Massive amounts of data can pile up quickly. So, how do you prevent yourself from drowning in your own data lake?
Collecting and storing large datasets isn’t free. To justify the expense, you need to use them effectively to achieve the business optimization goals that motivated the data collection in the first place.
Prevent massive amounts of data piling up
Everyone wants to be smarter, faster, and more efficient—in short, to optimize their business. Data optimization is the path forward for companies that don’t want to be overtaken by competitors.
Systems are monitored, and data is collected – often in such vast quantities that the overview is lost, and the data ends up unused.
It often begins with good intentions – either with monitoring solutions focused on a specific product or with comprehensive platforms that cover multiple systems.
However, data is peculiar – it’s hard to imagine just how quickly massive amounts of it can accumulate.
We frequently see companies measure everything in an effort to know everything.
It works well for the first week or two, but then comes the information overload. You simply drown in the abundance of data and status messages, losing your ability to see the bigger picture.
You get too much information but too little knowledge—and that becomes far more expensive than expected.
Even with an “as-a-Service” solution, where you only pay for what you use, the cost can spiral if you measure everything indiscriminately. Data volumes grow rapidly, driving up expenses.
Structure your monitoring
To avoid being overwhelmed by accumulating data, it’s wise to structure your monitoring efforts. It’s simpler than it sounds. Start by planning which 10 devices or services you want to monitor initially.
Organize the system into meaningful groups for reporting. Use this setup to establish a baseline for your infrastructure – understanding the normal load and performance. This will help you identify deviations and quickly pinpoint the causes of problems when they arise.
Any deviation will be easy to spot, allowing you to quickly identify the cause and eliminate the problem.”
Know your baseline
Take your internet connection as an example.
If last week’s load was at 60%, is that high or low?
If the usual load is 30%, then 60% is high.
But if the normal load is 80%, then 60% isn’t much at all.
It seems like common sense, but knowing your baseline is essential for getting the most out of your monitoring platform.
By focusing only on alerts for critical thresholds (e.g., when load approaches 80%), you can eliminate unnecessary status messages and maintain a clearer picture of your system’s health.
1.
Keep track of whether equipment requires maintenance or if certificates are about to expire—both of which can cause critical infrastructure failures.
3.
Track server, CPU, RAM, disk usage, and network equipment loads to assess your platform’s stress levels in real-time. This enables faster responses to issues.
