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实例探究 > CanvasPop Cuts Application Response Time to Microseconds with Help from New Relic

CanvasPop Cuts Application Response Time to Microseconds with Help from New Relic

技术
  • 应用基础设施与中间件 - API 集成与管理
适用行业
  • 零售
  • 电子商务
适用功能
  • 销售与市场营销
  • 商业运营
用例
  • 供应链可见性(SCV)
  • 实时定位系统 (RTLS)
服务
  • 系统集成
  • 软件设计与工程服务
挑战
CanvasPop, an online retail business, experiences major spikes in traffic, some more predictable than others. Most of the site’s traffic appears during the fourth-quarter holiday season, when average pageviews rise from about 25,000 per day to as many as 70,000 per day. At other times of the year, heavy media coverage may cause similar jumps in demand. Another challenge arises in the CanvasPop manufacturing facility, where order fulfillment requires a complex interchange between digital and physical processes. When a customer creates an order, he or she will upload a digital image and select from a variety of canvas sizes, frame designs, and image effects. Then the CanvasPop system delivers the image to an in-house graphic artist who can work one-on-one with the customer to recommend adjustments or enhancements. After printing on canvas, the customer’s digital image becomes a physical product, with CanvasPop employees laminating and then manually framing each piece of artwork prior to shipping. The interplay between digital image and physical product can make order fulfillment very tricky. If they’re not careful in navigating those transitions, an order can simply disappear from the system. That’s why the performance of their backend manufacturing application is so important — without it, they essentially don’t have a business.
关于客户
CanvasPop is a company that has delivered more than 280,000 high quality, custom-made canvas photo prints to over 100,000 customers across North America since 2009. The company matches every customer with a personal in-house designer to help ensure total satisfaction. CanvasPop operates two facilities in North America. One is the company’s headquarters in Ottawa, and the other is a 20,000 square foot facility in Las Vegas built to support manufacturing and order fulfillment across the continent. The vast majority of CanvasPop’s code-based infrastructure is hosted on Amazon Web Services. And PHP is the code of choice for most applications. The primary customer-facing application instance is a single Multi-AZ load balancer with a two-node cache cluster and a Multi-AZ instance on Amazon RDS.
解决方案
CanvasPop decided to migrate their entire system from ASP to PHP. After a six-month process of building and testing, CanvasPop went live with its new PHP-based system on August 1, 2012. The New Relic PHP client was with them every step of the way. Deploying New Relic was a five-minute job at most. They downloaded the Chef-specific recipe for the PHP agent, plugged it into Chef, and that was it. With their old monitoring solution, they would’ve needed to wait until the end of the day to start seeing numbers. But New Relic started giving them actionable information within minutes. It wasn’t long before the CanvasPop IT team realized that they could use New Relic to monitor not just the new PHP system, but legacy systems as well. New Relic plays a crucial role in CanvasPop’s continuous deployment strategy, providing the real time data necessary for engineers to deploy changes to production an average of three or four times every day.
运营影响
  • With help from New Relic, CanvasPop’s application performance isn’t just faster — it’s more consistent, too.
  • When Amazon Web Services experienced a major outage on the East Coast of the United States in October 2012, CanvasPop was able to stay one step ahead and avoid a significant service interruption.
  • In addition to providing up-to-the-minute metrics for proactive problem-solving, New Relic also alerted the CanvasPop IT team to longstanding issues that had simply gone unnoticed.
数量效益
  • By using one solution instead of four or five different solutions, they’re shaving off hours per week for every developer.
  • By simply changing from left to inner joins, they dropped that query from milliseconds to microseconds, which saved them huge amounts of

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