Vinit Dhatrak
Ex-Google, @DocuSign Lead Software Engineer with a passion for cloud, AI, and data.
San Francisco, California, United States
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Vinit is a seasoned software engineer with a demonstrated history of building on-premise and cloud-native distributed systems at scale. Currently, Vinit serves as a Lead Software Engineer at DocuSign, contributing to the Docusign's Storage team. With expertise encompassing cloud storage, distributed systems, and virtualization technologies such as Kubernetes, Docker, and the Linux Kernel, Vinit stands out as a thought leader in the tech industry. Throughout his career, Vinit has held pivotal roles at notable companies like Google, Box, Commvault, and Marvell, where he played an instrumental role in developing highly scalable and distributed cloud storage solutions. His proficiency in object-oriented design and systems programming, coupled with his capability to scale infrastructures to handle concurrent requests and planet-scale storage, positions him as a true expert in his field. (https://www.linkedin.com/in/vinit-dhatrak/)
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Navigating the Complex Landscape of Data Migration: A Case Study of AWS to Google Cloud Transition
In today's data-driven world, organizations face the challenge of efficiently managing and storing massive amounts of data. Migrating data from one cloud provider to another can offer cost savings and enhanced performance capabilities but also presents significant technical hurdles. This talk delves into the complexities of migrating a substantial 250PB of data from AWS to Google Cloud, a project that resulted in $20 million in annual savings.
Drawing on a concrete case study from Box Inc., the session offers a deep dive into the strategies and technologies employed to achieve a seamless transition between these two leading cloud providers. Attendees will explore the innovative approach our team took to design and implement a reliable, safe migration methodology which ensured data integrity and minimal downtime. We will explore the implementation of a hybrid cloud storage strategy that added "an extra 9" to the service level agreement (SLA), thereby ensuring superior reliability of the storage systems.
Key takeaways for participants include insights on managing distributed systems at a petabyte scale, handling enterprise-grade document storage systems, and the strategic considerations involved in selecting technology stacks. Attendees will also gain practical knowledge of leveraging technologies such as Kubernetes, Docker, and microservices architecture to build scalable, low-latency cloud storage solutions.
This discussion will benefit software engineers and cloud architects interested in system optimization, large-scale data management, and those looking for actionable insights into executing a successful cloud migration strategy. The session promises to equip participants with the tools and frameworks necessary to navigate their own cloud storage migrations, enhancing both operational efficiency and cloud infrastructure scalability.
Going from three nines to four nines using Kafka
Many organizations have chosen to go with a hybrid cloud architecture to give them the best of both worlds: the scalability and ease of deployment of cloud, and the security, latency & egress benefits of local storage.
Persistence of data on such an architecture can follow a write-back mode, where data is first written to local storage, and then uploaded to cloud asynchronously. However, this means that the applications cannot utilize the availability and durability guarantees of cloud, and the availability of storage is the availability SLA of on-premise storage, which is almost always less than the availability SLA of Cloud.
By switching the order, i.e. performing uploads to cloud, and then hydrating on-premise storage, applications get the benefit of availability SLAs of cloud. In our case, this allowed us to move from three 9’s of availability (99.9%) of local storage to four 9’s (99.99%).
Instead of uploading in write-back mode, we duplicated the incoming stream to upload to both cloud and on-premise. For on-premise uploads that failed, we leveraged Kafka’s event processing to queue up objects that need to be egressed out of Cloud into the local storage.
This architecture allowed us to hydrate the local storage with objects uploaded to Cloud. Furthermore, since local storage space is limited, we periodically purged data out of local storage and created a secondary copy of the data on cloud by leveraging Kafka event processing.
Cracking the Technical Interviews for FAANG and Beyond
This talk provides insider strategies and practical techniques to conquer technical interviews at FAANG companies and beyond. Led by Vinit Dhatrak, a Lead Software Engineer at DocuSign and former Google engineer who has successfully interviewed with and received offers from multiple FAANG companies, this session offers unparalleled insights into the interview process. Attendees will master coding problem-solving, system design principles, and behavioral interview techniques, gaining the confidence and skills to land their dream job. All necessary resources, including curated learning materials and practice problems, will be provided. This workshop aligns with TechMentor's goal of providing "real-world, independent" training, emphasizing "doing more with the technology they already own."
Detailed Agenda:
Day 1: Coding & System Design Fundamentals
Coding Interview Foundations
Welcome & Introductions
Efficient Problem Solving: Techniques for analyzing and breaking down complex coding problems.
Core Data Structures Review: Arrays, Linked Lists, Stacks, Queues, Hash Tables, Trees, Graphs.
Algorithm Fundamentals: Time/Space Complexity, Big O Notation, Searching, Sorting, Recursion.
Coding Patterns & LeetCode Mastery
Common Coding Patterns: Sliding Window, Two Pointers, Backtracking, Dynamic Programming, Greedy Algorithms.
Deep Dive into LeetCode 75 Blind List: Strategies for tackling the most frequently asked LeetCode problems.
Live Coding Demonstration & Best Practices
System Design Principles
Introduction to System Design: Scalability, Reliability, Performance, Consistency, Availability.
Architectural Patterns: Microservices, Message Queues, Distributed Databases.
Case Study: Designing a File Storage and Sharing System like Dropbox: High-level design, component interactions, API design.
Deep Dive into Dropbox System Design
Scalability and Performance: Handling millions of users and petabytes of data.
Database Design for Dropbox: Data modeling, schema design, and database selection.
API Design for File Uploads/Downloads
Day 2: Advanced Topics & Behavioral Interviews
Advanced System Design & Architecture
Consistency and Availability in Distributed Systems: CAP Theorem and trade-offs.
Fault Tolerance and Disaster Recovery.
Security Considerations in System Design.
Behavioral Interview Mastery
The STAR Method: Crafting compelling behavioral narratives.
Common Behavioral Questions: Leadership, Teamwork, Problem-Solving, Conflict Resolution.
FAANG-Specific Behavioral Expectations: Amazon's Leadership Principles, Google's focus on innovation, etc. Leveraging Vinit's interview experiences.
Mock Interviews & Personalized Feedback
Mock Coding Interview: Practice coding problems and receive feedback.
Mock Behavioral Interview: Practice behavioral responses and receive tailored guidance.
Q&A, Resources, & Wrap Up
Threads vs. Fibers: Analyzing the Noisy Neighbor Issue in Google Cloud Storage
This talk will delve deep into the innovative use of threads versus fibers in user-space cooperative scheduling, drawing upon real-world applications in the context of planet-scale storage systems, particularly Google Cloud Storage.
This talk will explore how Google Cloud Storage leverages fibers to address the challenge of "noisy neighbors" – non-conformant clients that can monopolize resources and degrade performance for others. By employing fibers and user-space cooperative scheduling, GCS achieves fairer CPU resource allocation, prioritizing conformant clients while strategically throttling non-conformant ones.
During this session, I will explore the architectural considerations and performance trade-offs between threads and fibers, leveraging my experiences from leading this project at Google.
This talk will be particularly beneficial for engineers and architects involved in building or maintaining large-scale distributed systems.
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Vinit Dhatrak
Ex-Google, @DocuSign Lead Software Engineer with a passion for cloud, AI, and data.
San Francisco, California, United States
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