DEV Community: ADITI

The Journey That Just Began — From Feeling Like a Beginner to Receiving My First Stipend

ADITI — Sun, 12 Oct 2025 10:44:31 +0000

A Morning I’ll Never Forget

It was the morning of June 27, 2025 — a date that will always stay with me.
I woke up to a message notification on my phone. Half asleep, I opened it and froze.

My first stipend had been credited.

For a moment, everything went still. The noise around me faded, the world blurred, and I could feel only one thing — quiet pride. It wasn’t just about money. It was about proof. Proof that the long days, late nights, and endless self-doubt had meant something.

That single moment made me rewind through every step of the journey — from a nervous beginner to a student who had finally started seeing her efforts take shape.

The Beginning — Stepping Into the Unknown

It all began when I joined PICT. Everything felt new: the campus, the people, even the language. I was a quiet girl trying to make sense of this new world, often feeling lost but determined to find my place.

Slowly, things began to fall into rhythm.
From confusion came clarity, and that clarity turned into results. I scored a perfect 10 in my first semester — and again in the second.

People often asked, “Why work so hard? A 9-pointer is enough.”
But I always wondered, “Why stop when I can see how far I can go?”

That question — that curiosity — became the compass for my journey.

The Commute of Dreams — Sixteen Kilometers and a Million Thoughts

Every day, I traveled sixteen kilometers to college and sixteen back. I walked a kilometer from the bus stop to campus. What could have been a tiring routine became something much deeper.

Those long rides became my reflection time.
I revised viva questions, finished assignments, and often daydreamed about where I wanted to be.

Somewhere between the noise of the road and the hum of the bus, I found silence — the kind that lets you think.
That’s when I began asking myself:
What do I want? What’s holding me back? Can I become better?

The Learning Curve — From Knowing Nothing to Building Something

Second year arrived like a storm. Suddenly, there was so much to learn: C++, Java, OOPs, DSA — even Marathi.

I wasn’t the best in my group, but I was always consistent. I showed up every day with one goal — to be a little better than yesterday.

Of course, it wasn’t easy. There were nights when I felt like I knew nothing. Times when I questioned everything — my skills, my confidence, my pace.

But each breakdown became a turning point.
I realized that growth isn’t linear — it’s built from every failure you rise from.

Whenever I fell behind, I reminded myself:
If you’re falling today, maybe you’re building tomorrow.

Grades, Grit, and Growth

That semester ended with a 9.73 GPA — a dip from my perfect 10s.
It hurt, but it also pushed me harder. I promised myself I’d bounce back.

In the next term, I focused deeply on DBMS. I stopped copy-pasting from ChatGPT or lecture notes and started experimenting — trying to truly understand how things worked.

I wanted to learn, not just submit.

The Teachers Who Lit the Way

No journey is complete without mentors.
I was fortunate to have teachers who were more than instructors — they were guides.

Some stayed late after class to explain a concept again. Some encouraged me when I doubted myself. And some simply said, “You can do this” — words that meant more than they probably realized.

They didn’t just teach me subjects. They taught me confidence.

To every teacher who believed in me before I believed in myself — thank you.

The Unexpected Knock — Hello, Siemens

In February, Siemens announced openings.
I didn’t expect much. There were students around me who seemed more prepared, more confident.

Still, I applied. And to my surprise, my resume got shortlisted.
Maybe all those quiet efforts were finally adding up.

I performed well in my in-sem exams, scoring 135/150. I gave everything I had in practicals and the end-sem.

Then came the online assessment. I gave it with a calm mind — and that’s when the real surprise came.

“Interview tomorrow at 10 AM.”

My heart was racing, but my mind was ready.

The Interview — A Test of More Than Just Knowledge

When I joined the call, I reminded myself of something from my school days — how I had once frozen on stage during a speech competition and how, years later, I had won the extempore contest in class 12.

That growth gave me courage.

The interview covered everything — aptitude, puzzles, DSA, OOP, DBMS, and projects. To my surprise, I handled the puzzle questions quite well.

The second round was Techno-HR — a fast-paced mix of personal and technical questions. They asked about my family, college choices, coaching, and mindset.

It ended earlier than expected, and I wasn’t sure what that meant.
But I knew I had given it my all — with honesty and calm confidence.

The Result — When Effort Becomes Reality

A few days later, I got the message.

I had been selected.

My first industry offer. My first stipend. My first taste of turning effort into something tangible.

It was one of those moments that make all the silent hard work worth it.

The Tribe — My Family, Friends, and Supporters

Behind that success was a village of support.

My friends who stayed up with me before exams.
My dad, who listened patiently when I talked about projects he didn’t fully understand.
My brother, who made sure I didn’t skip meals.
And my mom — who literally fed me while I worked late into the night.

This wasn’t just my win. It was ours.

Just the Beginning

27th June 2025 — the date my first stipend came in — marked more than a milestone.
It reminded me that every effort counts. Every small step, every failure, every doubt you overcome — they all lead somewhere.

The journey has just begun. And I’m ready for what’s next.

If you’re a student who feels lost or unsure right now, remember this:
Consistency, self-belief, supportive mentors, and a spark of madness can take you further than you imagine.

This is only the beginning.
You can read this article on Medium here:

🌱 The Journey That Just Began. From Feeling Like a Beginner to… | by ADITI | Medium

ADITI ・ Jun 27, 2025 ・
Medium

🌩️ Smart Cloud Computing: How AI and ML Are Transforming Cloud Cost Optimization

ADITI — Sun, 12 Oct 2025 10:37:54 +0000

☁️ The Cloud Is Smart — But Are We Using It Smartly?

Cloud computing has completely changed how businesses run. From startups to tech giants, everyone loves the flexibility, scalability, and pay-as-you-go pricing of the cloud.

But here’s the catch — while the cloud promises savings, it can quickly become a financial black hole if not managed wisely. Many companies overspend up to 70% due to underutilized resources, wrong pricing models, or lack of cost visibility.

That’s where Smart Cloud Computing comes in — using AI, ML, and automation to make the cloud not just scalable, but financially intelligent too.

🧠 What Is Smart Cloud Computing?

“Smart” here means data-driven decision-making — optimizing the cloud based on analytics, predictions, and intelligent automation instead of static rules or guesswork.

Think of it as upgrading from a manual car to a self-driving one. You still set the direction — but AI helps you drive efficiently, avoid bottlenecks, and save fuel (or in this case, cloud costs 💰).

🔍 Key Factors That Drive Cloud Costs

Before we optimize, let’s understand what drives cloud bills:

Compute: CPU, memory, and instance types

Storage: Data volume, replication, and retrieval frequency

Networking: Egress costs between regions or clouds

Monitoring & Logs: Often overlooked but can eat up 20–30% of bills

Replication: For reliability but adds extra storage and transfer cost

The trick is not just to reduce usage — but to use smarter.

⚙️ AI/ML-Powered Cost Optimization Strategies

🔮 1. Predictive Analytics for Demand Forecasting
Machine learning models like ARIMA or LSTM predict workload patterns. This helps allocate resources before demand spikes — preventing both overprovisioning and downtime.

🤖 2. Automated Scaling with AI
Traditional autoscaling reacts to thresholds (like 70% CPU usage).
Smart scaling uses reinforcement learning to anticipate demand and scale proactively.

📦 3. Intelligent Workload Placement
AI algorithms decide where to place workloads — across regions, instances, or even cloud providers — for optimal cost and performance.
Example: Shift workloads from high-cost AWS regions to lower-cost GCP zones dynamically.

💡 4. AI-Powered Governance
AI detects anomalies in billing and performance data — spotting cost spikes before they become disasters.

💰 Cost Optimization Techniques in Action

Smart cloud computing combines several practical strategies to make cloud usage more efficient and cost-effective. One of the most fundamental is right-sizing, which means matching cloud resources precisely to the actual workload demand. This ensures you’re not overpaying for unused capacity or risking performance issues from under-provisioning.

Next is the use of Reserved or Spot Instances, where you commit to long-term or flexible discounted pricing models for predictable workloads — achieving savings of up to 70–90% compared to on-demand rates.

Serverless computing takes cost efficiency even further by charging only for the actual execution time of functions. Since there’s no need to maintain idle servers, this model eliminates unnecessary infrastructure costs and scales automatically with demand.

Data Lifecycle Management (DLM) is another vital technique that automatically moves data between storage tiers based on access frequency — keeping active data in high-performance storage and shifting infrequently used data to cheaper archival tiers.

Finally, AI-based routing uses intelligent algorithms to analyze data transfer patterns and route traffic through the most cost-effective paths. This not only reduces network egress fees but also improves application performance and reliability.

Together, these strategies form the backbone of smart cloud cost optimization — ensuring that every compute cycle, storage byte, and data packet contributes to maximum efficiency and minimum waste.

🌿 Smart Cloud ≠ Just Cost Cutting
Modern optimization also focuses on sustainability and FinOps (Financial Operations).

🌎 Sustainability-Driven Cloud
AI helps schedule workloads in regions with lower carbon intensity — making cloud operations greener and more energy-efficient.

💼 FinOps: Financial Accountability in Tech
FinOps bridges engineering and finance — encouraging teams to share responsibility for cloud spending. It’s not just about saving money, but spending wisely.

🚀 The Future of Smart Cloud Computing
The future is not just about automation — it’s about intelligence.
Expect cloud systems that can:

Predict your future billing trends 📈

Automatically balance cost, performance, and sustainability ⚖️

Self-optimize across multi-cloud environments 🌐

AI, ML, and sustainability will merge into holistic, intelligent cloud ecosystems — where every compute cycle, every dollar, and every watt of energy is used wisely.

🏁 Conclusion
Smart Cloud Computing isn’t just a trend — it’s the future of efficient, intelligent cloud adoption.

By blending AI/ML-driven automation, FinOps practices, and sustainability, we can transform the cloud from a cost center into a strategic advantage.

So, the next time you deploy something to the cloud, ask yourself:

“Is my cloud smart enough to save itself?”

My Siemens Interview Experience — Honest Reflections, Learnings, and Tips

ADITI — Sun, 12 Oct 2025 10:29:43 +0000

When I recently cracked my Siemens interview, I knew I didn’t want to just list questions and answers. I wanted to share the entire experience — the atmosphere, the type of conversations that happen, and the lessons I carried from it.

This post is not a “cram before your interview” guide. It’s a reflection from one student to another — an honest look at what the process felt like and what really matters.

Technical Interview — Round 1

The first round was conducted by a panel of three interviewers, two of whom were actively involved in asking questions. What stood out immediately was how conversational it felt. It wasn’t an interrogation but a genuine discussion around what I knew and how I thought.

The Introduction

The interview began with a simple “Tell me about yourself.”
It’s a standard question, but it sets the tone. I made sure to keep it real — confidently walking them through my journey rather than memorizing a script.

Project Discussion

Next, they asked me to explain the project I was most proud of. I shared my screen and walked them through the architecture, workflow, and challenges.

What they really looked for wasn’t how big or complex the project was, but how deeply I understood it. They checked whether I had actually built it, explored alternatives, and thought through real-world use cases.

It was clear that depth mattered more than breadth.

Database Management

Since I had used MongoDB in my project, the questions went in that direction.
They asked about the difference between authentication and authorization, ACID properties, how MongoDB handles transactions, and how I connected it to the backend in JavaScript.

We also discussed HTTP request types and how I implemented them within my project.

Object-Oriented Programming

They shifted to OOP concepts next — asking me to first explain OOP to a non-technical person, and then to a technical one. From there, they dived deeper into inheritance, polymorphism, abstraction, and encapsulation.

To make it more relatable, I used an analogy of a College–Department–Student structure, which they appreciated.

Data Structures and Algorithms

This section began with the Leetcode “Two Sum” problem. I first described the brute-force approach, then optimized it with the two-pointer technique, and finally presented the O(N) solution using a hashmap.

We also discussed sorting algorithms and their complexities. I went a bit further to explain how the STL sort function works internally — and that caught their attention since few candidates talk about library internals.

Aptitude Questions

Then came a few logical and aptitude problems. These tested reasoning more than formulas:

Using 3-liter and 5-liter buckets to measure exactly 4 liters.

A scooter running on 2 tyres at a time with 3 tyres available, each lasting 5 km — finding the maximum distance.

Converting 600 meters in 5 minutes to km/h.

Finding how many small cubes remain unpainted when a 3×3×3 cube painted white on the outside is divided into 27 smaller cubes.

Each problem was less about math and more about structured problem-solving.

General Questions

Finally, they asked about my family, background, and hobbies. When they asked if I had any questions for them, I made sure to ask about Siemens’ tech stack and the structure of their internship program.

What I Learnt from the Technical Round

This round taught me several key lessons:

Turn interviews into conversations, not monologues.

Interviewers are there to select, not reject.

Don’t hesitate to ask for hints or clarifications.

Stay calm and composed — outcomes follow preparation.

Be honest if you don’t know something; never bluff.

Perfect English is not the goal — clarity and confidence are.

Let them see your thought process, not just your memory.

HR Round — The Techno-HR Mix
The final round was a blend of technical and HR discussions. There were two interviewers: one focused on technical details while the other explored my personality, opinions, and background.

Topics Covered

Self-Introduction
They revisited my academic journey — JEE/CET scores, why I chose engineering, and specifically why I opted for IT/CS. They also asked about my college and future plans, including whether I planned to pursue an MS.

Project Discussion
They cross-examined my projects again, questioning my design choices and asking whether my project could scale across multiple pages. They also pushed me to think about why I chose certain tools and whether I had considered alternate solutions.

General Questions
The questions shifted toward general awareness and personality:

My opinion on AI and whether it will replace developer jobs.

Differences between Python and C++.

Whether Python is compiled or interpreted.

My projects in C++, Java, and Python.

Finally, they asked if I had any questions for them. I asked about their internal tech stack and the skills I should work on before joining.

Their last question was direct: “Are you confident you’ll be selected?”
I answered honestly and confidently — and that was the end of the process.

What They Were Really Looking For

Looking back, the qualities they seemed to value most were:

Authenticity: Are you genuine or rehearsed?

Reliability: Can they trust you to deliver what you promise?

Confidence: Do you back your ideas without arrogance?

Depth: Do you understand your work beyond surface-level?

Teamwork: Can you collaborate effectively?

Learnability: Are you open to feedback and growth?

Attitude: Do you display a growth mindset?

Character: Do you take responsibility for mistakes and learning?

My Final Takeaways

If you’re preparing for Siemens or any similar company, here’s what I’d emphasize:

Be trainable — companies look for potential more than perfection.

Prepare a clear system architecture diagram for your full-stack projects.

Always understand the “why” behind your answers and projects.

Remember, they can teach you technology, but not attitude.

It’s okay to think differently — stand out by being yourself.

Above all, be real.

Every interview is a chance to learn, not just to get selected. The more honest and curious you are, the better impression you leave.

This was my Siemens interview experience. I hope it helps others preparing for their interviews. If you have questions or want to share your journey, feel free to drop a comment below — I’d love to hear your story too.

You can also read the original Medium version of this article here:
👉 My Siemens Interview Experience — Honest Reflections, Learnings & Tips (on Medium)