Posts

Showing posts from March, 2021

Visualizing Covid Vaccinations - Python data prep and steps

Image
We want to plot the Covid vaccination rates across different countries world-wide or different states in the USA. We need to create a standardized dataset that is accurate enough for our graphing purposes. The folks at Our World in Data (OWiD) gather that information to create composite data sets.  Each independent entity reports data on its own schedule.  The composite  dataset can be missing entire days of data for some entities or individual data attributes in some of the days that are actually reported.   Lets look at the steps required to create reasonable comparisons and progress graphics. Source Data and Code Dataset courtesy of  Our World in Data : GitHub Repository Python code and scripts described here are available  on GitHub Videos  links at the bottom of this article Data Consistency We want time-series data that lets us exactly line up the data for each reporter. This table shows two different countries, C1 and C2.  They each report data on their own schedules.   C1 does

Monitor Internet Broadband service with a Raspberry Pi 4 and some Python

Image
You can easily automate capturing broadband connection statistics with some Python code  running on a Raspberry Pi, a Mac or, a PC.  I used a Raspberry Pi 4 as my test appliance because it is cheap and can support 1GB/s ethernet connections. That means it is fast enough to service most residential or low-end commercial connections. I'm lazy and wanted the data to end up in a secure public cloud that could be populated and viewed from anywhere.  We can send our broadband statistics from 1 or more locations and graph the different locations against each other. Any tool could be used. Monitoring One or Compare Two  We wanted to compare two different internet provider's service levels.  One provider is a FIOS 1GB down / 1GB up.  The other is a cable service with 1GB down / 50MB up. The providers and the technology were different.  We wanted to know if the complaints about one of the providers were valid. Relies on Speedtest.net infrastructure We're going to leverage the popular

Querying Python logs Azure Application Insight

Image
You can send your Python logs to Azure Application Insights from anywhere and then leverage the Application Insights query and dashboard capabilities to do log analysis.  Getting access to the logs is trivial. I wanted to plot basic internet performance information from data generated from two different machines in two different locations.  The source code is on GitHub here  freemansoft/speedtest-app-insights . That project runs speedtest.net measurements and then posts them to Azure Application Insights.  It logs the raw data when the --verbose switch is set.  That verbose output is sent to Azure App Insights. Execution pre-requisites You have an Azure login You have created an Azure Application Insights Application key https://docs.microsoft.com/en-us/azure/azure-monitor/app/create-new-resource You have pushed data to Application Insights.  I used https://github.com/freemansoft/speedtest-app-insights with the _--verbose__ switch Video walkthrough not yet available Data Capture Notes

Querying Python Metrics custom tags as CustomDimensions in Azure Application Insight

Image
Azure Application Insights can be a collection point for Python Metrics that you can query and filter against.  We can send Open Census metrics from any data center into Azure Application Insights. This lets us see our program events from anywhere that can reach the Azure console.  It provides a zero admin performance console. We can add custom dimensions (attributes) to every metrics record we send to Azure Application Insights. The OpenCensus Azure Exporter sends tags to Azure Application Insights as CustomDimensions . Execution pre-requisites You have an Azure login You have created an Azure Application Insights Application key https://docs.microsoft.com/en-us/azure/azure-monitor/app/create-new-resource You have pushed data to Application Insights.  I used https://github.com/freemansoft/speedtest-app-insights Video walkthrough

Displaying Python Metrics in Azure Application Insights

Image
We can capture Python performance metrics in Azure Application Insights. This will let us see our program performance from anywhere that can reach the Azure console.  I've used this to capture a variety of Python data manipulation and process timing without having to stand up any metrics databases or dashboards. I wanted to plot basic internet performance information from data generated from two different machines in two different locations.  The source code is on GitHub here freemansoft/speedtest-app-insights . That project runs speedtest.net measurements and then posts them to Azure Application Insights.  We can create charts for any of the data gathered as part of this process. Target Graphic We want to create a graphical tile that shows our connection ping time broken out per test machine. The program code above posts new ping time data every 5 minutes.  This graphic shows the ping results for the last 4 hours. Execution pre-requisites You have an Azure login You have created a