Uptime Cloud Monitor Case Study. FeedMagnet

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1 Uptime Cloud Monitor Case Study FeedMagnet FeedMagnet uses IDERA s Uptime Cloud Monitor s server monitoring to troubleshoot issues and diagnose poor performance with the combination of real-time and historical data.

2 Company Profile FeedMagnet, an Austin based startup, aggregates and curates all major social media channels into manageable feeds and visualizations that allow fortune 500 companies to harness social media effectively by moderating content, increasing user engagement, and easily presenting content. Challenge Behind the scenes at FeedMagnet, there are over 100 hosted servers powering the social media utility. FeedMagnet actively uses a share nothing architecture, which allows customers to have their own dedicated RackSpace infrastructure. Thus, performance of an individual customer s systems will not be impacted as FeedMagnet grows as a company. Individual customers are permitted to spin up or down depending on their unique need level. This architecture enables FeedMagnet to grow indefinitely but also requires increasingly more time spent on managing servers.

3 Solution To decrease the amount of time spent on managing servers, FeedMagnet uses a combination of automation and monitoring solutions Hosted Chef and Uptime Cloud Monitor. Initially, Boyd Hemphill (Data and Systems) was skeptical of Uptime Cloud Monitor s claim of a 10 second install. He now remarks that the install isn t 10 seconds it s really less than that. The ultra fast install was particularly helpful when he ran a Chef script to install Uptime Cloud Monitor in over 100 servers in less than 10 minutes! Uptime Cloud Monitor s install was less than 10 seconds. In addition to saving time, FeedMagnet uses Uptime Cloud Monitor to monitor their fleet of servers and customer use. On the server side, they primarily use the Issues Tab in the Uptime Cloud Monitor UI to determine the immediacy of new issues and alerts. Here, FeedMagnet decides if the issues warrant immediate attention (such as resizing an instance or spawn more resources, like additional web servers), or simply acknowledgement if the issues are indications of slowing conditions. To monitor customer use and status, FeedMagnet uses the dashboard in a very logical way to group and categorize. By using the custom label function, they can immediately narrow the view to look at only a particular customer. Then, they can hone in on specific roles of customer servers by leveraging the tagging feature to note the size, and use of each server. FeedMagnet s strategic use of grouping was extremely instrumental when a large multinational customer unexpectedly needed a higher service level to handle the increased load from a user conference. FeedMagnet activity can increase either by the customer setting more search terms inside the app or due to a burst of social media activity. Uptime Cloud Monitor was the first indicator of the rapidly spiking activity, and allowed FeedMagnet to quickly find the right size the customer needed without any downtime or negative user feedback. If activity goes up within any customer instance, Uptime Cloud Monitor is always the first alert system.

4 Solution (Continued) Uptime Cloud Monitor has proven essential in real-time application troubleshooting, particularly in finding slow MySQL database queries. By correlating system load with the slow query log, FeedMagnet has been able to quickly diagnose app issues before they turn into customer issues. Uptime Cloud Monitor has also helped determine proper backup windows for backup agents that run across numerous servers, preventing backup jobs from overlapping high system load cycles. Not only does Uptime Cloud Monitor help FeedMagnet solve issues in the immediate present, Uptime Cloud Monitor provides great forensic information to diagnose poor performance in the past. It is very easy to navigate back in history and see that a process never completed. Uptime Cloud Monitor has proven essential in real-time application troubleshooting, particularly in finding slow MySQL database queries. The data history can be used to find trends and more subtle changes in performance that happen over longer periods of time. This information is then used to improve FeedMagnet code (such as tuning SQL parameters) and also to inform customers when they may need to upgrade the FeedMagnet service package due to IO-wait and load performance over time.

5 Benefits Uptime Cloud Monitor fits easily into FeedMagnet s business model and provides both operational and business benefits allowing customers the ability to scale up or down based on need without compromising customer or user experience. It also allows FeedMagnet to rightsize their environment and maximize profitability of their product. FeedMagnet is continually thinking of creative ways to use Uptime Cloud Monitor. Next on the list is to implement the auto-annotation of change events through the API. For example, when new FeedMagnet code is pushed, it will mark the event as an annotation in Uptime Cloud Monitor. If there are any downstream performance events, those will be correlated to the change event. The elasticity of the Uptime Cloud Monitor service matches the elasticity of the cloud. In closing, Boyd s comment best sums up his experience with Uptime Cloud Monitor: The elasticity of the Uptime Cloud Monitor service matches the elasticity of the cloud. To learn more visit idera.com today!