Cloud DevOps, Kubernetes & Site Reliability Engineering (SRE) Master Program
100% Placement Guaranteed | Linux, AWS Cloud, Docker, Kubernetes, Terraform IaC, CI/CD, DevSecOps, SRE & Observability | 100% Placement Guaranteed* (6 Months Fees Refund*)
Technologies You Will Master
100% Fees Refund* If Not Placed Within 6 Months
We believe in real career outcomes, not just empty certificates. If you complete the course modules, project milestones, and mock interview assessments but do not secure an IT engineering placement within 6 Months of course completion, MockAttempt guarantees a 100% full refund of your tuition fees* directly to your bank account with zero deductions.
Program Overview & Architectural Focus
### 🛡️ 100% Placement Assurance & Fees Refund Guarantee* (6-Month Window)
MockAttempt officially guarantees that upon graduating from this program and clearing the Job-Ready Assessment Pipeline, you will secure an IT engineering placement within 6 Months of course completion. If you are not placed within this 6-month post-completion period, you receive a **100% full refund of your course tuition fees*** directly into your bank account.
### 🎯 Multi-Dimensional Mastery & Assessment Framework (All Topics)
To ensure every graduate is genuinely world-class and job-ready for tier-1 enterprises:
- **Daily Topic Mock Tests (>98% Score Required)**: For every daily topic, students must score over 98% in proctored mock assessments. Students have access to **100+ dedicated Mock Tests per topic** to practice thoroughly.
- **Daily Topic-Wise AI Technical Interviews (>98% Score Required)**: Candidates undergo targeted AI technical voice interviews strictly testing that day's concept, requiring a >98% score.
- **Final Exit Benchmark (≥95% Minimum Score)**: To prove successful program completion and activate placement drives, candidates must achieve at least 95% in the comprehensive Final AI Interview and Mock Exam.
- **Multiple Re-Attempt Opportunities**: Students receive multiple chances to re-take assessments. Our goal is not just testing rote theoretical concepts, but rigorously developing **logical skills, problem-solving skills, and communication/articulation skills**.
*\*Terms & Conditions Apply. Subject to program milestones, attendance, project defense, topic mastery criteria, and active participation in placement drives.*
### 🎯 Target Engineering Roles & Audience
System Administrators, Software Engineers, DevOps Aspirants, Cloud Engineers, and Platform Engineers targeting senior DevOps, Kubernetes, and SRE roles.
Enterprise Technologies & Toolchain Mastered
Production-level toolchain and engineering ecosystems practiced during hands-on lab sessions, code reviews, and capstone engineering.
Structured Learning Path Roadmap (10 Phases)
Progressive pedagogical journey designed by staff engineers to transition candidates from fundamentals to enterprise defense.
Phase 1: IT, Linux & Enterprise Networking Foundations
Phase 2: GitOps, Shell Automation & Python for DevOps
Phase 3: AWS Cloud Architecture & Infrastructure Engineering
Phase 4: Enterprise Docker & Containerization
Phase 5: CI/CD Automation & DevSecOps Pipelines
Phase 6: Infrastructure as Code with Terraform & Ansible
Phase 7: Kubernetes Orchestration, Helm & Amazon EKS
Phase 8: Full-Stack Observability, Centralized Logging & Tracing
Phase 9: Site Reliability Engineering, Resilience & Platform Architecture
Phase 10: Enterprise Capstone, SRE Chaos Simulation & Career Placement
Daily Topic Mastery (>98%), AI Interviews & Exit Benchmark (≥95%)
Our goal is never simple rote memorization. MockAttempt is engineered to forge elite software professionals with world-class logical skills, problem-solving skills, and architectural communication clarity. For each topic and before graduating, students must clear our rigorous multi-dimensional evaluation pipeline:
For every single day's lesson/topic, candidates must score over 98% in proctored mock assessments. Students have access to 100+ dedicated Mock Tests per topic to practice edge cases, algorithmic variations, and syntax nuances until full clarity is proven.
Students undergo daily interactive, topic-specific AI voice and coding technical interviews. The AI strictly focuses on that day's concept, posing Socratic follow-ups to evaluate depth, articulation, and reasoning speed with a >98% score benchmark.
At the conclusion of the program, students must achieve a minimum of 95% in the comprehensive Final AI Technical Interview and Grand Mock Assessment to certify completion and qualify for corporate recruitment drives and the 100% Fees Refund Guarantee*.
Students receive multiple opportunities to re-attempt tests and interviews. The objective is not punitive but pedagogical: detailed telemetry, Big-O feedback, and AI hints help candidates learn from mistakes and cement true conceptual mastery.
Comprehensive Curriculum & Modules (33 Modules)
Hands-on engineering syllabus with real production implementations, daily mock tests & AI defense.
Foundations of modern computing infrastructure: servers, clients, data centers, hypervisors, virtualization, CPU, RAM, disk I/O, processes, threads, storage types, and private vs public cloud.
Comprehensive Linux system administration: kernel architecture, distributions, terminal shells, filesystem hierarchy (FHS), permissions, process monitoring, systemd services, SSH, and essential CLI tooling.
Network engineering fundamentals: OSI & TCP/IP stack, IPv4/IPv6, CIDR subnetting, ports, TCP vs UDP, DNS, DHCP, HTTP/HTTPS, SSL/TLS, routing, NAT, firewalls, and live troubleshooting with tcpdump, ss, dig, and curl.
Modern version control engineering: Git object model (blobs, trees, commits, tags), staging workflows, interactive rebasing, merge strategies, conflict resolution, GitHub pull requests, branch protection, and Git Flow.
Core principles of cloud computing: service models (IaaS, PaaS, SaaS), deployment models (public, private, hybrid, multi-cloud), global cloud infrastructure, elasticity, high availability, disaster recovery, and cloud economics.
Deep architectural dive into Amazon Web Services (AWS): IAM governance, EC2 compute, EBS/S3/EFS storage, VPC networking, ALB/NLB load balancing, Auto Scaling Groups, RDS/DynamoDB databases, Route 53 DNS, and CloudWatch.
Production Infrastructure as Code: Terraform architecture, HCL syntax, providers, resources, variables, remote state in S3 with DynamoDB locking, reusable modules, workspaces, provisioners, and drift detection.
Bash scripting mastery for system automation: variables, control flow, functions, exit codes, pipelines, I/O redirection, command substitution, cron scheduling, and writing robust server health, backup, and deployment scripts.
Enterprise containerization: Linux namespaces, cgroups, Docker daemon, image layering, Dockerfile directives, multi-stage builds, container networking, persistent storage volumes, and multi-container orchestration with Docker Compose.
Automating continuous integration: CI principles, automated test execution, GitHub Actions workflow syntax, triggers, jobs, steps, runners, environment secrets, matrix builds, artifact management, and building/pushing container images.
Enterprise automation using Jenkins: master-agent architecture, controller setup, Jenkins plugins, credentials management, Freestyle vs Declarative Pipelines, Jenkinsfile scripting, multi-branch pipelines, and automated deployments.
Foundations of Kubernetes container orchestration: Control Plane components (API Server, etcd, Scheduler, Controller Manager), Worker Node components (Kubelet, Kube-Proxy, CRI), Core Objects (Pods, ReplicaSets, Deployments), and kubectl.
Kubernetes networking architecture: Pod-to-Pod networking, CNI plugins, Service abstraction (ClusterIP, NodePort, LoadBalancer), CoreDNS service discovery, Ingress Nginx routing, and automated TLS certificates with Cert-Manager.
Managing state in Kubernetes: Volumes, PersistentVolumes (PV), PersistentVolumeClaims (PVC), StorageClasses for dynamic cloud provisioning, StatefulSets, headless services, and running production databases on Kubernetes.
Production Kubernetes management: node affinity, anti-affinity, taints, tolerations, topology spread constraints, resource requests/limits, QoS classes, Horizontal Pod Autoscaler (HPA), Canary and Blue/Green deployment strategies.
Kubernetes packaging with Helm 3: chart architecture, templates, values, Go template functions, control flow, chart dependencies, release lifecycles, environment overrides, and creating production Helm charts for microservices.
Enterprise Kubernetes in the cloud: Amazon EKS architecture, managed node groups, Fargate serverless pods, IAM Roles for Service Accounts (IRSA), AWS VPC CNI, AWS Load Balancer Controller, and automated EKS deployment pipelines.
Securing Kubernetes clusters: Role-Based Access Control (RBAC), ServiceAccounts, external secrets integration, NetworkPolicies for zero-trust pod isolation, Pod Security Standards, non-root containers, and security contexts.
Production monitoring architecture: Prometheus pull-based metrics collection, Time Series Database (TSDB), PromQL query language, Node Exporter, kube-state-metrics, Grafana dashboards, and Alertmanager routing.
Enterprise centralized logging for microservices and cloud infrastructure: application logs, container stdout/stderr, Elasticsearch cluster indexing, Logstash/Fluent Bit log collection, and Kibana log search dashboards.
Microservice latency profiling and distributed tracing: distributed trace concepts, spans, trace context propagation, OpenTelemetry (OTel) Collector architecture, auto-instrumentation, and trace analysis with Jaeger.
Google Site Reliability Engineering principles: DevOps vs SRE, reliability engineering framework, Service Level Indicators (SLIs), Service Level Objectives (SLOs), Service Level Agreements (SLAs), and error budget mathematics.
Operating production systems at scale: error budget burn rates, freeze policies, identifying and automating toil, incident response command hierarchies, severity levels, and conducting blameless postmortems.
Engineering resilient architectures: multi-AZ redundancy, health-check probes, disaster recovery strategies (Backup/Restore, Pilot Light, Warm Standby, Active-Active), circuit breakers, bulkheads, rate limiting, and load shedding.
Securing cloud environments: IAM least privilege conditions, VPC security hardening, private subnets, bastion hosts, VPC endpoints (PrivateLink), secrets encryption with KMS, CloudTrail audit trails, and Amazon GuardDuty AI threat detection.
Integrating security into the DevOps pipeline: shifting security left, Static Application Security Testing (SAST), Software Bill of Materials (SBOM), dependency vulnerability scanning, container image scanning with Trivy, and SonarQube quality gates.
Architecting real-world cloud systems: 3-tier web applications, microservices platforms, high-concurrency e-commerce backends, multi-environment AWS platforms, enterprise Kubernetes platforms, and disaster recovery architectures.
The evolution of DevOps into Platform Engineering: Internal Developer Platforms (IDP), self-service infrastructure, developer experience (DevEx), declarative GitOps with Argo CD, automated sync, self-healing, and drift correction.
Operating Kubernetes in high-stakes production environments: cluster version upgrades, node cordoning/draining, PodDisruptionBudgets, and solving 30+ real-world failure scenarios including CrashLoopBackOff, OOMKilled, and DNS outages.
Cloud financial management and cost optimization: analyzing AWS cost drivers (compute, storage, data transfer), rightsizing EC2 instances, Spot instances, Savings Plans, and governing Kubernetes cluster cost with OpenCost and namespace quotas.
Execution of industry-grade capstone projects: Production CI/CD Platform, Kubernetes Microservices Platform, Production EKS Platform with Terraform, and the SRE Chaos Simulation & Auto-Healing Enterprise Platform.
Comprehensive interview preparation: deep-dive questions and architectural defenses across Linux internals, computer networking, AWS cloud, Docker containers, Kubernetes orchestration, Terraform IaC, and SRE operational practices.
DevOps automation coding with Python and Bash, building a high-impact technical portfolio, ATS-optimized infrastructure resume crafting, 25+ technical mock interviews, and guaranteed corporate placement drives.
Portfolio Capstone & Production Projects (9 Projects)
Build and defend production repositories featuring clean architecture, CI/CD, and benchmark testing.
Enterprise Linux Server Hardening, Bastion Host & Network Troubleshooting Lab
Hands-on architectural implementation built with industry clean-code standards.
High-Availability Multi-AZ AWS Infrastructure Deployment with ALB & Auto Scaling
Hands-on architectural implementation built with industry clean-code standards.
Complete Production AWS Infrastructure as Code with Modular Terraform
Hands-on architectural implementation built with industry clean-code standards.
Zero-Vulnerability Containerization & DevSecOps CI/CD Pipeline with GitHub Actions
Hands-on architectural implementation built with industry clean-code standards.
Production Microservices Orchestration with Kubernetes & Custom Helm Charts
Hands-on architectural implementation built with industry clean-code standards.
Production Enterprise Managed Kubernetes Platform on Amazon EKS with IRSA
Hands-on architectural implementation built with industry clean-code standards.
Full-Stack Observability, Centralized Logging & Distributed Tracing Stack
Hands-on architectural implementation built with industry clean-code standards.
Internal Developer Platform (IDP) with Argo CD Declarative GitOps
Hands-on architectural implementation built with industry clean-code standards.
Production SRE Chaos Simulation & Automated Incident Remediation Platform
Hands-on architectural implementation built with industry clean-code standards.
Progressive Certification Ladder (5 Verified Levels)
Candidates earn industry shareable digital credentials as they clear milestone coding rounds and architecture reviews.
Certified Linux & Enterprise Cloud Associate
CLCACertified Cloud Infrastructure & Terraform Practitioner
CCIPCertified Kubernetes Administrator & Helm Specialist
CKASCertified DevSecOps & Observability Engineer
CDOECertified Site Reliability Engineer & Platform Architect
CSRE-PA🎯 Target Audience & Career Persona
System Administrators, Software Engineers, DevOps Aspirants, Cloud Engineers, and Platform Engineers targeting senior DevOps, Kubernetes, and SRE roles.
📋 Academic & Technical Prerequisites
Basic understanding of computer systems and familiarity with terminal command-line operations.
Frequently Asked Questions & Placement Refund Policy
Everything you need to know about the 6-Month 100% Fees Refund Policy, curriculum structure, and placement drives.
How does the 100% Fees Refund Policy* work if I am not placed within 6 Months? ↓
Every enrolled candidate is covered by our legally backed 100% Fees Refund Guarantee*. To qualify for refund claims if not placed in an IT role within 6 Months post-completion, students must complete the training and satisfy our rigorous mastery benchmarks:
- Daily Topic Mastery (>98%): Complete daily topic mock tests scoring greater than 98% (with 100+ mock tests available per topic).
- Daily AI Topic Interview (>98%): Clear topic-wise AI interviews scoring greater than 98% evaluating conceptual depth, logical problem-solving, and articulation.
- Final Exit Evaluation (≥95%): Score at least 95% on the Grand Mock Test and comprehensive Final AI Technical Interview.
- Multiple Retake Opportunities: Students are provided multiple re-test opportunities so the objective is true concept mastery, not high-stress one-shot testing.
If these academic benchmarks are met and you do not secure a verified IT placement within 6 Months after graduation, MockAttempt refunds 100% of your paid course tuition fees directly to your bank account with zero deductions.* Read our full refund policy terms here.
What companies recruit from this MockAttempt career track? ↓
Our candidates are actively hired by 150+ tier-1 IT consulting enterprises, Fortune 500 GCCs (Global Capability Centers), and high-growth technology product firms across India and overseas. We coordinate exclusive placement drives, resume shortlisting, and direct interview scheduling.
How does the MockAttempt AI Teleprompter and AI Mock Interview feature work? ↓
Students receive complimentary unlimited access to the MockAttempt AI Virtual Interview platform. You can practice real-time technical voice interviews, receive instant Big-O complexity feedback, and utilize our Windows desktop stealth teleprompter HUD to polish your problem-solving speech and live coding articulation before company interviews.
Can I learn this program if I am a non-CS student or complete beginner? ↓
Yes. Module 0 and Phase 1 start directly from fundamental computer concepts, operating systems, and basic programming logic. Our dedicated discord teaching assistants and weekly live doubt-clearing sessions ensure every candidate masters every concept thoroughly.
Backed by our 100% money-back guarantee: if not placed within 6 months post-training, your complete tuition is refunded.
Enroll with 6-Month Placement Assurance
Speak with a technical advisor and receive your complete syllabus roadmap and legal guarantee agreement.
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