All the 9s in the World Won't Save You from Taylor Swift
November 18, 2022

Marcus Merrell
Sauce Labs

Share this

Let me explain.

It's a time-honored tradition to drag ticketing platforms through the mud. There's no easier blog to write than the one that bags on an entire industry for pricing, fees, and a monopoly on live events. The president is even getting in on it. True or not, that's not my purpose here.

I want to talk about software testing.

Look, no matter how you think about online ticket brokers, what they're trying to do is really hard. I'm not talking about their business, events management, artist contracts or any of that. I'm talking about the logistics of creating a software platform with ultra-high-volume ticket sales that come in dramatic bursts.

The event covered here occurred at the intersection of three different kinds of testing: performance, security, and chaos. I've never worked or consulted for a company where these were done by the same team — folklore has it that the teams doing this testing generally don't even work directly with the people responsible for the areas they're testing!

Each of these is a career path unto itself. Many books have been written, and much venture capital has spilled into companies centered around them.

Why don't they talk to each other?


It's important to understand the convergence of these disciplines, lest you live in perpetual fear of the Swifties.

What Happened

On November 1, Taylor Swift announced the Eras Tour, her 6th world tour, commemorating the release of her 10th studio album. Presales tickets popped up on a major ticketing site, which promptly groaned, creaked, and fell over. Fearless Swifties hammered the site without mercy, and as the small Utah theme park called "Evermore" found out, that can be a problem.

Unlike the decidedly low-tech method available to me when I bought Van Halen tickets from the grocery store in 1989, the whole world is now standing in the same virtual queue, and even the most durable cloud architecture can't handle this level of deluge.

People will abandon a brand in a flash when they don't have a good experience, so when they don't have a choice about where they get their tickets from, they turn to the best tools they have (TikTok, Twitter, and Instagram) for their outrage.

We Are Measured In Uptime

Your reputation is measured in 9s. If you have "3 9s of reliability," your site is up 99.9% of the time. In the early 2010s, this was the gold standard, even though it meant you could only be in the red for 8h 46m in a year (about 10 minutes a week). This was the early days of cloud computing, distributed architecture, regional failover, and SRE.

Now, 4- and 5-9s is the standard — you don't even have seconds before Reddit sees hundreds of angry posts. The average Taylor Swift lover doesn't care if you have 99.999% up-time (5:16 of outage per year). The only time Swifties are even looking at your ticketing site is during that 5 minutes of outage!


That is a very powerful, very loud, very large group of people to be angry with you all at once. This isn't just ticketing platforms — it extends to game releases, the newest iPhone, Marvel movies, mortgage interest rate changes, bank runs, toilet paper hoarding and many, many more.

Performance Testing

Any time you have a large number of requests sent to a service with finite resources, you risk it being overrun.

Not just API-based performance testing, but also functional performance testing, preferably with multiple browsers and mobile devices, done from multiple data centers around the US (or around the world) to ensure you can cover traffic with different latencies, different geographic origin, etc.

Most performance testing seems to be done from internal infrastructure, and this is where I would urge you to rely on cloud providers to give you the diversity of region, machine type, and device. It also requires deep monitoring and error reporting to be embedded into production systems.

Security Testing

Once hackers get wind that a site is down for one reason, they can look for open pathways to attack other parts of the system. They can even start to anticipate this when they know that particular businesses are regularly brought down by large traffic volumes!

And this isn't just penetration and hacker testing, but also DDOS testing, and making sure your systems are resilient to more than code attacks. When a microservice is brought down by an attack, it can be like an open pipe — one that runs in both directions. You need to make sure a partial system outage doesn't render the rest of your system open to unintended uses of your APIs.

Chaos Testing

This issue is related to chaos testing because, well, it's right there in the word: a situation arises where not only do you not control, but also you don't even know what's going on in various parts of the system.

Chaos testing isn't as widespread as it should be. Companies that do have dedicated teams and infrastructure enjoy a level of confidence in their system that inspires envy in others, but they also tend to work in isolation. If they have their own environment, segregated from the dev/test environments, it's often not known how their work can apply to other teams (unless they uncover something huge). They need to work with Security and Performance testing teams to make sure that systems can expect the unexpected, and that failover systems work as designed.

Conclusion

This issue is related to all three of these disciplines because you simply can't cover this with a single methodology. People tend to think of QA as one monolithic blob of overlapping skill sets, but there are significant differences between the craft, the threats, and the risk profile covered by each. I can't give you the recipe for how to fix it, except to say that it's going to depend on your particular situation, and the human element of how your teams communicate. Risk modeling for this needs to be hyper-collaborative.

This requires strong executive leadership, as well as a good understanding of the blast radius of these failures. It's not only very difficult, but until recently I'd argue that it wasn't possible.

My advice to all these teams: get into a room together and speak, now, unless you want these headlines to keep waking you up on random midnights!

Thank goodness BTS is on a break — now you have some time to prepare; though I hear Harry Styles has a lot going on …

Marcus Merrell is VP of Technology Strategy at Sauce Labs
Share this

The Latest

February 21, 2024

Generative AI will usher in advantages within various industries. However, the technology is still nascent, and according to the recent Dynatrace survey there are many challenges and risks that organizations need to overcome to use this technology effectively ...

February 20, 2024

In today's digital era, monitoring and observability are indispensable in software and application development. Their efficacy lies in empowering developers to swiftly identify and address issues, enhance performance, and deliver flawless user experiences. Achieving these objectives requires meticulous planning, strategic implementation, and consistent ongoing maintenance. In this blog, we're sharing our five best practices to fortify your approach to application performance monitoring (APM) and observability ...

February 16, 2024

In MEAN TIME TO INSIGHT Episode 3, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at Enterprise Management Associates (EMA) discusses network security with Chris Steffen, VP of Research Covering Information Security, Risk, and Compliance Management at EMA ...

February 15, 2024

In a time where we're constantly bombarded with new buzzwords and technological advancements, it can be challenging for businesses to determine what is real, what is useful, and what they truly need. Over the years, we've witnessed the rise and fall of various tech trends, such as the promises (and fears) of AI becoming sentient and replacing humans to the declaration that data is the new oil. At the end of the day, one fundamental question remains: How can companies navigate through the tech buzz and make informed decisions for their future? ...

February 14, 2024

We increasingly see companies using their observability data to support security use cases. It's not entirely surprising given the challenges that organizations have with legacy SIEMs. We wanted to dig into this evolving intersection of security and observability, so we surveyed 500 security professionals — 40% of whom were either CISOs or CSOs — for our inaugural State of Security Observability report ...

February 13, 2024

Cloud computing continues to soar, with little signs of slowing down ... But, as with any new program, companies are seeing substantial benefits in the cloud but are also navigating budgetary challenges. With an estimated 94% of companies using cloud services today, priorities for IT teams have shifted from purely adoption-based to deploying new strategies. As they explore new territories, it can be a struggle to exploit the full value of their spend and the cloud's transformative capabilities ...

February 12, 2024

What will the enterprise of the future look like? If we asked this question three years ago, I doubt most of us would have pictured today as we know it: a future where generative AI has become deeply integrated into business and even our daily lives ...

February 09, 2024

With a focus on GenAI, industry experts offer predictions on how AI will evolve and impact IT and business in 2024. Part 5, the final installment in this series, covers the advantages AI will deliver: Generative AI will become increasingly important for resolving complicated data integration challenges, essentially providing a natural-language intermediary between data endpoints ...

February 08, 2024

With a focus on GenAI, industry experts offer predictions on how AI will evolve and impact IT and business in 2024. Part 4 covers the challenges of AI: In the short term, the rapid development and adoption of AI tools and products leveraging AI services will lead to an increase in biased outputs ...

February 07, 2024

With a focus on GenAI, industry experts offer predictions on how AI will evolve and impact IT and business in 2024. Part 3 covers the technologies that will drive AI: The question on every leader's mind in 2023 was - how soon will I see the return on my AI investment? The answer may lie in quantum computing ...