Hands-On Python for DevOps: Leverage Python's native libraries to streamline your workflow and save time with automation

Cover....1 Title Page....2 Copyright and Credits....3 Contributors....5 Table of Contents....8 Preface....14 Part 1: Introduction to DevOps and role of Python in DevOps....20 Chapter 1: Introducing DevOps Principles....22 Exploring automation....23 Automation and how it relates to the world....23 How automation evolves from the perspective of an operations engineer....23 Understanding logging and monitoring....25 Logging....25 Monitoring....26 Alerts....26 Incident and event response....26 How to respond to an incident (in life and DevOps)....27 Site reliability engineering....28 Incident response teams....29 Post-mortems....30 Understanding high availability....30 SLIs, SLOs, and SLAs....31 RTOs and RPOs....32 Error budgets....33 How to automate for high availability?....34 Delving into infrastructure as a code....34 Pseudocode....35 Summary....36 Chapter 2: Talking about Python....38 Python 101....39 Beautiful-ugly/explicit-implicit....41 Simple-complex-complicated....42 Flat-nested/sparse-dense....42 Readability-special cases-practicality-purity-errors....43 Ambiguity/one way/Dutch....43 Now or never....44 Hard-bad/easy-good....45 Namespaces....45 What Python offers DevOps....46 Operating systems....46 Containerization....47 Microservices....47 A couple of simple DevOps tasks in Python....48 Automated shutdown of a server....48 Autopull a list of Docker images....55 Summary....56 Chapter 3: The Simplest Ways to Start Using DevOps in Python Immediately....58 Technical requirements....59 Introducing API calls....59 Exercise 1 – calling a Hugging Face Transformer API....60 Exercise 2 – creating and releasing an API for consumption....63 Networking....66 Exercise 1 – using Scapy to sniff packets and visualize packet size over time....66 Exercise 2 – generating a routing table for your device....69 Summary....71 Chapter 4: Provisioning Resources....72 Technical requirements....73 Python SDKs (and why everyone uses them)....73 Creating an AWS EC2 instance with Python’s boto3 library....74 Scaling and autoscaling....76 Manual scaling with Python....77 Autoscaling with Python based on a trigger....78 Containers and where Python fits in with containers....80 Simplifying Docker administration with Python....81 Managing Kubernetes with Python....82 Summary....83 Part 2: Sample Implementations of Python in DevOps....84 Chapter 5: Manipulating Resources....86 Technical requirements....87 Event-based resource adjustment....87 Edge location-based resource sharing....88 Testing features on a subset of users....89 Analyzing data....91 Analysis of live data....91 Analysis of historical data....92 Refactoring legacy applications....93 Optimize....94 Refactor....95 Restart....96 Summary....96 Chapter 6: Security and DevSecOps with Python....98 Technical requirements....99 Securing API keys and passwords....99 Store environment variables....100 Extract and obfuscate PII....101 Validating and verifying container images with Binary Authorization....103 Incident monitoring and response....105 Running runbooks....105 Pattern analysis of monitored logs....111 Summary....115 Chapter 7: Automating Tasks....116 Automating server maintenance and patching....117 Sample 1: Running fleet maintenance on multiple instance fleets at once....118 Sample 2: Centralizing OS patching for critical updates....120 Automating container creation....121 Sample 1: Creating containers based on a list of requirements....121 Sample 2: Spinning up Kubernetes clusters....123 Automated launching of playbooks based on parameters....124 Summary....128 Chapter 8: Understanding Event-Driven Architecture....130 Technical requirements....131 Introducing Pub/Sub and employing Kafka with Python using the confluent-kafka library....131 Understanding the importance of events and consequences....133 Exploring loosely coupled architecture....136 Killing your monolith with the strangler fig....138 Summary....141 Chapter 9: Using Python for CI/CD Pipelines....142 Technical requirements....143 The origins and philosophy of CI/CD....143 Scene 1 – continuous integration....143 Scene 2 – continuous delivery....144 Scene 3 – continuous deployment....146 Python CI/CD essentials – automating a basic task....147 Working with devs and infrastructure to deliver your product....150 Performing rollback....153 Summary....155 Part 3: Let’s Go Further, Let’s Build Bigger....156 Chapter 10: Common DevOps Use Cases in Some of the Biggest Companies in the World....158 AWS use case – Samsung electronics....159 Scenario....160 Brainstorming....160 Solution....161 Azure Use Case – Intertech....162 Scenario....162 Brainstorming....163 Solution....164 Google Cloud use case – MLB and AFL....165 Scenario....167 Brainstorming....167 Solution....168 Summary....170 Chapter 11: MLOps and DataOps....172 Technical requirements....173 How MLOps and DataOps differ from regular DevOps....173 DataOps use case – JSON concatenation....173 MLOps use case – overclocking a GPU....174 Dealing with velocity, volume, and variety....175 Volume....175 Velocity....177 Variety....179 The Ops behind ChatGPT....181 Summary....182 Chapter 12: How Python Integrates with IaC Concepts....184 Technical requirements....185 Automation and customization with Python’s Salt library....185 How Ansible works and the Python code behind it....189 Automate the automation of IaC with Python....193 Summary....194 Chapter 13: The Tools to Take Your DevOps to the Next Level....196 Technical requirements....197 Advanced automation tools....197 Advanced monitoring tools....201 Advanced event response strategies....206 Summary....208 Index....210 Other Books You May Enjoy....217