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.
Capacity Planning and Resource Optimization
Covers forecasting, provisioning, and operating compute, memory, storage, and network resources efficiently to meet demand and service level objectives. Key skills include monitoring resource utilization metrics such as central processing unit usage, memory consumption, storage input and output and network throughput; analyzing historical trends and workload patterns to predict future demand; and planning capacity additions, safety margins, and buffer sizing. Candidates should understand vertical versus horizontal scaling, autoscaling policy design and cooldowns, right sizing instances or containers, workload placement and isolation, load balancing algorithms, and use of spot or preemptible capacity for interruptible workloads. Practical topics include storage planning and archival strategies, database memory tuning and buffer sizing, batching and off peak processing, model compression and inference optimization for machine learning workloads, alerts and dashboards, stress and validation testing of planned changes, and methods to measure that capacity decisions meet both performance and cost objectives.
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.
Platform Architecture for Organizational Scale
Designing internal platforms and infrastructure to support large engineering organizations and evolving teams. Topics include developer experience and self service platform design, deployment platforms that enable safe frequent releases for hundreds of engineers, platform automation and observability patterns that provide cross service visibility, governance and operational policies, service onboarding and lifecycle, and how to evolve platform capabilities as headcount and service count grows. Candidates should discuss trade offs between centralized platform services and team autonomy, metrics for platform health, and approaches to encourage adoption while minimizing operational friction.
Amazon Web Services Architecture and Operations
Advanced knowledge of Amazon Web Services platform services, architectural patterns, operational best practices, and trade offs. Candidates should be able to justify compute choices such as Amazon Elastic Compute Cloud instance types, instance sizing and performance tuning, and Auto Scaling strategies; storage and durability decisions including Amazon Simple Storage Service storage classes, versioning, lifecycle management, replication and archival strategies; database patterns such as Amazon Relational Database Service with multi availability zone deployments, read replicas and failover behavior, and Amazon DynamoDB capacity modes and throughput trade offs; networking design including Amazon Virtual Private Cloud topology, subnet and routing strategies, peering, gateway and interface endpoints, and network security controls; infrastructure as code and deployment patterns using Amazon CloudFormation including stack management and automated rollbacks; serverless and event driven design such as Amazon Web Services Lambda concurrency and cold start considerations and integration with Amazon API Gateway; content delivery and caching with Amazon CloudFront and Amazon ElastiCache including cache invalidation and expiry strategies; service specific operational concerns such as rate limiting, backup and restore, monitoring, logging, alerting and incident response; and cross cutting concerns including identity and access governance, cost optimization, disaster recovery planning and testing, and automation. Interview focus is on design reasoning, anticipating failure modes, scaling strategies, performance tuning, observability and automation, and provider specific operational practices.
Amazon Web Services Core Services
Comprehensive knowledge of the foundational Amazon Web Services that are commonly used to design, deploy, and operate cloud applications. This includes compute services such as Amazon Elastic Compute Cloud for virtual machines and instance families, Amazon Web Services Lambda for serverless functions, and Amazon Elastic Beanstalk for managed application platforms; storage services such as Amazon Simple Storage Service for object storage, Amazon Elastic Block Store for block volumes, and Amazon Elastic File System for shared file storage; database services such as Amazon Relational Database Service for managed relational databases, Amazon DynamoDB for NoSQL, and Amazon ElastiCache for in memory caching; networking and content delivery including Amazon Virtual Private Cloud networking concepts, subnets, security groups, load balancers, and Amazon CloudFront; container and orchestration options such as Amazon Elastic Container Service and Amazon Elastic Kubernetes Service; and management and security services including Identity and Access Management, Amazon CloudWatch monitoring and logging, Auto Scaling, and cost and service limit considerations. Candidates should understand core service characteristics, common configuration choices and trade offs, operational considerations such as high availability and fault tolerance, basic security and compliance approaches, performance and cost optimization, and guidance for selecting one service over another for typical application patterns.