Siddhartha K.

🚗 Ever wondered how #Uber handles millions of real-time requests across the globe, without crashing? Uber System Design: Scalable, Modular & Real-time Uber’s architecture is built to support real-time operations across the globe, using modern cloud-native tools and layered system components. 1. IaC (Infrastructure as Code): Uber uses Terraform to automate infrastructure provisioning, ensuring consistency and speed across cloud environments. 2. Containerization & orchestration: Docker and Containerd manage containerized services, while Kubernetes handles scaling, availability, and service orchestration. 3. Databases: A diverse stack including Cassandra, MySQL, Redis, Hadoop, and Docstore supports real-time, analytical, and document-based data needs. 4. Cloud storage: Uber leverages Amazon S3, Azure Storage, and Google Cloud to store and access data across multiple cloud providers efficiently. 5. Microservices & caching: Built on microservices, the platform uses Redis-backed query and storage engines to reduce latency and ensure fast data access. 6. Big data platform: Kafka ingests data into systems like Hive, Spark, and Presto for large-scale processing and business analytics. 7. Observability & monitoring: Grafana, Jaeger, Prometheus, and other tools offer full visibility into performance, logs, and service health. [Explore more in the post] In summary: Uber’s system design reflects a robust, multi-cloud, real-time infrastructure, optimized for scale, speed, and seamless user experience across millions of rides and data interactions. 🔁 Save this for reference and share with someone preparing for system design interviews! 👉 DM me for any mentorship program to successfully land your dream tech role. Everyone Who Codes (EWC) has a simple mission: helping engineers get hired! 💼 Follow Lakshmi Marikumar for tech career & job search insights. Subscribe to our free newsletter on Substack: https://lnkd.in/gN83YA4H #systemdesign #softwareengineering #techjobs #interviews #backend #softwareengineer #softwaredeveloper #MAANG #2ndtier #hiring #jobsearch #uber  

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H-1B Visa Charges: Protecting Jobs or Killing Competitiveness? The recent hike in H-1B filing costs has thrown both corporate recruitment teams and staff augmentation firms into uncharted waters. While some hail it as a win for local talent, others warn it could cripple industries like semiconductors, AI, and advanced software that already face severe skill shortages. For corporate TA teams, the dilemma is clear: 🔸Do you absorb the higher costs to secure critical skills? 🔸Or risk delaying projects while trying to fill gaps locally? For staffing firms, the challenge bites harder: 🔸Bill rate pressures are real - how do you sell higher costs to clients? 🔸Do you double-down on nearshore/offshore delivery? 🔸Or retreat from niche, high-skill areas where local pipelines simply don’t exist? The bigger question: ❓Are we safeguarding local talent - or pushing innovation and global competitiveness further away from US soil by making access to top global talent more expensive? is this really our loss or the US's in long run? Recruitment leaders & staffing partners - what’s your take? Will this shift really fuel local hiring and upskilling, or is it just a short-term patch that risks long-term damage? #H1B #Trump #TrumpCard #Recruitment #Staffing

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Amazon's recent layoffs, including AWS employees, highlight a tough reality: companies prioritize cost savings. If you're impacted, it's crucial to act strategically. Focus on value positioning – showcase how you've reduced costs, improved speed, or increased reliability. Choose a lane related to funded work like cloud cost optimization or data engineering, and build a portfolio of case studies. Finally, create a 30/60/90-day plan to stabilize finances, rebuild your narrative, and reconnect with your network. Remember, you're selling outcomes, not just keywords. #Layoffs #CareerAdvice #AWS #ValuePositioning #JobSearch

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Sharing from Shalini Goyal - 10 essential system design trade-offs!! Every architectural decision you make comes with a price. Want more speed? You might lose consistency. Need scalability? Get ready for added complexity. Here are 10 essential system design trade-offs every engineer should understand to build systems that actually work in the real world. In system design, every choice comes with trade-offs. Understanding these 10 critical decision points helps you build scalable, performant, and reliable systems tailored to your application’s needs. 1. Vertical vs Horizontal Scaling Choose between scaling up a single machine (vertical) or distributing load across servers (horizontal). Horizontal is essential for resilience at scale. 2. SQL vs NoSQL SQL offers structured schemas and ACID compliance. NoSQL provides flexibility for unstructured data and high scalability in distributed systems. 3. Batch vs Stream Processing Batch handles data in chunks at scheduled intervals. Stream processes data in real-time for low-latency insights and reactive systems. 4. Normalization vs Denormalization Normalize for data integrity and reduced redundancy. Denormalize to boost read performance by reducing joins. 5. Consistency vs Availability In distributed systems (as per the CAP theorem), prioritize between strict data accuracy or always-available services—even under network failure. 6. Strong vs Eventual Consistency Strong ensures instant, global updates. Eventual trades immediate consistency for performance, syncing updates over time. 7. REST vs GraphQL REST offers multiple endpoints per resource. GraphQL delivers tailored responses with flexible queries from a single endpoint. [Explore More In The Post] 🎯 Bottom Line: There is no one-size-fits-all. The key to great system design lies in understanding these trade-offs and applying them based on your system’s goals, scale, and constraints.

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I asked an Amazon Bar Raiser how to make the perfect resume. Here is what Steve Huynh said: Steve spent 18 years at Amazon, conducted 850+ interviews, and helped set the hiring standards at Amazon. 1️⃣ Your resume has an F-shape. Recruiters read the top left first, then scan down and across. That top section is prime real estate, so put your best stuff there. 2️⃣ Add a short summary. One or two sentences that make it easy to see why you’re qualified. A recruiter only spends about six seconds on your resume. 3️⃣ No one clicks your links. Don’t hide your impact behind GitHub or portfolios. Show your value clearly on the page. 4️⃣ Depth beats breadth. Don’t list every language or framework you’ve touched. Go deep on one skill or project and make it yours. 5️⃣ Show delivery. Big tech looks for people who get things done. Bias for action matters more than buzzwords. Steve’s advice is simple but powerful. Focus on clarity, proof of impact, and self-awareness. That’s what separates applicants from hires. ♻️ Repost to help someone land their next job.

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