[100% Off] Cisco Devnet Professional 350-901 ─ Exam Test 1500 Questions

Covers: APIs, Python, CI/CD, Cisco Platforms, IaC & Automation, Security & Troubleshooting

Added on December 30, 2025 IT & Software 3 min read

What you’ll learn

• Analyze REST API behavior
• HTTP methods
• headers
• and status codes to predict automation outcomes in production systems.
• Reason about API pagination
• filtering
• rate limits
• and versioning when designing long-lived automation solutions.
• Design Python automation logic with strong validation
• exception handling
• and predictable failure behavior.
• Structure Python code for reuse
• clarity
• and maintainability in automation-heavy environments.
• Apply CI/CD principles to automation pipelines with controlled testing
• staging
• and production delivery.
• Identify pipeline failures and determine whether issues originate in code
• APIs
• platforms
• or environments.
• Integrate automation workflows with Cisco platforms
• controllers
• and device-level APIs.
• Reason about telemetry
• state exposure
• and feedback loops in programmable network platforms.
• Design Infrastructure as Code systems that enforce idempotency
• consistency
• and drift prevention.
• Troubleshoot automation
• security
• and delivery failures using structured
• hypothesis-driven analysis.

Requirements

• Strong understanding of IP networking fundamentals and basic routing concepts.
• General familiarity with security principles such as authentication and authorization.
• Prior exposure to scripting or automation concepts
• preferably using Python.
• Experience working with enterprise network or platform environments.
• Ability to read technical documentation and interpret system behavior accurately.
• Willingness to think in systems
• not just commands or isolated scripts.

Description

This course is designed as a high-discipline decision-training environment for engineers preparing for the Cisco DevNet Professional 350-901 exam. It is not a shortcut, and it is not a collection of random recall questions. Every question is written to train how you reason, design, and troubleshoot automation systems that operate in real production environments.

Modern network automation is no longer about sending API calls or writing small scripts. It is about understanding how software behavior, infrastructure state, security boundaries, and delivery pipelines interact. This course reflects that reality.

Across six deep-focus sections, you move from API fundamentals to automation governance, security, and operational troubleshooting. The goal is to help you think like an engineer responsible for automation at scale — where mistakes have consequences and reliability matters more than speed.

In the first section, the focus is on APIs as production systems. You analyze REST behavior, resource modeling, HTTP methods, headers, status codes, pagination, filtering, and error handling. Questions challenge you to interpret API documentation accurately, predict responses, and identify design flaws that cause automation failures. Instead of memorizing endpoints, you learn to reason about idempotency, versioning, rate limits, and backward compatibility — skills that directly impact long-term automation stability.

In the second section, attention shifts to Python as an automation engine rather than a scripting convenience. You reason about data structures, control flow, functions, modules, exception handling, and environment management in automation contexts. Scenarios expose how weak logic, poor validation, or improper error handling create fragile automation that breaks under real conditions. This section trains you to write automation logic that behaves predictably, scales safely, and fails in controlled ways.

The third section introduces CI/CD pipelines and the automation lifecycle. Here, automation is treated as software delivery. You evaluate version control workflows, pipeline stages, testing strategies, and deployment models for infrastructure and network code. Questions highlight risks caused by missing validation, uncontrolled changes, or lack of environment separation. You learn how disciplined CI/CD practices reduce operational risk when automation controls production systems.

In the fourth section, abstract automation concepts are connected to real Cisco platforms and controllers. You analyze programmability models, device-level APIs, centralized controllers, and telemetry exposure. Scenarios compare intent-based workflows with traditional configuration approaches and examine control boundaries between platforms. The emphasis is on recognizing architectural patterns and trade-offs rather than memorizing product features.

The fifth section focuses on Infrastructure as Code and automation governance. You reason about declarative versus imperative models, state management, idempotency, dependency handling, and drift prevention. Scenarios demonstrate how poor IaC design leads to instability, audit risk, and operational confusion. This section reinforces that automation is a system requiring structure, documentation, and accountability — not just faster configuration.

In the sixth section, everything comes together through security, troubleshooting, and operational validation. You analyze failures involving authentication, authorization, secrets handling, API misuse, pipeline errors, and platform-side constraints. Questions train you to interpret logs, telemetry, and system feedback to isolate root causes without guesswork. The focus is on hypothesis-driven troubleshooting and safe recovery, even under pressure.

All 1,500 questions are aligned with the official DevNet Professional 350-901 exam objectives and written to reflect how Cisco expects candidates to think. You can retake the tests unlimited times, allowing you to reinforce weak areas and deepen understanding through repetition.

This course prepares you not only to pass the exam, but to operate confidently in automation-driven environments, where APIs, pipelines, platforms, and security controls intersect. It builds the mindset required to design automation responsibly, defend architectural decisions, and troubleshoot complex systems with clarity.