Historically, most supervision solutions are based on a pooler in charge of collecting information and on a database to record the states and their history. It is on this second part that any user interface in charge of displaying data and generating essential reports is based.
With larger and larger infrastructures to monitor, poolers are still adapted but databases show their limits. Local databases that limit configurations to a certain number of checks or centralized architectures whose limits are quickly reached.
Before choosing a monitoring solution, it is therefore essential to ensure that it can meet your data volume requirements. Of course, in the short term, many solutions can meet your needs, but what about in the long term?
How will your platform perform after collecting data for several hundred devices, several thousand checkpoints and several thousand metrics? And over time? What will this look like after several months? after several years?
With our ServiceNav product, we decided in 2016, to opt for BigData technologies to ensure significant scalability of the product and to ensure long term performance and capabilities.
Today, ServiceNav's SaaS platform collects information from over 50,000 devices, 350,000 checkpoints and 750,000 metrics every day.
With an average check every 2 to 3 minutes, hundreds of millions of data are collected every day and fill the databases while allowing a fluid and dynamic display of the information.
