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Inference performance bottlenecks on Lambda
Cold starts loading the model, memory and CPU limits, no GPU, and package size dominate; mitigate with provisioned concurrency, loading the model once outside the handler, smaller models, and right-sized…
How would you build CI/CD for an ML model?
Data and model versioning, automated training plus evaluation gates, model registry, deployment with monitoring and retraining triggers.
How would you speed up slow single-GPU training?
Vertical scaling to bigger or multi-GPU instances, then data-parallel or model-parallel distributed training across nodes.
Design auto drift detection and retraining
Capture inputs and predictions, compute data and concept drift metrics on a schedule, alert on threshold breach, and trigger a retraining and redeploy pipeline.
Design petabyte-scale distributed training
Object storage with columnar formats, distributed preprocessing, a data-parallel framework with efficient sharded loading, and managed orchestration.
Explain the Well-Architected Framework pillars
Name the pillars, operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability, and explain each briefly.
Lift-and-shift versus replatforming migration
Rehosting moves apps unchanged for speed and low risk; replatforming makes targeted optimizations for cloud benefits; explain the speed-versus-value trade-off.
Design a highly available web application
Redundant stateless instances across multiple zones behind a load balancer with health checks, auto-scaling, and a replicated multi-AZ datastore.
Explain the Strangler Fig pattern
A facade routes traffic, new services gradually replace legacy features one slice at a time, and the old system is retired when fully strangled.
Managed services versus self-hosting trade-offs
Managed services cut operational burden and speed delivery but cost more and limit control; self-hosting offers full control and tuning at the price of patching, scaling, and reliability work.
Technical challenges of a multi-cloud strategy
Data consistency and egress costs across providers, cross-cloud networking and latency, and federating disparate IAM systems, plus operational and tooling overhead.
Design an enterprise cloud landing zone
Multi-account or subscription structure, centralized identity and SSO, network topology like hub-and-spoke, guardrails via policy and SCPs, and centralized logging.
Migrate an OLTP database with minimal downtime
Take an initial bulk load, then use change data capture to replicate ongoing changes until source and target are in sync, validate, then cut over during a brief window with a rollback plan.
Balance agility and compliance in regulated cloud
PaaS for speed where allowed, IaaS where control is required, enforced by encryption, IAM least privilege, network isolation, policy-as-code guardrails, and continuous audit logging.
When to choose bare metal over a VM
Bare metal suits latency-sensitive or high-throughput workloads needing no hypervisor overhead, single-tenant isolation for compliance, or direct hardware and licensing access.
Configure a Kubernetes Horizontal Pod Autoscaler
HPA adjusts replica count toward a target CPU metric, needs the metrics server and pod resource requests, and scales a deployment between min and max.
Strangler Fig with serverless and an event bus
API Gateway acts as the routing facade, new features run as Lambda functions, an event bus decouples and fans out to new services, and traffic shifts feature by feature until the monolith…
Optimize cost of a big-data analytics platform
Storage tiering and lifecycle plus compression and partitioning; compute via spot instances, right-sizing, and efficient file formats; query and pipeline optimization to scan less data.
Event bus versus message queue for triggers
A queue is point-to-point buffered work for one consumer group; an event bus routes and filters one event to many decoupled subscribers. Event bus wins when many independent services must react.
Design a multi-tenant model serving platform
Share infrastructure to cut cost while enforcing tenant data isolation, fair resource allocation against noisy neighbors, and per-tenant performance via quotas and autoscaling.