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Prepping for Black Friday Success

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Prepping for Black Friday Success
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It’s that time of year again, when the IT staff at eCommerce companies is staring down a looming deadline – get the infrastructure ready for the Black Friday surge in the next few months or risk the lost revenue and bad headlines that follow a meltdown.

Here at ScaleArc, lots of our customers are in the throes of these Black Friday preparations. They’re working on projects like scaling the database, enabling active/active operations, optimizing application code, and increasing website performance.

To share more information on the steps you can take to prep for Black Friday, we’re hosting a virtual meet up in a couple weeks. Leading the discussion is Craig Thayer, CTO for Sazze, which is the parent company to a range of eCommerce sites. One of the properties, BlackFridayFM, goes from nearly zero traffic to being one of the world’s most popular iPhone apps on Black Friday. So he has the fun task of prepping for a nearly infinite increase in traffic.

Read the entire article here, Prepping for Black Friday Success – ScaleArc

via the fine folks at ScaleArc

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ScaleArc ScaleArc enables consumer-grade apps for today’s digital business – apps that are never down, always fast, and scale anywhere. ScaleArc’s database load balancing software helps organizations of all sizes eliminate application downtime from database outages or maintenance, improve application performance, and scale database capacity – all without writing a single line of code. ScaleArc augments SQL Server, deploying transparently between applications or websites and SQL Server databases. The more sophisticated the SQL Server deployment, the more value you can unlock from the ScaleArc software. Our software works with AlwaysOn to make database failovers transparent to the application. You can also mark servers offline and ScaleArc software will route around them, enabling zero downtime patching. Our connection management and caching improves application performance, and we simplify cloud adoption by managing query load to distributed database servers.

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