Software Development and Programming

Serverless Computing with AWS Lambda and Azure Functions

Name: Vision Reach Global Consultancy
Address: Nairobi, KE
Telephone: +254 757 398 919

Serverless platforms let teams ship code without provisioning servers and pay only for actual execution, but they demand different design habits from traditional applications. Over ten days you compare execution models on AWS Lambda and Azure Functions, including cold starts, concurrency, scaling limits and pricing models. You then wire functions to triggers, bindings and event sources such as HTTP endpoints, queues, storage events and schedules. Packaging, dependency management and deployment automation follow, using infrastructure as code and CI/CD pipelines.

Stateless design patterns and data persistence options, including DynamoDB and Cosmos DB, show how to manage state safely outside the function. Orchestration sessions use Step Functions and Durable Functions to compose multi-step workflows with retries and error handling. Security, identity and governance complete the core material, covering IAM roles, managed identities, secrets and least-privilege access. Cloud developers, back-end engineers, DevOps practitioners and solution architects designing event-driven systems will find the labs directly relevant. By the end you can build, deploy and secure a serverless application on either cloud and judge when the model suits a workload.

10 DaysIntermediateClassroomCPD-Accredited

About this course

Organizations and professionals increasingly rely on software dev and programming courses knowledge to stay competitive and deliver results. This course provides hands-on training in the methods, tools, and frameworks that matter most in today's environment.

Participants complete the course ready to apply these skills immediately in their own roles and organizations.

Throughout the programme, participants work through realistic scenarios drawn from development initiatives, donor-funded programmes, nonprofit operations, and public sector environments, examining how serverless computing with AWS lambda and azure functions is applied in practice and where it most often breaks down. Delegates will develop practical skill in designing appropriate frameworks, selecting and applying the right tools for security, identity and governance, interpreting findings, and communicating conclusions clearly to colleagues, management and external stakeholders. Sessions move deliberately from principles to application, so that each technique introduced is practised against a realistic problem before the programme moves on — strengthening both individual effectiveness and the wider capability of the organizations delegates return to.

Training Objectives

By the end of this course, participants will be able to:

Develop robust serverless computing with AWS lambda and azure functions frameworks that support successful implementation and measurable outcomes.
Analyze performance using recognized evaluation methods drawn from security, identity and governance.
Design practical systems that strengthen accountability, transparency and evidence generation.
Evaluate outcomes and assess longer-term impact across a range of operating contexts.
Apply relevant tools, frameworks and analytical methodologies confidently and appropriately.
Integrate triggers, bindings and event sources into existing organizational processes and reporting structures.
Strengthen decision-making and operational effectiveness through evidence-based professional practice.

What you'll learn

Execute key processes and workflows in serverless computing

Apply best-practice frameworks and methodologies

Solve real-world problems using course tools and techniques

Lead projects and initiatives with confidence

Measure and communicate impact and results

Build sustainable capability within your team

Stay current with evolving standards and practices

Key Takeaways

By the end of the Serverless Computing with AWS Lambda and Azure Functions, participants will leave with:

A comprehensive working understanding of serverless computing with AWS lambda and azure functions principles and performance-measurement methodology.
Enhanced ability to design practical systems and evaluate outcomes reliably.
Improved competency in security, identity and governance, reporting structures and analytical interpretation.
Practical techniques for translating findings into strategic insight and clear recommendations.
Greater confidence in applying serverless computing with AWS lambda and azure functions and assessing measurable results.
Stronger capability to support organizational learning and continuous performance improvement.
Improved approaches to strengthening sustainability, accountability and operational effectiveness.

Training Methodology

This training course adopts a practical, participant-centered learning approach that builds serverless computing with AWS lambda and azure functions expertise, strengthens analytical capability and develops confident professional judgement. The methodology combines specialist facilitation, applied hands-on experience and globally recognized professional practice, so that delegates return able to apply what they have learned immediately rather than in theory only.

Methodology includes:

Expert-led sessions facilitated by experienced serverless computing with AWS lambda and azure functions practitioners and subject-matter specialists.
Practical application of the frameworks, tools and techniques used in security, identity and governance.
Real-world case studies drawn from development initiatives, donor-funded programmes, nonprofit operations, and public sector environments.
Tool-based demonstrations of the systems, templates and reporting applications used in current practice.
Interactive discussion and scenario-based learning focused on realistic challenges and decision points.
Structured group exercises with facilitator feedback, reinforcing learning through practice rather than lecture alone.

Day 1: Serverless Execution Models and Cloud Function Fundamentals

Function-as-a-Service compared with virtual machines, containers and PaaS
AWS Lambda execution environment: handlers, runtimes, memory-to-CPU coupling
Azure Functions hosting plans: Consumption, Premium and Dedicated
Cold starts, warm invocations and concurrency limits explained
Setting up local tooling: AWS SAM CLI, Azure Functions Core Tools, VS Code extensions
Writing, running and debugging a first function on each platform
Common challenges, risks and failure points in serverless execution models and cloud function fundamentals

Day 2: Triggers, Bindings and Event Sources

API Gateway, Lambda function URLs and HTTP-triggered Azure Functions
Queue, topic and stream triggers: SQS, SNS, Kinesis, Azure Service Bus, Event Hubs
Storage and database events: S3 notifications, DynamoDB Streams, Blob and Cosmos DB triggers
Timer and schedule-based invocations with EventBridge Scheduler and CRON expressions
Azure Functions input and output bindings versus explicit SDK calls in Lambda
Event payload shapes, batching and partial batch failure handling
Worked example: applying triggers, bindings and event sources in a live serverless computing with AWS lambda and azure functions context

Day 3: Packaging, Dependencies and Deployment Automation

Deployment packages, Lambda layers and container image functions
Dependency management for Python, Node.js and .NET function apps
Infrastructure as code with AWS SAM, CloudFormation and Azure Bicep/ARM
Environment variables, application settings and configuration per stage
Versions, aliases, deployment slots and traffic shifting
Building CI/CD pipelines with GitHub Actions and Azure DevOps
Decision points and escalation routes in packaging, dependencies and deployment automation

Day 4: Data Persistence and Stateless Design Patterns

Choosing between DynamoDB, Aurora Serverless, Cosmos DB and Azure SQL Serverless
Connection management and pooling with RDS Proxy and serverless SQL
Idempotency keys and exactly-once semantics in retried invocations
Caching strategies with ElastiCache, Momento-style patterns and in-memory reuse
Handling large payloads through object storage and pre-signed URLs
Designing stateless handlers with externalised session and state
Technology and automation supporting data persistence and stateless design patterns

Day 5: Orchestration and Workflow Composition

AWS Step Functions: standard versus express workflows and Amazon States Language
Azure Durable Functions: orchestrators, activities and entity functions
Durable patterns: function chaining, fan-out/fan-in, human interaction, monitor
Saga and compensating transaction patterns for distributed operations
Error handling, retry policies, timeouts and catch blocks in workflows
Choreography with EventBridge and Azure Event Grid event buses
Planning and sequencing orchestration and workflow composition within the wider workflow

Day 6: Security, Identity and Governance

Least-privilege IAM execution roles and resource-based policies for Lambda
Managed identities, Azure RBAC and Key Vault references in Functions
Secrets handling with AWS Secrets Manager and Parameter Store
Authenticating APIs with Cognito, Azure AD, JWT validation and API keys
Network isolation: VPC-attached functions, private endpoints, egress control
Guardrails with service control policies, Azure Policy and function-level auth levels
Resourcing, cost and capacity considerations

Day 7: Observability, Testing and Reliability Engineering

Structured logging to CloudWatch Logs and Application Insights
Distributed tracing with AWS X-Ray and Application Insights end-to-end transactions
Custom metrics, alarms and dashboards for invocation errors and throttles
Unit, integration and contract testing of handlers with mocked events
Dead-letter queues, retry policies and poison-message recovery
Chaos and load testing serverless endpoints to expose concurrency ceilings
Reviewing outcomes and capturing lessons learned

Day 8: Performance Tuning and Cost Optimisation

Right-sizing memory and measuring with AWS Lambda Power Tuning
Reducing cold starts: provisioned concurrency, Premium plan pre-warmed instances, SnapStart
ARM/Graviton runtimes and language runtime performance trade-offs
Reserved concurrency, scaling limits and protecting downstream systems
Cost modelling per invocation, GB-second and data transfer charges
Deciding when functions are cheaper than containers or always-on services
Standards, frameworks and good practice governing performance tuning and cost optimisation

Day 9: Multi-Cloud Architecture and Migration Practice

Mapping AWS Lambda constructs to Azure Functions equivalents and back
Refactoring a monolithic API into functions with the strangler pattern
Portability options: containerised functions, OpenTelemetry, framework abstractions
Cross-cloud event integration and hybrid connectivity considerations
Vendor lock-in assessment and exit-cost analysis for stakeholders
Workshop: migrating a sample Lambda workload to Azure Functions
Regulatory, ethical and compliance dimensions of multi-cloud architecture and migration practice

D10

Day 10: Capstone Build, Operating Model and Standards Watch

Capstone: design and deploy an event-driven application across both platforms
Documenting architecture decisions and presenting trade-offs to reviewers
Defining team standards for repository structure, naming and tagging
Reporting reliability and cost outcomes to technical and business audiences
Building internal capability: templates, reusable layers and onboarding guides
Tracking platform releases, runtime deprecations and serverless community practice
Practical exercise and facilitated review

Upcoming cohorts

CPD-Accredited

Official invoice & confirmation letter provided

Team discount for 3+ seats

Request Custom Quote →Training Calendar →

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Our training team can help with group pricing, invoicing, or picking the right schedule.

Chat on WhatsApp training@visionreachglobal.org +254 757 398 919

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FAQ

Frequently Asked Questions About Serverless Computing with AWS Lambda and Azure Functions

Everything you need to know about this course before you register.

By the end of the Serverless Computing with AWS Lambda and Azure Functions programme, you'll be able to execute key processes and workflows in serverless computing, apply best-practice frameworks and methodologies, solve real-world problems using course tools and techniques, and lead projects and initiatives with confidence. The full breakdown of topics is covered session by session in the Course Outline tab above.

" Serverless Computing with AWS Lambda and Azure Functions suits engineers and architects who already build and deploy applications and now need to run event-driven workloads without managing servers across AWS and Azure. Typical delegates include Cloud Application Developers moving monolithic or container workloads to functions, Backend and API Developers building HTTP-triggered and queue-triggered services, Cloud Solutions Architects designing multi-cloud event-driven architectures, DevOps and Platform Engineers automating function deployment pipelines, Site Reliability Engineers responsible for observability, cold starts, and cost of serverless estates, Integration Developers connecting SaaS systems through messaging and orchestration services, and Technical Leads evaluating AWS Lambda against Azure Functions for new projects.

Serverless Computing with AWS Lambda and Azure Functions typically runs as 10 Days. It's available as in-person classroom training — every course can also be delivered on-site for your team on dates that suit you.

Serverless Computing with AWS Lambda and Azure Functions is scheduled in-classroom in Mombasa, Kenya, Naivasha, Kenya, Nairobi, Kenya, and Kisumu, Kenya, and 14 other locations, plus a live interactive virtual classroom you can join from anywhere. Check the schedule panel above for exact upcoming dates and fees in each location.

The next live virtual cohort of Serverless Computing with AWS Lambda and Azure Functions starts November 2, 2026, with new classroom cohorts also running on a rolling basis. Pick a date and location in the schedule panel above, then click "Register for the Course" — it takes a few minutes and your seat is confirmed once payment or a signed purchase order is received.

Yes — delegates who meet the attendance requirement receive a Certificate of Completion for Serverless Computing with AWS Lambda and Azure Functions from Vision Reach Global Consultancy, issued in the name you register with, so double-check the spelling at checkout.

Serverless Computing with AWS Lambda and Azure Functions is pitched at intermediate professionals. If you're unsure whether it's the right fit for your current role or background, message our training advisors before you register and they'll help you confirm.

Fees for Serverless Computing with AWS Lambda and Azure Functions vary by delivery location and format and are shown in real time in the schedule panel above once you pick a date. Register 3 or more delegates on the same course together and a 5% team discount is applied automatically — larger cohorts can request a custom corporate quote.

Yes — Serverless Computing with AWS Lambda and Azure Functions can be delivered on-site at your offices (or virtually for distributed teams), with case studies and examples tailored to your industry and the specific challenges your team is working through. Switch to the "In-House" tab in the schedule panel above to request a proposal.

Still have questions about Serverless Computing with AWS Lambda and Azure Functions? Chat with an advisor·Visit the full FAQ

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Next intake Nov 2, 2026