Shubham Malik

The worst way to teach/interview/learn system design is to design the entire company (ex: Quora, Airbnb, PayPal, Paytm, Hotstar) 🤦‍♂️ When you pick such a big system, you will create hypothetical Microservices and will not have time to go into engineering depth. A good system design discussion is when a problem statement is focused. You get a chance to discuss the component in-depth and touch upon the engineering aspects like bottlenecks, locking, and transactions. Yahi to asli maza hai! Tackling engineering challenges at scale. This is why every single system I discuss in my course has a limited scope so that I can cover it in-depth from all directions. ps: arpitbhayani.me/course

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After TikTok, this guy from IIT Madras wants to buy Google Chrome Aravind Srinivas, CEO of Perplexity AI, just made the tech industry's most audacious move: a $34.5 BILLION all-cash offer to acquire Google Chrome. Let that sink in. His company is valued at $18 billion. He's offering to buy Chrome for nearly double that. Here's why this matters more than you think: Perfect Timing: The DOJ is forcing Google to sell Chrome as part of antitrust remedies. This isn't just a random bid it's strategic. Chrome = Digital Real Estate: With 3.45 billion users and 65% market share, Chrome isn't just a browser. It's the gateway to the internet and Google's $300B ad empire. AI Browser Wars: Perplexity has already built "Comet," an AI-powered browser that can book flights, manage emails, and browse autonomously. Imagine that tech powering the world's most popular browser. This is just wow Per reports, multiple funds have offered to finance the bid with serious interest, even if the odds are long The Big Picture: This could be the AT&T breakup of our generation. If successful, it reshapes how we access information online and breaks Big Tech's stranglehold on digital distribution. The skeptics say it's impossible. Google will fight tooth and nail. Other tech giants will counter-bid. But here's what is mindblowing - Sometimes the biggest disruptions come from the most unexpected places. A 29-year-old from Chennai already built a billion-dollar AI company that threatens Google Search. Now he wants to own the front door to the internet. Whether he wins or not, Aravind just proved that in the age of AI, no monopoly is too big to challenge.

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For folks who use GitHub and are in early stage careers and hope to add GitHub as a value add to your profile - here is a note. If interviewing for an SDE role, GitHub projects that don't solve a problem and are just a coding exercise are not very helpful. This may sound perplexing but it needs to be said. : Hiring managers and tech leads (like me) look for problem-solvers. A repository full of practice exercises might show you can write code, but it doesn’t demonstrate that you can build impactful solutions. ► How to Make Your Projects Stand Out 1. Frame Them as Solutions: Instead of presenting your project as "just another app," position it as a business solution or a tool that solves a real-world problem. For example: - Instead of “Expense Tracker App,” say, “A tool for freelancers to manage and categorize expenses for tax season.” - Instead of “Weather App,” frame it as, “A weather app optimized for agricultural planning with location-based crop suggestions.” 2. Highlight the Problem It Solves: Every great project starts with a problem. Make it clear what problem you identified and how your project addresses it. - Example: “This tool was designed for small business owners who struggle with automating their daily sales tracking.” 3. Show Quantifiable Value: Numbers tell a story. Include metrics like: - How much time/money the solution saves. - How many users it could potentially impact. - Any test data or feedback you’ve collected. - Example: “This app reduced invoice processing time by 35% in a real-world test case.” 4. Document It Well: A project is only as good as its README. Include: - A brief description of the problem it solves. - Key features. - Instructions on how to run/test it. - Screenshots, GIFs, or a demo link to bring it to life. Having a GitHub full of clone apps or unfinished side projects sends the wrong signal. It doesn’t show creativity, ownership, or impact, it shows you can follow tutorials, and that’s not what companies hire for. Instead, invest your time into one or two high-impact projects that: - Solve real-world problems. - Show off your ability to understand user needs. - Demonstrate your thought process, design skills, and technical execution. So, take a step back, revisit your GitHub, and think: - Does this project solve a problem? - Can I explain its value to someone outside of tech? - Would I hire someone based on this work? If the answer isn’t “yes,” it’s time to rethink how you approach your projects. Remember: One impactful project > 100 clones. Focus on impact, not just output.

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🍀 6 months at Google.... Today I have completed 6 months at Google after having joined back in January 27th, 2025. These 6 months have been a rollercoaster of learning, exploration, meeting some exceptionally skilled people, and growth. Summarizing my journey at Google, here's the top 6 learnings for me over the period of the last 6 months... 1️⃣. Imposter Syndrome is real - Working at a place like Google, the talent density is the real deal. With being surrounded by some the smartest folks in the industry and working alongside them, its easy to feel lost and out of place. 2 things kept me going here - a. The support from the team in my rampup. b. The confidence that I've done harder things in the past - this too shall pass. 2️⃣. Ownership matters - At a place like Google, with highly skilled people all around, its kinda obvious that people like to own their work and expect you to do the same. How to own your work end to end, and to deliver it with the highest quality is something I've greatly learnt in the past few months. 3️⃣. Communication >>> Code - At a place, where any code change you make affects billions, communication and alignment regarding the same becomes something of utmost nessecity. Skillful communication within the team, cross teams, and with multiple stakeholders to effectively deliver work is something I've seen matter more than ever here. 4️⃣. Asking for help is a strength - In companies like Google and Microsoft, asking for help is looked on as a strength, not a weakness. The culture fosters that. However, to get help, you've to ask for it. Getting over the thought of judgment, to reach out for help, is a key learning which helped me a lot in the journey. 5️⃣. Make meaningful connections - Walking in any journey, what makes it worthwhile are the friends you make along the way. Making intentional connections, and going out of the way to help others move ahead in their journey, is the way to move ahead in the journey. This is something I also try to incorporate in my Linkedin journey by trying to give back to the community. 6️⃣. You're never too good at something, Keep learning - Tech is a fast moving space. The thought of "I already know enough" becomes obsolete as fast as the tech of today. Its a journey of constant of learning and upskilling. Parallely, make your basics stronger, that's what allows you to keep up the learning pace, with the industry. The last 6 months have been really exciting, fun, full of learnings and challenges all along the way. As its said in Google, being a Noogler is like "trying to drink from a firehose". Really excited for what the next 6 months unfolds. Stay tuned for more such content!!✌🏻🚀

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In 2019, Hotstar hit a peak concurrency of 25.3 million viewers, a world record for live streaming at the time. To put that into perspective, this was 3X YouTube’s record for live concurrency. 1. Scaling for Sudden Traffic Spikes  Live sports events bring massive spikes in user traffic, unlike most other types of applications. Here's what Hotstar faced:  - Toss happens → 3-4M people join instantly   - Match starts → Traffic doubles in minutes   - Dhoni comes to bat → 1.1M people join every minute   - Dhoni gets out → Traffic drops by 10M+ instantly  But Auto-scaling is too slow for these spikes. If servers take 5-6 minutes to boot up, the game might already be over by then.  🔹 How they solved it:  - Pre-warmed infrastructure: Servers were already scaled in advance, based on predictive models.  - Custom auto-scaling: Instead of waiting for CPU or memory usage to increase, they scaled based on live user concurrency and request rates.   2. Handling Sudden Drops in Traffic  Most platforms fear traffic surges, but sudden drops can be equally dangerous.  Why? When a match ends, millions of users suddenly exit the video stream and land on the homepage.  - During a match, users only request video playback (minimal backend load).  - When they exit, the homepage loads personalized recommendations, history, ads, and other API-heavy content.  - If 25M people suddenly request personalized content, it can overwhelm backend servers.  🔹 Hotstar’s approach:   - Graceful degradation: Non-essential services like personalization and recommendations were disabled during peak loads.  - Feature toggles: If a service was struggling, they returned a simple "200 OK" response to avoid cascading failures.   3. The Hidden Bottleneck: Load Balancers & Network Limits  - AWS Elastic Load Balancers (ELBs) are not truly "elastic".  - ELBs have predefined peak limits. If you don’t pre-warm them, your traffic can get throttled.  - Hotstar sharded load balancers and distributed traffic across multiple AWS regions to prevent overload.  💡 Fun fact: Their load tests generated so much traffic that it impacted other AWS customers, forcing them to move to a geo-distributed load generation model.   4. Chaos Engineering: Preparing for the Worst  🔹 They regularly simulated failures, including:   - Pushing 50M fake concurrent users to see what breaks.   - Taking down key databases mid-stream to check if failovers worked.   - Deliberately breaking network connections to test how services recovered.  At this scale, failures are inevitable. The key is ensuring they don’t affect users.  When systems were at risk, Hotstar sacrificed non-essential features to ensure smooth streaming.  - P0 services (video playback, ads, payments) → Always on   - P1 services (recommendations, search, user profiles) → Disabled if needed  If login services were failing, users were allowed to watch content without logging in.

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I cleared LLD interviews at top companies like Intuit, Uber, Zepto, Groupon, SenseHQ, and Meesho! How? By sticking to these 4 focused steps 🔥 ✅ 𝐌𝐚𝐬𝐭𝐞𝐫 𝐭𝐡𝐞 𝐅𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬 → Solidify your basics in OOP and SOLID principles ✅ 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐌𝐚𝐭𝐭𝐞𝐫 → Creational: Singleton, Factory, Builder → Structural: Adapter, Facade, Decorator → Behavioral: Strategy, Observer, Command ✅ 𝐔𝐌𝐋 𝐃𝐢𝐚𝐠𝐫𝐚𝐦𝐬 𝐟𝐨𝐫 𝐂𝐥𝐚𝐫𝐢𝐭𝐲 → Class Diagrams: Attributes, Methods, Interfaces → Other Key Diagrams: Sequence, Use Case, Activity ✅ 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞 & 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧 → Solved 8-10 complete LLD problems, applying design patterns and principles → Simulated interview conditions with a 1-hour timer ⏱️ 💡 LLD can be a game-changer for backend roles—it’s not just about writing code but designing scalable, maintainable systems that interviewers love! If you’re serious about cracking LLD rounds, join my Live LLD MasterClass where I’ll break down real interview problems and share proven strategies. 📅 Date: 1st March 2025 🔗 Register Here: https://lnkd.in/dx3fCtQz #LLD #LowLevelDesign #BackendDevelopment #SystemDesign #InterviewPrep #Uber #Meesho #Intuit #Zepto #Groupon #SenseHQ

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