🎓 Program Overview
DevOps in 2026 is no longer a single role — it has fractured into specialisations: platform engineering, SRE, cloud security, MLOps, and FinOps. But every one of those paths starts from the same foundation: Linux, networking, containers, CI/CD, and Infrastructure as Code on a major cloud platform. This course builds that foundation on AWS — the most widely used cloud platform in the world, holding over 31% of global cloud market share, and the platform that appears in the majority of remote DevOps job postings targeting Pakistan's IT export market.
The core program covers everything a working DevOps engineer needs to be productive on day one. Six specialist advanced tracks — each 2–3 additional weeks — let you go deep on Kubernetes, security, serverless, platform engineering, ML infrastructure, or SRE without paying for content irrelevant to your goals.
📐 Program Structure — Core + Choose Your Specialisation
Core Program
4–5 weeks · Linux, Docker, AWS, Terraform, GitHub Actions, ECS, Observability, Security, FinOps · Aligned with AWS SAA + SysOps Associate
Track 1
Kubernetes & EKS — 3 weeks · Helm, ArgoCD, Karpenter, GitOps, Argo Rollouts · Aligned with CKA
Track 2
Security & Compliance Engineering — 2 weeks · DevSecOps pipeline, OPA, SBOM, Cosign · Aligned with AWS Security Specialty
Track 3
Serverless & Event-Driven Architecture — 2 weeks · Lambda, Step Functions, EventBridge, DynamoDB · Aligned with AWS Developer Associate
Track 4
Platform Engineering & Advanced IaC — 2 weeks · CDK, Pulumi, Backstage, multi-account · Aligned with AWS DevOps Engineer Pro + HashiCorp Terraform Associate
Track 5
ML Infrastructure & DataOps — 2 weeks · SageMaker, Glue, Athena, MWAA, MLflow · Aligned with AWS ML Specialty
Track 6
SRE & Advanced Observability — 2 weeks · Prometheus, Grafana, Loki, Tempo, chaos engineering · Aligned with AWS SysOps Pro
💡 Why AWS DevOps in 2026
AWS holds over 31% of the global cloud market — more than Azure and Google Cloud combined — making it the single most valuable cloud platform to know for employment
GitHub Actions has replaced Jenkins as the default CI/CD platform — simpler, cheaper, and better integrated with modern development workflows
Terraform remains the most employer-demanded IaC tool globally — appearing in the vast majority of senior DevOps and platform engineering job postings
Containers and Kubernetes are now baseline skills for any cloud infrastructure role — not advanced specialisations
The shift-left security movement means DevOps engineers now own security scanning, secrets management, and compliance in the pipeline
FinOps has become mandatory as organisations try to control rapidly growing cloud bills — engineers who can reduce costs are extremely valuable
Remote DevOps roles from Pakistan pay significantly above local market rates — AWS certification + hands-on project experience is the fastest path to these positions
📚 Core Program — 4 to 5 Weeks
The foundation every DevOps engineer needs before specialising. Five weeks covering every layer of a production AWS deployment — from the operating system up to cost control.
W1
Week 1
Linux, Networking & Shell Automation
12 topics · The foundation everything else sits on
−
DevOps starts with Linux. Every container, every EC2 instance, every CI/CD runner is a Linux environment. This week builds the OS and networking knowledge that everything else depends on.
- Linux fundamentals: process management, systemd services, file permissions, user management, and the /proc and /sys filesystems
- Shell scripting in Bash: variables, conditionals, loops, functions, error handling with
set -euo pipefail, and production-grade automation scripts - Text processing tools: grep, awk, sed, cut, sort, jq for JSON, and yq for YAML — the DevOps data transformation toolkit
- File system and storage: inodes, hard links, soft links, mount points, LVM, and disk usage analysis
- Networking fundamentals: TCP/IP, subnets (CIDR notation), routing tables, DNS resolution, NAT, and how packets move through a cloud VPC
- Linux networking tools: ip, ss, netstat, curl, dig, nslookup, tcpdump, and nc for debugging connectivity
- TLS/SSL: how certificates work, the certificate chain, Let's Encrypt, and inspecting certificates with openssl
- SSH: key generation, SSH config files, agent forwarding, tunnelling, and hardening SSH server configuration
- Cron and systemd timers: scheduling recurring tasks reliably on Linux
- Vim and nano: editor proficiency to edit files on remote servers without a GUI
- Git advanced workflows: rebasing, cherry-picking, reflog, bisect, signed commits, and monorepo patterns
- Python for DevOps automation: scripts with boto3, subprocess, pathlib, and argparse — replacing Bash for complex automation
W2
Week 2
Docker & Containers in Depth
12 topics · From internals to production builds
+
Containers are the unit of deployment in modern cloud infrastructure. This week covers Docker from first principles to production-quality builds — not just how to use Docker but why it works.
- Container fundamentals: namespaces, cgroups, and the Linux kernel features that make containers possible
- Docker architecture: the Docker daemon, containerd, runc, image layers, and the union filesystem (OverlayFS)
- Writing production Dockerfiles: multi-stage builds, minimal base images (distroless, alpine, scratch), non-root users, and build cache optimisation
- Docker image security: scanning with Trivy and Docker Scout, removing secrets from build context, and .dockerignore
- Docker networking: bridge, host, overlay, and macvlan drivers — inter-container communication and exposing ports
- Docker volumes: bind mounts vs named volumes, tmpfs, and managing persistent data
- Docker Compose: multi-container stacks — depends_on, health checks, environment files, and profiles
- Container registries: AWS ECR — pushing, pulling, tagging strategies, lifecycle policies, and cross-account access
- Container resource limits: CPU and memory limits — preventing noisy neighbour problems
- Docker in CI/CD: building and pushing images in GitHub Actions — layer caching and multi-platform builds (ARM + AMD64) with buildx
- Debugging containers: docker exec, docker logs, docker inspect, and attaching to running containers
- Docker security: AppArmor/seccomp profiles, read-only root filesystems, and capability dropping
W3
Week 3
AWS Core Services & Infrastructure as Code with Terraform
21 topics · AWS from a DevOps perspective
+
AWS from the perspective of a DevOps engineer — not using console buttons, but provisioning everything as code with proper networking, security, and automation.
AWS Fundamentals for DevOps
- AWS account structure: root account, IAM users, roles, policies, and the principle of least privilege
- VPC architecture: subnets (public/private), route tables, internet gateways, NAT gateways, VPC endpoints, security groups vs NACLs
- EC2: instance types, AMIs, launch templates, user data scripts, instance profiles, EBS volumes, and Auto Scaling Groups
- Load balancers: ALB (Layer 7) vs NLB (Layer 4) — target groups, health checks, listener rules, and SSL termination
- S3: bucket policies, versioning, lifecycle rules, cross-region replication, and S3 as a Terraform state backend
- RDS: managed PostgreSQL and MySQL — parameter groups, snapshots, read replicas, and Multi-AZ
- ElastiCache: Redis clusters — node types, replication groups, and failover
- IAM in depth: role assumption, cross-account roles, OIDC identity providers for GitHub Actions, and IAM Access Analyzer
- Route 53: hosted zones, record types, health checks, routing policies (weighted, latency, failover), and DNS validation for ACM
- ACM (Certificate Manager): provisioning and renewing TLS certificates for ALB and CloudFront
- AWS CLI and aws-vault: authenticating securely, profile management, and scripting AWS operations
Terraform for AWS
- Terraform core concepts: providers, resources, data sources, locals, variables, and outputs
- HCL in depth: expressions, functions, for_each, count, dynamic blocks, and the depends_on meta-argument
- Terraform state: local vs remote state, S3 + DynamoDB locking, state isolation per environment
- Terraform modules: writing reusable VPC, ECS, and RDS modules — module versioning and the Terraform Registry
- Workspaces and environment promotion: dev → staging → production with separate state files
- Provisioning a complete AWS environment: VPC, subnets, security groups, EC2 Auto Scaling, ALB, RDS, and S3
- Terraform Cloud and Atlantis: team-based IaC workflows with plan-on-PR and apply-on-merge
- Drift detection: identifying infrastructure that has diverged from Terraform state
- Checkov: static analysis of Terraform code for security misconfigurations before applying
- Terragrunt: DRY Terraform configurations across multiple environments
W4
Week 4
CI/CD with GitHub Actions & ECS Fargate Deployments
17 topics · Code push to production, automated
+
The complete pipeline: code push to production deployment, automated, secure, and repeatable. GitHub Actions as the CI/CD platform, ECS Fargate as the production container hosting target.
GitHub Actions in Depth
- GitHub Actions architecture: workflows, jobs, steps, runners (GitHub-hosted and self-hosted), and the event model
- Workflow triggers: push, pull_request, schedule, workflow_dispatch, and repository_dispatch
- Jobs and dependencies: needs, matrix builds, and parallel job execution
- Secrets and OIDC-based AWS authentication: authenticating to AWS without stored access keys
- Composite actions and reusable workflows: building a shared action library for your organisation
- Caching in GitHub Actions: actions/cache for npm, pip, Docker layers, and Terraform providers
- Environments and protection rules: manual approval gates before deploying to production
- GitHub Actions security: pinning action versions to commit SHAs, least-privilege OIDC roles, and secret scanning
- Self-hosted runners on EC2: cost-efficient runners for large teams with private network access requirements
ECS Fargate Deployments
- ECS architecture: clusters, task definitions, services, tasks, and the Fargate launch type
- Task definitions: container definitions, resource limits, Secrets Manager environment injection, and awslogs log configuration
- ECS services: desired count, deployment configuration (rolling update vs blue/green), and service auto-scaling
- Blue/green deployments with CodeDeploy: zero-downtime — shifting traffic between task set versions
- ECS service discovery: AWS Cloud Map for service-to-service communication within a VPC
- ECS Exec: accessing running containers for debugging without SSH
- Complete CI/CD pipeline: GitHub Actions → Trivy scan → Docker build → ECR push → Terraform plan → ECS task definition update → smoke test → notify
- Lambda deployments: packaging, deploying with Terraform, and versioning with aliases
W5
Week 5
Observability, Security & FinOps
25 topics · The three concerns of every working DevOps engineer
+
The three concerns that occupy most of a working DevOps engineer's week: understanding what your systems are doing, keeping them secure, and keeping the bill under control.
Observability
- The three pillars: metrics, logs, and traces — why you need all three to debug production incidents
- CloudWatch Logs: log groups, log streams, structured JSON logging, metric filters, and Log Insights queries
- CloudWatch Metrics: built-in AWS metrics, custom metrics with PutMetricData, and metric math
- CloudWatch Alarms: threshold alarms, composite alarms, and routing to SNS → Slack / PagerDuty
- CloudWatch Dashboards: operational dashboards for ECS services, RDS, and Lambda
- AWS X-Ray: distributed tracing for Lambda and ECS — trace maps and segment analysis
- OpenTelemetry with ADOT: the AWS Distro for OpenTelemetry Collector — receiving OTel spans and forwarding to CloudWatch and X-Ray
- Container Insights: ECS cluster-level metrics — CPU, memory, network, and storage per task
- Structured logging best practices: correlation IDs, request tracing fields, and log level discipline
AWS Security Fundamentals
- AWS Secrets Manager: storing and rotating database credentials, API keys, and certificates
- AWS Systems Manager Parameter Store: lightweight secrets and configuration — SecureString parameters
- IAM best practices: MFA enforcement, service control policies, permission boundaries, and Access Analyzer
- Security groups and NACLs: layered network security — stateful vs stateless filtering
- AWS GuardDuty: threat detection — understanding findings and automating remediation
- AWS Config: tracking resource configuration changes and compliance rules
- S3 security: blocking public access, bucket policies, server-side encryption, and VPC endpoint access
- Shift-left security in CI/CD: Trivy for containers, Checkov for Terraform, and git-secrets for credential leak prevention
FinOps & Cost Control
- AWS cost visibility: Cost Explorer, cost allocation tags, and per-team/per-service cost tracking
- AWS Budgets: setting budget alerts and automated actions when thresholds are breached
- Rightsizing: identifying over-provisioned EC2 and RDS instances with Compute Optimizer
- Reserved Instances and Savings Plans: committing to usage for 30–70% savings
- Spot Instances: using spot for fault-tolerant workloads — CI runners, batch jobs, stateless services
- S3 storage classes: Intelligent-Tiering, Glacier, and lifecycle policies to reduce storage costs
- NAT Gateway cost optimisation: one of the consistently surprising AWS cost items — VPC endpoints as a replacement
- Data transfer costs: understanding cross-AZ, cross-region, and internet egress pricing
🚀 Advanced Add-On Tracks
Six specialist tracks, each 2–3 additional weeks. Take any track individually or combine multiple. All tracks require the core program as prerequisite. Each track is aligned with a specific AWS or industry certification.
T1
3 weeks · Add-On · Additional Fee
Kubernetes & EKS — Fundamentals, Production Clusters & GitOps
Aligned with: CKA (Certified Kubernetes Administrator)
+
Kubernetes is the most in-demand DevOps skill and the most complex. Three weeks dedicated to learning it properly — not just running deployments but understanding the internals, operating clusters safely, and building the platform layer on EKS.
Week 1 — Kubernetes Fundamentals
- Architecture: control plane (API server, etcd, scheduler, controller manager) and worker nodes (kubelet, kube-proxy, container runtime)
- Core objects: Pods, ReplicaSets, Deployments, StatefulSets, DaemonSets, Jobs, CronJobs — when each is appropriate
- Services: ClusterIP, NodePort, LoadBalancer — service discovery with DNS
- Ingress and Ingress Controllers: NGINX Ingress, AWS ALB Ingress Controller — TLS and path-based routing
- ConfigMaps and Secrets: injecting configuration and sensitive data into Pods
- Persistent Volumes: PV, PVC, StorageClass, and the AWS EBS CSI driver for dynamic provisioning
- Namespaces and RBAC: isolating teams and workloads, ClusterRoles vs Roles, and ServiceAccounts
- Resource requests and limits: LimitRanges, ResourceQuotas, and QoS classes
- Health checks: liveness, readiness, and startup probes — probes that Kubernetes can trust
- Pod scheduling: nodeSelector, affinity/anti-affinity, taints, tolerations, and PodDisruptionBudgets
Week 2 — EKS in Production
- EKS cluster provisioning with Terraform: managed node groups, Fargate profiles, and cluster add-ons
- EKS networking: AWS VPC CNI plugin, pod IP assignment, security groups for pods, and Calico network policy
- IAM Roles for Service Accounts (IRSA): giving pods least-privilege AWS permissions without static credentials
- EKS cluster upgrades: control plane first, then node groups — zero-downtime upgrade strategy
- Karpenter: next-generation node autoscaler — NodePools, NodeClaims, and consolidation
- HPA and VPA: Horizontal and Vertical Pod Autoscalers with custom metrics from Prometheus
- External Secrets Operator with AWS Secrets Manager: syncing secrets to Kubernetes automatically
- EKS observability: Container Insights, Fluent Bit log forwarding, Prometheus + Grafana, and AWS Managed Prometheus
Week 3 — GitOps & Advanced Deployment Patterns
- Helm: packaging Kubernetes applications — charts, values files, hooks, and release management
- Kustomize: environment-specific overlays — base + overlays pattern without duplicating manifests
- ArgoCD: GitOps CD — Applications, ApplicationSets, App of Apps pattern, and sync policies
- FluxCD: CNCF-native GitOps — source controller, kustomize controller, and helm controller
- Progressive delivery with Argo Rollouts: canary deployments, blue/green, and automated analysis for rollback
- Sealed Secrets and External Secrets: managing secrets safely in a GitOps repository
- Service mesh basics with Istio: traffic management, mTLS, and observability overview
T2
2 weeks · Add-On · Additional Fee
AWS Security & Compliance Engineering — DevSecOps Pipeline
Aligned with: AWS Security Specialty
+
Security automated into the pipeline and infrastructure — not bolted on at the end. Essential for regulated industries, enterprise clients, and any company handling user data.
Week 1 — Infrastructure Security
- AWS Security Hub: centralised findings across GuardDuty, Inspector, Config, Macie, and IAM Access Analyzer
- AWS Inspector v2: continuous vulnerability scanning for EC2, Lambda, and container images in ECR
- AWS Macie: discovering and protecting sensitive data (PII, credentials) in S3
- KMS: CMKs, key policies, envelope encryption, and rotating keys for RDS, S3, EBS, and Secrets Manager
- AWS WAF: OWASP managed rule groups, rate limiting, and geo-blocking for ALB and CloudFront
- VPC security hardening: private subnets, VPC Flow Logs analysis, and network ACL layering
- AWS CloudTrail: auditing all API calls — log integrity validation and alerting on suspicious activity
- AWS Control Tower: multi-account governance — OU structure, guardrails, and account vending machine
Week 2 — DevSecOps Pipeline & Compliance
- Shift-left pipeline: Trivy (containers), Checkov (IaC), Semgrep (SAST), OWASP Dependency-Check, and Gitleaks in GitHub Actions
- SBOM: generating Software Bills of Materials with Syft and storing in ECR for audit and vulnerability tracking
- Container image signing with Cosign: signing at build time and verifying signatures before deployment
- Supply chain security: SLSA framework and provenance attestation
- OPA and Kyverno: policy-as-code for Kubernetes — admission controllers enforcing security standards at deployment
- Secrets rotation automation: automatic rotation with Secrets Manager rotation Lambdas
- Compliance frameworks: SOC 2, ISO 27001, and PCI-DSS controls mapped to AWS — AWS Audit Manager for evidence collection
- Incident response: runbooks for common security incidents, isolating compromised resources, forensic investigation
T3
2 weeks · Add-On · Additional Fee
Serverless & Event-Driven Architecture on AWS
Aligned with: AWS Developer Associate
+
Serverless is the fastest path to zero-ops infrastructure — no servers to patch, no clusters to manage, pay-per-execution pricing. The full AWS serverless ecosystem and event-driven architecture patterns.
- Lambda deep dive: execution environment, cold starts, SnapStart, concurrency (reserved and provisioned), and the Lambda power tuning tool
- Lambda layers: sharing code and dependencies — packaging custom runtimes
- API Gateway: REST API vs HTTP API vs WebSocket API — integration types, custom authorisers, throttling, and caching
- Lambda deployment strategies: blue/green with aliases, weighted routing for canary releases
- AWS Step Functions: multi-step serverless workflows — Express vs Standard Workflows and error handling
- EventBridge: the AWS event bus — event patterns, rules, targets, and event-driven architectures
- EventBridge Pipes: point-to-point integrations with filtering and enrichment
- SQS: standard vs FIFO queues — dead-letter queues, long polling, and Lambda event source mapping
- SNS: fan-out patterns — topic subscriptions, message filtering, and SQS+SNS integration
- Kinesis Data Streams: real-time streaming — shards, consumers, and Lambda stream processing
- DynamoDB: partition keys, sort keys, GSIs, DynamoDB Streams, TTL, and on-demand billing
- AppSync: managed GraphQL — resolvers backed by DynamoDB, Lambda, and HTTP endpoints
- Serverless observability: Lambda Power Tools for Python/Node.js — structured logging, tracing, and metrics
T4
2 weeks · Add-On · Additional Fee
Platform Engineering & Advanced IaC
Aligned with: AWS DevOps Engineer Pro + HashiCorp Terraform Associate
+
Platform Engineering — building the internal developer platform that lets development teams self-serve infrastructure without becoming cloud experts. The fastest-growing DevOps specialisation.
- Platform Engineering principles: golden paths, paved roads, and reducing cognitive load for developers
- AWS CDK: defining AWS infrastructure in TypeScript, Python, or Go — L1, L2, and L3 constructs and CDK Pipelines
- Pulumi: infrastructure as real code — TypeScript and Python Pulumi programs, stacks, and state management
- Terraform advanced patterns: module composition, provider aliasing, dynamic provider configuration, and native test framework
- Backstage: Spotify's internal developer portal — service catalogue, TechDocs, scaffolding templates, and AWS plugin integration
- Service cataloguing: publishing golden path templates that provision full application infrastructure from a single Backstage template
- AWS Service Catalog: curated products developers can self-serve without direct IAM permissions
- DORA metrics: deployment frequency, lead time, MTTR, change failure rate — measuring platform effectiveness
- Policy as code at scale: OPA Conftest for validating Terraform plans and Kubernetes manifests before apply
- Multi-account AWS strategy: AWS Organizations, SCPs, delegated admin, and account-per-environment patterns
- AWS Control Tower customisations: custom guardrails, lifecycle event hooks, and account factory automation
T5
2 weeks · Add-On · Additional Fee
ML Infrastructure & DataOps on AWS
Aligned with: AWS Machine Learning Specialty
+
As AI workloads move into production, DevOps engineers increasingly need to provision and operate GPU infrastructure, ML pipelines, and data platforms. The infrastructure side of ML engineering.
- AWS SageMaker infrastructure: training job provisioning, managed spot training, and SageMaker Studio setup
- GPU instance types on AWS: p3, p4d, g4dn, g5 — when to use each and cost comparison with SageMaker
- S3 as a data lake: partitioned Parquet datasets, S3 event notifications, and organising landing/raw/curated/serving layers
- AWS Glue: serverless ETL — crawlers, Data Catalog, Glue jobs in Python/Spark, and Glue Studio
- AWS Athena: serverless SQL over S3 — partition projection, workgroups, and cost control with result reuse
- Apache Airflow on AWS (MWAA): managed workflow orchestration — DAG deployment, connections, and worker scaling
- AWS Batch: managed batch computing for CPU and GPU workloads — job queues and compute environments
- MLflow on AWS: running the MLflow tracking server on ECS with S3 artifact store and RDS backend
- Model serving: deploying to SageMaker Real-Time Endpoints, Serverless Inference, and Batch Transform
- SageMaker Feature Store: online and offline stores, feature groups, and ingestion pipelines
- Data pipeline CI/CD: testing and deploying Glue jobs and Airflow DAGs with GitHub Actions
- Data cost control: Athena query management, Glue DPU optimisation, and S3 Intelligent-Tiering
T6
2 weeks · Add-On · Additional Fee
SRE & Advanced Observability — Prometheus, Grafana & Chaos Engineering
Aligned with: AWS SysOps Administrator Professional
+
Site Reliability Engineering — applying software engineering to operations. Defining SLOs, automating toil, and building the systems that prevent incidents and recover faster when they occur.
Week 1 — Advanced Observability Stack
- Prometheus: scraping configuration, service discovery, recording rules, and federation for large-scale metrics
- PromQL in depth: rate, irate, histogram_quantile, topk, and writing useful alerting rules
- Grafana: production dashboards — templating, variables, annotations, and on-call alert routing
- Loki: log aggregation without indexing overhead — LogQL queries, label design, and Promtail agents
- Tempo: distributed tracing storage — trace ID correlation between Grafana, Loki, and Tempo
- OpenTelemetry Collector: central telemetry pipeline — receivers, processors, exporters, and pipelines
- AWS Managed Grafana and AWS Managed Prometheus: the managed observability stack on AWS
- Grafana OnCall: on-call schedule management, escalation policies, and alert grouping
Week 2 — SRE Practice
- SLIs, SLOs, and error budgets: defining service level indicators, setting realistic objectives, and calculating error budget consumption
- Alerting on SLOs: multi-window, multi-burn-rate alerts — the Google SRE approach to actionable alerting
- Incident management: detect → respond → mitigate → resolve → review lifecycle, roles, and communication templates
- Blameless post-mortems: timeline reconstruction technique and action item tracking
- Chaos engineering with AWS FIS: running controlled experiments — EC2 failures, network latency, and AZ outages
- Resilience testing: validating Auto Scaling Group failover and RDS Multi-AZ switchover times
- Toil reduction: identifying repetitive operational work and automating with Lambda, Systems Manager, and EventBridge
- Capacity planning: using CloudWatch and Cost Explorer data to forecast and plan ahead of traffic growth
🎓 AWS Certifications Aligned
Every component of this program is aligned with one or more industry certifications. The hands-on project experience from each track substantially reduces time-to-certification.
Core Program
AWS SAA + SysOps Associate
Solutions Architect Associate and SysOps Administrator Associate
Track 1 — EKS
CKA — Certified Kubernetes Administrator
The most in-demand Kubernetes certification globally
Track 2 — Security
AWS Security Specialty
The professional-level AWS security certification
Track 3 — Serverless
AWS Developer Associate
Lambda, API Gateway, DynamoDB, and event-driven services
Track 4 — Platform
AWS DevOps Engineer Pro + HashiCorp TF Associate
The highest AWS DevOps certification + Terraform
Track 5 — ML
AWS Machine Learning Specialty
SageMaker, Glue, Athena, and ML infrastructure on AWS
📅 Schedule & Timings
Choose one group based on your availability. Maximum 5 candidates per group — individual hands-on lab support and direct instructor access throughout.
Weekday Groups
Group 1Mon–Wed · 10 AM – 1 PM
Group 2Mon–Wed · 4 PM – 7 PM
Weekend Groups
Group 3Sat & Sun · 10 AM – 2 PM
Group 4Sat & Sun · 4 PM – 8 PM
📍 Location: In-house training, F-11 Markaz, Islamabad · 📱 Online option available for out-of-city participants
🎯 Who This Is For
Backend or full-stack developers who want to own the infrastructure layer — the combination of development + DevOps skills commands the highest salaries
System administrators transitioning to cloud-native DevOps roles — your Linux and networking skills transfer directly
Engineers targeting remote DevOps, SRE, or platform engineering roles — the AWS specialisations in this program are exactly what those job postings require
Technical leads who need to make infrastructure and deployment decisions for their teams
Anyone pursuing AWS certification with hands-on practical training to complement exam prep — exams alone are not enough for real roles
No prior AWS or DevOps experience required for the core program — only basic Linux command line and programming basics