In Sopra Steria we manage the IT infrastructure and applications of big clients. We process millions of service tickets and infrastructure events. This massive stream of data comes from monitoring tools such as Zabbix, Nagios, Solarwinds, and higher level frameworks:
I had to permanently erase data from a few external hard drives before selling them. Some of them were USB, some were NAS (connected through Ethernet). I collected some observations which some people might find helpful. In most filesystems, deleting
This post explains how to generate management-quality PDF or HTML reporting directly from Jupyter Notebook. With this technique, I reduced to zero the most irritating part of my projects: copy-pasting diagrams into PowerPoint.
Python is powerful, concise, and robust. Simply great. Except…when you work with time. Coping with mysterious errors in transforming dates and timestamps took me hours and days of frustration. I was like, ‘why is Python doing it to me’? I
For the Data Puzzle I posted last week, I received about a dozen of thoughtful and highly relevant answers. THANK YOU. I want to primarily thank to Luis Ruiz Santiago, Chetan Waman and anonymous J for comments under the previous
Here is a new data puzzle, coming from my recent analytics in Sopra Steria. I will describe the problem, but not the answer. If you like the challenge, please contribute your thoughts in the comments. The title of the data
I love mountains. Some of my dear ones say that this is only because they resemble histograms, which I love more. Not true (ha ha), but I must agree that visualizations done properly brings plenty of satisfaction. Histograms, when prepared
In this article I tackle the following problem: how to define and distinguish anomalies (spikes, peaks, and outliers in data) in real-life, production situations. Typically, the data drift results in the absence of a reference level. Since we do not
I feel that today’s network lags are not normal… But is it really so? Or is it my mind playing tricks on me? The KS test (Kolmogorov-Smirnov) is a practical tool to provide objective answers to such questions. Here is
Suppose all you had was a history of user requests to the service desk. Would you be able to determine how many of those requests were honest?