Full Stack Engineer (Vue+Node)

The second volume of Grokking the System Design Interview, aimed at senior and staff (L5/L6) design rounds. It works through harder case studies such as a payment system, flash sale, notification service, unique ID generator, Gmail, Reddit, Google Calendar and a code judging system, then goes beneath them with patterns like quorum, write-ahead logs and vector clocks and deep dives into Dynamo, Cassandra, Kafka, Chubby, HDFS, GFS and BigTable.

• System design
• Backend
• Job search

The original Grokking system design course, which made the design round learnable. It teaches a repeatable interview approach and the key trade-offs (SQL versus NoSQL, strong versus eventual consistency, REST versus RPC and more), then works through 15 classic designs such as a URL shortener, Instagram, Dropbox, Twitter, YouTube, a rate limiter, a web crawler, Uber and Ticketmaster, each with requirements, estimates and trade-off discussion.

• System design
• Job search
• Backend

A browsable practice library of coding problems that can be filtered by pattern, data structure, difficulty and company, so you can drill exactly the weakness you found this week. Patterns include two pointers, sliding window, hash maps, stacks, backtracking and greedy algorithms, with company filters for Google, Meta, Microsoft, Amazon, Oracle and LinkedIn. Free to browse, with an in-browser editor and solutions.

• Job search
• DSA

A course built around 75 coding interview questions chosen for coverage across 18 topic areas, from arrays and sliding window to graphs, backtracking, dynamic programming and tries. Each question has a step-by-step algorithm, a walkthrough and complexity analysis, with solutions in six languages. It suits candidates with a few weeks before an interview who need a balanced, finite problem set rather than an endless list.

• Job search
• DSA

A quick-revision companion to the DSA roadmap in nine chapters: complexity, arrays and hashing, linked lists, stacks and queues, recursion, sorting and searching, trees and heaps, graphs, coding patterns, dynamic programming and timed practice habits. Costs are stated for every structure and algorithm, in Python, Java, C++ or JavaScript editions. Use it after each roadmap stage and before a contest or coding round.

• Programming
• DSA
• Web

An eight-stage path from Big-O through arrays, hashing, recursion, trees, graphs, coding patterns and dynamic programming to timed, mixed practice, in Python, Java, C++ or JavaScript. It suits students and developers who can write code but freeze on problems with no obvious library call. By the end you can pick the right data structure, recognise common problem shapes and solve a medium problem in about 35 minutes with edge cases tested.

• Programming
• DSA
• Web