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How Facebook Syncs Time Across Millions of Servers
How Facebook Syncs Time Across Millions of Servers
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Disclaimer: The details in this post have been derived from the Facebook/Meta Engineering Blog. All credit for the technical details goes to the Facebook engineering team. The links to the original articles are present in the references section at the end of the post. We’ve attempted to analyze the details and provide our input about them. If you find any inaccuracies or omissions, please leave a comment, and we will do our best to fix them.
A clock showing the wrong time is worse than a faulty clock.
This is the challenge Facebook had to deal with while operating millions of servers connected to the Internet and each other.
All of these devices have onboard clocks that are expected to be accurate. However, many onboard clocks contain inaccurate internal oscillators, which cause seconds of inaccuracy per day and need to be periodically corrected.
Think of these internal oscillators as the “heartbeat” of the clock. Just like how an irregular heartbeat can affect a person’s health, an inaccurate oscillator can cause the clock to gain or lose time.
Incorrect time can lead to issues with varying degrees of impact. It could be missing a simple reminder or failing a spacecraft launch.
As Facebook’s infrastructure has grown, time precision has become extremely important. For example, knowing the accurate time difference between two random servers in a data center is critical to preserving the order of transactions across these servers.
In this post, we’ll learn how Facebook achieved time precision across its millions of servers with NTP and later with PTP.
Network Time Protocol
Facebook started with Network Time Protocol (NTP) to keep the devices in sync.
NTP is a way for computers to synchronize their clocks over a network. It helps ensure that all devices on the network have the same, accurate time.
Having synchronized clocks is critical for many tasks, such as:
Scheduling events and meetings
Logging and tracking activities
Ensuring a proper sequence of transactions
Coordinating actions between different systems
NTP uses a hierarchical system of time servers where the most accurate servers are at the top. There is a 3-step process to how NTP works:
Computers on the network periodically request the current time from these servers.
The servers respond with their current time taking into account the network delay.
The requesting computer adjusts its clock based on the information received from the server.
The diagram below shows the hierarchical system of servers used by NTP.
Facebook built an NTP service at scale. They used chrony, a modern NTP server implementation. While they used the ntpd service initially, testing revealed that chrony was far more accurate and scalable.
Chrony was a fairly new daemon at the time, but it offered a chance to bring the precision down to nanoseconds. Also, from a resource consumption perspective, chrony consumed less RAM compared to ntpd.
See the diagram below that shows the difference of around 1MB when it came to RAM consumption between chrony and ntpd.
Source: Facebook Engineering Blog They designed the NTP service in four layers based on the hierarchical structure of NTP.
Stratum 0 is a layer of satellites with precise atomic clocks from a global navigation satellite system (GNSS), such as GPS, GLONASS, or Galileo.
Stratum 1 is a Facebook atomic clock synchronizing with a GNSS.
Stratum 2 is a pool of NTP servers synchronizing to the Stratum 1 devices.
Lastly, Stratum 3 is a tier of servers configured for a larger scale.
The diagram below shows the layers of Facebook’s NTP service.
Source: Facebook Engineering Blog There are a couple of interesting concepts to note over here:
Leap second
Smearing
The Earth’s rotation is not consistent and can vary slightly over time. Therefore, clocks are kept in sync with the Earth’s rotation by occasionally adding or removing a second. This is called a leap second.
While adding or removing a leap second is hardly noticeable to humans, it can cause server issues. Servers expect time to move forward continuously, and a sudden change of a second can cause them to miss important tasks.
To mitigate the impact of leap seconds on servers, a technique called “smearing” is used.
Instead of adding or removing a full second at once, the time is gradually adjusted in small increments over several hours. It’s similar to masking a train’s delay by spreading the adjustment across multiple stations.
In the case of Facebook’s NTP service, the Leap-second smearing happens at Stratum 2. The Stratum 3 servers receive smeared time and are ignorant of leap seconds.
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The Arrival of Precision Time Protocol
NTP adoption was quite successful for Facebook. It helped them improve accuracy from 10 milliseconds to 100 microseconds.
However, as Facebook wanted to scale to more advanced systems and build the metaverse, they wanted even greater levels of accuracy.
Therefore, in late 2022, Facebook moved from NTP to Precision Time Protocol (PTP).
There were some problems with NTP, which are as follows:
NTP and Asynchronous Systems: Systems using NTP are asynchronous, meaning they work independently without a shared global clock. These systems periodically check in with each other to ensure synchronization. However, as the system grows larger, more check-ins are required, which can slow down the network.
NTP and Timekeeping Methods: NTP is susceptible to variance and latency due to its timekeeping methods of using physical clocks. In other words, NTP is like a microwave clock that keeps time on-device. If there’s a time change (e.g., daylight savings), the clock needs to be manually adjusted.
In contrast, PTP works like a smartphone clock that updates its time automatically. When there’s a time change or the phone moves to a new time zone, the clock updates itself by referencing the time over a network.
While NTP provided millisecond-level synchronization, PTP networks could hope to achieve nanosecond-level precision.
What makes PTP More Effective?
As discussed earlier, a special computer called a Stratum acts as a time reference for other computers on a network. When a computer needs to know the current time, it sends a request to the Stratum, which replies with the current time. This process is known as sync messaging.
When the Stratum sends the current time to another computer, the information travels across the network, resulting in some latency. Several factors can increase this latency, such as:
The speed at which signals travel through the fiber optic cables.
The time it takes for the network devices to convert signals.
The quality of network equipment, like routers and switches.
The time it takes for software and drivers to process the time information.
Due to latency, the time received by the other computer is no longer accurate when it arrives at the receiving computer.
The obvious solution is to measure the latency and add it to the time received by the other computer to get a more accurate time. However, measuring latency is challenging because each computer has its clock, and there is no universal clock to compare against.
To measure latency, two assumptions about consistency and symmetry are made:
The latency a packet experiences while traveling across the network is consistent.
The latency from the Stratum to the other computer is equal to the latency from the other computer back to the Stratum. In other words, the network is symmetric.
Therefore, it follows that the accuracy of time synchronization can be improved by maximizing consistency and symmetry in the network.
PTP is a solution that helps achieve this.
PTP uses hardware timestamping to improve consistency. This means that timestamps are added to the time information at the hardware level, reducing the impact of software and driver delays.
PTP also uses transparent clocks, which are special devices that measure and compensate for the time the information spends passing through network equipment.
The Need for PTP
Let’s look at a practical case where PTP is needed.
Imagine you’re using Facebook and you post a new status update. When you try to view your post, there’s a chance that your request to see the post is handled by a different server than the one that originally processed your post.
If the server handling your view request doesn’t have the latest updated data, you might not see your post. This is annoying for users and goes against the promise that interacting with a distributed system like Facebook should work the same as interacting with a single server that has all the data.
In the old solution, Facebook used to send your view request to multiple servers and wait for a majority of them to agree on the data before showing it to you. But this takes up extra computing resources and adds delay because of the back-and-forth communication over the network.
By using PTP to keep precise time synchronization across all its servers, they can simply have the view request wait until the server has caught up to the timestamp of your original post. There is no need for multiple requests and responses.
The diagram below shows this scenario.
However, this only works if all the server clocks are closely synchronized. Also, the difference between a server’s clock and the reference time needs to be known.
PTP provides this tight synchronization. It could synchronize time about 100 times more precisely than NTP, which was necessary for Facebook’s requirement.
This was just one example. There were several additional use cases where PTP excelled such as:
Event tracing
Cache invalidations
Privacy violation detection improvements
Latency compensation in the metaverse
The PTP Architecture
Facebook’s PTP architecture consists of three main components:
The PTP Rack
The PTP Network
The PTP Client
See the diagram below for a high-level view of the architecture:
Source: Facebook Engineering Blog Let’s look at each component and understand how they work together to provide precise timekeeping.
The PTP Rack
The PTP rack houses the hardware and software that serve time to clients.
It consists of critical components such as:
GNSS Antenna: This is where time originates on Earth. The antenna receives time signals from GPS, Galileo, and other satellite constellations. Facebook uses a GNSS-over-fiber technology to distribute the signal, which is more reliable and easier to install than traditional coaxial cables.
Time Appliance: This is the heart of the timing infrastructure. It disciplines the time received from the GNSS antenna using atomic clocks for improved accuracy and stability. Facebook has developed a new Time appliance that can support up to 1 million clients without compromising accuracy.
Oscillatord: This is a software component that configures and monitors the Time appliance, including the GNSS receiver and atomic clocks. It exports data that helps decide if the Time Appliance should serve clients or be taken offline.
Network Card (NIC): It’s the interface between the Time Appliance and the network. It timestamps PTP packets using its clock, which is synchronized with the Time Appliance for nanosecond-level accuracy.
Ptp4u: This is Facebook’s custom-built PTP server software that can handle over 1 million clients per server, far more than existing solutions. It runs on the Time Appliance and sends PTP messages to the clients.
The GNSS Antenna in a Datacenter (Source: Facebook Engineering Blog) The PTP Network
The PTP network is responsible for distributing time from the PTP rack to clients. Facebook uses PTP over a standard IP network with a few key enhancements:
PTP Unicast: They use unicast PTP instead of multicast for simpler network configuration and better scalability. Clients request time from servers, and servers grant requests and send PTP messages.
Transparent Clocks: Each network switch between the client and server acts as a transparent clock. It measures the time each PTP packet spends in the switch and records it in the packet. This allows clients to accurately account for network delays.
Boundary Clock Avoidance: Facebook avoided using boundary clocks, which act as both clients and servers, to reduce complexity. They rely solely on transparent clocks in the network switches.
A typical PTP unicast flow consists of the following steps:
Client Initiates Negotiation: The PTP client starts the process by requesting unicast transmission from the PTP server. It sends three types of requests:
Sync Grant Request: The client asks the server to send a specified number of Sync and Follow-Up messages per second, containing the current time, for a certain duration. This helps the client adjust its clock to match the server’s clock.
Announce Grant Request: The client requests the server to send a specific number of Announce messages per second, containing the server’s status, for a certain duration. This helps the client make sure that the server hasn’t stopped or gone haywire.
Delay Response Grant Request: The client informs the server that it will send Delay Request messages, and asks the server to respond with Delay Response packets for a specified duration. This helps the client account for any delay in communication.
Server Grants Requests: The PTP server needs to grant these requests and send corresponding grant responses to the client.
Server Sends PTP Messages: Once the requests are granted, the server starts sending the requested PTP messages
Client Sends Delay Requests: The client sends Delay Request messages to the server at the agreed-upon interval to determine the network path delay.
Client Refreshes Grant: The client needs to periodically refresh the grant by repeating the negotiation process before the current grant expires.
The diagram below shows the PTP Exchange Process
The PTP Client
The PTP client software runs on each server that needs accurate time. Facebook uses a few different components:
ptp4I: An open-source PTP client that receives PTP messages from the server and disciplines the NIC hardware clock. Facebook has made several enhancements to ptp4I to handle its scale and unique requirements.
fbclock: This is Facebook’s custom API that provides PTP time to applications. Instead of a single timestamp, it gives a “window of uncertainty” - a time range that is guaranteed to contain the true time with a high degree of certainty.
Kernel Timestamping: The Linux kernel on each server timestamps incoming and outgoing PTP packets in hardware for maximum accuracy. This relies on NIC driver support and careful configuration.
Conclusion
To conclude, Facebook’s adoption of Precision Time Protocol (PTP) across its infrastructure is a significant step forward in ensuring precise and reliable timekeeping at an unprecedented scale. By redesigning and rebuilding various components, Facebook has pushed the boundaries of what’s possible with PTP.
Also, the open-source nature of most of the work helps us learn from the PTP solution implemented by them.
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Few global companies can afford to ignore the growing importance of India. As the world’s fifth-largest economy, with a rapidly expanding middle class and one of the largest consumer markets in the world, India presents promising opportunities in almost every sector, from chemicals to healthcare to fashion. But many challenges remain. In a new article on India—part of our McKinsey Explainers series—we discuss seven factors shaping the country, and this week, we explore some of these trends in depth.
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That’s the amount that agriculture could contribute to India’s GDP by 2030—if the country can ramp up modern farming techniques with agricultural technology, or agtech. In 2022, venture capitalists invested more than $1.2 billion in Indian agtech companies, a 50 percent increase from the previous year and triple the investment made in 2020. But investors in Indian agtech may want to consider some basic issues first, suggest McKinsey senior partner Avinash Goyal and colleagues. For example, it’s important for the agtech to have both physical and digital infrastructure, as most farming households still prefer physical touchpoints for digital support, such as tutorials and ground visits to help with app installation.
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Why is the credit card called “the most profitable product in banks”?
How does VISA/Mastercard make money?
The diagram below shows the economics of the credit card payment flow.
1. The cardholder pays a merchant $100 to buy a product.
2. The merchant benefits from the use of the credit card with higher sales volume, and needs to compensate the issuer and the card network for providing the payment service. The acquiring bank sets a fee with the merchant, called the “𝐦𝐞𝐫𝐜𝐡𝐚𝐧𝐭 𝐝𝐢𝐬𝐜𝐨𝐮𝐧𝐭 𝐟𝐞𝐞.”
3 - 4. The acquiring bank keeps $0.25 as the 𝐚𝐜𝐪𝐮𝐢𝐫𝐢𝐧𝐠 𝐦𝐚𝐫𝐤𝐮𝐩, and $1.75 is paid to the issuing bank as the 𝐢𝐧𝐭𝐞𝐫𝐜𝐡𝐚𝐧𝐠𝐞 𝐟𝐞𝐞. The merchant discount fee should cover the interchange fee.
The interchange fee is set by the card network because it is less efficient for each issuing bank to negotiate fees with each merchant.
5. The card network sets up the 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 𝐚𝐬𝐬𝐞𝐬𝐬𝐦𝐞𝐧𝐭𝐬 𝐚𝐧𝐝 𝐟𝐞𝐞𝐬 with each bank, which pays the card network for its services every month. For example, VISA charges a 0.11% assessment, plus a $0.0195 usage fee, for every swipe.
6. The cardholder pays the issuing bank for its services.
Why should the issuing bank be compensated?The issuer pays the merchant even if the cardholder fails to pay the issuer.
The issuer pays the merchant before the cardholder pays the issuer.
The issuer has other operating costs, including managing customer accounts, providing statements, fraud detection, risk management, clearing & settlement, etc.
Over to you: Does the card network charge the same interchange fee for big merchants as for small merchants?
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What is a Load Balancer?
A load balancer is a device or software application that distributes network or application traffic across multiple servers.
What Does a Load Balancer Do?
1. Distributes Traffic
2. Ensures Availability and Reliability
3. Improves Performance
4. Scales ApplicationsTypes of Load Balancers
1. Hardware Load Balancers: These are physical devices designed to distribute traffic across servers.
2. Software Load Balancers: These are applications that can be installed on standard hardware or virtual machines.
3. Cloud-based Load Balancers: Provided by cloud service providers, these load balancers are integrated into the cloud infrastructure. Examples include AWS Elastic Load Balancer, Google Cloud Load Balancing, and Azure Load Balancer.
4. Layer 4 Load Balancers (Transport Layer): Operate at the transport layer (OSI Layer 4) and make forwarding decisions based on IP address and TCP/UDP ports.
5. Layer 7 Load Balancers (Application Layer): Operate at the application layer (OSI Layer 7) .
6. Global Server Load Balancing (GSLB): Distributes traffic across multiple geographical locations to improve redundancy and performance on a global scale.
Top 10 k8s Design Patterns
Foundational Patterns
These patterns are the fundamental principles for applications to be automated on k8s, regardless of the application's nature.
1. Health Probe Pattern
This pattern requires that every container must implement observable APIs for the platform to manage the application.
2. Predictable Demands Pattern
This pattern requires that we should declare application requirements and runtime dependencies. Every container should declare its resource profile.
3. Automated Placement Pattern
This pattern describes the principles of Kubernetes’ scheduling algorithm.Structural Patterns
These patterns focus on structuring and organizing containers in a Pod.
4. Init Container Pattern
This pattern has a separate life cycle for initialization-releated tasks.
5. Sidecar Pattern
This pattern extends a container’s functionalities without changing it.Behavioral Patterns
These patterns describe the life cycle management of a Pod. Depending on the type of the workload, it can run as a service or a batch job.
6. Batch Job Pattern
This pattern is used to manage isolated atomic units of work.
7. Stateful Service Pattern
This pattern creates distributed stateful applications.
8. Service Discovery Pattern
This pattern describes how clients discover the services.Higher-Level Patterns
These patterns focus on higher-level application management.
9. Controller Pattern
This pattern monitors the current state and reconciles with the declared target state.
10. Operator Pattern
This pattern defines operational knowledge in an algorithmic and automated form.
Reference: developers.redhat. com/blog/2020/05/11/top-10-must-know-kubernetes-design-patterns
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by "ByteByteGo" <bytebytego@substack.com> - 11:35 - 3 Aug 2024 -
The 15 tech trends to watch
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Given the rapid pace of tech advancements—and the tech-related disruptions companies need to navigate—planning for the long-term tech future might seem daunting. But that’s exactly what companies must do, say McKinsey’s Lareina Yee, Michael Chui, Roger Roberts, and Mena Issler. In this month’s featured story, the McKinsey Technology Council identifies the 15 most significant technology trends unfolding today, including new areas like digital trust and cybersecurity, and underscores the need for companies to invest meaningfully as they transition from experimentation to broader implementation. Our second featured story covers three actions that data and AI leaders can consider to help them move from generative AI (gen AI) pilots to scaling data solutions. Other highlights include the following topics:
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how CFOs view the future of finance
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ideas that leaders risk overlooking with gen AI in the spotlight
•
the benefits of embracing healthy longevity
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resilience strategies from a two-time Olympic gold medalist
Toward the long term: CFO perspectives on the future of finance
In a new survey, CFOs report a growing focus on longer-term planning and high expectations for technology, including generative AI.
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Gen AI and beyond: Where else to focus now
Yes, gen AI can be dazzling. But to deliver value, leaders will have to look beyond center stage.
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The ‘evergreen economy’: Harnessing the power of healthy longevity
Economist Andrew J. Scott, author of The 100-Year Life and The Longevity Imperative, discusses the opportunity for positive and profound change in an aging society.
Live a healthier, more engaged life
In the long run: What leaders can learn from an Olympic gold medalist
Alistair Brownlee, a two-time Olympic gold medalist, shares his strategies for staying resilient amid pushback, removing barriers to creating habits, and leading with conviction.
Take it from a champ
Supply chain ‘goes rouge’: Inside Coty’s makeover
Coty chief global supply chain officer Graeme Carter explains how the beauty company’s people-first approach to digital and AI is helping it reach its goals.
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Where procurement is going next
Our latest procurement benchmarking data reveals the tools, capabilities, and ways of working that are helping leading companies protect their profits in turbulent times.
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by "McKinsey Highlights" <publishing@email.mckinsey.com> - 11:27 - 3 Aug 2024 -
Are you preventing middle managers from delivering value in their roles?
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The beleaguered middle layer. It’s been one year since McKinsey partners Emily Field and Bryan Hancock and senior partner emeritus Bill Schaninger published their book, Power to the Middle. Results of a 2023 survey developed by Field, Hancock, Schaninger, and Marino Mugayar-Baldocchi show that by treating middle management as a catchall, many companies may be unintentionally thwarting middle managers’ ability to perform in their roles.
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Buried in paperwork. The survey findings suggest that middle managers are stuck in the menial, spending nearly one full day out of every week on administrative work. Although these respondents are all people managers, on average they say they spend less than a third of their time on talent and people management. See three areas where companies could better support middle managers to deliver value, and discover Power to the Middle: Why Managers Hold the Keys to the Future of Work on its one-year anniversary.
—Edited by Belinda Yu, editor, Atlanta
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by "Only McKinsey" <publishing@email.mckinsey.com> - 01:11 - 2 Aug 2024 -
A Crash Course on Domain-Driven Design
A Crash Course on Domain-Driven Design
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Developing software for complex domains is a challenging task.
As the complexity of the problem domain grows, it becomes increasingly difficult to create software that accurately represents the business concepts, rules, and processes. Poorly designed software can quickly turn into an incomprehensible tangle of code that is difficult to understand, maintain, and extend.
Domain-Driven Design (DDD) offers a solution to this problem.
DDD is an approach to software development that tackles domain complexity by emphasizing the importance of modeling the core domain and business logic and using those models as the foundation for software design.
At its heart, Domain-Driven Design is about:
Placing the primary focus on the core domain.
Basing complex designs on a model of the domain
Building collaboration between technical and domain experts.
The need for Domain-Driven Design has become more pressing in recent years. Architectures based on microservices and cloud computing have resulted in systems composed of numerous small components that interact in intricate ways. Without a clear and well-defined model of the domain guiding their design, such systems can quickly become a "big ball of mud".
In this article, we’ll understand the basics of Domain-Driven Design and its key concepts that can help us build more maintainable and extensible systems that are aligned with the core domain and business logic.
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by "ByteByteGo" <bytebytego@substack.com> - 11:36 - 1 Aug 2024
