More recent posts from the Servicenav team
Historically, most monitoring solutions are based on a poller responsible for collecting information and recording status (current and historical) to a database . It is the latter that critically underpins user interfaces tasked with displaying such data and the production of valuable reports.
With ever expanding infrastructures to monitor, pollers remain up to the task, but the databases show signe fo deficiency. Local databases may limit configuration to a certain number of checks or the current databases of centralized architectures may have capacity limits that are rapidly reached.
Before choosing a monitoring solution, it is therefore essential to ensure that it can meet your anticipated data volumes. Of course, in the short term, almost all potential solutions will meet your needs, but what about the longer term?
What performance will your platform offer once its collecting data for several hundred devices, thousands of checks and thousands of metrics? What will it be like after several months? After several years ?
For our ServiceNav product, we made the decision in 2016 to opt for BigData technologies in order to ensure, significant product scalability, long-term performance and opportunities for significant feature enhancements.
Today the ServiceNav SaaS platform collects information every day from more than 50,000 devices, 350,000 check points and 750,000 metrics.
With an average check executing every 2 to 3 minutes that’s hundreds of millions of datapoints that are collected every day and stored in the database while still supporting a fluid/ dynamic display of information.