ThousandEyes Peers Into Cloud Performance
October 11, 2013
While outsourcing applications or infrastructure to the public cloud relieves IT of some operational burdens, IT still has to monitor that infrastructure. Companies often overlook the complexity of troubleshooting a cloud app integrated with local infrastructure. If there’s a performance problem, is it the cloud provider's fault? A congested link on the Internet path between the application and the consumer? A problem on the LAN?
How does one find the root cause without the provider and IT department pointing fingers at each other? This is the problem that ThousandEyes wants to address. ThousandEyes was founded in January 2010 to address the challenge of network performance management in the cloud era. I saw a presentation from ThousandEyes at Network Field Day 6, and have also played with a trial version of the service.
The startup sees the issue of cloud consumption as three separate problem domains for businesses: performance of the local network, performance across the path transiting the Internet and performance of the cloud application or service itself. The company combines metrics from these three domains into one interface that lets customers zoom in on the root problem.
ThousandEyes is itself a cloud service. It gathers performance data using two types of agents. Private agents are Linux packages or virtual machines that are installed by ThousandEyes customers into the customers' infrastructure. Public agents, which are maintained by ThousandEyes, are distributed globally in key locations. The company says it has partnerships pending with a number of cloud providers, but it did not disclose those partners at Network Field Day.
[Cloud services can also protect companies. Find out how in “Cloud-Based Security Helps Aspen Fend Off Malware.”]
The agent performs transactional measurements (such as execute a task much like an end user would) and sends all of its measurements to data collectors maintained by ThousandEyes. The data is organized into a hierarchy of elements that can be reviewed individually, but in the context of the overall transaction.
The service provides real-time monitoring and tracks historical failures. Customers can share failure reports with anyone they like, including their cloud providers. This is a useful feature because a customer can present a provider with hard data about a performance problem, which should (I hope) cut down on finger-pointing.
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