AZ305 50 exam questions

A multinational financial services company needs to migrate their core banking system from on-premises SQL Server 2019 (Always-On Availability Group) to Azure with zero downtime. Database is 500GB, 10,000 concurrent users, uses SQL Server-specific features. RPO must be <1 minute, RTO <5 minutes. Current network: 500 Mbps ExpressRoute. What is the optimal migration strategy? A) Azure SQL Database with geo-replication and Azure Database Migration Service online mode B) Azure SQL Managed Instance with failover groups and Azure Database Migration Service online mode C) SQL Server on Azure VMs with Always-On configured across Availability Zones D) Azure Cosmos DB with custom application rewrite

B

A global e-commerce platform processes 500,000 requests/second at peak with 99.99% availability across a single region. Current: App Service with 100 instances using Application Gateway. During Black Friday tests, experiences 15-20% request failures due to control plane saturation beyond 50 instances. What architectural change best addresses the bottleneck? A) Increase Application Gateway throughput capacity and implement connection draining B) Migrate to Azure Kubernetes Service (AKS) with Horizontal Pod Autoscaler configured for aggressive scaling C) Implement Azure Front Door to distribute load before reaching App Service limits D) Add additional Application Gateways in serial configuration for redundancy

B

A healthcare provider operates across 15 states with HIPAA compliance requirements. Patient data must stay in the state where treatment occurred and cannot be replicated across state lines. Current: 15 separate regional Azure subscriptions with independent SQL databases ($2M/year). They want to consolidate without violating data residency. Which approach achieves this? A) Single Azure SQL Database with state-level partitioning and Azure Policy enforcing region-specific deployment B) Single Cosmos DB instance with state-level containers and manually managed region restrictions C) Separate logical databases per state within single managed instance using database-scoped credentials D) Consolidate all data to central subscription and use application-level access controls

A

A SaaS startup's recommendation engine uses Azure Cosmos DB (strong consistency, $100K/month) but customer analytics show eventual consistency acceptable for 95% of queries. Current response time: 200ms (strong consistency). Testing shows eventual consistency: 50-100ms. However, switching breaks customer contracts guaranteeing strong consistency. Switching alone would save $60K/month. What is the optimal approach maintaining contracts while reducing costs? A) Implement dual-consistency model: strong for contract-guaranteed queries, eventual for analytics B) Renegotiate contracts to accept eventual consistency in exchange for price reduction C) Migrate to Azure SQL Database with read-only replicas for faster reads at lower cost D) Maintain current strong consistency but implement aggressive caching to reduce effective latency

A

An organization running 200+ microservices in AKS discovers that during a regional outage lasting 2 hours, their disaster recovery cluster in secondary region took 45 minutes to stabilize, during which customers lost access. RTO requirement is 15 minutes. Pod replication already set to 3 replicas with anti-affinity rules. What additional architectural change is needed to meet the 15-minute RTO? A) Implement active-active deployment across regions with Azure Traffic Manager for global load balancing B) Increase pod replicas from 3 to 5 across zones for faster startup C) Implement Azure Site Recovery for continuous replication with faster failover automation D) Switch from AKS to App Service for faster redundancy capabilities

A

A company processes 1TB of data daily through Azure Data Factory pipelines (cost: $500/month). Audit reveals that 40% of pipeline runs are duplicate executions due to poorly configured triggers, and 30% process already-processed data due to schedule conflicts. Implementing proper deduplication would cost $50K engineering. Improving trigger logic would cost $20K. What is the optimal cost-reduction approach? A) Implement both deduplication ($50K) and trigger improvements ($20K) for maximum efficiency B) Implement only trigger improvements ($20K) to address 30% of waste while deferring deduplication C) Implement only deduplication ($50K) to eliminate the more significant 40% waste D) Accept current costs as acceptable operational overhead and monitor quarterly

B

A global financial company uses Azure Blob Storage for transaction records (10PB, cost: $1M/year). Compliance requires 7-year retention, but audit shows 95% of queries access data

B

A startup's mobile app performs 100M API calls/day through Azure API Management ($50K/month). Analytics show 80% of calls are from bots/scrapers. Implementing rate limiting could block 40M bot calls but 5% legitimate traffic might also be blocked. Removing rate limiting would increase infrastructure costs by $30K/month due to resource contention but guarantee 99.9% legitimate traffic reaches API. What is the optimal approach? A) Implement aggressive rate limiting to eliminate bot traffic entirely B) Keep current configuration and absorb the $30K additional infrastructure cost C) Implement intelligent rate limiting with behavior-based detection to block likely bot traffic while preserving legitimate traffic D) Implement requirement for API authentication to eliminate anonymous bot traffic

C

A company migrates 100 applications from on-premises to Azure over 12 months. Month 6 post-migration, they discover unexpected cost: $2M/month vs. budgeted $800K/month due to underestimated licensing. Renegotiating Microsoft licenses for better rates takes 3 months and could save $400K/month. Implementing resource optimization could save $300K/month in 6 weeks. What is the prioritized cost-reduction strategy? A) Immediately implement resource optimization ($300K savings in 6 weeks) while parallel-pathing license renegotiation B) Pause license renegotiation and focus entirely on resource optimization for faster savings C) Initiate license renegotiation immediately to establish formal commitment before optimizing resources D) Accept temporary overage and recover through operational efficiency improvements over next 12 months

A

A healthcare system requires disaster recovery for critical databases: 15-minute RTO, 1-hour RPO. Current solution (daily snapshots + manual failover) achieves 24-hour RTO. Implementing continuous replication with automated failover would cost $200K/month but meets RTO. Implementing hourly snapshots with 2-hour manual restoration would cost $20K/month and achieves 2-hour RTO. Given budget constraints, what is the appropriate solution? A) Implement continuous replication ($200K/month) to achieve full 15-minute RTO requirement B) Implement hourly snapshots ($20K/month) as interim solution, plan for continuous replication upgrade when budget allows C) Maintain daily snapshots ($0 additional cost) and accept current RTO while prioritizing other compliance requirements D) Split approach: continuous replication for 3 most critical databases ($60K/month) + hourly snapshots for others

D

A company running Azure SQL Database discovers query performance degradation over 6 months: average query time increased 40% (200ms → 280ms). Database size increased 20%, no schema changes. Current: single General Purpose instance. Adding more cores would cost $5K/month. Implementing query optimization ($30K engineering) could achieve 30% improvement. What is the cost-optimal performance improvement strategy? A) Immediately upgrade to Business Critical tier for guaranteed performance ($5K/month) B) Implement query optimization engineering ($30K one-time, 30% improvement) C) Upgrade to Hyperscale tier with better performance characteristics ($10K/month) D) Implement query optimization ($30K) plus monitoring to prevent future degradation

D

A SaaS platform uses Azure Service Bus for asynchronous message processing (cost: $20K/month for 100K messages/day). Audit shows 60% of messages are status updates that could use Event Grid instead (cost: $5K/month for same volume). Converting to Event Grid would require code changes ($50K engineering, 3-week timeline). Service Bus is stable and handles current load adequately. What is the optimal architecture decision? A) Convert entirely to Event Grid ($50K engineering) for long-term cost savings B) Maintain Service Bus for stability and accept current cost C) Implement hybrid approach: Service Bus for transactional messages, Event Grid for status updates ($50K engineering saves $75K/year) D) Gradually migrate messages to Event Grid over 6 months to reduce risk

C

An organization with 50 Azure subscriptions discovers cost anomaly: $500K/month for resources that should cost $200K/month. Root cause: untagged resources making cost attribution impossible. Implementing comprehensive tagging would take 4 weeks and $50K engineering. During investigation, they identify $100K/month in clearly unused resources (orphaned VMs, abandoned storage accounts). What is the recommended first step? A) Immediately implement comprehensive tagging ($50K, 4 weeks) to understand all costs B) Quickly delete identified orphaned resources ($100K/month savings immediately), plan tagging for remaining cost understanding C) Implement automated Azure Policy to tag resources going forward while gradually addressing existing untagged resources D) Hire cost optimization consultant to audit all 50 subscriptions ($75K) before making changes

B

A fintech company processes 50K transactions/second at peak with strict ACID guarantees. Current: Azure SQL Managed Instance with failover groups (achieves strong consistency). During DR testing, failover from primary to secondary region takes 20 seconds, causing 1000+ transaction failures. Improving failover detection from 5 seconds to 2 seconds requires expensive hardware upgrade ($100K). Relaxing consistency to eventual consistency for 5 seconds during failover would eliminate failures without cost. Customers willing to accept 5-second eventual consistency windows. What is the optimal solution? A) Implement expensive hardware upgrade ($100K) to maintain strong consistency throughout failover B) Implement application-level eventual consistency window during failover detection to eliminate transaction failures C) Accept transaction failures as acceptable cost of disaster recovery and increase failover frequency testing D) Implement read-only mode during failover to eliminate write failures while maintaining consistency

B

A company's Azure Blob Storage bill jumps from $100K/month to $150K/month after major product launch. Investigation shows: 30% increase in stored data, 100% increase in data egress. Current: single-region hot storage. Implementing geo-redundant storage would save on egress costs ($30K/month) but increase storage costs ($15K/month). Implementing CDN would cost $20K/month but provide 50% egress reduction. What is the cost-optimal architecture? A) Upgrade to geo-redundant storage (net savings: $15K/month) B) Implement CDN (net savings: $40K/month) instead of geo-redundant storage C) Implement both CDN ($20K/month) and geo-redundant storage ($15K/month net) for comprehensive optimization (total savings: $55K/month) D) Implement only hot storage with aggressive cache policies to eliminate egress (minimal cost increase)

C

A manufacturing company runs real-time production monitoring on 1000+ IoT sensors. Current: Azure Event Hubs → Stream Analytics → Cosmos DB (cost: $80K/month). Response time from sensor to visualization dashboard: 5 seconds. Business requires <2 second response time for anomaly detection. Implementing faster pipeline would require: higher-tier Event Hubs ($30K/month), optimized Stream Analytics ($20K/month), Cosmos DB with stronger consistency ($15K/month). Total additional cost: $65K/month. What is the architectural recommendation? A) Upgrade all tiers for <2 second response time (additional $65K/month cost) B) Keep current architecture and accept 5-second latency as operational constraint C) Implement Edge computing with Azure IoT Edge for local anomaly detection, reducing cloud response time dependency D) Implement caching layer to reduce Cosmos DB queries, achieving <2 second SLA within current budget

C

A company with 50 Azure subscriptions discovers cost anomaly. Implementing comprehensive tagging would take 4 weeks and $50K. Implementing Azure Cost Analysis categorization using resource naming patterns + Azure Policy for new resources achieves 85% cost visibility in 1 week. What is the practical approach? A) Use Azure Cost Analysis automated categorization + resource naming patterns + Azure Policy while planning longer-term automated tagging B) Implement full tagging immediately despite timeline constraints C) Skip cost analysis and focus on optimization without visibility D) Use manual cost tracking spreadsheet

A

A company discovers Azure Blob Storage soft-delete is consuming $50K/month storing deleted blobs (5M deleted blobs/week = 50GB, 90-day retention). Soft-delete enabled by default. Disabling soft-delete immediately saves $50K/month but risks accidental deletion recovery. Selective soft-delete: disable for non-critical data, enable only for critical with automated immutable backups. What is the risk-balanced approach? A) Disable soft-delete entirely to save $50K/month immediately B) Keep soft-delete enabled for all data to maintain recovery capability C) Implement selective soft-delete: disable for non-critical data, enable only for critical with separate immutable backup policy D) Implement manual cleanup of soft-deleted blobs weekly

C

A company running batch processing on Azure Batch finds that current architecture processes 100K jobs/day with costs of $50K/month. New requirement: Process jobs within 1 hour vs. current 4-hour average latency. Achieving this requires: maintaining larger idle pool (additional $20K/month) or intelligent job pre-scheduling ($50K engineering for 80% prediction accuracy). What is achievable within current $50K budget? A) Upgrade to larger pool achieving 1-hour processing at $50K baseline cost B) Implement hybrid: statistical modeling ($10K engineering) predicting 60% of jobs, pre-warm capacity for high-probability types, accept 2-hour latency for remaining 40% C) Implement full 1-hour processing with $20K additional cost for idle pool D) Accept current 4-hour latency as operational constraint

B

A healthcare provider implements comprehensive Azure backup strategy costing $200K/month. 99% of recovery requests are <30 days old, 1% for older data. Keeping 10 years online costs $150K/month. Moving to: 30-day rolling Online tier ($50K/month) + older data to Archive tier. Archive retrieval SLA: 48 hours. What is optimal tiering? A) Keep all backups online at $200K/month for instant access B) Implement tiered: 30-day Online ($50K/month) + Archive for compliance, 48-hour retrieval SLA for older data C) Move all backups to Archive tier immediately for maximum cost savings D) Implement 7-day online retention only, delete older data

B

A company's Azure costs jump from $1M/month to $2.3M/month after product launch. Root cause: cross-region data transfer ($0.02/GB × 65TB/day transfer = $1.3M overage). Cost reduction options: (1) optimize transfer 50%: $100K engineering, $650K savings, (2) data locality/replication: $200K setup, $300K/month savings, (3) negotiate Microsoft discount: $0 setup, potential 10-20% savings. What is optimal first move? A) Immediately pursue option 2 (data locality) for fastest cost reduction B) Pursue option 1 (optimization) for engineering-driven improvement C) Negotiate volume discount immediately (zero cost, saves $130-260K/month) while pursuing optimization engineering D) Implement all three approaches simultaneously

C

A startup analyzes Azure costs and finds $100K/month savings via 3-year Reserved Instance commitment ($3.6M upfront). VC advises against long-term commitments for startup flexibility. Current cash: $10M. What is financial decision? A) Commit to full 3-year RI ($3.6M) for cost savings B) Avoid commitment to preserve flexibility and operational cash C) Use 1-year commitment ($1M cost) for core infrastructure, keep $3.6M for operational flexibility achieving $50K/month savings D) Don't commit and pay higher pay-as-you-go rates

C

A company running Azure Service Bus discovers $500K annual cost for messaging with 60% of throughput replaceable with Event Hubs at 1/10th cost. Migration: $100K engineering + $50K redesign cost. Is migration justified? A) No - current Service Bus sufficient, avoid engineering investment B) Yes: $600K total migration cost achieves $300K/year savings (2-year payback), execute phased migration starting with highest-throughput queues C) Maybe - implement partial migration to reduce risk D) No - stick with Service Bus to avoid complexity

B

A financial trading firm uses Azure dedicated hosts for HIPAA/PCI compliance customers. Cost: $2.5K/host/month. Currently: 30 hosts (75% utilized). Migration to shared infrastructure with software-based isolation (passing SOC2) would save $90K/year. Migration cost: $200K, timeline: 6 months. Is migration justified? A) No - stay on dedicated hosts for maximum security B) Yes: 6-month payback ($200K ÷ $30K savings per 6-month), then $90K/year perpetual savings, plus assuming 10% customer rejection still saves $75K/year overall C) No - 6-month payback too long, defer decision D) Maybe - implement pilot migration first

B

A company discovers Azure Hybrid Benefits usage is 200 licenses but only 150 licenses paid (Software Assurance agreements). Options: (1) pay $50K for 50 additional licenses, (2) remove 50 instances, (3) risk audit ($150K+ penalty). What is financial decision? A) Immediately pay $50K for compliance - cost of non-compliance risk far exceeds proactive payment B) Accept risk and avoid additional cost C) Implement cost optimization to reduce license count below 150 D) Renegotiate Software Assurance agreement

A

A startup's recommendation engine locked into Azure Cosmos DB reserved capacity until renewal (6 months). Actual peak load confirmed at 200K op/sec (80% over-provisioned). Early termination fee: $15K. Paying for waste: $30K/month for 6 months ($180K total). Should they terminate early? A) No - keep commitment to avoid termination penalty B) Keep commitment and optimize application to use reserved capacity C) Pay early termination ($15K) if confident in lower actual load - saves $65K total ($15K penalty vs. $180K waste) D) Renegotiate capacity with Microsoft

C

A company implements Azure Functions cold-start adding 500ms latency. Switching to always-on App Service costs 10x more ($50K vs. $5K/month). Traffic shows 70% warm (no cold-start), 30% cold-start. Moving only 30% to App Service costs additional $10K/month. Engineering effort to split: $20K. Is split justified? A) No - maintain single App Service for simplicity B) Yes: $20K engineering investment pays back in 6 months with ongoing $40K/month savings vs. $50K full migration C) No - accept cold-start latency as acceptable overhead D) Maybe - implement other optimization strategies first

B

A SaaS company discovers Cosmos DB bill doubled to $100K/month after one customer's heavy-write application impacts other customers' reads due to RU contention. Customer willing to pay for dedicated capacity but contract doesn't allow. Options: (1) move to separate instance ($150K setup, $20K/month), (2) API-layer throttling ($30K engineering), (3) upgrade tier ($60K/month). What is business-optimal? A) Move customer to dedicated instance accepting revenue loss B) Implement urgent API throttling ($30K, 2 weeks) to stabilize others, negotiate contract amendment for paid tier at premium ($25K/month additional revenue) C) Upgrade tier to handle all load ($60K/month) D) Accept performance degradation and retain customer at current pricing

B

A company discovers Azure Firewall unplanned cost: $100K/month. Rollback increases security risk on 20% of workload. Partial rollback protecting critical systems only costs $30K/month. What is risk-cost balanced approach? A) Rollback entirely to eliminate cost B) Implement partial rollback protecting critical systems ($30K/month), accept risk on non-critical systems with documented risk acceptance C) Maintain full Firewall ($100K/month) for complete protection D) Implement cheaper network security approach

B

A company uses Azure Hybrid Benefits (bring own Microsoft licenses). Audit reveals 200 licenses in use but only 150 paid in Software Assurance agreements. Compliance options: (1) pay $50K for 50 additional licenses, (2) remove 50 instances, (3) risk penalty. What is prudent decision? A) Pay $50K immediately - compliance is cheaper than contingent penalty liability B) Accept risk and avoid additional cost C) Implement aggressive cost optimization immediately D) Renegotiate Microsoft licensing terms

A

An organization discovers 90% of Azure Functions calls within 15 minutes of previous call (warm), 10% cold-start. Cold-start adds 500ms. Switching all to always-on App Service: 10x cost. Moving only cold-start workload (10%) to App Service: costs $5K/month additional. Engineering to split: $20K. Is split justified? A) Yes: $20K upfront pays back in 4 months with $60K/month ongoing savings vs. full expensive migration B) No - maintain all on Functions to minimize cost C) No - implement other cold-start mitigation strategies D) Maybe - pilot approach before full implementation

A

A company needs to reduce Azure costs from $5M/month to $3M/month. Engineering team identifies $800K/month savings potential from code optimization. Finance wants immediate $500K/month savings. Operations can achieve $300K/month through resource cleanup without engineering. What is prioritized approach? A) Implement operations cleanup ($300K immediate) only, defer engineering optimization B) Focus entirely on engineering optimization for larger long-term savings C) Implement operations cleanup ($300K immediate) + engineering optimization in parallel ($800K over 3 months) to meet immediate need while building longer-term solution D) Accept temporary overage and plan longer-term optimization

C

A healthcare provider implements encryption using customer-managed keys. Monthly rotation required per compliance. Cost: $50K setup + $5K/month. Azure Key Vault handles automated rotation. Manual rotation would be: $110K/year operational. What is appropriate implementation? A) Implement CMK with manual rotation to maintain control B) Use Microsoft-managed keys to avoid CMK costs C) Implement CMK with automated Key Vault rotation ($50K setup + $5K/month operational cost only, satisfies compliance) D) Defer encryption implementation until budget allows

C

A company using Cosmos DB for global user profiles ($200K/month) with eventual consistency experiences staleness issues. Strong consistency would cost 3x ($600K/month). Hybrid approach: strong for preferences, eventual for analytics (same $200K/month cost). What is optimal solution? A) Accept eventual consistency staleness issues and maintain current cost B) Upgrade to strong consistency ($600K/month) for consistency guarantee C) Implement hybrid consistency model ($200K/month with architectural effort required) D) Migrate to SQL Database for guaranteed consistency

C

A financial institution's batch processing on Azure Batch shows cost volatility: $20K-$80K/month depending on volume. $30K/month Reserved Instance covers expected capacity. Testing shows average actual load: $50K/month. What is financially optimal commitment? A) Pay-as-you-go ($50K/month average) with no commitment B) Commit to full $80K/month at Reserved Instance pricing C) Hybrid approach: $30K/month reserved capacity + pay-as-you-go for overages (optimal given load variability) D) Commit to $50K/month Reserved Instance pricing

C