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<title>Non-intuitive downtime and possibly not lost sales - UnixDaemon: In search of (a) life</title>
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<h1 class="title" itemprop="name">Non-intuitive downtime and possibly not lost sales</h1>
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<div class="date"><time datetime='Mon, May 29, 2017' data-updated="true" itemprop="datePublished">Mon, May 29, 2017</time>
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<a href="https://www.unixdaemon.net/categories/online"> online </a>
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<div class="entry-content" itemprop="articleBody"><p>One of the things you’ll often read in web operation books is the idea
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that while you’re experiencing downtime your customers are fleeing in
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droves and taking their orders to your competitors out of frustration.
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However this isn’t always the truism that people take it for.</p>
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<p>If your outages are rare, and your site is normally performant and easy
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to use (or has a monopoly), you’ll find this behaviour a lot less common
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than you’ve been told. Most people have a small set of sites they are
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comfortable using and have gradually built up trust and an order history
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with. This is especially true if you operate in certain niches, such as
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being <em>the</em> fashion site, or have a very strongly defined brand.</p>
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<p>After a period of a few months of short but recurring outages we went
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back over our traffic logs and ran some queries to see how badly we’d
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been impacted and help us create our business case for more resources.
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The results were a little surprising for the more ‘conventional wisdom’
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trusting members of the team.</p>
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<p><img src="/images/blog/2017/05/what-we-expected.png" alt="Expected behaviour" title="Our expected traffic behaviour"></p>
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<p>Instead of seeing a reverse hockey stick graph of our customers
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deserting us in our hours of need before stabilising at a lower than before
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constant we saw that while orders did drop off
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during production outages, as you’d expect from a dead system, as
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long as recovery times stayed in the range of minutes, and very rarely a
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small number of hours, we always saw the daily order volume and sales
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totals bounce back to within a few percentages points of a normal day.
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In some cases we even saw brief periods of higher than usual levels as
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everyone finished their pending transactions as soon as we returned.</p>
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<p><img src="/images/blog/2017/05/what-we-saw.png" alt="Actual behaviour" title="What we actually saw"></p>
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<p>After witnessing this we had a few discussions and made some minor
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changes while waiting for the larger issues to be resolved. For example
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one aspect to consider is that if you can architect your failures to
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help users preserve even some of their effort you heavily increase the
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odds of them finishing. Keeping services like baskets and wishlists
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active make it increasingly likely they’ll return to complete their
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transaction with you. Once they’ve gone to the effort of finding their newest
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‘must have’ you have a small amount of grace points to spend while you’re
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getting everything back to normal before they’ll discard their own time
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investment and move on.</p>
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<p>It seems that as an industry we’ve managed to train our users to accept
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small amounts of failure, especially if your customers favour mobile
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devices on cellular networks. While i don’t want to try and convince you
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that downtime has no impact I do think it’s worth going over the numbers
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after your incidents to see what the slightly longer term impact was and
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how far away from a normal day your recovery curve gets you.</p>
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<p>I should also note that this doesn’t cover security issues. Those
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have very different knock on effects and are typically orders of
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magnitude worse.</p>
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Dean Wilson
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