Cloud Computing (AWS/Azure)
An advanced, hands-on cloud engineering course. You learn to design, secure, deploy, observe, recover and cost-optimize a workload on AWS using Terraform, containers and a release pipeline, then transfer parts of it to Azure and complete a bounded GCP exercise. You finish with a documented capstone and client handover. All business data is simulated. Labs need an authorised learning cloud account and can cost money.
- Duration: 20 weeks
- Modules: 12
- Fee: Rs 19,999 (about Rs 3,333 a month on EMI)
- Field: Dev & Technology
Roles this track prepares you for
- Cloud Support Engineer
- Cloud Engineer
- Junior Solutions Architect
- DevOps Engineer
- Junior DevOps Engineer
- AWS Cloud Engineer
- Site Reliability Engineer
- Infrastructure Engineer
- Cloud Operations Engineer
- Technical Support Engineer
Curriculum
- Architecture Thinking, Readiness and Lab Setup - Check your readiness, turn a business brief into measurable requirements, write architecture decisions and prepare a safe, cost-aware learning account.
- Take the readiness diagnostic and choose your path
- Bridge: Linux, networking and Git gaps
- Shared responsibility, regions and zones
- Turn a business brief into measurable requirements
- Write an architecture decision record
- Prepare the lab account, budget alerts and preflight check
- AWS Identity, Accounts and Access - Protect the root identity, use temporary roles, write and read policies, apply explicit denies and verify both allowed and denied actions.
- Protect the root identity and organize accounts
- Roles and temporary credentials
- Read and write a policy
- Identity policies versus resource policies
- Explicit deny and permission boundaries
- Audit trail and effective-permission reasoning
- Linux, CLI and VPC Network Diagnosis - Diagnose host and network failures with commands and logs, build a segmented VPC and trace a request hop by hop through DNS, routing, firewalls and ports.
- Processes, services and reading logs
- Test DNS, HTTP, TLS and sockets from the command line
- CIDR plans, subnets and route tables
- Internet gateways, NAT paths and endpoint costs
- Security groups, network ACLs and four test packets
- Packet path, DNS answers and the diagnosis note
- EC2, EBS and S3 - Launch and operate EC2 with launch templates and workload roles, manage EBS snapshots and recovery, and build private S3 workflows with lifecycle and signed access.
- Instance types, images and launch templates
- Bootstrap a service and attach a workload role
- EBS lifecycle, snapshots and volume recovery
- S3 keys, versioning and delete markers
- Private S3 access, encryption and lifecycle rules
- Signed access and content delivery with caching
- Load Balancing, Scaling and Managed Data - Reason about listeners, targets, health checks and scaling signals, connect the application to PostgreSQL on RDS securely, and choose between relational and key-value storage.
- Load balancer listeners, targets and TLS
- Health checks, readiness and connection draining
- Autoscaling signals, limits and startup timing
- RDS PostgreSQL, secrets and connection pressure
- Backups, replicas, failover and restore compatibility
- DynamoDB access patterns and workload fit
- Lambda and Event-Driven Reliability - Build event-driven processing with Lambda, queues and event routing, handle retries, duplicates and dead-letter events, and prove business effects are not duplicated.
- Lambda execution model, packaging and permissions
- API and queue triggers
- Queues and event routing concepts
- Retries, timeouts and concurrency
- Idempotency and duplicate events
- Dead-letter queues and safe replay
- Terraform and Infrastructure Lifecycle - Write Terraform for the lab, protect and move state, read plans critically, manage drift and replacement risk, and recover from a failed change.
- Providers, resources, variables and outputs
- Dependencies, plan, apply and destroy
- Remote state, locking and recovery
- Modules and environments
- Drift, imports and replacements
- Terraform and CloudFormation side by side
- Containers, CI/CD and Release Engineering - Build and run a containerized service on ECS, release it through a pipeline with checks, blocked bad releases and rollback, using short-lived credentials.
- Dockerfiles, builds and image provenance
- Registries, tags and digests
- ECS services, task identity and networking
- A pipeline with automated checks
- Short-lived pipeline credentials and environment gates
- Deployment verification and rollback
- Observability, Security and Governance - Design logs, metrics, dashboards and alerts, define SLIs and SLOs, diagnose incidents, then investigate a misconfigured sandbox and fix exposures without breaking legitimate access.
- Structured logs, metrics and correlation IDs
- Actionable alerts, SLIs, SLOs and error budgets
- Diagnose an incident from telemetry
- Threat modeling and permission escalation awareness
- Encryption, KMS keys and secrets handling
- Remediation and negative testing
- Reliability, Backup, Disaster Recovery and FinOps - Plan failure domains and recovery objectives, restore into a clean target and measure recovery, then reconcile a bill and recommend quantified cost changes.
- Failure domains, timeouts, backoff and jitter
- RTO, RPO and disaster recovery patterns
- Restore into a clean target and reconcile data
- Read a bill: billing dimensions, tags and budgets
- Unit cost per fulfilled order and bill reconciliation
- Rightsizing, schedules, lifecycle rules and commitments
- Azure Transfer and GCP Essentials - Map AWS capabilities to Azure identity, networking, compute and operations, deploy a compatible workload slice with managed identity, and run a bounded GCP container exercise with verified cleanup.
- Azure tenants, subscriptions, resource groups and RBAC
- Azure VNets, NSGs and compute choices
- Managed identity, secrets and application configuration
- Azure Monitor, diagnosis and recovery
- GCP projects, service accounts and billing context
- Run a container on Cloud Run with verified cleanup
- Migration, Incident Command and Capstone - Plan a migration and cutover, lead a simulated incident, then deliver and defend an integrated, reproducible workload with tests, recovery evidence, a cost model, verified cleanup and a client handover.
- Discovery, dependency mapping and migration strategy
- Cutover, rollback and stakeholder updates
- Incident command and a blameless review
- Capstone build: infrastructure, release, access tests
- Capstone operation: telemetry, recovery and cost model
- Handover package and design defense
Frequently asked questions
How long is the Cloud Computing (AWS/Azure) course?
It runs for 20 weeks, with 12 modules. It is self-paced online learning from EasySkill Career Academy, Surat.
How much does the Cloud Computing (AWS/Azure) course cost?
The fee is Rs 19,999, or about Rs 3,333 a month on EMI.
What will I build in Cloud Computing (AWS/Azure)?
Every module ends in a graded practical task that AI checks in about 30 seconds, so you finish with a portfolio you can show to employers or clients.
Which roles does Cloud Computing (AWS/Azure) prepare me for?
It prepares you to apply for roles such as Cloud Support Engineer, Cloud Engineer, Junior Solutions Architect, DevOps Engineer, Junior DevOps Engineer. It does not guarantee a job or income.
Can I learn online, or do I have to visit a centre?
You can learn fully online. EasySkill also has centres in Adajan, Vesu and Bhestan, Surat, if you prefer to visit.
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