Learn critical system design lessons from Netflix's live-streaming failure during the Tyson vs. Paul fight, exploring traffic spikes, CDN issues, and playback challenges developers must overcome for scalable streaming solutions.

This blog shows how to program using the DSPy framework. As means to that end, it walks us through a proof of concept conducted for an easy to understand use case involving SEO of digital text-based courses. It covers Inline and class-based signatures and shows the results of using a class-based signature with both the Predict and the ChainOfThought module (with multiple completion steps). The prompts that are generated under the hood are also shown. There is discussion on how the optimizers like LabeledFewShot, BootstrapFewShot and BootstrapFewShotRandomSearch work behind the scenes. The blog also shows how to write a customized metric function, create training and test data, and finetune using two of the optimizers. It shares some reflections on the results obtained.

Search algorithms are at the core of coding interviews and real-world applications like search engines and databases. Understanding them, especially efficient techniques like binary search, is crucial for programmers. This blog begins with linear search, a simple method that checks each element in a list until the target is found. While easy to implement, it is less efficient for larger datasets. Next, it covers binary search, which requires sorted data and operates by dividing the search interval in half, drastically improving efficiency with a time complexity of 𝑂(log⁡𝑛). Finally, it introduces the modified binary search, a variant that solves specific problems like searching in rotated sorted arrays or finding peak elements in bitonic arrays. These advanced patterns tweak the traditional binary search to handle unique scenarios, enhancing problem-solving skills and preparing you for coding interviews. Mastering these algorithms is key to excelling in technical coding interviews.

Get ready to ace the AWS Solutions Architect Certification SAA-C03 exam with this detailed guide. This tutorial delves into the exam structure, covering its key domains: designing secure, resilient, high-performing, and cost-optimized architectures. It introduces a systematic approach to solving scenario-based questions, helping candidates tackle practical AWS challenges. Featuring 10 curated sample questions with detailed answers and explanations, the guide provides real-world insights into AWS services and solutions. Additionally, it offers valuable tips, FAQs, and preparation resources to build confidence and maximize your chances of certification success.

Start your journey into Angular with this complete beginner’s guide, covering everything you need to build web apps today.

Graphs are important in computer science and are used in many areas like maps, social networks, and scheduling tasks. A graph consists of nodes (vertices) and edges (connections). In solving problems with graphs, basic algorithms like Breadth-First Search (BFS) and Depth-First Search (DFS) help find paths and explore graphs. More advanced methods, such as Kosaraju’s and Tarjan’s algorithms, identify strongly connected node groups in directed graphs. Graph coloring is useful for problems that need different labels for connected nodes. Hamiltonian path and cycle problems explore whether it’s possible to visit all nodes in a single path or cycle. Understanding these algorithms is key to solving interview challenges and real-world problems effectively.

In this blog, we’ll explore how to ace FAANG behavioral interviews using the STAR method, breaking down strategies to craft impactful, structured responses.

SciPy, Python's essential library for scientific computing, offers optimized mathematical functions, data handling, and powerful packages for tasks like linear algebra, optimization, and clustering. Scientists utilize SciPy for various scientific applications.