DevOps

Python for DevOps and SRE Bootcamp

Online

On-site

Hybrid

Python for DevOps and SRE Bootcamp

Build a strong foundation in Python automation for DevOps and SRE workflows, from system checks to resilient API and Kubernetes automation. Learn how to write production-ready scripts with logging, error handling, configuration management, and safe CLI design to support incident response and operational reliability.

Duration:

3 days

Level:

Intermediate

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1500+ users onboarded

Who will Benefit from this Training?

DevOps Engineers
SRE Engineers
Cloud Engineers
Platform Engineers
Linux Administrators
QA Automation Engineers moving into DevOps workflows
Developers who want operational automation skills

Training Objectives

Use Python confidently for DevOps and SRE automation tasks.
Write scripts to automate operational workflows such as system checks, log parsing, service validation, backups, and cleanup jobs.
Work with Linux from Python using subprocess, OS utilities, and filesystem libraries.
Interact with REST APIs using Python including authentication, pagination, retries, and safe error handling.
Work with structured data formats used in DevOps: JSON, YAML, and CSV.
Automate cloud and Kubernetes workflows using Python by calling kubectl and parsing outputs.
Apply reliable scripting patterns including logging, config-driven scripts, safe exception handling, and timeouts.
Build production-ready automation tools with CLI interface, proper logging, exit codes, and retry mechanisms.
Design scripts as reusable SRE tools rather than one-off hacks.

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Key training modules

Comprehensive, hands-on modules designed to take you from basics to advanced concepts

Module 1: Python for DevOps and SRE Automation (Foundations)
1. Why Python is used in DevOps/SRE (automation speed and ecosystem)
2. Python essentials for automation (functions, modules, venv basics)
3. Writing safe scripts (inputs, validations, predictable outputs)
4. Exit codes and reliability mindset (success vs failure states)
5. Hands-on: Lab: Build a simple health-check script with structured output and exit codes
Module 2: Automating Operational Workflows (Checks, Backups, Cleanup)
1. System checks automation (disk, CPU, memory, processes overview)
2. Service validation workflows (HTTP checks, port checks, dependency checks)
3. Backup automation patterns (copy, archive, retention basics)
4. Cleanup jobs (log rotation concepts, temp file cleanup, stale resources)
5. Hands-on: Lab: Create an operational workflow script for daily checks + backup + cleanup simulation
Module 3: Linux Automation from Python (subprocess and Filesystem)
1. Using subprocess safely (shell=False patterns, capture output)
2. Common Linux commands for automation (ps, df, free, systemctl overview)
3. Filesystem operations (pathlib, permissions, file discovery)
4. Parsing command output and converting to structured JSON
5. Hands-on: Lab: Build a Linux diagnostics script that runs commands and produces a JSON report
Module 4: Log Parsing and Analysis (Operational Troubleshooting)
1. Reading large log files safely (streaming, tail patterns)
2. Regex-based parsing and pattern detection
3. Aggregating results (error counts, top offenders, timeline concept)
4. Writing summary reports and exporting results (CSV/JSON)
5. Hands-on: Lab: Build a log parser that detects incidents and generates a summary report
Module 5: REST API Automation (Auth, Pagination, Retries, Errors)
1. Calling APIs using requests (GET/POST basics)
2. Authentication patterns (tokens, headers, basic OAuth concepts)
3. Pagination handling (next token, page offsets)
4. Retries, timeouts, and safe error handling patterns
5. Hands-on: Lab: Build an API monitoring script that checks multiple endpoints with retries and structured outputs
Module 6: Working with DevOps Data Formats (JSON, YAML, CSV)
1. Reading and writing JSON safely (schema awareness concept)
2. Reading and writing YAML for config-driven automation
3. CSV handling for reports and exports
4. Converting formats (YAML → JSON, JSON → CSV) for pipelines
5. Hands-on: Lab: Build a config-driven tool that reads YAML config and outputs JSON + CSV reports
Module 7: Kubernetes and Cloud Automation with Python (kubectl Integration)
1. Calling kubectl from Python (subprocess patterns)
2. Parsing kubectl output (json output and jq-like filtering concepts)
3. Automation use cases (pods health, node status, events, deployments)
4. Safe cluster automation patterns (read-only checks first)
5. Hands-on: Lab: Build a Kubernetes status checker that reports unhealthy pods and key failure reasons
Module 8: Reliable Scripting Patterns (Logging, Config, Exceptions, Timeouts)
1. Structured logging patterns (timestamps, severity, context fields)
2. Config-driven execution (env vars + YAML + CLI flags)
3. Exception handling strategy (fail fast vs continue patterns)
4. Timeouts and preventing stuck automation runs
5. Hands-on: Lab: Add logging, config, and timeouts to an existing script and validate reliability
Module 9: Building Production-Ready CLI Tools (Exit Codes, Retries, UX)
1. CLI design (subcommands, flags, help text)
2. Exit codes aligned to monitoring and CI/CD usage
3. Retry mechanisms with backoff and safe defaults
4. Packaging automation tools for reuse (basic structure and distribution)
5. Hands-on: Lab: Build a CLI tool that performs checks and fails with correct exit codes for CI usage
Module 10: Designing Reusable SRE Tools (Not One-Off Scripts)
1. Turning scripts into maintainable tools (modules, shared utils)
2. Standard output formats and contracts (JSON outputs for automation)
3. Testing basics for automation tools (unit tests concept)
4. Operational documentation (README + runbook usage examples)
5. Hands-on: Capstone Workshop: Build a reusable SRE automation toolset with config, CLI, logs, and reports

Hands-on Experience with Tools

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Training Delivery Format

Flexible, comprehensive training designed to fit your schedule and learning preferences

Opt-in Certifications

AWS, Scrum.org, DASA & more

100% Live

on-site/online training

Hands-on

Labs and capstone projects

Lifetime Access

to training material and sessions

How Does Personalised Training Work?

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Skill-Gap Assessment

Analysing skill gap and assessing business requirements to craft a unique program

1

Personalisation

Customising curriculum and projects to prepare your team for challenges within your industry

2

Implementation

Supplementing training with consulting support to ensure implementation in real projects

3

Faster automation delivery: Python scripts solve operational gaps quickly without waiting for heavy tooling changes.
Reduced manual troubleshooting: Automated health checks and diagnostics reduce MTTR during incidents.
Standardized operational tooling: Teams move from ad-hoc scripts to reusable and maintainable automation tools.
Better reliability outcomes: Consistent validation and reporting improves stability and release confidence.
Higher engineering productivity: Less firefighting, more time for platform improvement and automation.

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Frequently Asked Questions

1. What are the pre-requisites for this training?

The training does not require you to have prior skills or experience. The curriculum covers basics and progresses towards advanced topics.

2. Will my team get any practical experience with this training?

With our focus on experiential learning, we have made the training as hands-on as possible with assignments, quizzes and capstone projects, and a lab where trainees will learn by doing tasks live.

3. What is your mode of delivery - online or on-site?

We conduct both online and on-site training sessions. You can choose any according to the convenience of your team.

4. Will trainees get certified?

Yes, all trainees will get certificates issued by Uptut under the guidance of industry experts.

5. What do we do if we need further support after the training?

We have an incredible team of mentors that are available for consultations in case your team needs further assistance. Our experienced team of mentors is ready to guide your team and resolve their queries to utilize the training in the best possible way. Just book a consultation to get support.

Python for DevOps and SRE Bootcamp

Who will Benefit from this Training?

Training Objectives

Build a high-performing, job-ready tech team.

Key training modules

Hands-on Experience with Tools