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### Real Questions from Google, Microsoft, Apple — Decoded for 2–4 Yrs Developers
👨‍💻 Are system design interviews making you nervous?
🏗️ Struggling to explain architecture when you’ve never built large systems?
🔥 Want to prepare like a pro — without drowning in theory?
This FREE live meetup is built just for you!
***
### 🎯 What You’ll Learn (From Real MNC Interviews):
🔹 How to design a Scalable URL Shortener (Google-style)
🔹 Build a Notification Service like WhatsApp/Web Push (Microsoft-style)
🔹 Architecture of Apple iCloud File Sync System
🔹 Design a Rate Limiter with Redis (Backend Infra Round)
🔹 Interviewer Expectations — What to say, what not to say
***
### 💡 Why This Meetup is Different
✅ No boring lectures — Hands-on walkthroughs
✅ Real questions from real MNC interviews
✅ Learn how 2–4 year devs can confidently explain high-level architecture
✅ Resume + LinkedIn-ready talking points
✅ Mock Interview Feedback for 5 selected attendees
***
### 📦 Bonus Content:

• Live whiteboarding session
• Free PDF: "Top 10 System Design Questions for 2025"
• Networking Room with 1000+ fellow engineers
• Certificate of Participation

***
### 🧠 Who Should Attend?

• Developers with 2–4 years experience
• Preparing for interviews at FAANG, top startups, or product MNCs
• Anyone who has heard of “Scalability, Load Balancer, Cache” but never applied it

## 🧠 Agenda:
### 1. Coding Challenge: Automate Deployment with Ansible (25 mins)

• Objective: Write an Ansible playbook to automate the deployment of a web application across multiple environments.
• Key Concepts: Infrastructure as Code (IaC), configuration management, idempotency.
• Discussion Points:
• Handling environment-specific variables.
• Ensuring idempotent operations.
• Integrating with CI/CD pipelines.

***
### 2. Face-to-Face Interview Simulation: Debugging CI/CD Pipeline Failures (25 mins)

• Scenario: You're presented with a failing CI/CD pipeline in Jenkins that halts during the testing phase.
• Tasks:
• Identify and resolve the root cause of the failure.
• Discuss strategies to prevent similar issues in the future.
• Key Concepts: Continuous Integration/Continuous Deployment (CI/CD), pipeline as code, test automation.

***
### 3. System Design Session: Designing a Scalable Logging Infrastructure (25 mins)

• Objective: Architect a centralized logging system capable of handling logs from thousands of microservices.
• Discussion Points:
• Choosing appropriate logging tools (e.g., ELK stack, Fluentd).
• Ensuring high availability and scalability.
• Implementing log aggregation and analysis.

***
### 4. Real-World Product Issue: Handling Deployment Rollbacks (25 mins)

• Scenario: A recent deployment introduced critical bugs into the production environment.
• Tasks:
• Implement a rollback strategy to restore the previous stable state.
• Discuss monitoring and alerting mechanisms to detect such issues promptly.
• Key Concepts: Blue-green deployments, canary releases, monitoring and alerting, incident response

***
### 5. Q&A and Interactive Discussion (30 mins)

• Open floor for attendees to ask questions, share experiences, and discuss challenges faced during interviews or in real-world DevOps projects.

Are you a Data Analyst with 2-8 years of experience craving the next-level skills to crack complex datasets, optimize pipelines, and deliver real-time business impact?
If yes, this meetup is your golden ticket!
***
🎯 What we’re covering:
🚀 Extreme Real-Time Analytics & Data Internals

• Architecting lightning-fast data pipelines that don’t break under pressure
• Understanding streaming data platforms (Kafka, Spark Streaming) — beyond the basics
• Real-time anomaly detection, predictive analytics, and instant dashboards

📊 Advanced Data Modeling & Query Optimization

• Deep dive into SQL internals and performance tuning for massive datasets
• How to design scalable, maintainable data models for complex business scenarios
• Data warehouse vs. data lake vs. lakehouse: pros, cons, and use cases

🛠️ Tools & Techniques You’ll Love

• Leveraging Python & R for advanced stats and machine learning
• Automation hacks for ETL, data cleaning, and data quality checks
• Hands-on tips for using BI tools like Power BI, Tableau with real-time data

📈 What real employers expect from senior analysts

• Storytelling with data under extreme time constraints
• Cross-functional collaboration: influencing product and engineering with data
• From data wrangling to strategic decision-making: your complete playbook

Why it works: Most pros know K8s basics—this dives into real-world challenges and solutions.
Subtopics:

• Real production outage war stories
• Node pressure, evictions, autoscaling pains
• Resource tuning (CPU/Mem/Pod limits)
• Monitoring beyond Prometheus & Grafana
• Readiness/Liveness vs startup probes
• Helm pitfalls and GitOps wins

💡 Add Live Demo: Chaos engineering with `kubectl` and `chaos-mesh`.

***

### ⚙️ 2. “Kubernetes at Scale: 1 Million Pods and 10,000 Nodes”

Why it works: Shows high-scale architecture and tuning—perfect for infra-heavy audiences.
Subtopics:

• etcd scaling and shard patterns
• kubelet optimizations, CRI tuning
• Cluster federation vs multi-cluster service mesh
• Use of CRDs to customize control plane
• Scaling logs/metrics/ingress

💡 Add Open-source Showcase: Show your infra-as-code Terraform/GitOps setup.

***

### 🔐 3. “Zero Trust Security in Kubernetes”

Why it works: Security is top priority; show real isolation models and best practices.
Subtopics:

• NetworkPolicies and Calico setup
• RBAC hardening (least privilege)
• Secrets management: HashiCorp Vault + K8s
• Zero trust service mesh (Istio/ZTunnel/Linkerd)
• Container image scanning (Trivy/Snyk)

💡 Live Attack Demo: Try a misconfigured pod → access cloud metadata, then fix.

***

### 🚀 4. “From Dev to Prod: Enterprise CI/CD with Kubernetes”

Why it works: DevOps folks love end-to-end automation.
Subtopics:

• Jenkins + ArgoCD + Helm flow
• Canary & Blue/Green deployments with Istio
• GitHub Actions + K8s deployment pipeline
• Secrets management in CI
• ChatOps and Slack deploy bots

💡 Live Deploy: Trigger code → GitHub Actions → ArgoCD deploy → verify in real-time.

***

### 🤖 5. “Kubernetes Operators: Automate Anything”

Why it works: Few people master Operators; it’s a hot area.
Subtopics:

• What’s an Operator vs Controller
• How to write one (Kubebuilder)
• Use case: Auto-scaling DB clusters, Backup jobs
• Watchers, Reconcilers, CRDs explained
• Real operator (e.g. Prometheus, Kafka)

💡 Live Demo: Build and deploy a mini custom Operator.

### 👉 Suggested Flow for 2.5 Hours:

| Time | Segment |
| ---- | ------- |
| 0–15 min | Opening talk + story why this topic matters |
| 15–60 min | Deep dive session with live diagrams & case studies |
| 60–90 min | Live demo (20–30 min) |
| 90–120 min | Q&A + group discussion, real-world use |
| 120–150 min | Bonus insights, tools, free resources + networking |

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