Dependability is Crucial for Real-Time Experiences

Millions of people around the world experienced a major disruption after an October 2021 outage saw Facebook, WhatsApp and Instagram go offline. A few days prior, the popular workplace collaboration platform, Slack, also went down for some users. And in the last few weeks of 2021, Amazon’s AWS caused considerable global chaos after significant networking issues in its busiest data center, US East 1, disrupting streaming services such as Disney+ and Netflix.

Downtime can be costly, causing organizations to lose $5,600 per minute and up to $300,000 per hour, on average, according to Gartner. But it’s not only financial and reputational loss that businesses need to worry about. Outages also seriously downgrade—and in the case of real-time experiences, completely disruptive—the customer experience.

At a time when consumers are demanding more live and interactive digital experiences, organizations can ill afford disruption or downtime, as customers quickly move to other services that ‘just work’.

It’s not just the capacity within a real-time system that matters, but also globally distributed failover capabilities when something does go wrong. While organizations could try to build their own failover mechanisms, it’s extremely difficult to failover so services continue seamlessly, regardless of the status of its underlying infrastructure. Simple failover systems not only take longer to resume but typically suffer data loss during the time that a region is disrupted. Businesses need to know that even if, say, AWS suffers an outage, they won’t be affected.

This is why it’s vital that organizations get it right when looking to develop their own real-time infrastructure. Managing tens of thousands if not hundreds of thousands of concurrent connections while synchronizing data in real-time means that if anything does go wrong it’s immediately obvious to users. If tech behemoths like Amazon and Facebook can’t get it right, what chance do organizations with far fewer resources have when building and managing their own real-time infrastructure?

The Steps to Success With Real-Time Infrastructure

Regardless of whether it’s for synchronized multi-user collaboration, audience engagement or instant updates, developers have a hard enough time developing even the most basic of real-time infrastructure, let alone making sure it’s dependent. There are four key elements to achieve dependability: Predictable performance, data integrity, reliability of service and high scalability.

  • Predictable pperformance: When we think of performance we usually imagine more computing power or speed. But when it comes to real-time, it’s not just about minimizing latency and bandwidth, it’s about having a predictable system. If developers have global latencies and bandwidth within certain operating boundaries, it provides certainty in uncertain operating conditions. This makes it easier to design, build and scale features around this certainty.
  • data integrity: As we all know, the internet can be an unreliable network. Users abruptly disconnect and reconnect all the time, resulting in data that gets lost, is delivered in the wrong sequence or that is sent multiple times. As a result, organizations must ensure their infrastructure can guarantee high integrity without sacrificing anything else.
  • Reliability of service: The live nature of delivering updates in real-time requires total reliability. Outages can cause distrust and annoyance from users. Organizations could find their reputation taking a hit or customers quickly jumping ship if reliability proves to be a recurring issue. To prevent this, organizations should develop infrastructure that’s fault-tolerant and redundant at both a global and regional level so they can deliver a great experience even if there are multiple failures.
  • High scaley: More often than not, delivering an experience in real-time can result in unpredictable traffic; for example, a huge number of people wanting sports updates for a World Cup game. If thousands of devices connect over a short period of time but capacity can’t scale up quickly enough, then an outage will occur. To avoid this, developers must use infrastructure that can be elastic and meet changing levels of demand. Otherwise, the user experience is seriously affected and real-time capabilities crash when the network is swamped with connections it can’t cope with.

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