Cloud & Infrastructure Topics
Cloud platform services, infrastructure architecture, Infrastructure as Code, environment provisioning, and infrastructure operations. Covers cloud service selection, infrastructure provisioning patterns, container orchestration (Kubernetes), multi-cloud and hybrid architectures, infrastructure cost optimization, and cloud platform operations. For CI/CD pipeline and deployment automation, see DevOps & Release Engineering. For cloud security implementation, see Security Engineering & Operations. For data infrastructure design, see Data Engineering & Analytics Infrastructure.
Technical Vision and Infrastructure Roadmap
This topic assesses a candidate's ability to define a multi year technical vision for infrastructure, platform, and systems and to translate that vision into a practical execution roadmap. Core skills include evaluating technology choices and architecture evolution, planning migration and modernization paths, anticipating scalability and capacity needs, and balancing cost performance with resilience and operational reliability. Candidates should demonstrate approaches to managing technical debt, sequencing investments across quarters and releases, estimating resources and timelines, establishing measurable infrastructure goals and key performance indicators, and implementing governance and standards. Discussion may also cover reliability and observability, security and compliance considerations, trade offs between short term stability and long term rearchitecture, prioritization to enable business outcomes, and communicating technical trade offs to both technical and non technical stakeholders.
Cost Optimization at Scale
Addresses cost conscious design and operational practices for systems operating at large scale and high volume. Candidates should discuss measuring and improving unit economics such as cost per request or cost per customer, multi tier storage strategies and lifecycle management, caching, batching and request consolidation to reduce resource use, data and model compression, optimizing network and input output patterns, and minimizing egress and transfer charges. Senior discussions include product level trade offs, prioritization of cost reductions versus feature velocity, instrumentation and observability for ongoing cost measurement, automation and runbook approaches to enforce cost controls, and organizational practices to continuously identify, quantify, and implement savings without compromising critical service level objectives. The topic emphasizes measurement, benchmarking, risk assessment, and communicating expected savings and operational impacts to stakeholders.
Infrastructure Implementation and Operations
Hands on design, deployment, and operational management of infrastructure components and services. This includes setting up and configuring load balancers, database replication and high availability, caching layers, networking and network security, service discovery and routing, container deployment and orchestration, monitoring and observability, logging and alerting, backup and disaster recovery strategies, and secrets management in runtime. Candidates should be able to walk through concrete implementations, explain trade offs, demonstrate troubleshooting and performance tuning, and show how infrastructure components integrate to meet availability, scalability, and security requirements.
Understanding the Company's Infrastructure Context
Research the company's public infrastructure information (engineering blog, tech talks, published case studies, job description). Understand what systems they operate at scale, what problems they likely face, and what your role would contribute to.
Capacity Planning and Forecasting
Covers forecasting demand and planning infrastructure and platform capacity to meet expected business needs reliably and cost effectively. Candidates should be able to analyze historical usage and growth trends, build and validate capacity models, define capacity metrics and thresholds, estimate headroom and safety margins, and translate business growth scenarios into procurement or cloud provisioning plans and timelines. Includes storage and compute lifecycle planning such as archiving and retention strategies, upgrade and rollout planning to avoid disruption, and trade offs between overprovisioning and right sizing. Also addresses design for scale and redundancy, autoscaling and elasticity patterns, load balancing and failover planning, capacity testing and stress testing, monitoring and alerting for capacity signals, and techniques to measure and improve forecast accuracy. Finally it covers operational governance and decision making including cross team resource allocation, capacity reviews, cost optimization and budgeting, runbooks and change control, and alignment of capacity plans with service level objectives and business projections.
Build vs. Buy vs. Cloud vs. On Premise Trade Offs
Understanding key trade-offs in technology decision-making: (1) Build vs. Buy - custom development flexibility vs. packaged software speed/cost, (2) Cloud vs. On-Premise - operational burden, control, scalability, security, cost, (3) SaaS vs. Licensed - flexibility, upgrade frequency, customization options. Understanding implications for cost, time-to-value, flexibility, control, and ongoing support.
Cloud Platform Fundamentals
Comprehensive understanding of core public cloud services and the primary trade offs when selecting among them across major providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Candidates should know compute options including virtual machines, managed compute, containers and serverless functions; storage types including object, block and file storage and lifecycle and archival strategies; managed database offerings for relational, non relational, and data warehouse workloads; networking fundamentals including virtual private networks, subnets, routing, load balancing, content delivery networks, and private connectivity; messaging and integration services such as message queues and event streaming; identity and access management and secrets management; monitoring, logging, and observability; autoscaling, elasticity, high availability, and basic disaster recovery patterns; and cost and pricing considerations. The topic also covers the trade offs between managed services and self managed infrastructure in terms of consistency, latency, cost, operational overhead, and durability, and the ability to map common workload requirements to the right service categories.
Infrastructure Scaling and Capacity Planning
Operational and infrastructure level planning to ensure systems meet current demand and projected growth. Topics include forecasting demand headroom planning and three to five year capacity roadmaps; autoscaling policies and metrics driven scaling using central processing unit memory and custom application metrics; load testing benchmarking and performance validation methodologies; cost modeling and right sizing in cloud environments and trade offs between managed services and self hosted solutions; designing non disruptive upgrade and migration strategies; multi region and availability zone deployment strategies and implications for data placement and latency; instrumentation and observability for capacity metrics; and mapping business growth projections into infrastructure acquisition and scaling decisions. Candidates should demonstrate how to translate requirements into capacity plans and how to validate assumptions with experiments and measurements.
Cloud Cost Optimization and Financial Operations
Covers strategies and organizational practices for minimizing and managing cloud and infrastructure spend while balancing performance, reliability, and business priorities. Candidates should understand cloud cost drivers such as compute, storage, data transfer, and managed services; pricing models including on demand pricing, reserved capacity commitments, savings plans, and interruptible or spot offerings; and engineering techniques that reduce spend such as rightsizing, autoscaling, storage tiering, caching, and workload placement. This topic also includes financial operations practices for continuous cost management and governance: resource tagging and cost allocation, budgeting and forecasting, chargeback and showback models, anomaly detection and alerting, cost reporting and dashboards, and processes to gate changes that affect spend. Interviewees should be able to estimate recurring costs and total cost of ownership, identify and quantify optimization opportunities, weigh trade offs between cost and business objectives, and describe tools and metrics used to monitor and communicate cost to stakeholders.