast stream:
A consumer begins the negotiation (requesting unicast transmission). Due to this fact, it should ship:
- A Sync Grant Request (“Hey server, please ship me N Sync and Comply with-Up messages per second with the present time for the subsequent M minutes”)
- An Announce Grant Request (“Hey server, please ship me X Announce messages per second together with your standing for the subsequent Y minutes”)
- A Delay Response Grant Request (“Hey server, I’m going to ship you Delay Requests — please reply with Delay Response packets for the subsequent Z minutes”)
- The server must grant these requests and ship grant responses.
- Then the server wants to begin executing subscriptions and sending PTP messages.
- All subscriptions are unbiased of each other.
- It’s on the server to obey the ship interval and terminate the subscription when it expires. (PTP was initially multicast solely, and one can clearly see the multicast origin on this design).
- In two-step configuration, when the server sends Sync messages, it has to learn the TX {hardware} timestamp and ship a Comply with-Up message containing that timestamp.
- The consumer will ship Delay Requests inside the agreed-upon interval to find out the trail delay. The server must learn the RX {hardware} timestamp and return it to the consumer.
- The consumer must periodically refresh the grant, and the method repeats.
Schematically (only for the illustration), it’ll seem like this:

Clear clocks
We initially thought-about leveraging boundary clocks in our design. Nevertheless, boundary clocks include a number of disadvantages and issues:
- You want community tools or some particular servers to behave as a boundary clock.
- A boundary clock acts as a time server, creating better demand for short-term stability and holdover efficiency.
- Because the info has to cross by the boundary clocks from the time servers right down to the purchasers, we must implement particular assist for this.
To keep away from this extra complexity, we determined to rely solely on PTP clear clocks.
Clear clocks (TCs) allow purchasers to account for variations in community latency, making certain a way more exact estimation of clock offset. Every information middle swap within the path between consumer and time server stories the time every PTP packet spends transiting the swap by updating a area within the packet payload, the aptly named Correction Area (CF).
PTP purchasers (additionally known as unusual clocks, or OCs) calculate community imply path delay and clock offsets to the time servers (grandmaster clocks, or GMs) utilizing 4 timestamps (T1, T2, T3, and T4) and two correction area values (CFa and CFb), as proven within the diagram beneath:

- T1 is the {hardware} timestamp when the SYNC packet is shipped by the Time Server.
- T2 is the {hardware} timestamp when the OC receives the SYNC packet.
- CFa is the sum of the swap delays recorded by every swap (TC) within the path from time server to the consumer (for SYNC packet).
- T3 is the {hardware} timestamp the delay request is shipped by the Shopper.
- T4 is the {hardware} timestamp when the time server receives the delay request.
- CFb is the sum of the swap delays recorded by every swap within the path from the Shopper to the time server (for Delay Request packet).
To grasp the impression of only one disabled clear clock on the best way between consumer and a server, we are able to study the logs:
We are able to see the trail delay explodes, generally even changing into unfavourable which shouldn’t occur throughout regular operations. This has a dramatic impression on the offset, transferring it from ±100 nanoseconds to -400 microseconds (over 4000 occasions distinction). And the worst factor of all, this offset won’t even be correct, as a result of the imply path delay calculations are incorrect.
Based on our experiments, trendy switches with giant buffers can delay packets for as much as a few milliseconds which is able to end in a whole lot of microseconds of a path delay calculation error. This can drive the offset spikes and will probably be clearly seen on the graphs:
The underside line is that operating PTP in datacenters within the absence of TCs results in unpredictable and unaccountable asymmetry within the roundtrip time. And the worst of all – there will probably be no easy option to detect this. 500 microseconds might not sound like loads, however when prospects count on a WOU to be a number of microseconds, this will likely result in an SLA violation.
The PTP Shopper
Timestamps
Timestamping the incoming packet is a comparatively previous function supported by the Linux kernel for many years. For instance software program (kernel) timestamps have been utilized by NTP daemons for years. It’s essential to grasp that timestamps usually are not included into the packet payload by default and if required, should be positioned there by the consumer utility.
Studying RX timestamp from the consumer area is a comparatively easy operation. When packet arrives, the community card (or a kernel) will timestamp this occasion and embody the timestamp into the socket control message, which is simple to get together with the packet itself by calling a recvmsg syscall with MSG_ERRQUEUE flag set.
128 bits | 64 bits | 64 bits | 64 bits |
Socket management message header | Software program Timestamp | Legacy Timestamp | {Hardware} Timestamp |
For the TX {Hardware} timestamp it’s somewhat extra sophisticated. When sendto syscall is executed it doesn’t result in a right away packet departure and neither to a TX timestamp era. On this case the consumer has to poll the socket till the timestamp is precisely positioned by the kernel. Typically we’ve got to attend for a number of milliseconds which naturally limits the ship fee.
{Hardware} timestamps are the key sauce that makes PTP so exact. Many of the trendy NICs have already got {hardware} timestamps assist the place the community card driver populates the corresponding part.
It’s very straightforward to confirm the assist by operating the ethtool command:
$ ethtool -T eth0
Time stamping parameters for eth0:
Capabilities:
hardware-transmit
hardware-receive
hardware-raw-clock
PTP {Hardware} Clock: 0
{Hardware} Transmit Timestamp Modes:
off
on
{Hardware} Obtain Filter Modes:
none
All
It’s nonetheless potential to make use of PTP with software program (kernel) timestamps, however there received’t be any sturdy ensures on their high quality, precision, and accuracy.
We evaluated this risk as nicely and even thought-about implementing a change within the kernel for “faking” the {hardware} timestamps with software program the place {hardware} timestamps are unavailable. Nevertheless, on a really busy host we noticed the precision of software program timestamps jumped to a whole lot of microseconds and we needed to abandon this concept.
ptp4l
ptp4l is an open supply software program able to appearing as each a PTP consumer and a PTP server. Whereas we needed to implement our personal PTP server resolution for efficiency causes, we determined to stay with ptp4l for the consumer use case.
Preliminary exams within the lab revealed that ptp4l can present glorious synchronization high quality out of the field and align time on the PHCs within the native community right down to tens of nanoseconds.
Nevertheless, as we began to scale up our setup some points began to come up.
Edge circumstances
In a single explicit instance we began to note occasional “spikes” within the offset. After a deep dive we recognized basic {hardware} limitations of one of the vital standard NICs available on the market:
- The NIC has solely a timestamp buffer for 128 packets.
- The NIC is unable to differentiate between PTP packets (which want a {hardware} timestamp) and different packets which don’t.
This in the end led to the reliable timestamps being displaced by timestamps coming from different packets. However what made issues loads worse – the NIC driver tried to be overly intelligent and positioned the software program timestamps within the {hardware} timestamp part of the socket management message with out telling anybody.
It’s a basic {hardware} limitation affecting a big portion of the fleet which is unimaginable to repair.
We needed to implement an offset outliers filter, which modified the habits of PI servo and made it stateful. It resulted in occasional outliers being discarded and the imply frequency set through the micro-holdover:
If not for this filter, ptp4l would have steered PHC frequency actually excessive, which might end in a number of seconds of oscillation and unhealthy high quality within the Window of Uncertainty we generate from it.
One other subject arose from the design of BMCA. The aim of this algorithm is to pick the perfect Time Equipment when there are a number of to select from within the ptp4l.conf. It does by evaluating a number of attributes equipped by Time Servers in Announce messages:
- Precedence 1
- Clock Class
- Clock Accuracy
- Clock Variance
- Precedence 2
- MAC Tackle
The issue manifests itself when all aforementioned attributes are the identical. BMCA makes use of Time ApplianceMAC handle because the tiebreaker which suggests underneath regular working circumstances one Time Server will appeal to all consumer visitors.
To fight this, we launched a so-called “sharding” with totally different PTP purchasers being allotted to totally different sub-groups of Time Home equipment from your complete pool.

This solely partially addressed the problem with one server in every subgroup taking your complete load for that grouping. The answer was to allow purchasers to precise a choice, and so we launched Priority3 into the choice standards simply above the MAC handle tiebreaker. Which means purchasers configured to make use of the identical Time Home equipment can favor totally different servers.
Shopper 1:
[unicast_master_table]
UDPv6 time_server1 1
UDPv6 time_server2 2
UDPv6 time_server3 3
Shopper 2:
[unicast_master_table]
UDPv6 time_server2 1
UDPv6 time_server3 2
UDPv6 time_server1 3
This ensures we are able to distribute load evenly throughout all Time Home equipment underneath regular working circumstances.
One other main problem we confronted was making certain PTP labored with multi-host NICs – a number of hosts sharing the identical bodily community interface and subsequently a single PHC. Nevertheless, ptp4l has no information of this and tries to self-discipline the PHC like there aren’t any different neighbors.
Some NIC producers developed a so-called “free operating” mode the place ptp4l is simply disciplining the components contained in the kernel driver. The precise PHC just isn’t affected and retains operating free. This mode leads to a barely worse precision, but it surely’s fully clear to ptp4l.
Different NIC producers solely assist a “actual time clock” mode, when the primary host to seize the lock truly disciplines the PHC. The benefit here’s a extra exact calibration and better high quality holdover, but it surely results in a separate subject with ptp4l operating on the opposite hosts utilizing the identical NIC as makes an attempt to tune PHC frequency haven’t any impression, resulting in inaccurate clock offset and frequency calculations.
PTP profile
To explain the datacenter configuration, we’ve developed and published a PTP profile, which displays the aforementioned edge circumstances and lots of extra.
Different PTP purchasers
We’re evaluating the potential of utilizing another PTP consumer. Our most important standards are:
- Assist our PTP profile
- Meets our synchronization high quality necessities
- Open supply
We’re evaluating the Timebeat PTP consumer and, up to now, it appears to be like very promising.
Constantly incrementing counter
Within the PTP protocol, it doesn’t actually matter what time we propagate so long as we cross a UTC offset right down to the purchasers. In our case, it’s Worldwide Atomic Time (TAI), however some individuals might select UTC. We like to consider the time we offer as a constantly incrementing counter.
At this level we aren’t disciplining the system clock and ptp4l is solely used to self-discipline the NIC’s PHC.
fbclock
Synchronizing PHCs throughout the fleet of servers is sweet, but it surely’s of no profit until there’s a option to learn and manipulate these numbers on the consumer.
For this goal, we developed a easy and light-weight API referred to as fbclock that gathers info from PHC and ptp4l and exposes straightforward digestible Window Of Uncertainty info:

By means of a really environment friendly ioctl PTP_SYS_OFFSET_EXTENDED, fbclock will get a present timestamps from the PHC, newest information from ptp4l after which applies math components to calculate the Window Of Uncertainty (WOU):
$ ptpcheck fbclock
"earliest_ns":1654191885711023134,"latest_ns":1654191885711023828,"wou_ns":694
As you might even see, the API doesn’t return the present time (aka time.Now()). As an alternative, it returns a window of time which accommodates the precise time with a really excessive diploma of chance On this explicit instance, we all know our Window Of Uncertainty is 694 nanoseconds and the time is between (TAI) Thursday June 02 2022 17:44:08:711023134 and Thursday June 02 2022 17:44:08:711023828.
This strategy permits prospects to attend till the interval is handed to make sure precise transaction ordering.
Error sure measurement
Measuring the precision of the time or (Window Of Uncertainty) signifies that alongside the delivered time worth, a window (a plus/minus worth) is offered that’s assured to incorporate the true time to a excessive degree of certainty.
How sure we should be is decided by how vital it’s that the time be appropriate and that is pushed by the precise utility.
In our case, this certainty must be higher than 99.9999% (6-9s). At this degree of reliability you may count on lower than 1 error in 1,000,000 measurements.
The error fee estimation makes use of commentary of the historical past of the information (histogram) to suit a chance distribution operate (PDF). From the chance distribution operate one can calculate the variance (take a root sq. and get the usual deviation) and from there it is going to be easy multiplication to get to the estimation of the distribution based mostly on its worth.
Under is a histogram taken from the offset measurement from ptp4l operating on the unusual clock.
To estimate the entire variance (E2E) it’s essential to know the variance of the time error amassed by the point server all the best way to the tip node NIC. This consists of GNSS, atomic clock, and Time Card PHC to NIC PHC (ts2phc). The producer gives the GNSS error variance. Within the case of the UBX-F9T it’s about 12 nanoseconds. For the atomic clock the worth is dependent upon the disciplining threshold that we’ve set. The tighter the disciplining threshold, the smaller offset variance however decrease holdover efficiency. On the time of operating this experiment, the error variance of the atomic clock has been measured to 43ns (normal deviation, std). Lastly, the software ts2phc will increase the variance by 30ns (std) leading to a complete variance of 52ns.
The noticed outcomes matches the calculated variance obtained by the “Sum of Variance Legislation.”
Based on the sum of variance regulation, all we have to do is so as to add all of the variance. In our case, we all know that the entire observer E2E error (measured by way of the Calnex Sentinel) is about 92ns.
On the opposite fingers for our estimation, we are able to have the next:
Estimated E2E Variance = [GNSS Variance + MAC Variance + ts2phc Variance] + [PTP4L Offset Variance] = [Time Server Variance] + [Ordinary Clock Variance]
Plugging within the values:
Estimated E2E Variance = (12ns 2) + (43ns2) + (52ns2) + (61ns2) = 8418, which corresponds to 91.7ns
These outcomes present that by propagating the error variance down the clock tree, the E2E error variance could be estimated with a very good accuracy. The E2E error variance can be utilized to calculate the Window Of Uncertainty (WOU) based mostly on the next desk.
Merely, by multiplying the estimated E2E error variance in 4.745 we are able to estimate the Window Of Uncertainty for the chance of 6-9s.
For our given system the chance of 6-9s is about 92ns x 4.745 = 436ns
Which means given a reported time by PTP, contemplating a window measurement of 436ns round worth ensures to incorporate the true time by a confidence of over 99.9999%.
Compensation for holdover
Whereas all of the above appears to be like logical and nice, there’s a huge assumption there. The idea is that the connection to the open time server (OTS) is on the market, and every thing is in regular operation mode. A whole lot of issues can go improper such because the OTS taking place, swap taking place, Sync messages not behaving as they’re speculated to, one thing in between decides to get up the on-calls and so forth. In such a scenario the error sure calculation ought to enter the holdover mode. The identical issues apply to the OTS when GNSS is down. In such a scenario the system will improve the Window Of Uncertainty based mostly on a compound fee. The speed will probably be estimated based mostly on the steadiness of the oscillator (scrolling variance) throughout regular operations. On the OTS the compound fee will get adjusted by the correct telemetry monitoring of the system (Temperature, Vibration, and so forth). There’s a truthful quantity of labor by way of calibrating coefficients right here and attending to the perfect end result and we’re nonetheless engaged on these high-quality tunings.
Throughout the intervals of community synchronization availability, the servo is continually adjusting the frequency of the native clock on the consumer aspect (assuming the preliminary stepping resulted in convergence). A break within the community synchronization (from shedding connection to the time server or the time server itself taking place) will depart the servo with a final frequency correction worth. Consequently, such worth just isn’t aimed to be an estimation of precision of the native clock however as a substitute a short lived frequency adjustment to cut back the time error (offset) measured between the cline and the time server.
Due to this fact, it’s essential to first account for synchronization loss intervals and use the perfect estimation of frequency correction (often, the scrolling common of earlier correction values) and second, account for the error sure improve by wanting on the final correction worth and evaluating it with the scrolling common of earlier correction values.
How we monitor the PTP structure
Monitoring is among the most essential components of the PTP structure. Because of the nature and impression of the service, we’ve spent fairly a little bit of time engaged on the tooling.
Calnex
We labored with the Calnex staff to create the Sentinel HTTP API, which permits us to handle, configure, and export information from the gadget. At Meta, we created and open-sourced an API command line software permitting human and script pleasant interactions.
Utilizing Calnex Sentinel 2.0 we’re capable of monitor three most important metrics per time equipment — NTP, PTP, and PPS.
This enables us to inform engineers about any subject with the home equipment and exactly detect the place the issue is.
For instance, on this case each PTP and PPS monitoring resorts in a roughly lower than 100 nanosecond variation over 24 hours when NTP stays inside 8 microseconds.
ptpcheck
With a purpose to monitor our setup, we carried out and open-sourced a software referred to as ptpcheck. It has many various subcommands, however essentially the most fascinating are the next:
diag
Shopper subcommand gives an total standing of a ptp consumer. It stories the time of receipt of final Sync message, clock offset to the chosen time server, imply path delay, and different useful info:
$ ptpcheck diag
[ OK ] GM is current
[ OK ] Interval since final ingress is 972.752664ms, we count on it to be inside 1s
[ OK ] GM offset is 67ns, we count on it to be inside 250µs
[ OK ] GM imply path delay is 3.495µs, we count on it to be inside 100ms
[ OK ] Sync timeout rely is 1, we count on it to be inside 100
[ OK ] Announce timeout rely is 0, we count on it to be inside 100
[ OK ] Sync mismatch rely is 0, we count on it to be inside 100
[ OK ] FollowUp mismatch rely is 0, we count on it to be inside 100
fbclock
Shopper subcommand that permits querying of an fbclock API and getting a present Window of Uncertainty:
$ ptpcheck fbclock
"earliest_ns":1654191885711023134,"latest_ns":1654191885711023828,"wou_ns":694
sources
Chrony-style consumer monitoring, permits to see all Time Servers configured within the consumer configuration file, their standing, and high quality of time.
$ ptpcheck sources
+----------+----------------------+--------------------------+-----------+--------+----------+---------+------------+-----------+--------------+
| SELECTED | IDENTITY | ADDRESS | STATE | CLOCK | VARIANCE | P1:P2 | OFFSET(NS) | DELAY(NS) | LAST SYNC |
+----------+----------------------+--------------------------+-----------+--------+----------+---------+------------+-----------+--------------+
| true | abcdef.fffe.111111-1 | time01.instance.com. | HAVE_SYDY | 6:0x22 | 0x59e0 | 128:128 | 27 | 3341 | 868.729197ms |
| false | abcdef.fffe.222222-1 | time02.instance.com. | HAVE_ANN | 6:0x22 | 0x59e0 | 128:128 | | | |
| false | abcdef.fffe.333333-1 | time03.instance.com. | HAVE_ANN | 6:0x22 | 0x59e0 | 128:128 | | | |
+----------+----------------------+--------------------------+-----------+--------+----------+---------+------------+-----------+--------------+
oscillatord
Server subcommand, permits to learn a abstract from the Time Card.
$ ptpcheck oscillatord
Oscillator:
mannequin: sa5x
fine_ctrl: 328
coarse_ctrl: 10000
lock: true
temperature: 45.33C
GNSS:
repair: Time (3)
fixOk: true
antenna_power: ON (1)
antenna_status: OK (2)
leap_second_change: NO WARNING (0)
leap_seconds: 18
satellites_count: 28
survey_in_position_error: 1
Clock:
class: Lock (6)
offset: 1
For instance, we are able to see that the final correction on the Time Card was simply 1 nanosecond.
phcdiff
This subcommand permits us to get a distinction between any two PHCs:
$ ptpcheck phcdiff -a /dev/ptp0 -b /dev/ptp2
PHC offset: -15ns
Delay for PHC1: 358ns
Delay for PHC2: 2.588µs
On this explicit case the distinction between Time Card and a NIC on a server is -15 nanoseconds.
Shopper API
It’s good to set off monitoring periodically or on-demand, however we wish to go even additional. We wish to know what the consumer is definitely experiencing. To this finish, we embedded a number of buckets proper within the fbclock API based mostly on atomic counters, which increment each time the consumer makes a name to an API:

This enables us to obviously see when the consumer experiences a problem — and sometimes earlier than the consumer even notices it.
Linearizability checks
PTP protocol (and ptp4l particularly) don’t have a quorum choice course of (in contrast to NTP and chrony). This implies the consumer picks and trusts the Time Server based mostly on the data offered by way of Announce messages. That is true even when the Time Server itself is improper.
For such conditions, we’ve got carried out a final line of protection referred to as a linearizability examine.
Think about a scenario during which a consumer is configured to make use of three time servers and the consumer is subscribed to a defective Time Server (e.g., Time Server 2):

On this scenario, the PTP consumer will suppose every thing is okay, however the info it gives to the applying consuming time will probably be incorrect, because the Window of Uncertainty will probably be shifted and subsequently inaccurate.
To fight this, in parallel, the fbclock establishes communication with the remaining time servers and compares the outcomes. If nearly all of the offsets are excessive, this implies the server our consumer follows is the outlier and the consumer just isn’t linearizable, even when synchronization between Time Server 2 and the consumer is ideal.

PTP is for as we speak and the longer term
We imagine PTP will turn out to be the usual for preserving time in laptop networks within the coming a long time. That’s why we’re deploying it on an unprecedented scale. We’ve needed to take a vital have a look at our total infrastructure stack — from the GNSS antenna right down to the consumer API — and in lots of circumstances we’ve even rebuilt issues from scratch.
As we proceed our rollout of PTP, we hope extra distributors who produce networking tools will reap the benefits of our work to assist convey new tools that helps PTP to the trade. We’ve open-sourced most of our work, from our supply code to our {hardware}, and we hope the trade will be part of us in bringing PTP to the world. All this has all been completed within the identify of boosting the efficiency and reliability of the present options, but in addition with a watch towards opening up new merchandise, providers, and options sooner or later.
We wish to thank everybody concerned on this endeavor, from Meta’s inner groups to distributors and producers collaborating with us. Particular thanks goes to Andrei Lukovenko, who related time fans.
This journey is only one p.c completed.