What caused Facebooks recent outage?

7

October

2021

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On Monday the 4th of October, Facebook was hit by its largest outage since 2019. Facebook alongside its platforms including WhatsApp, Instagram, and Messenger went down for nearly six hours, impacting 3.5 billion users globally (Martin, 2021). The disruption was felt widespread, not only impacting external users but internal communication networks went dark as well. Its impact was felt the hardest by content creators and small businesses that are heavily dependent on these platforms for sources of income (Lawler & Heath, 2021). 

Facebook released a statement on Tuesday, saying that a faulty configuration change in the backend of the system was at fault (Janardhan, 2021). Normally, the system tells routers that are trying to access information where the relevant data centers are located. On Monday however, it seemed to routers that these data centers did not exist, promoting a total wipeout of Facebook’s internal and external servers.

Later that day Cloudflare, a company that also recently experienced such an outage provided a more detailed explanation of what happened. Essentially the internet runs off of two systems, Domain Name System (DNS), and Border Gateway Protocol (BGP)(Taylor, 2021). DNS acts as an address book for all websites, where the Internet Protocol (IP address) of a website is stored. Whereas the BGP closely resembles what we refer to as a GPS, a system that configures the most efficient pathway to get to that IP address. After an update from Facebook, the BGP was unable to compute a pathway to the respective IP address (Taylor, 2021). Consequently millions of users were unable to access the platforms of Facebook. 

Such malfunctions are quite common and fixing them is normally rather straightforward. A couple of debugs and a reboot of the data centers are usually sufficient and can be done remotely. However, in the case of Facebook, the system used to access the data centers was the same network that went dark. Therefore the only solution was for data scientists and experts to physically go to the affected data centers. Upon arrival, the experts incurred another issue which was that the access cards to these data centers were also dependent on the internal network (which were also down) (Martin, 2021). Causing a major delay, eventually taking experts close to six hours to resolve the issue. 

Facebook’s recent outage has surprised many users and experts worldwide. Prompting the question, how it is possible that one of the most influential and used companies in the world runs its systems through the same network? Luckily Facebook was able to react decently quickly and restore the issue within a few hours. It will be interesting to investigate the developments Facebook will take to ensure users that such a widespread outage will not occur again. 

Sources:

Janardhan, S. (2021). Update about the October 4th outage. Facebook Engineering. Retrieved 7 October 2021, from https://engineering.fb.com/2021/10/04/networking-traffic/outage/.

Jordan, B. (2020). Facebook [Image]. Retrieved 7 October 2021, from https://unsplash.com/photos/tWX_ho-328k. 

Lawler, R., & Heath, A. (2021). Facebook is back online after a massive outage that also took down Instagram, WhatsApp, Messenger, and Oculus. The Verge. Retrieved 7 October 2021, from https://www.theverge.com/2021/10/4/22708989/instagram-facebook-outage-messenger-whatsapp-error.

Martin, A. (2021). Facebook outage: What actually caused WhatsApp and Instagram to go down?. Sky News. Retrieved 7 October 2021, from https://news.sky.com/story/facebook-outage-what-actually-caused-whatsapp-and-instagram-to-go-down-12426383.

Taylor, J. (2021). Facebook outage: what went wrong and why did it take so long to fix after social platform went down?. the Guardian. Retrieved 7 October 2021, from https://www.theguardian.com/technology/2021/oct/05/facebook-outage-what-went-wrong-and-why-did-it-take-so-long-to-fix.

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Are Data Scientists replacing Football agents?

2

October

2021

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It is an undeniable reality that data science has been increasingly adopted in sports, and its outcomes have been prolific. What was once a relatively unknown concept two decades ago has totally transformed the industry, which is predicted to be valued at $4.4 billion by 2022 (Sri, 2021). Its popularity is due to its potential application in seemingly every aspect of sports, from scouting a new prodigy to improving a golf swing or predicting the direction of penalty kicks (source). 

Laurie Shaw, a former astrophysicist, and Treasury policy adviser in the UK, made headlines in January by joining Premier League champions Manchester City (Harper, 2021). His first-team role is to lead the development of data science, in order to predict future events. Whereas, data science currently is being used to analyze past events. Therefore this development has the potential to further enhance the competitive advantage of the English Champions. The signing of such a high-profile data scientist, prompts the question; are data scientists becoming the new golden signings in the football industry? It is absolutely clear that data science is here to stay, and its impact will incrementally grow on an industrial level. What about on a more business level?

In April of 2021, Manchester City captain, Kevin de Bruyne, took the media by storm, ’Kevin De Bruyne uses data analysts to broker £83m Man City contract without an agent (McDonnell, 2021)’. The decision to go against traditional forms of negotiation in sports was previously unseen in European football. The process of negotiation in football mostly follows the hiring of an agent. These individuals are often ruthless and in combination with their strong network, often succeed in fulfilling the demands of the player, at a very high cost. Agents normally take around 5-10% of the negotiated purchasing price and salary (Hendley, 2021). In the case of Kevin de Bruyne, this figure would have exceeded 15+ million pounds.

The football star was able to innovatively leverage his impact from all the games he’s played for the club, in terms of his contributions to the club’s success over the past four years. Whilst also predicting the impact impact in the future and the economic value he will add to the organization. The case of Kevin de Bruyne was the first with a player of such magnitude, in European football. Not only was he able to gain a 30% increase in wage, he also managed to avoid the excessive costs associated with traditional forms of negotiation (Vulpen, 2021). Evidently, the application potential of data science in sports is vast. More recently, it has proved an effective tool for negotiation and will most probably be widely adopted in the future, as it is already doing so in NBA and NFL. 

Sources:

Sri, T. (2021). How is big data analytics changing sports?. Selerity. Retrieved 2 October 2021, from https://seleritysas.com/blog/2021/03/27/how-is-big-data-analytics-changing-sports/.

Harper, J. (2021). Data experts are becoming football’s best signings. BBC News. Retrieved 2 October 2021, from https://www.bbc.com/news/business-56164159.

McDonnell, D. (2021). De Bruyne uses data analysts to broker £83m Man City contract without agent. Mirror. Retrieved 2 October 2021, from https://www.mirror.co.uk/sport/football/news/kevin-de-bruyne-uses-data-23870686.

Hendley, A. (2021). How much money football agents earn – and how you become one. Mirror. Retrieved 2 October 2021, from https://www.mirror.co.uk/sport/football/news/how-much-money-football-agents-14580322.

Vulpen, E. (2021). How a Soccer Player Hired Data Scientists for Contract Negotiations | AIHR Blog. AIHR. Retrieved 2 October 2021, from https://www.aihr.com/blog/kevin-de-bruyne/.

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