Healthcare Data Processing - Function Timeout
MedConnect processes large medical imaging files (500MB-2GB) through Azure Functions for AI analysis. The current function times out after 5 minutes when processing larger files. The solution must maintain serverless benefits while handling variable file sizes. What should you do?
A. Increase the function timeout to 10 minutes in Consumption plan
B. Migrate to Premium hosting plan with 60-minute timeout
C. Use Durable Functions with activity chaining
D. Switch to Azure Container Instances for processing
Processing time varies from 2-45 minutes depending on file size and complexity. Must remain cost-effective for variable workloads.
Domain: Develop Azure Compute Solutions (25-30%)
Answer: C. Use Durable Functions with activity chaining.
Durable Functions can run indefinitely through orchestrator patterns and activity chaining, breaking large processing tasks into smaller chunks. This maintains serverless benefits while avoiding timeout limitations.
Option A is incorrect - Consumption plan maximum is 10 minutes. Option B works but loses cost benefits of serverless scaling. Option D abandons serverless architecture entirely.
Durable Functions provide unlimited execution time through orchestration patterns
Key services: Durable Functions, activity chaining, orchestrator pattern
E-Learning Platform - Database Scaling
EduTech’s learning platform experiences 10x traffic increase during exam periods. Their Azure SQL Database reaches DTU limits causing performance issues. The database contains course content (read-heavy) and user progress (write-heavy). What’s the most cost-effective scaling approach?
A. Scale up to higher DTU tier during peak periods
B. Implement read replicas for course content queries
C. Migrate to Azure SQL Managed Instance
D. Use Azure Cosmos DB for the entire application
Peak periods last 2-3 weeks twice yearly. Normal operations require minimal resources. Budget constraints require cost optimization.
Domain: Develop for Azure Storage (10-15%)
Answer: B. Implement read replicas for course content queries.
Read replicas handle the read-heavy course content queries, reducing load on the primary database for write operations (user progress). This targets the specific bottleneck cost-effectively.
Option A works but expensive during long peak periods. Option C is over-engineered and costly. Option D requires complete application rewrite and may not be cost-effective.
Read replicas specifically address read-heavy workload scaling patterns
Key services: Azure SQL Database, read replicas, workload separation
Financial API - Key Rotation
SecureFinance needs to implement automated certificate rotation for their REST APIs without service interruption. The system processes 50,000 transactions per minute with zero tolerance for downtime. Current certificates expire in 30 days. What’s the best approach?
A. Use Azure Key Vault auto-rotation with versioned secrets
B. Implement blue-green deployment with certificate updates
C. Use Application Gateway with automatic certificate renewal
D. Store certificates in Azure Storage with custom rotation logic
APIs are accessed by 200+ partner applications. Certificate updates must be seamless without partner notification requirements.
Domain: Implement Azure Security (15-20%)
Answer: A. Use Azure Key Vault auto-rotation with versioned secrets.
Key Vault auto-rotation provides seamless certificate updates through versioning, allowing applications to automatically retrieve the latest valid certificate without service interruption.
Option B requires deployment windows and potential downtime. Option C works for web applications but not comprehensive for API-to-API communication. Option D lacks the automated security features and compliance benefits of Key Vault.
Key Vault versioning enables zero-downtime certificate rotation
Key services: Azure Key Vault, auto-rotation, versioned secrets, certificate management
Video Streaming - Performance Monitoring
StreamMax serves 5 million users globally with video content. Users report buffering issues in specific regions, but current monitoring shows normal server performance. The team needs to identify the root cause of regional performance differences. What monitoring approach should they implement?
A. Enable Application Insights with custom telemetry for video metrics
B. Implement Azure Monitor with geo-distributed availability tests
C. Use Azure CDN analytics with real user monitoring
D. Deploy custom logging to track regional user experience
Issues appear region-specific with normal backend performance. Need correlation between user location and streaming quality metrics.
Domain: Monitor, Troubleshoot and Optimize Azure Solutions (10-15%)
Answer: C. Use Azure CDN analytics with real user monitoring.
CDN analytics provide region-specific performance data and real user monitoring captures actual user experience metrics by geographic location, directly addressing regional streaming performance issues.
Option A provides general telemetry but lacks geographic correlation. Option B tests synthetic transactions, not real user experience. Option D requires significant development effort and lacks built-in analytics capabilities.
CDN analytics provide geographic performance insights for content delivery optimization
Key services: Azure CDN, real user monitoring, analytics, geographic performance tracking
Retail Inventory - Event Processing
RetailChain processes inventory updates from 2000+ stores through various channels (POS systems, mobile apps, web). Updates must be processed in order per store to maintain accurate stock levels, but can be processed in parallel across stores. What messaging architecture should you implement?
A. Azure Service Bus queues with session-based processing
B. Azure Event Hubs with partition key by store ID
C. Azure Storage Queues with store-specific queue names
D. Azure Event Grid with custom topic filtering
Processing must guarantee order within each store but allow parallel processing across stores. Handle 100,000+ messages per hour during peak times.
Domain: Connect to and Consume Azure Services and Third-party Services (25-30%)
Answer: A. Azure Service Bus queues with session-based processing.
Service Bus sessions ensure ordered processing within each session (store) while allowing parallel processing across different sessions. This perfectly matches the requirement for per-store ordering with cross-store parallelism.
Option B lacks guaranteed ordering within partitions. Option C doesn’t provide session-based ordering guarantees. Option D is event-driven but doesn’t provide the queuing and ordering semantics needed.
Service Bus sessions provide ordered processing within sessions while enabling parallelism across sessions
Key services: Azure Service Bus, sessions, ordered processing, parallel processing
Manufacturing IoT - Data Pipeline
IndustryTech collects sensor data from 10,000+ manufacturing devices. Critical alerts need sub-second processing, while historical data requires batch processing for analytics. The system must handle device failures gracefully and provide exactly-once processing guarantees. What architecture should you design?
A. Event Hubs for ingestion with Stream Analytics for real-time and Data Factory for batch
B. IoT Hub with Azure Functions for alerts and Synapse for batch processing
C. Service Bus with Logic Apps for processing and SQL Database for storage
D. Event Grid with Function Apps for routing and Cosmos DB for storage
Device connectivity is intermittent. Critical alerts affect production safety. Historical analytics support business decisions requiring high accuracy.
Domain: Connect to and Consume Azure Services and Third-party Services (25-30%)
Answer: B. IoT Hub with Azure Functions for alerts and Synapse for batch processing.
IoT Hub is purpose-built for IoT scenarios with device management, security, and reliable messaging. Functions provide sub-second alert processing, while Synapse handles large-scale analytics. IoT Hub’s device twin and telemetry features handle device failures gracefully.
Option A lacks IoT-specific features like device management. Options C and D don’t provide IoT-optimized ingestion and device management capabilities.
IoT Hub provides comprehensive IoT device management and reliable messaging optimized for industrial scenarios
Key services: IoT Hub, Azure Functions, Synapse Analytics, device management
SaaS Multi-Tenant - Resource Isolation
CloudSoft provides project management SaaS to enterprise customers. Each customer requires complete data isolation for compliance, but the application code should remain shared. Customer usage varies dramatically (10-10,000 users per tenant). What architecture provides optimal isolation and cost efficiency?
A. Separate App Service and SQL Database per tenant
B. Shared App Service with tenant-specific databases
C. Container instances per tenant with shared database
D. Shared infrastructure with row-level security in database
Customers require audit trails showing complete data separation. Some customers need dedicated compute for performance SLAs while others prioritize cost efficiency.
Domain: Develop Azure Compute Solutions (25-30%)
Answer: B. Shared App Service with tenant-specific databases.
This approach balances cost efficiency (shared compute) with strong data isolation (separate databases) while meeting compliance requirements for data separation. Tenant-specific databases provide clear audit trails and isolation.
Option A is most secure but prohibitively expensive for smaller tenants. Option C complicates deployment and management. Option D provides weak isolation that may not meet enterprise compliance requirements.
Shared compute with isolated data stores balances cost efficiency with compliance requirements
Key services: App Service, Azure SQL Database, multi-tenant architecture, data isolation
Document Processing - Scalable Storage
LegalFirm manages millions of legal documents ranging from 1KB text files to 500MB scanned images. Documents have different access patterns: recent cases (daily access), closed cases (monthly), archived cases (yearly). The firm needs full-text search and must retain documents for 25 years for compliance. What storage strategy should you implement?
A. Blob Storage with lifecycle policies and Azure Cognitive Search
B. SharePoint Online with retention policies and search
C. Azure Files with tiered storage and SQL full-text search
D. Cosmos DB with TTL policies and built-in indexing
25-year retention is legally required. Search must cover document content, not just metadata. Cost optimization is critical due to storage volume growth.
Domain: Develop for Azure Storage (10-15%)
Answer: A. Blob Storage with lifecycle policies and Azure Cognitive Search.
Blob Storage lifecycle policies automatically move documents through access tiers based on age, optimizing costs over the 25-year retention period. Cognitive Search provides powerful full-text search capabilities across document content.
Option B has limitations on storage volume and cost at this scale. Option C lacks automated tiering for long-term cost optimization. Option D is not optimized for large document storage and lacks advanced search capabilities for document content.
Blob Storage lifecycle management optimizes long-term retention costs while Cognitive Search enables advanced document search
Key services: Blob Storage, lifecycle policies, Azure Cognitive Search, document retention
API Gateway - Security Implementation
TechAPI exposes internal microservices through a public API gateway. Different API consumers need different access levels: public APIs (rate limiting only), partner APIs (authentication required), internal APIs (full access). The system must prevent API abuse while maintaining sub-100ms response times. What security implementation should you use?
A. API Management with subscription keys and policies
B. Application Gateway with WAF and custom authentication
C. Azure Front Door with rate limiting and custom rules
D. Function Apps with custom middleware for authentication
Public APIs serve mobile apps, partner APIs serve B2B integrations, internal APIs serve web applications. Each tier has different SLA requirements.
Domain: Implement Azure Security (15-20%)
Answer: A. API Management with subscription keys and policies.
API Management provides comprehensive API security with subscription keys for authentication, granular policies for different access levels, and built-in rate limiting while maintaining low latency through caching and geographic distribution.
Option B focuses on web application security rather than API management. Option C provides CDN and DDoS protection but lacks comprehensive API management features. Option D requires significant custom development and lacks built-in API management capabilities.
API Management provides comprehensive API security, rate limiting, and policy enforcement optimized for API scenarios
Key services: API Management, subscription keys, policies, rate limiting
Real-time Analytics - Data Processing
SportsTech processes live game statistics from multiple sports venues. Data arrives in bursts during game events and must be processed within 2 seconds to update live scoreboards. Between games, the system is mostly idle. Processing includes complex calculations and external API calls. What compute approach provides optimal cost and performance?
A. Azure Functions with Premium plan and pre-warmed instances
B. Container Apps with scale-to-zero and burst scaling
C. App Service with autoscaling based on queue depth
D. Virtual Machine Scale Sets with predictive scaling
Game events create 1000x traffic spikes lasting 2-4 hours. Processing involves external sports data API integration requiring consistent performance during active periods.
Domain: Develop Azure Compute Solutions (25-30%)
Answer: A. Azure Functions with Premium plan and pre-warmed instances.
Premium plan provides sub-second cold start performance through pre-warmed instances while maintaining serverless cost benefits during idle periods. The plan handles burst scaling for 1000x traffic spikes while supporting complex processing and external API calls.
Option B may have cold start delays affecting the 2-second requirement. Option C maintains compute resources during idle periods, increasing costs. Option D requires manual scaling management and doesn’t provide the event-driven architecture benefits.
Functions Premium plan combines serverless cost benefits with consistent performance through pre-warmed instances
Key services: Azure Functions, Premium plan, pre-warmed instances, burst scaling
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Event-Driven Architecture - Message Ordering
EventCorp processes financial transactions through multiple microservices. Each customer’s transactions must be processed in order to maintain account balance accuracy, but different customers can be processed in parallel. The system handles 500,000 transactions per hour during market hours. What messaging solution should you implement?
A. Azure Event Grid with custom topic filters and Function App subscribers
B. Azure Service Bus queues with session-based processing using customer ID as session ID
C. Azure Event Hubs with partition key set to customer ID
D. Azure Storage Queues with separate queues per customer
Financial regulations require audit trails and exactly-once processing. System must handle market volatility spikes of 10x normal volume.
Domain: Connect to and Consume Azure Services and Third-party Services (25-30%)
Answer: B. Azure Service Bus queues with session-based processing using customer ID as session ID.
Service Bus sessions guarantee ordered processing within each session (customer) while enabling parallel processing across different customers. This meets financial compliance requirements with built-in duplicate detection and dead letter queues for failed transactions.
Option A lacks ordering guarantees. Option C doesn’t provide guaranteed ordering within partitions. Option D requires complex custom logic for ordering and lacks enterprise messaging features like duplicate detection.
Service Bus sessions provide FIFO ordering within sessions while maintaining high throughput across sessions
Key services: Azure Service Bus, sessions, ordered processing, duplicate detection
Container Orchestration - Scaling Strategy
ContainerTech runs a microservices architecture with 50+ services in production. Services have different scaling requirements: web APIs (predictable load), background processors (queue-based scaling), ML inference (GPU requirements). Current Kubernetes management overhead is high. What Azure container solution should you implement?
A. Azure Kubernetes Service (AKS) with Virtual Node scaling and GPU node pools
B. Azure Container Instances (ACI) with Logic Apps for orchestration
C. Azure Container Apps with KEDA-based autoscaling and CPU/GPU workload profiles
D. Azure App Service for containers with custom scaling rules
Must support GPU workloads, event-driven scaling, and reduce operational overhead. Budget requires cost optimization for idle periods.
Domain: Develop Azure Compute Solutions (25-30%)
Answer: C. Azure Container Apps with KEDA-based autoscaling and CPU/GPU workload profiles.
Container Apps provides serverless container orchestration with KEDA autoscaling for queue-based scaling, GPU support through workload profiles, and scale-to-zero capabilities for cost optimization. It reduces operational overhead compared to full Kubernetes management.
Option A provides more control but maintains high operational overhead. Option B lacks orchestration capabilities for complex microservices. Option D doesn’t support GPU workloads and has limited scaling options.
Container Apps offers managed Kubernetes benefits without operational complexity
Key services: Azure Container Apps, KEDA, workload profiles, serverless containers
Data Lake Analytics - Processing Pipeline
DataFlow processes petabytes of customer behavioral data for real-time personalization and historical analytics. Data arrives from web, mobile, and IoT sources. Real-time processing needs sub-second latency, while batch analytics can tolerate 24-hour delays. What architecture should you design?
A. Azure Synapse Analytics with dedicated SQL pools and Spark pools for all processing
B. Azure Stream Analytics for real-time + Azure Data Factory with Databricks for batch
C. Azure Event Hubs + Azure Functions for real-time + Synapse Serverless for batch
D. Cosmos DB with Change Feed + Azure Synapse for analytics
Data volumes grow 50% yearly. Must support machine learning model training and real-time inference. Cost optimization critical for batch workloads.
Domain: Develop for Azure Storage (10-15%)
Answer: B. Azure Stream Analytics for real-time + Azure Data Factory with Databricks for batch.
Stream Analytics provides low-latency real-time processing with built-in windowing functions. Data Factory orchestrates cost-effective batch processing with Databricks providing machine learning capabilities and auto-scaling clusters for variable workloads.
Option A uses expensive dedicated resources for all processing. Option C lacks orchestration for complex batch workflows. Option D isn’t optimized for large-scale analytics workloads.
Stream Analytics excels at real-time analytics while Databricks provides cost-effective batch ML processing
Key services: Stream Analytics, Data Factory, Databricks, data orchestration
Identity Federation - B2B Integration
PartnerNet enables B2B collaboration where external partners access internal applications using their own corporate identities. 200+ partner organizations use different identity providers (Azure AD, Google Workspace, ADFS). Users need single sign-on without creating new accounts. What identity solution should you implement?
A. Azure AD B2C with custom policies and identity provider federation
B. Azure AD B2B with guest user invitations and direct federation
C. API Management with OAuth 2.0 and custom authentication providers
D. Application Gateway with Azure AD authentication and user provisioning
Partners manage their own users and security policies. Solution must support just-in-time access and conditional access policies. Integration should require minimal partner setup.
Domain: Implement Azure Security (15-20%)
Answer: B. Azure AD B2B with guest user invitations and direct federation.
Azure AD B2B enables external partner users to access resources using their home organization credentials. Direct federation allows automatic provisioning with partner identity providers. Supports conditional access and just-in-time access without requiring partners to create new identity infrastructure.
Option A is designed for customer scenarios, not B2B partner collaboration. Option C requires custom development and lacks enterprise identity features. Option D focuses on application-level authentication rather than comprehensive B2B identity federation.
B2B collaboration maintains partner identity ownership while enabling seamless access
Key services: Azure AD B2B, direct federation, conditional access, guest users
Disaster Recovery - Multi-Region Strategy
CriticalApp serves financial services requiring 99.99% availability and RPO of 15 minutes. The application uses App Service, SQL Database, and Blob Storage. Current single-region deployment creates business risk. Regulatory requirements mandate data residency in specific regions. What disaster recovery strategy should you implement?
A. Azure Site Recovery with VM replication to secondary region
B. App Service with Traffic Manager + SQL Database geo-replication + GRS storage
C. Azure Front Door with multi-region deployment and active-active configuration
D. Availability Zones within single region with zone-redundant services
Failover time must be under 5 minutes. Costs should remain reasonable during normal operations. Must maintain compliance across regions.
Domain: Monitor, Troubleshoot and Optimize Azure Solutions (10-15%)
Answer: B. App Service with Traffic Manager + SQL Database geo-replication + GRS storage.
This provides automated failover meeting RPO/RTO requirements. SQL geo-replication ensures data consistency, GRS storage provides automatic replication, and Traffic Manager handles DNS-based failover. Cost-effective as secondary region resources are used only during disasters.
Option A requires VM management complexity. Option C provides better performance but higher costs with active-active setup. Option D doesn’t address region-level disasters.
Geo-replication with automated failover balances availability and cost for disaster recovery
Key services: Traffic Manager, SQL geo-replication, GRS storage, disaster recovery
Serverless Integration - Workflow Orchestration
WorkflowCorp automates business processes involving document approval, email notifications, and third-party API integrations. Processes can take hours to complete with human approval steps. Need error handling, retry logic, and audit trails. What serverless orchestration approach should you use?
A. Azure Functions with Durable Functions orchestrator pattern
B. Azure Logic Apps with built-in connectors and approval workflows
C. Azure Event Grid with Function Apps for each workflow step
D. Azure Service Bus with Function Apps and custom state management
Workflows involve external dependencies and human interactions. Must handle long-running processes and provide visual workflow monitoring. Non-technical users need to modify workflows.
Domain: Connect to and Consume Azure Services and Third-party Services (25-30%)
Answer: B. Azure Logic Apps with built-in connectors and approval workflows.
Logic Apps provides visual workflow designer, built-in connectors for common services, human approval steps, and comprehensive monitoring. Declarative approach allows non-technical users to modify workflows without coding. Handles long-running workflows with automatic state management.
Option A requires significant coding for UI and approval processes. Option C lacks workflow orchestration and state management. Option D requires custom development for workflow features.
Logic Apps excels at business process automation with visual design and built-in integrations
Key services: Logic Apps, workflow orchestration, human approval, visual designer
High-Performance Computing - Batch Processing
ScienceCloud processes large-scale simulations requiring thousands of CPU cores for 2-12 hour jobs. Workloads are batch-oriented with variable demand (heavy during research deadlines, idle between projects). Need cost optimization and support for custom software environments. What compute solution should you implement?
A. Azure Batch with auto-scaling pools and custom VM images
B. Azure CycleCloud with HPC clusters and Slurm scheduler
C. Azure Container Instances with container groups for parallel processing
D. Azure Kubernetes Service with job controllers and node autoscaling
Jobs require MPI communication, shared file systems, and specialized software. Budget requires pay-per-use model with automatic resource cleanup.
Domain: Develop Azure Compute Solutions (25-30%)
Answer: A. Azure Batch with auto-scaling pools and custom VM images.
Azure Batch is purpose-built for large-scale parallel workloads with automatic scaling, job scheduling, and cost optimization through low-priority VMs. Supports custom VM images for specialized software and automatic cleanup after job completion.
Option B provides more HPC features but requires more management overhead. Option C lacks HPC-specific features like MPI support. Option D requires significant configuration for HPC workloads and job management.
Azure Batch optimizes parallel processing with automatic resource management and cost controls
Key services: Azure Batch, auto-scaling, low-priority VMs, parallel processing
API Rate Limiting - Traffic Management
APIGateway serves mobile applications with 1 million+ daily users. Different user tiers have different rate limits: Free (100 requests/hour), Premium (10,000 requests/hour), Enterprise (unlimited). Need real-time enforcement, analytics, and developer portal. What API management strategy should you implement?
A. Azure API Management with subscription-based policies and rate limiting
B. Azure Front Door with rate limiting rules and WAF policies
C. Azure Application Gateway with custom rate limiting and backend pools
D. Azure Functions with custom middleware and Redis caching for rate tracking
Must provide detailed analytics, developer onboarding, and API versioning. System handles traffic spikes during product launches with burst allowances.
Domain: Connect to and Consume Azure Services and Third-party Services (25-30%)
Answer: A. Azure API Management with subscription-based policies and rate limiting.
API Management provides comprehensive API governance with subscription-based rate limiting, developer portal, detailed analytics, and policy-based traffic management. Supports burst allowances and different rate limits per subscription tier with real-time enforcement.
Option B focuses on CDN and security, not API management features. Option C lacks API-specific features like developer portal. Option D requires extensive custom development for API management capabilities.
API Management provides complete API lifecycle management with built-in rate limiting and developer experience
Key services: API Management, rate limiting, subscription policies, developer portal
Machine Learning Pipeline - Model Deployment
MLOps team deploys machine learning models for real-time prediction and batch scoring. Models are retrained weekly with new data. Need A/B testing, model versioning, and automatic rollback on performance degradation. What ML deployment strategy should you implement?
A. Azure Machine Learning with managed endpoints and blue-green deployments
B. Azure Container Instances with custom model serving and load balancing
C. Azure App Service with deployment slots for model versions
D. Azure Kubernetes Service with custom ML serving infrastructure
Models serve 100,000+ predictions/day with sub-100ms latency requirements. Must support multiple model versions and traffic splitting for experiments.
Domain: Develop Azure Compute Solutions (25-30%)
Answer: A. Azure Machine Learning with managed endpoints and blue-green deployments.
Azure ML managed endpoints provide native ML model serving with built-in A/B testing, traffic splitting, automatic scaling, and model versioning. Blue-green deployments enable safe rollouts with automatic rollback based on performance metrics.
Option B requires custom development for ML-specific features. Option C lacks ML-optimized serving capabilities. Option D requires significant infrastructure management and custom ML serving logic.
Azure ML managed endpoints provide enterprise-grade ML serving with built-in MLOps capabilities
Key services: Azure Machine Learning, managed endpoints, blue-green deployments, A/B testing
Cost Optimization - Reserved Capacity
FinanceApp runs predictable workloads with consistent resource usage for core business hours (8 AM - 6 PM weekdays). Usage drops 80% during nights and weekends. Current pay-as-you-go costs are high. Need cost optimization while maintaining performance during business hours. What pricing strategy should you implement?
A. Azure Reserved Instances for baseline capacity + autoscaling for peaks
B. Azure Spot VMs for all workloads with automatic failover
C. Azure Hybrid Benefit with on-premises license migration
D. Consumption-based pricing with automatic shutdown during off-hours
Must maintain SLA compliance and quick scale-up capabilities. Budget constraints require 30% cost reduction while ensuring business continuity.
Domain: Monitor, Troubleshoot and Optimize Azure Solutions (10-15%)
Answer: A. Azure Reserved Instances for baseline capacity + autoscaling for peaks.
Reserved Instances provide significant cost savings (up to 72%) for predictable baseline usage during business hours. Autoscaling handles demand peaks with pay-as-you-go pricing for additional capacity. This hybrid approach optimizes costs while maintaining performance guarantees.
Option B risks service interruptions with spot instance evictions. Option C only applies to specific licensing scenarios. Option D may impact availability during critical business operations.
Reserved capacity combined with autoscaling optimizes both cost and performance for predictable workloads
Key services: Reserved Instances, autoscaling, cost optimization, hybrid pricing
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E-Commerce Platform - App Service Configuration
TechRetail Inc. is modernizing their legacy e-commerce platform. You need to host the main web application with support for staging deployments and automatic scaling. Which Azure service should you use and how would you configure it?
Must support .NET 8 applications, zero-downtime deployments required, handle 10x traffic spikes during sales events
Domain: Develop Azure Compute Solutions (25-30%)
Use Azure App Service with deployment slots. Create a production slot and staging slot, configure autoscaling rules based on CPU/memory metrics, and use slot swapping for zero-downtime deployments. Configure the App Service Plan with Standard or Premium tier for deployment slots support.
Consider using staging slot for testing before production deployment
Key services: App Service, deployment slots, autoscaling
E-Commerce Platform - Serverless Order Processing
The order processing system experiences variable workloads (high during sales, low overnight). How would you implement a cost-effective serverless solution for TechRetail Inc.?
Variable workloads with significant cost optimization requirements, integration with existing payment processors
Domain: Develop Azure Compute Solutions (25-30%)
Use Azure Functions with Consumption hosting plan. Create functions triggered by Service Bus queues for order processing. The Consumption plan automatically scales from zero and charges only for execution time, making it cost-effective for variable workloads.
Consumption plan is ideal for unpredictable workloads
Key services: Azure Functions, Consumption plan, Service Bus
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Develop Azure Compute Solutions (25-30%)111
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Develop for Azure Storage (15-20%)82
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Implement Azure Security (15-20%)41
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Monitor, Troubleshoot, and Optimize Azure Solutions (10-15%)25
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Connect to and Consume Azure Services and Third-party Services (20-25%)38
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Case Studies32
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Test111
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