SShortSingh.
Back to feed

Redux Toolkit Explained: Why Enterprise React Apps Choose It Over Context API

0
·1 views

Redux Toolkit (RTK) is a widely adopted state management solution for large-scale React applications, offering a more structured alternative to the built-in Context API. While Context API suits simple use cases like themes and authentication, Redux Toolkit is better suited for applications with frequent state updates, complex business logic, and multiple developers. RTK simplifies traditional Redux by eliminating repetitive boilerplate through features like configureStore and createSlice, which bundle state, reducers, and actions into a single file. The library also ships with built-in support for Redux DevTools and useful middleware defaults out of the box. This overview is part of a ongoing React Mastery Series aimed at helping developers build and understand enterprise-grade React applications.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Rust-based micro AI code reviewer 'ratatop' targets CI/CD latency and memory issues

A developer has detailed the architecture of 'ratatop', a lightweight AI-powered code reviewer built entirely in Rust, designed to run locally or in minimal containers on every commit. The project was created to address shortcomings of mainstream Python and Node.js code review tools, which often suffer from slow cold starts, high memory usage, and unpredictable execution times. Rust was chosen for its zero-cost abstractions, garbage-collector-free memory safety, and strong interoperability with C/C++ libraries used in high-performance diffing algorithms. A key engineering focus was zero-copy diff parsing using unsafe Rust blocks to eliminate heap allocations when processing large code changes via FFI. The tool also integrates Prometheus and libbpf to monitor its real-time impact on the host system.

0
ProgrammingDEV Community ·

AI Ops Agents Turn Prompt Injection Into a Cloud Infrastructure Security Threat

Security researchers warn that AI agents granted cloud credentials face a far broader prompt injection threat than previously understood, extending well beyond chat interfaces. Because these agents read resource tags, logs, metadata, commit messages, and ticket bodies while working, any attacker who can write to those sources can embed malicious instructions directly into the agent's context. Large language models cannot reliably distinguish operator commands from data they process, meaning injected text can trigger real cloud API calls such as terminating instances or exposing security groups. Long-term memory features in platforms like AWS Bedrock AgentCore and Azure AI Foundry compound the risk, as a poisoned instruction stored today can execute in a future session with no attacker present. Standard defenses like least-privilege IAM and input sanitization are considered necessary but insufficient, since an ops agent's legitimate permissions are inherently powerful and natural language has no clear parser boundary between data and command.

0
ProgrammingDEV Community ·

AI Token Prices Are Falling, But Engineering Teams Are Paying More Than Ever

OpenAI recently cut GPT-5.6 Luna pricing by 80% and GPT-5.6 Terra by 20%, while Claude Opus 5 launched on Amazon Bedrock at competitive rates, continuing a broader trend of falling AI token costs. Despite cheaper tokens, many engineering teams are reporting higher AI-related cloud bills each quarter. The core reason is the Jevons Paradox: lower prices unlock previously unviable workloads, driving far greater usage and ultimately higher spend. Beyond token costs, new layers of AI infrastructure — including agent runtimes, memory stores, observability tooling, and GPU pools — now make up a growing share of total AI spend, estimated to shift from roughly 20% in 2024 to around 70% of the total bill. Unlike token pricing, these infrastructure components follow standard cloud cost curves and require traditional FinOps practices, not vendor price cuts, to control.

0
ProgrammingDEV Community ·

Google DeepMind launches Gemini Robotics 2 to power full-body humanoid control

Google DeepMind released Gemini Robotics 2 on July 30, a suite of three AI models designed to control humanoid robots from head to toe. The system separates reasoning from motor execution: Gemini Robotics ER 2 handles high-level planning, while a vision-language-action model translates instructions into physical movements. A third variant, Gemini Robotics On-Device 2, runs the same motor conversion locally on the robot itself. ER 2 is accessible to developers via the Gemini API and Google AI Studio, while motor control models remain limited to select partners. The architecture has been demonstrated on robots from Apptronik and Boston Dynamics, handling multi-step tasks such as walking, grasping, and inter-robot coordination.