As a DevOps Engineer at Roku, you play a vital role in powering the technology that delivers entertainment to millions of active households globally. Roku is not just a hardware company; it is a massive streaming platform, an advertising giant, and a content distributor. The backend systems supporting this ecosystem must handle immense traffic spikes, maintain ultra-low latency, and guarantee high availability. Your work directly impacts how reliably users can stream their favorite content and how seamlessly developers can deploy code to production.

In this role, you will design, build, and maintain the infrastructure that supports Roku's streaming services, smart TV operating systems, and ad-tech platforms. You will work closely with software engineering, security, and product teams to bridge the gap between code development and system operations. At Roku, DevOps is not merely about managing tools; it is about engineering scalable systems, automating away manual interventions, and solving complex infrastructure challenges at scale.

The culture at Roku values self-motivation, ownership, and practical problem-solving. As a DevOps Engineer, you will have the autonomy to make impactful architectural decisions while managing cloud environments, containerized applications, and continuous integration pipelines. Preparing for this role requires a strong grasp of systems internals, modern cloud-native technologies, and algorithmic problem-solving.

The following questions are representative of what candidates face during the Roku interview process. These questions are drawn from real interview experiences and are categorized to help you identify patterns in how Roku evaluates technical competency.

Linux Systems & Networking

These questions evaluate your deep understanding of operating system internals, core networking protocols, and system-level troubleshooting.

• How do you change the stack size of a running process in Linux?
• Can you explain how you would troubleshoot and fix a broken Logical Volume Manager (LVM) configuration?

Preparing for a DevOps Engineer interview at Roku requires a balanced approach. You must demonstrate deep operational expertise alongside strong software engineering fundamentals.

Systems and Infrastructure Expertise – You must show a granular understanding of Linux internals, containerization, and cloud infrastructure. Interviewers want to see that you do not just use tools like Docker or Terraform, but that you understand their underlying mechanics and limitations.

Problem-Solving & Diagnostic Ability – When production issues arise, you must be logical and methodical. Roku values engineers who can systematically isolate a problem, form hypotheses, and use diagnostic tools to verify their assumptions under pressure.

Algorithmic Thinking – Unlike some traditional systems administration roles, Roku expects its DevOps Engineers to write clean, maintainable, and efficient code. Showing competence in writing scripts and solving algorithmic challenges is critical to passing the technical rounds.

Collaborative Leadership – You will work across multiple engineering organizations to drive DevOps best practices. You need to demonstrate that you can influence software developers to adopt modern deployment patterns, monitor their applications effectively, and prioritize operational health.

The interview process for a DevOps Engineer at Roku is thorough, structured, and designed to test both your immediate technical skills and your long-term engineering potential. The process begins with standard recruiter alignment and quickly moves into intensive technical evaluations. Candidates should expect a highly organized experience, though the technical depth required can make the later stages demanding.

Initially, you will speak with a recruiter who will evaluate your resume, discuss your day-to-day work experience, and ensure your career expectations align with the team's culture. Following a successful screening, you will move to a technical screening round, which focuses heavily on your resume's technical stack, systems administration, and basic infrastructure design. If you pass this screen, you will be invited to a multi-hour virtual onsite interview loop that covers coding, deep-dive system architecture, monitoring, and behavioral scenarios.

The visual timeline above outlines the typical progression from your initial application to the final hiring decision. Most candidates complete this entire loop within three to five weeks, depending on scheduling availability. Understanding where you are in the pipeline will help you pace your preparation and focus on the specific demands of each upcoming round.

Linux Systems Internals & Networking

At Roku, your systems knowledge is tested at a very low level. You cannot rely solely on high-level orchestration platforms; you must understand the operating system itself. Interviewers will present real-world degradation scenarios and expect you to explain how you would triage them using standard operating system utilities.

Be ready to go over:

• Process & Memory Management – Understanding virtual memory, swap space, thread allocation, and how to manipulate running process parameters.
• Storage & Volume Management – Working knowledge of file systems, partition tables, and Logical Volume Manager (LVM) recovery techniques.
• Kernel & Container namespaces – How cgroups and namespaces isolate resources in containerized environments.

Example questions or scenarios:

• "A database server is experiencing high CPU steal time. How do you identify the root cause?"
• "Walk me through how you would recover a corrupted LVM partition on a legacy system without losing data."
• "Explain the difference between soft limits and hard limits in Linux resource allocation."

Infrastructure Automation & CI/CD

Managing infrastructure at Roku's scale requires robust automation. This evaluation area focuses on your ability to write clean Infrastructure as Code (IaC) and design reliable continuous integration and continuous deployment (CI/CD) pipelines.

Be ready to go over:

• Terraform Best Practices – State management, module design, and multi-account AWS architectures.
• CI/CD Pipeline Design – Building scalable Jenkins pipelines, handling artifact versioning, and integrating security scanning tools.
• Configuration Management – Ensuring consistent system states across thousands of virtual instances.
• Advanced concepts (less common) – Multi-cloud failover strategies, custom Terraform providers, and immutable infrastructure patterns.

Example questions or scenarios:

• "How do you rollback a Terraform deployment safely if a critical resource fails to provision midway through?"
• "Design a Jenkins pipeline that deploys a microservice to a Kubernetes cluster using a blue-green deployment strategy."

Coding & Data Structures (DSA)

Even though this is an infrastructure-focused role, Roku places a strong emphasis on programming. You will face coding challenges to prove you can write production-grade scripts and tools.

Be ready to go over:

• String & Array Manipulation – Efficiently parsing, filtering, and restructuring data structures.
• File I/O & Parsing – Reading, processing, and extracting metrics from large system logs programmatically.
• Time Complexity – Optimizing your code to run with optimal Big O time and space complexity.

Example questions or scenarios:

• "Write a Python script that reads a directory of configuration files and validates their JSON/YAML syntax, listing all nested keys that violate a specific naming convention."
• "Solve a Leetcode-medium array manipulation problem within 35 minutes, explaining your algorithmic trade-offs."

Monitoring, Observability & Alerting

Deploying code is only half the battle; keeping it running smoothly is where observability comes in. You will be evaluated on your philosophy around monitoring and how you design alerting systems that minimize noise while catching real incidents.

Be ready to go over:

• Metrics Collection – Understanding the difference between logs, metrics, and traces (the three pillars of observability).
• Alerting Thresholds – Designing alerts based on Service Level Indicators (SLIs) and Service Level Objectives (SLOs) rather than arbitrary CPU thresholds.
• Log Aggregation – Designing scalable log pipelines using tools like ELK, Splunk, or Prometheus/Grafana.

Example questions or scenarios:

• "How would you design an alerting strategy for a streaming API to ensure engineers are only paged for actionable, user-impacting issues?"
• "A service is experiencing intermittent 5xx errors. Explain how you would use distributed tracing to isolate the failing component."