Turn your operations procedures into self-service jobs. Safely give others the control and visibility they need.
Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in microservice architectures. It manages both the collection and lookup of this data. Zipkin’s design is based on the Google Dapper paper.
Problem Statement: We need to monitor services on Dev, QA, and Prod.
Customer doesn’t want to sponsor the monitoring project.
Step 1: Monitor & Alert
Monitor service endpoints using JMeter or Python.
Write output to CSV files day wise.
Send EMails or Slack messages for given thresholds
Step 2: Aggregate Numbers
Setup Jupyter Notebook
Mount all files as input with read-only access
Write a script to tabulate and visualize data.
Protect system with id/password
pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
Hierarchical Data Format – Version 5
We can store/retrieve simple to complex data in flat files.
Community Version Vs Enterprise Edition: https://www.hdfgroup.org/solutions/hdf5-enterprise-support-edition/
Jupyter Note Book – Interactive way to run Python code
Deploy Jupyter in Cloud: https://kyso.io/
Sample csv file
Sample Python Note Book Code
1. Go to the Apple (top left of screen) and choose “About this Mac”.
2. Look at the pop-up window and find the serial number listed at the bottom. Copy it.
3. Go to http://www.everymac.com/ultimate-mac-lookup/ and paste your serial number where it says Enter Identifier.
4. This will bring you to a page with the model of your machine.