Mastering Serverless Data Analytics for Future-Proof Career Growth
You're at a turning point. The world of data analytics is shifting fast, and traditional architectures are becoming costly, slow, and hard to scale. If you're still relying on manual pipelines, over-provisioned servers, or batch processing models, you're already falling behind. The future belongs to those who can deliver real-time insights at scale, with agility and precision. Enter serverless data analytics. It’s not just a trend-it’s the core infrastructure of high-performance data systems across Silicon Valley, global banks, and Fortune 500 innovation labs. But most professionals are stuck. They don’t know where to start, which tools to trust, or how to translate platform features into business outcomes. Mastering Serverless Data Analytics for Future-Proof Career Growth is your direct path from uncertainty to confidence. This is not a theoretical overview. It's a battle-tested, outcome-driven programme designed to take you from concept to deployment of production-ready serverless analytics pipelines in under 30 days-with a board-ready implementation framework you can present immediately. Jamie R., a senior data architect at a leading fintech in London, used this exact framework to replace a $42,000/month legacy ETL system with a fully automated, event-driven serverless pipeline. The result? 68% cost reduction, 94% improvement in latency, and a promotion within 8 weeks. No prior AWS Lambda or streaming expertise required. If you're tired of being reactive, overwhelmed by complexity, or unsure how to stay relevant as AI and real-time analytics dominate, this is your moment. The tools are accessible. The methods are proven. The demand for your skills is accelerating. Your competition isn’t waiting. They’re building faster, cheaper, and smarter. This course gives you the exact architecture blueprints, security protocols, cost optimisation strategies, and deployment workflows that top-tier organisations now expect. Here’s how this course is structured to help you get there.Course Format & Delivery Details Flexible, Immediate, and Built for Your Career Rhythm
This is a self-paced, on-demand learning experience with full lifetime access. You begin the moment you're ready. No fixed schedules, no expiration, and no pressure to catch up. Dive in during your morning commute, late-night deep work sessions, or weekend upskilling blocks-your progress is always preserved. Learners typically complete the core implementation track in 21 to 28 days, with many reporting functional prototype deployment by Day 10. You can go faster. You can go slower. The structure adapts to you, not the other way around. Continuous Updates, Zero Extra Cost
Cloud platforms evolve constantly. That’s why your enrolment includes automatic updates at no additional charge. Every time AWS, Azure, or GCP releases a new serverless analytics capability, our curriculum evolves with it-ensuring your knowledge stays current for years. Trusted, Recognised Certification
Upon completion, you earn a Certificate of Completion issued by The Art of Service. This credential is globally recognised, verified, and cited by professionals in over 78 countries. Recruiters at Google, Deloitte, and Siemens have confirmed it as a differentiator in technical evaluations. Mobile-Friendly, Always Accessible
Access your materials anytime, anywhere. Our platform is fully responsive and compatible with smartphones, tablets, and desktops. Review architecture diagrams on your phone during downtime or study deployment checklists from the airport lounge-your learning follows you. Practical Support, Real Guidance
This is not a solo journey. You’ll receive direct feedback on your implementation roadmap from certified cloud instructors with 10+ years of real-world serverless systems design. Submit your architecture decisions, security configurations, or cost models, and get detailed written guidance to refine your work. No Risk. Guaranteed.
We offer a 30-day satisfied or refunded commitment. If this course doesn’t deliver measurable clarity, structured guidance, and tangible advancement in your technical execution, simply request a full refund. No forms, no hoops, no questions asked. Secure, Transparent, and Hassle-Free Enrollment
Pricing is straightforward with no hidden fees, subscriptions, or upsells. One payment, full access. We accept Visa, Mastercard, and PayPal. After enrolment, you’ll receive a confirmation email, and your access credentials will be sent separately once your course materials are prepared. “Will This Work for Me?” - We’ve Got You Covered
Yes. This works whether you’re a data analyst moving into engineering, a cloud newcomer from a non-traditional background, or a legacy ETL developer transitioning to modern architectures. Our learners include Microsoft data leads, NHS health informatics specialists, and UN analytics officers-all with different starting points, all achieving the same outcome: deployable, scalable, secure serverless systems. This works even if you’ve never provisioned a cloud function, written an event trigger, or used a stream processor. The step-by-step workflows assume zero advanced knowledge and are built to scaffold your learning with confidence. Your success is protected by design. From onboarding clarity to gamified progress tracking and real-time feedback loops, every element reduces friction and increases your odds of completion and mastery.
Module 1: Foundations of Serverless Data Analytics - Understanding the shift from server-based to serverless computing
- Key economic drivers of serverless adoption in data platforms
- Core principles of event-driven architecture
- Defining cold starts, concurrency, and auto-scaling behaviour
- Comparing serverless to containers and VMs in analytics workloads
- Understanding pay-per-execution pricing models
- Common use cases: real-time dashboards, fraud detection, IoT telemetry
- Vendor landscape: AWS Lambda, Azure Functions, Google Cloud Functions
- When not to go serverless: anti-patterns and limitations
- Setting up your cloud sandbox environment securely
- Managing IAM roles and permissions for least-privilege access
- Using infrastructure-as-code for repeatable environments
- Cloud provider account setup and billing alerts
- Tool selection criteria: region availability, cold start performance, VPC integration
- Introduction to observability in serverless systems
Module 2: Core Architecture Patterns for Analytics Workflows - Event sourcing vs polling: breaking down the trade-offs
- Designing data ingestion pipelines with minimal latency
- Building fan-out architectures with message brokers
- Chain execution flows using step functions and orchestration tools
- Idempotency design for fault-tolerant processing
- State management in stateless functions
- Using dead-letter queues for error handling
- Implementing circuit breakers in serverless contexts
- Parallel processing for batch analytics at scale
- Streaming vs batch: choosing the right model for your data
- Backpressure handling in high-volume scenarios
- Asynchronous invocation patterns and callback handling
- Request-response vs fire-and-forget execution models
- Security context propagation across service boundaries
- Architecture decision records for team alignment
Module 3: Serverless Data Ingestion and Event Sources - Configuring Amazon S3 event notifications for analytics triggers
- Using API Gateway to inject data from external applications
- Processing data from AWS Kinesis Data Streams
- Integrating with Apache Kafka on Confluent Cloud
- Consuming events from Azure Event Hubs
- Using Google Cloud Pub/Sub as a serverless messaging backbone
- Database change capture with DynamoDB Streams
- Working with RDS binary logs and Debezium
- Setting up IoT device telemetry ingestion
- Batch file polling with scheduled triggers (Cron expressions)
- Processing form submissions and webhook payloads
- Using EventBridge rules to route events dynamically
- Schema validation at ingestion time with AWS Glue Schema Registry
- Handling multi-tenant data routing in shared functions
- Rate limiting and throttling upstream producers
Module 4: Processing and Transformation with Serverless Compute - Writing Lambda functions in Python and Node.js
- Optimising function layers for reusability
- Managing dependencies with container images and zip deployments
- Minimising cold start times with provisioned concurrency
- Using async await patterns for non-blocking operations
- Parsing JSON, CSV, Parquet, and Avro formats
- Streaming data transformation with line-by-line processing
- Calling external APIs securely within functions
- Using environment variables and secrets management
- Batching operations to reduce API call overhead
- Error handling and retry logic with exponential backoff
- Structuring code for testability and readability
- Performance benchmarking of function execution time
- Memory allocation optimisation for cost-performance balance
- Using custom runtimes for legacy or niche languages
Module 5: Real-Time Stream Processing at Scale - Introduction to event time vs processing time semantics
- Windowing strategies: tumbling, sliding, session
- Using AWS Lambda with Kinesis for real-time analytics
- Processing streams with Azure Functions and Event Hubs
- Google Cloud Functions with Pub/Sub: guaranteed delivery models
- Aggregating metrics: counts, averages, percentiles
- Implementing deduplication in stream pipelines
- Detecting anomalies in live data feeds
- Stateful processing with DynamoDB as backing store
- Watermarking for late-arriving data
- Checkpointing to resume from failure points
- Scaling stream consumers across partitions
- Monitoring stream lag and processing backlog
- Backfilling historical data into streaming systems
- Testing stream logic with synthetic data generators
Module 6: Serverless Data Storage and Cataloging - Choosing storage backends: S3 vs DynamoDB vs Firestore
- Partitioning strategies for high-throughput writes
- Using S3 as a data lake foundation for analytics
- Versioning and lifecycle policies for cost control
- Enabling Cross-Region Replication for disaster recovery
- Setting up lifecycle transitions to Glacier
- Integrating AWS Glue for metadata extraction
- Creating and managing data catalogues
- Schema evolution handling in Parquet and ORC formats
- Implementing ACID transactions in serverless databases
- Using Athena for SQL queries on S3 data
- Building materialised views for fast reporting
- Partition pruning and predicate pushdown optimisation
- Securing data at rest with KMS and customer-managed keys
- Auditing data access with CloudTrail and DataZone
Module 7: Analytics Orchestration and Workflow Automation - Using AWS Step Functions for state machine design
- Creating parallel branches for independent tasks
- Defining error handling paths and fallback logic
- Implementing human approval gates in automated workflows
- Integrating with Slack and Teams for notifications
- Building retry loops with contextual data persistence
- Using dynamic parallelism for variable workloads
- Passing data between states with result selectors
- Versioning and testing workflows in isolation
- Modelling long-running processes with wait states
- Monitoring workflow execution with CloudWatch metrics
- Cost analysis of orchestration overhead
- Recovering from workflow failures with replay tools
- Integrating with third-party workflow engines
- Exporting workflow definitions as code for CI/CD
Module 8: Security, Compliance, and Governance - Principle of least privilege for function roles
- Securing environment variables with parameter stores
- Using VPCs and private subnets for data isolation
- Encrypting data in transit with TLS 1.3
- Enabling end-to-end encryption for sensitive fields
- Managing secrets with AWS Secrets Manager
- Integrating with AWS IAM and Azure AD
- Setting up audit trails with CloudTrail and Logging
- GDPR and CCPA compliance in data pipelines
- Data residency and sovereignty constraints
- Masking PII in logs and error messages
- Implementing data retention schedules
- Role-based access control in data catalogues
- Penetration testing serverless APIs
- Using AWS Config to enforce compliance rules
Module 9: Performance Optimisation and Debugging - Analysing function duration with CloudWatch Logs Insights
- Reducing memory usage with efficient data structures
- Minimising network hops with edge placement
- Warming up connections with external services
- Reusing database connections across invocations
- Using persistent storage in /tmp for caching
- Profiling CPU and memory bottlenecks
- Setting realistic timeouts to avoid truncation
- Using X-Ray for distributed tracing
- Analysing cold start patterns across regions
- Choosing the right runtime for performance
- Eliminating redundant code in execution paths
- Monitoring invocation concurrency limits
- Tuning Kinesis shard count for throughput
- Using custom metrics for SLI tracking
Module 10: Cost Management and Budgeting - Understanding serverless pricing models by provider
- Estimating monthly costs based on invocation volume
- Using AWS Pricing Calculator for projections
- Setting up billing alarms and cost alerts
- Identifying cost spikes with anomaly detection
- Right-sizing memory and timeout configurations
- Avoiding unnecessary reprocessing with idempotency
- Using reserved concurrency to prevent bill shock
- Monitoring data transfer costs between zones
- Choosing availability zones for cost efficiency
- Archiving cold data to reduce query spend
- Using Spot equivalents for preview workloads
- Analysing cost per transformation step
- Implementing budget enforcement via policies
- Reporting cost efficiency to stakeholders
Module 11: Observability and Monitoring Systems - Setting up CloudWatch Alarms for error rates
- Creating custom dashboards for KPI tracking
- Using structured logging with JSON format
- Correlating logs across distributed services
- Setting up distributed tracing with X-Ray
- Annotating traces with business context
- Monitoring function concurrency and throttling
- Using synthetic transactions for uptime checks
- Alerting on latency percentiles (p95, p99)
- Integrating with third-party tools like Datadog
- Setting up SLOs and error budgets
- Automating incident response with runbooks
- Exporting logs to long-term storage
- Analysing error patterns with log group queries
- Building health check endpoints for external monitoring
Module 12: CI/CD and DevOps for Serverless - Setting up CI pipelines with GitHub Actions
- Using Jenkins for serverless deployment automation
- Managing multiple environments: dev, test, prod
- Versioning functions with alias and stage support
- Implementing blue-green deployments
- Canary testing with gradual traffic shifting
- Using SAM CLI for local testing
- Validating templates with cfn-lint
- Storing deployment artefacts in version-controlled buckets
- Automating security scans in pre-deploy hooks
- Rolling back failed deployments automatically
- Using Terraform for infrastructure provisioning
- Managing configurations across environments
- Integrating with CI/CD secrets managers
- Reporting deployment status to stakeholder channels
Module 13: Data Visualisation and Dashboarding - Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Understanding the shift from server-based to serverless computing
- Key economic drivers of serverless adoption in data platforms
- Core principles of event-driven architecture
- Defining cold starts, concurrency, and auto-scaling behaviour
- Comparing serverless to containers and VMs in analytics workloads
- Understanding pay-per-execution pricing models
- Common use cases: real-time dashboards, fraud detection, IoT telemetry
- Vendor landscape: AWS Lambda, Azure Functions, Google Cloud Functions
- When not to go serverless: anti-patterns and limitations
- Setting up your cloud sandbox environment securely
- Managing IAM roles and permissions for least-privilege access
- Using infrastructure-as-code for repeatable environments
- Cloud provider account setup and billing alerts
- Tool selection criteria: region availability, cold start performance, VPC integration
- Introduction to observability in serverless systems
Module 2: Core Architecture Patterns for Analytics Workflows - Event sourcing vs polling: breaking down the trade-offs
- Designing data ingestion pipelines with minimal latency
- Building fan-out architectures with message brokers
- Chain execution flows using step functions and orchestration tools
- Idempotency design for fault-tolerant processing
- State management in stateless functions
- Using dead-letter queues for error handling
- Implementing circuit breakers in serverless contexts
- Parallel processing for batch analytics at scale
- Streaming vs batch: choosing the right model for your data
- Backpressure handling in high-volume scenarios
- Asynchronous invocation patterns and callback handling
- Request-response vs fire-and-forget execution models
- Security context propagation across service boundaries
- Architecture decision records for team alignment
Module 3: Serverless Data Ingestion and Event Sources - Configuring Amazon S3 event notifications for analytics triggers
- Using API Gateway to inject data from external applications
- Processing data from AWS Kinesis Data Streams
- Integrating with Apache Kafka on Confluent Cloud
- Consuming events from Azure Event Hubs
- Using Google Cloud Pub/Sub as a serverless messaging backbone
- Database change capture with DynamoDB Streams
- Working with RDS binary logs and Debezium
- Setting up IoT device telemetry ingestion
- Batch file polling with scheduled triggers (Cron expressions)
- Processing form submissions and webhook payloads
- Using EventBridge rules to route events dynamically
- Schema validation at ingestion time with AWS Glue Schema Registry
- Handling multi-tenant data routing in shared functions
- Rate limiting and throttling upstream producers
Module 4: Processing and Transformation with Serverless Compute - Writing Lambda functions in Python and Node.js
- Optimising function layers for reusability
- Managing dependencies with container images and zip deployments
- Minimising cold start times with provisioned concurrency
- Using async await patterns for non-blocking operations
- Parsing JSON, CSV, Parquet, and Avro formats
- Streaming data transformation with line-by-line processing
- Calling external APIs securely within functions
- Using environment variables and secrets management
- Batching operations to reduce API call overhead
- Error handling and retry logic with exponential backoff
- Structuring code for testability and readability
- Performance benchmarking of function execution time
- Memory allocation optimisation for cost-performance balance
- Using custom runtimes for legacy or niche languages
Module 5: Real-Time Stream Processing at Scale - Introduction to event time vs processing time semantics
- Windowing strategies: tumbling, sliding, session
- Using AWS Lambda with Kinesis for real-time analytics
- Processing streams with Azure Functions and Event Hubs
- Google Cloud Functions with Pub/Sub: guaranteed delivery models
- Aggregating metrics: counts, averages, percentiles
- Implementing deduplication in stream pipelines
- Detecting anomalies in live data feeds
- Stateful processing with DynamoDB as backing store
- Watermarking for late-arriving data
- Checkpointing to resume from failure points
- Scaling stream consumers across partitions
- Monitoring stream lag and processing backlog
- Backfilling historical data into streaming systems
- Testing stream logic with synthetic data generators
Module 6: Serverless Data Storage and Cataloging - Choosing storage backends: S3 vs DynamoDB vs Firestore
- Partitioning strategies for high-throughput writes
- Using S3 as a data lake foundation for analytics
- Versioning and lifecycle policies for cost control
- Enabling Cross-Region Replication for disaster recovery
- Setting up lifecycle transitions to Glacier
- Integrating AWS Glue for metadata extraction
- Creating and managing data catalogues
- Schema evolution handling in Parquet and ORC formats
- Implementing ACID transactions in serverless databases
- Using Athena for SQL queries on S3 data
- Building materialised views for fast reporting
- Partition pruning and predicate pushdown optimisation
- Securing data at rest with KMS and customer-managed keys
- Auditing data access with CloudTrail and DataZone
Module 7: Analytics Orchestration and Workflow Automation - Using AWS Step Functions for state machine design
- Creating parallel branches for independent tasks
- Defining error handling paths and fallback logic
- Implementing human approval gates in automated workflows
- Integrating with Slack and Teams for notifications
- Building retry loops with contextual data persistence
- Using dynamic parallelism for variable workloads
- Passing data between states with result selectors
- Versioning and testing workflows in isolation
- Modelling long-running processes with wait states
- Monitoring workflow execution with CloudWatch metrics
- Cost analysis of orchestration overhead
- Recovering from workflow failures with replay tools
- Integrating with third-party workflow engines
- Exporting workflow definitions as code for CI/CD
Module 8: Security, Compliance, and Governance - Principle of least privilege for function roles
- Securing environment variables with parameter stores
- Using VPCs and private subnets for data isolation
- Encrypting data in transit with TLS 1.3
- Enabling end-to-end encryption for sensitive fields
- Managing secrets with AWS Secrets Manager
- Integrating with AWS IAM and Azure AD
- Setting up audit trails with CloudTrail and Logging
- GDPR and CCPA compliance in data pipelines
- Data residency and sovereignty constraints
- Masking PII in logs and error messages
- Implementing data retention schedules
- Role-based access control in data catalogues
- Penetration testing serverless APIs
- Using AWS Config to enforce compliance rules
Module 9: Performance Optimisation and Debugging - Analysing function duration with CloudWatch Logs Insights
- Reducing memory usage with efficient data structures
- Minimising network hops with edge placement
- Warming up connections with external services
- Reusing database connections across invocations
- Using persistent storage in /tmp for caching
- Profiling CPU and memory bottlenecks
- Setting realistic timeouts to avoid truncation
- Using X-Ray for distributed tracing
- Analysing cold start patterns across regions
- Choosing the right runtime for performance
- Eliminating redundant code in execution paths
- Monitoring invocation concurrency limits
- Tuning Kinesis shard count for throughput
- Using custom metrics for SLI tracking
Module 10: Cost Management and Budgeting - Understanding serverless pricing models by provider
- Estimating monthly costs based on invocation volume
- Using AWS Pricing Calculator for projections
- Setting up billing alarms and cost alerts
- Identifying cost spikes with anomaly detection
- Right-sizing memory and timeout configurations
- Avoiding unnecessary reprocessing with idempotency
- Using reserved concurrency to prevent bill shock
- Monitoring data transfer costs between zones
- Choosing availability zones for cost efficiency
- Archiving cold data to reduce query spend
- Using Spot equivalents for preview workloads
- Analysing cost per transformation step
- Implementing budget enforcement via policies
- Reporting cost efficiency to stakeholders
Module 11: Observability and Monitoring Systems - Setting up CloudWatch Alarms for error rates
- Creating custom dashboards for KPI tracking
- Using structured logging with JSON format
- Correlating logs across distributed services
- Setting up distributed tracing with X-Ray
- Annotating traces with business context
- Monitoring function concurrency and throttling
- Using synthetic transactions for uptime checks
- Alerting on latency percentiles (p95, p99)
- Integrating with third-party tools like Datadog
- Setting up SLOs and error budgets
- Automating incident response with runbooks
- Exporting logs to long-term storage
- Analysing error patterns with log group queries
- Building health check endpoints for external monitoring
Module 12: CI/CD and DevOps for Serverless - Setting up CI pipelines with GitHub Actions
- Using Jenkins for serverless deployment automation
- Managing multiple environments: dev, test, prod
- Versioning functions with alias and stage support
- Implementing blue-green deployments
- Canary testing with gradual traffic shifting
- Using SAM CLI for local testing
- Validating templates with cfn-lint
- Storing deployment artefacts in version-controlled buckets
- Automating security scans in pre-deploy hooks
- Rolling back failed deployments automatically
- Using Terraform for infrastructure provisioning
- Managing configurations across environments
- Integrating with CI/CD secrets managers
- Reporting deployment status to stakeholder channels
Module 13: Data Visualisation and Dashboarding - Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Configuring Amazon S3 event notifications for analytics triggers
- Using API Gateway to inject data from external applications
- Processing data from AWS Kinesis Data Streams
- Integrating with Apache Kafka on Confluent Cloud
- Consuming events from Azure Event Hubs
- Using Google Cloud Pub/Sub as a serverless messaging backbone
- Database change capture with DynamoDB Streams
- Working with RDS binary logs and Debezium
- Setting up IoT device telemetry ingestion
- Batch file polling with scheduled triggers (Cron expressions)
- Processing form submissions and webhook payloads
- Using EventBridge rules to route events dynamically
- Schema validation at ingestion time with AWS Glue Schema Registry
- Handling multi-tenant data routing in shared functions
- Rate limiting and throttling upstream producers
Module 4: Processing and Transformation with Serverless Compute - Writing Lambda functions in Python and Node.js
- Optimising function layers for reusability
- Managing dependencies with container images and zip deployments
- Minimising cold start times with provisioned concurrency
- Using async await patterns for non-blocking operations
- Parsing JSON, CSV, Parquet, and Avro formats
- Streaming data transformation with line-by-line processing
- Calling external APIs securely within functions
- Using environment variables and secrets management
- Batching operations to reduce API call overhead
- Error handling and retry logic with exponential backoff
- Structuring code for testability and readability
- Performance benchmarking of function execution time
- Memory allocation optimisation for cost-performance balance
- Using custom runtimes for legacy or niche languages
Module 5: Real-Time Stream Processing at Scale - Introduction to event time vs processing time semantics
- Windowing strategies: tumbling, sliding, session
- Using AWS Lambda with Kinesis for real-time analytics
- Processing streams with Azure Functions and Event Hubs
- Google Cloud Functions with Pub/Sub: guaranteed delivery models
- Aggregating metrics: counts, averages, percentiles
- Implementing deduplication in stream pipelines
- Detecting anomalies in live data feeds
- Stateful processing with DynamoDB as backing store
- Watermarking for late-arriving data
- Checkpointing to resume from failure points
- Scaling stream consumers across partitions
- Monitoring stream lag and processing backlog
- Backfilling historical data into streaming systems
- Testing stream logic with synthetic data generators
Module 6: Serverless Data Storage and Cataloging - Choosing storage backends: S3 vs DynamoDB vs Firestore
- Partitioning strategies for high-throughput writes
- Using S3 as a data lake foundation for analytics
- Versioning and lifecycle policies for cost control
- Enabling Cross-Region Replication for disaster recovery
- Setting up lifecycle transitions to Glacier
- Integrating AWS Glue for metadata extraction
- Creating and managing data catalogues
- Schema evolution handling in Parquet and ORC formats
- Implementing ACID transactions in serverless databases
- Using Athena for SQL queries on S3 data
- Building materialised views for fast reporting
- Partition pruning and predicate pushdown optimisation
- Securing data at rest with KMS and customer-managed keys
- Auditing data access with CloudTrail and DataZone
Module 7: Analytics Orchestration and Workflow Automation - Using AWS Step Functions for state machine design
- Creating parallel branches for independent tasks
- Defining error handling paths and fallback logic
- Implementing human approval gates in automated workflows
- Integrating with Slack and Teams for notifications
- Building retry loops with contextual data persistence
- Using dynamic parallelism for variable workloads
- Passing data between states with result selectors
- Versioning and testing workflows in isolation
- Modelling long-running processes with wait states
- Monitoring workflow execution with CloudWatch metrics
- Cost analysis of orchestration overhead
- Recovering from workflow failures with replay tools
- Integrating with third-party workflow engines
- Exporting workflow definitions as code for CI/CD
Module 8: Security, Compliance, and Governance - Principle of least privilege for function roles
- Securing environment variables with parameter stores
- Using VPCs and private subnets for data isolation
- Encrypting data in transit with TLS 1.3
- Enabling end-to-end encryption for sensitive fields
- Managing secrets with AWS Secrets Manager
- Integrating with AWS IAM and Azure AD
- Setting up audit trails with CloudTrail and Logging
- GDPR and CCPA compliance in data pipelines
- Data residency and sovereignty constraints
- Masking PII in logs and error messages
- Implementing data retention schedules
- Role-based access control in data catalogues
- Penetration testing serverless APIs
- Using AWS Config to enforce compliance rules
Module 9: Performance Optimisation and Debugging - Analysing function duration with CloudWatch Logs Insights
- Reducing memory usage with efficient data structures
- Minimising network hops with edge placement
- Warming up connections with external services
- Reusing database connections across invocations
- Using persistent storage in /tmp for caching
- Profiling CPU and memory bottlenecks
- Setting realistic timeouts to avoid truncation
- Using X-Ray for distributed tracing
- Analysing cold start patterns across regions
- Choosing the right runtime for performance
- Eliminating redundant code in execution paths
- Monitoring invocation concurrency limits
- Tuning Kinesis shard count for throughput
- Using custom metrics for SLI tracking
Module 10: Cost Management and Budgeting - Understanding serverless pricing models by provider
- Estimating monthly costs based on invocation volume
- Using AWS Pricing Calculator for projections
- Setting up billing alarms and cost alerts
- Identifying cost spikes with anomaly detection
- Right-sizing memory and timeout configurations
- Avoiding unnecessary reprocessing with idempotency
- Using reserved concurrency to prevent bill shock
- Monitoring data transfer costs between zones
- Choosing availability zones for cost efficiency
- Archiving cold data to reduce query spend
- Using Spot equivalents for preview workloads
- Analysing cost per transformation step
- Implementing budget enforcement via policies
- Reporting cost efficiency to stakeholders
Module 11: Observability and Monitoring Systems - Setting up CloudWatch Alarms for error rates
- Creating custom dashboards for KPI tracking
- Using structured logging with JSON format
- Correlating logs across distributed services
- Setting up distributed tracing with X-Ray
- Annotating traces with business context
- Monitoring function concurrency and throttling
- Using synthetic transactions for uptime checks
- Alerting on latency percentiles (p95, p99)
- Integrating with third-party tools like Datadog
- Setting up SLOs and error budgets
- Automating incident response with runbooks
- Exporting logs to long-term storage
- Analysing error patterns with log group queries
- Building health check endpoints for external monitoring
Module 12: CI/CD and DevOps for Serverless - Setting up CI pipelines with GitHub Actions
- Using Jenkins for serverless deployment automation
- Managing multiple environments: dev, test, prod
- Versioning functions with alias and stage support
- Implementing blue-green deployments
- Canary testing with gradual traffic shifting
- Using SAM CLI for local testing
- Validating templates with cfn-lint
- Storing deployment artefacts in version-controlled buckets
- Automating security scans in pre-deploy hooks
- Rolling back failed deployments automatically
- Using Terraform for infrastructure provisioning
- Managing configurations across environments
- Integrating with CI/CD secrets managers
- Reporting deployment status to stakeholder channels
Module 13: Data Visualisation and Dashboarding - Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Introduction to event time vs processing time semantics
- Windowing strategies: tumbling, sliding, session
- Using AWS Lambda with Kinesis for real-time analytics
- Processing streams with Azure Functions and Event Hubs
- Google Cloud Functions with Pub/Sub: guaranteed delivery models
- Aggregating metrics: counts, averages, percentiles
- Implementing deduplication in stream pipelines
- Detecting anomalies in live data feeds
- Stateful processing with DynamoDB as backing store
- Watermarking for late-arriving data
- Checkpointing to resume from failure points
- Scaling stream consumers across partitions
- Monitoring stream lag and processing backlog
- Backfilling historical data into streaming systems
- Testing stream logic with synthetic data generators
Module 6: Serverless Data Storage and Cataloging - Choosing storage backends: S3 vs DynamoDB vs Firestore
- Partitioning strategies for high-throughput writes
- Using S3 as a data lake foundation for analytics
- Versioning and lifecycle policies for cost control
- Enabling Cross-Region Replication for disaster recovery
- Setting up lifecycle transitions to Glacier
- Integrating AWS Glue for metadata extraction
- Creating and managing data catalogues
- Schema evolution handling in Parquet and ORC formats
- Implementing ACID transactions in serverless databases
- Using Athena for SQL queries on S3 data
- Building materialised views for fast reporting
- Partition pruning and predicate pushdown optimisation
- Securing data at rest with KMS and customer-managed keys
- Auditing data access with CloudTrail and DataZone
Module 7: Analytics Orchestration and Workflow Automation - Using AWS Step Functions for state machine design
- Creating parallel branches for independent tasks
- Defining error handling paths and fallback logic
- Implementing human approval gates in automated workflows
- Integrating with Slack and Teams for notifications
- Building retry loops with contextual data persistence
- Using dynamic parallelism for variable workloads
- Passing data between states with result selectors
- Versioning and testing workflows in isolation
- Modelling long-running processes with wait states
- Monitoring workflow execution with CloudWatch metrics
- Cost analysis of orchestration overhead
- Recovering from workflow failures with replay tools
- Integrating with third-party workflow engines
- Exporting workflow definitions as code for CI/CD
Module 8: Security, Compliance, and Governance - Principle of least privilege for function roles
- Securing environment variables with parameter stores
- Using VPCs and private subnets for data isolation
- Encrypting data in transit with TLS 1.3
- Enabling end-to-end encryption for sensitive fields
- Managing secrets with AWS Secrets Manager
- Integrating with AWS IAM and Azure AD
- Setting up audit trails with CloudTrail and Logging
- GDPR and CCPA compliance in data pipelines
- Data residency and sovereignty constraints
- Masking PII in logs and error messages
- Implementing data retention schedules
- Role-based access control in data catalogues
- Penetration testing serverless APIs
- Using AWS Config to enforce compliance rules
Module 9: Performance Optimisation and Debugging - Analysing function duration with CloudWatch Logs Insights
- Reducing memory usage with efficient data structures
- Minimising network hops with edge placement
- Warming up connections with external services
- Reusing database connections across invocations
- Using persistent storage in /tmp for caching
- Profiling CPU and memory bottlenecks
- Setting realistic timeouts to avoid truncation
- Using X-Ray for distributed tracing
- Analysing cold start patterns across regions
- Choosing the right runtime for performance
- Eliminating redundant code in execution paths
- Monitoring invocation concurrency limits
- Tuning Kinesis shard count for throughput
- Using custom metrics for SLI tracking
Module 10: Cost Management and Budgeting - Understanding serverless pricing models by provider
- Estimating monthly costs based on invocation volume
- Using AWS Pricing Calculator for projections
- Setting up billing alarms and cost alerts
- Identifying cost spikes with anomaly detection
- Right-sizing memory and timeout configurations
- Avoiding unnecessary reprocessing with idempotency
- Using reserved concurrency to prevent bill shock
- Monitoring data transfer costs between zones
- Choosing availability zones for cost efficiency
- Archiving cold data to reduce query spend
- Using Spot equivalents for preview workloads
- Analysing cost per transformation step
- Implementing budget enforcement via policies
- Reporting cost efficiency to stakeholders
Module 11: Observability and Monitoring Systems - Setting up CloudWatch Alarms for error rates
- Creating custom dashboards for KPI tracking
- Using structured logging with JSON format
- Correlating logs across distributed services
- Setting up distributed tracing with X-Ray
- Annotating traces with business context
- Monitoring function concurrency and throttling
- Using synthetic transactions for uptime checks
- Alerting on latency percentiles (p95, p99)
- Integrating with third-party tools like Datadog
- Setting up SLOs and error budgets
- Automating incident response with runbooks
- Exporting logs to long-term storage
- Analysing error patterns with log group queries
- Building health check endpoints for external monitoring
Module 12: CI/CD and DevOps for Serverless - Setting up CI pipelines with GitHub Actions
- Using Jenkins for serverless deployment automation
- Managing multiple environments: dev, test, prod
- Versioning functions with alias and stage support
- Implementing blue-green deployments
- Canary testing with gradual traffic shifting
- Using SAM CLI for local testing
- Validating templates with cfn-lint
- Storing deployment artefacts in version-controlled buckets
- Automating security scans in pre-deploy hooks
- Rolling back failed deployments automatically
- Using Terraform for infrastructure provisioning
- Managing configurations across environments
- Integrating with CI/CD secrets managers
- Reporting deployment status to stakeholder channels
Module 13: Data Visualisation and Dashboarding - Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Using AWS Step Functions for state machine design
- Creating parallel branches for independent tasks
- Defining error handling paths and fallback logic
- Implementing human approval gates in automated workflows
- Integrating with Slack and Teams for notifications
- Building retry loops with contextual data persistence
- Using dynamic parallelism for variable workloads
- Passing data between states with result selectors
- Versioning and testing workflows in isolation
- Modelling long-running processes with wait states
- Monitoring workflow execution with CloudWatch metrics
- Cost analysis of orchestration overhead
- Recovering from workflow failures with replay tools
- Integrating with third-party workflow engines
- Exporting workflow definitions as code for CI/CD
Module 8: Security, Compliance, and Governance - Principle of least privilege for function roles
- Securing environment variables with parameter stores
- Using VPCs and private subnets for data isolation
- Encrypting data in transit with TLS 1.3
- Enabling end-to-end encryption for sensitive fields
- Managing secrets with AWS Secrets Manager
- Integrating with AWS IAM and Azure AD
- Setting up audit trails with CloudTrail and Logging
- GDPR and CCPA compliance in data pipelines
- Data residency and sovereignty constraints
- Masking PII in logs and error messages
- Implementing data retention schedules
- Role-based access control in data catalogues
- Penetration testing serverless APIs
- Using AWS Config to enforce compliance rules
Module 9: Performance Optimisation and Debugging - Analysing function duration with CloudWatch Logs Insights
- Reducing memory usage with efficient data structures
- Minimising network hops with edge placement
- Warming up connections with external services
- Reusing database connections across invocations
- Using persistent storage in /tmp for caching
- Profiling CPU and memory bottlenecks
- Setting realistic timeouts to avoid truncation
- Using X-Ray for distributed tracing
- Analysing cold start patterns across regions
- Choosing the right runtime for performance
- Eliminating redundant code in execution paths
- Monitoring invocation concurrency limits
- Tuning Kinesis shard count for throughput
- Using custom metrics for SLI tracking
Module 10: Cost Management and Budgeting - Understanding serverless pricing models by provider
- Estimating monthly costs based on invocation volume
- Using AWS Pricing Calculator for projections
- Setting up billing alarms and cost alerts
- Identifying cost spikes with anomaly detection
- Right-sizing memory and timeout configurations
- Avoiding unnecessary reprocessing with idempotency
- Using reserved concurrency to prevent bill shock
- Monitoring data transfer costs between zones
- Choosing availability zones for cost efficiency
- Archiving cold data to reduce query spend
- Using Spot equivalents for preview workloads
- Analysing cost per transformation step
- Implementing budget enforcement via policies
- Reporting cost efficiency to stakeholders
Module 11: Observability and Monitoring Systems - Setting up CloudWatch Alarms for error rates
- Creating custom dashboards for KPI tracking
- Using structured logging with JSON format
- Correlating logs across distributed services
- Setting up distributed tracing with X-Ray
- Annotating traces with business context
- Monitoring function concurrency and throttling
- Using synthetic transactions for uptime checks
- Alerting on latency percentiles (p95, p99)
- Integrating with third-party tools like Datadog
- Setting up SLOs and error budgets
- Automating incident response with runbooks
- Exporting logs to long-term storage
- Analysing error patterns with log group queries
- Building health check endpoints for external monitoring
Module 12: CI/CD and DevOps for Serverless - Setting up CI pipelines with GitHub Actions
- Using Jenkins for serverless deployment automation
- Managing multiple environments: dev, test, prod
- Versioning functions with alias and stage support
- Implementing blue-green deployments
- Canary testing with gradual traffic shifting
- Using SAM CLI for local testing
- Validating templates with cfn-lint
- Storing deployment artefacts in version-controlled buckets
- Automating security scans in pre-deploy hooks
- Rolling back failed deployments automatically
- Using Terraform for infrastructure provisioning
- Managing configurations across environments
- Integrating with CI/CD secrets managers
- Reporting deployment status to stakeholder channels
Module 13: Data Visualisation and Dashboarding - Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Analysing function duration with CloudWatch Logs Insights
- Reducing memory usage with efficient data structures
- Minimising network hops with edge placement
- Warming up connections with external services
- Reusing database connections across invocations
- Using persistent storage in /tmp for caching
- Profiling CPU and memory bottlenecks
- Setting realistic timeouts to avoid truncation
- Using X-Ray for distributed tracing
- Analysing cold start patterns across regions
- Choosing the right runtime for performance
- Eliminating redundant code in execution paths
- Monitoring invocation concurrency limits
- Tuning Kinesis shard count for throughput
- Using custom metrics for SLI tracking
Module 10: Cost Management and Budgeting - Understanding serverless pricing models by provider
- Estimating monthly costs based on invocation volume
- Using AWS Pricing Calculator for projections
- Setting up billing alarms and cost alerts
- Identifying cost spikes with anomaly detection
- Right-sizing memory and timeout configurations
- Avoiding unnecessary reprocessing with idempotency
- Using reserved concurrency to prevent bill shock
- Monitoring data transfer costs between zones
- Choosing availability zones for cost efficiency
- Archiving cold data to reduce query spend
- Using Spot equivalents for preview workloads
- Analysing cost per transformation step
- Implementing budget enforcement via policies
- Reporting cost efficiency to stakeholders
Module 11: Observability and Monitoring Systems - Setting up CloudWatch Alarms for error rates
- Creating custom dashboards for KPI tracking
- Using structured logging with JSON format
- Correlating logs across distributed services
- Setting up distributed tracing with X-Ray
- Annotating traces with business context
- Monitoring function concurrency and throttling
- Using synthetic transactions for uptime checks
- Alerting on latency percentiles (p95, p99)
- Integrating with third-party tools like Datadog
- Setting up SLOs and error budgets
- Automating incident response with runbooks
- Exporting logs to long-term storage
- Analysing error patterns with log group queries
- Building health check endpoints for external monitoring
Module 12: CI/CD and DevOps for Serverless - Setting up CI pipelines with GitHub Actions
- Using Jenkins for serverless deployment automation
- Managing multiple environments: dev, test, prod
- Versioning functions with alias and stage support
- Implementing blue-green deployments
- Canary testing with gradual traffic shifting
- Using SAM CLI for local testing
- Validating templates with cfn-lint
- Storing deployment artefacts in version-controlled buckets
- Automating security scans in pre-deploy hooks
- Rolling back failed deployments automatically
- Using Terraform for infrastructure provisioning
- Managing configurations across environments
- Integrating with CI/CD secrets managers
- Reporting deployment status to stakeholder channels
Module 13: Data Visualisation and Dashboarding - Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Setting up CloudWatch Alarms for error rates
- Creating custom dashboards for KPI tracking
- Using structured logging with JSON format
- Correlating logs across distributed services
- Setting up distributed tracing with X-Ray
- Annotating traces with business context
- Monitoring function concurrency and throttling
- Using synthetic transactions for uptime checks
- Alerting on latency percentiles (p95, p99)
- Integrating with third-party tools like Datadog
- Setting up SLOs and error budgets
- Automating incident response with runbooks
- Exporting logs to long-term storage
- Analysing error patterns with log group queries
- Building health check endpoints for external monitoring
Module 12: CI/CD and DevOps for Serverless - Setting up CI pipelines with GitHub Actions
- Using Jenkins for serverless deployment automation
- Managing multiple environments: dev, test, prod
- Versioning functions with alias and stage support
- Implementing blue-green deployments
- Canary testing with gradual traffic shifting
- Using SAM CLI for local testing
- Validating templates with cfn-lint
- Storing deployment artefacts in version-controlled buckets
- Automating security scans in pre-deploy hooks
- Rolling back failed deployments automatically
- Using Terraform for infrastructure provisioning
- Managing configurations across environments
- Integrating with CI/CD secrets managers
- Reporting deployment status to stakeholder channels
Module 13: Data Visualisation and Dashboarding - Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Connecting serverless backends to dashboard tools
- Serving data to Tableau via API endpoints
- Streaming metrics into Power BI in real time
- Using QuickSight for serverless-native visualisations
- Generating PDF reports on demand
- Automating daily summary emails with analytics
- Embedding dashboards in internal portals
- Using Grafana with cloud-native data sources
- Building dynamic query interfaces with React
- Creating role-based dashboards for teams
- Setting up drill-down analytics for root cause
- Scheduling recurring reports with Lambda
- Exporting visuals to presentation formats
- Securing access to dashboards with SSO
- Monitoring dashboard usage and engagement
Module 14: Industry-Specific Use Case Implementations - Retail: real-time inventory tracking and pricing alerts
- Healthcare: patient monitoring with anomaly detection
- Finance: fraud detection in payment streams
- E-commerce: personalised recommendations at checkout
- Manufacturing: predictive maintenance from sensor data
- Energy: smart grid load balancing analytics
- Logistics: vehicle tracking and ETA prediction
- Media: content engagement analytics for streaming
- Telecom: network performance optimisation by region
- Government: public service usage trend analysis
- Education: learning pattern detection in LMS data
- Insurance: claims processing acceleration
- Travel: dynamic pricing model triggers
- HR Tech: employee sentiment analysis from feedback
- Non-profit: donation pattern forecasting
Module 15: Building a Production-Ready End-to-End Pipeline - Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan
Module 16: Certification Preparation and Career Advancement - Reviewing core serverless concepts for mastery
- Practising scenario-based problem solving
- Preparing implementation case studies
- Documenting your hands-on project
- Submitting for feedback from instructors
- Revising based on expert review
- Finalising your certificate-eligible submission
- Understanding how certificates are verified
- Linking your credential to LinkedIn
- Using your project as a portfolio piece
- Crafting technical storytelling for interviews
- Positioning serverless expertise in job descriptions
- Reaching out to cloud recruiters with confidence
- Setting 6-month skill progression goals
- Planning your next certification or specialisation
- Defining business objectives for your use case
- Mapping data sources and target outputs
- Designing the complete architecture diagram
- Selecting components for scalability and cost
- Implementing data ingestion from mock sources
- Building transformation logic with clean code
- Setting up storage with lifecycle policies
- Orchestrating steps with state machines
- Adding error handling and retry strategies
- Securing all components with IAM policies
- Enabling logging, monitoring, and tracing
- Testing edge cases and failure modes
- Optimising for performance and cost
- Documenting decisions in architecture records
- Presenting a board-ready implementation plan