YAML, or "YAML Ain't Markup Language," is a human-readable data serialization format. It is commonly used for configuration files and data exchange between languages with different data structures. YAML is designed to be readable and concise, with a focus on data readability over markup verbosity...
Protocol Buffers (often referred to as protobuf) is a language-neutral, platform-independent method for serializing structured data. Originally created at Google, it excels at enabling efficient data interchange between services, storing information in a compact binary format, and sustaining backwar...
JSON, or JavaScript Object Notation, is a lightweight data-interchange format that is easy for humans to read and write and easy for machines to parse and generate. It is a text format that is completely language independent but uses conventions familiar to programmers of the C family of languages, ...
Message queues enable asynchronous, decoupled communication in distributed systems by allowing publishers to send messages to a queue that consumers process independently, typically in first-in, first-out order. This approach reduces direct dependencies between services, enhances reliability and sca...
In modern distributed architectures, messaging systems form an essential backbone for decoupling services, handling asynchronous communication, and enabling more resilient data flows. They allow separate applications or microservices to interact by sending and receiving messages through well-defined...
Batch processing is a method for handling large volumes of data by grouping them into a single batch, typically without immediate user interaction. It is often useful in scenarios where tasks can be processed independently and do not require real-time results, such as nightly analytics jobs, buildin...
Stream processing involves ingesting, analyzing, and taking action on data as it is produced. This near-real-time or real-time methodology is helpful for applications that need to respond quickly to continuously updating information, such as IoT sensor readings, financial transactions, or social med...
Caching is a technique used to speed up data retrieval by placing frequently accessed or computationally heavy information closer to the application or the end user. Below is an expanded set of notes on caching, presented with a simple ASCII diagram and bullet points that emphasize key consideration...
Redis is an open-source, in-memory data store that can be used as a high-performance cache system. It's often referred to as a "data structure server" because it can store and manipulate various data structures like strings, lists, sets, and more. As a backend developer, understanding how to use Red...
Netlify allows you to easily deploy and manage static websites...
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gRPC is a high-performance open-source framework that was developed at Google for remote procedure calls. It uses the Protocol Buffers (protobuf) serialization format by default and runs over HTTP/2 to support features like full-duplex streaming and efficient compression. Many microservices architec...
Stateful and stateless designs are common terms in software architecture. They describe how an application handles data over multiple interactions. This set of notes explains the differences between applications that remember information between requests and those that treat every request as a fresh...
GraphQL is a query language for APIs that allows clients to request exactly the data they need in a single request. It provides a type system to describe data and offers a more efficient, flexible, and powerful alternative to traditional REST-based architectures. These notes explore the fundamentals...
Data transmission in API design covers how information is sent and received between a client and a server. This involves choosing data formats, transport protocols, security measures, and techniques to ensure both correctness and efficiency. Whether an application is stateful or stateless affects th...
Representational State Transfer, often referred to as REST, is an architectural style used to design web services. It uses a stateless communication model between clients and servers, relies on standard HTTP methods, and focuses on simple but powerful conventions. These notes explore the core princi...
API communication protocols describe how different software components exchange data and invoke functionality across networks. They define the transport mechanisms, data formats, interaction styles, and often how developers should structure their requests and responses. These protocols are often cho...
Hypertext Transfer Protocol (HTTP) is the foundational communication protocol of the World Wide Web. It follows a client-server model and defines how messages are formatted and transmitted, as well as how servers and clients respond to various commands. HTTP was originally designed for fetching hype...
Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) are foundational Internet protocols that operate on top of IP (Internet Protocol). They determine how data is packaged, addressed, transmitted, and received between devices. TCP prioritizes reliability and ordered delivery. UDP foc...
In modern distributed systems, the performance and reliability of communication channels, APIs, and network infrastructure are critical factors that determine user experience. Metrics and analysis offer insights into system behavior under varying loads, help identify bottlenecks, and guide capacity ...
Network communications in a backend context involve the flow of data between clients (browsers, mobile apps, or other services) and server-side applications or services. This process spans multiple layers, from physical transmission over cables or wireless signals, through protocols such as TCP or U...
WebSockets introduce an event-driven, two-way communication channel between clients and servers over a single TCP connection. Unlike traditional HTTP request-response systems, WebSockets enable real-time data exchange with minimal overhead, effectively eliminating the need for repeated polling or lo...
Databases store and organize data so that applications and users can retrieve, manage, and manipulate information efficiently. The choice of database often depends on data structure requirements, scale, performance expectations, and the nature of the workload. Over the years, numerous types of datab...
Replication is a method of maintaining copies of data across multiple nodes in distributed systems, making it useful for improving availability, reducing latency, and distributing load. Below are detailed notes, organized in bullet points, each containing one highlighted word in the middle to emphas...
Data warehousing unifies large volumes of information from different sources into a centralized repository that supports analytics, reporting, and strategic decision-making. By collecting operational data, transforming it, and then loading it into one or more specialized databases, data warehouses a...
Isolation levels in relational-database systems govern how simultaneously running transactions perceive one another’s changes. They sit on a spectrum that trades consistency guarantees—how “correct” every read is—against concurrency—how many transactions can safely overlap. Choosing the right level ...
Indexing is one of the most effective ways to optimize database queries. By maintaining auxiliary data structures that map certain key values to their physical or logical locations, indexes allow a database to rapidly locate rows that match a search condition. This reduces the number of full-table s...
In large-scale distributed architectures, multiple processes, microservices, or nodes must operate in concert to achieve consistency, fault tolerance, and robust state management. Coordination services address these challenges by offering primitives like distributed locks, leader election, and confi...
The Gossip Protocol is a technique in distributed systems for sharing information across a network of nodes, especially useful when nodes frequently join or leave the network...
Operational Transform is a technique in distributed systems for real-time collaborative editing of shared documents...
Linearizability is a consistency model used to make it seem like there's only one copy of the data. It ensures that...
Locking is about managing concurrent access to shared data. Engineers often make it sound harder than it is, but the core idea is simple: choose between optimistic or pessimistic approaches depending on how costly retries are...
What it is: A string encoding of latitude/longitude into a hierarchical grid. Why it’s important: Enables very fast proximity searches (e.g. “find all users within 1 km”) by turning 2D spatial queries into simple prefix lookups. Interviewers often probe how you’d build location-based...
Concurrent writes happen when two clients write to a database at the same time, unaware of each other's write. This can cause inconsistencies in the replicas...
In time series analysis, understanding the relationships between observations at different time lags is crucial for model identification and forecasting. Two essential tools for analyzing these relationships are the Autocorrelation Function (ACF) and the Partial Autocorrelation Function (PACF)...