Modern Big Data type application architectures are all about distributed development and resources. When it comes to running apps though, those distributed architecture also have multiple points of potential failure that need to be monitored for optimum efficiency and uptime.
One solution for the challenge of monitoring Big Data comes from startup Boundary. Boundary offers an in-the-cloud service based model for monitoring Big Data apps. Boundary first emerged out of stealth mode in November and is now announcing the general availability of their Big Data apps monitoring effort.
“Big Data applications are built differently than more traditional static applications,” Boundary CEO, Gary Read told InternetNews.com. “The infrastructure is very dynamic, typically built on cloud infrastructures where servers come and go on a regular basis and as a result problems occur in terms of application degradation on a distributed basis.”
Read noted that with Big Data applications, it’s usually not a single root cause that causes performance issues, but rather a combination of different issues that all together trigger the degradation.
The way the Boundary system works is it collects data from the multiple components that underpin a Big Data application deployment. That data is then streamed through the Boundary real time engine where queries are run against it. A graphical interface is provided for end-users that displays on a second by second basis what is actually happening in the environment.
Read explained that traditional monitoring solutions have been focused on a device centric model where servers are the key components. In contrast, with Boundary the focus is on understanding the whole distributed environment.
Read the full story at EnterpriseAppsToday:
Meeting Challenge of Monitoring Big Data in the Cloud
Sean Michael Kerner is a senior editor at InternetNews.com, the news service of the IT Business Edge Network, the network for technology professionals Follow him on Twitter @TechJournalist.
