As usage-based pricing models have continued to increase over the past decade, particularly for technology companies, there has been a major shift in budget planning and resource allocation. Since CFOs can no longer predict or approve each and every expense before they’re incurred, variations in usage costs can often make or break a company’s profitability. For example, two of the most common usage-based costs come from online advertising and IT-related cloud costs.
The COVID-19 pandemic has had a major impact on our working lives. Companies have adopted by transforming their workforce to work remotely through video conferencing software. Cisco’s Webex Meetings, one of the most popular video conference softwares, plays a critical role in helping employees stay connected, enhance collaboration and drive productivity.
Military strategists will often tell you that the best way to win a conflict is to prevent it by projecting an unmistakable posture of strength, preparedness and resolve. As history has shown in the seven decades since the Second World War, deterrence doesn’t come cheap, certainly not in the era of modern, technology-enabled warfare. Yet it is still far less costly in lives, dollars, and equipment than letting a hostile situation escalate out of hand.
As the business world continues to integrate AI and machine learning to better manage big data processes, one area that arguably has benefitted the most is business monitoring. From IT management to business intelligence, the last few years have seen a drastic shift in how companies are monitoring their data.
When it comes to data, let’s start with the obvious. Averages suck. As developers, we all know that percentiles are much more useful. Metrics like P90, P95, P99 give us a much better indication of how our software is performing. The challenge, historically, is how to track the underlying data and calculate the percentiles. Today I will show you how amazingly easy it is to aggregate and create SQL based percentile rollups with Postgresql and t-digest histograms!
This is a beginner’s tutorial for how to write static data in batches to InfluxDB 2.0 using these three methods. Before beginning, make sure you’ve either installed InfluxDB OSS or have registered for a free InfluxDB Cloud account. Registering for an InfluxDB Cloud account is the fastest way to get started using InfluxDB.
This is Part Two of Getting Started Tutorials for InfluxDB v2. If you’re new to InfluxDB v2, I recommend first learning about different methods for writing static data in batches to InfluxDB v2 in Part One of this Getting Started series. This is a beginner’s tutorial for how and when to write real-time data to InfluxDB v2. The repo for this tutorial is here. For this tutorial, I used Alpha Vantage’s free “Digital & Crypto Currencies Realtime” API to get the data.
