How to Load Test Magento 2 and Plan Capacity Before a Traffic Surge Breaks It

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Load testing helps Magento 2 teams measure the exact traffic thresholds their stores can handle, rather than discovering limits during a live flash sale or peak event. Experts recommend defining service-level objectives upfront — such as p95 TTFB under 800ms and error rates below 0.5% — before designing any test. Realistic tests must reflect actual traffic patterns, including a mix of category pages, product detail views, cart actions, and both anonymous and logged-in user sessions. The test environment should mirror production in data volume, PHP-FPM configuration, Redis, Elasticsearch, and Varnish setup to ensure results are meaningful. Teams are advised to run both warm-cache and cold-cache scenarios using dedicated load-generation tools like k6, and to generate traffic from a separate machine outside the application server.

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Chinese LLM APIs in 2026: Flagship Models Cost ¥4–¥12 Per Million Tokens

As of August 21, 2026, Chinese large language model APIs offer some of the most competitive pricing globally, with flagship models ranging from ¥4.00 to ¥12.00 per million input tokens, according to pricing data verified by llmabacus. Leading models in this range include Baidu ERNIE 5.1 at the low end and Alibaba's Qwen3.7 Max at the high end, while budget options like Qwen3.5 Flash go as low as ¥0.20 per million input tokens. DeepSeek's models stand out for aggressive caching discounts, with DeepSeek V4 Flash offering cached input at just ¥0.10 per million tokens. Analysts attribute the sustained price decline to cheaper hardware, intensifying domestic competition, and the rise of aggregator gateways that unify access across vendors. Compared to Western counterparts, Chinese value-tier models are estimated to be 80–98% cheaper than GPT-5.5-class equivalents, though buyers are advised to weigh cache hit rates and tool-calling compatibility alongside list prices.

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ProgrammingDEV Community ·

Browser-Based Tools Can Edit Files Locally Without Uploading Your Data

Most free online file-editing tools silently upload user files to remote servers, raising privacy concerns for sensitive documents like tax forms, IDs, and contracts. Modern browsers can now handle many common tasks — such as image compression, PDF merging, and text formatting — entirely on the user's device using JavaScript and WebAssembly. This client-side processing means files never leave the browser tab, eliminating the risk of third-party storage or analysis. Users can verify whether a tool works locally by checking the browser's network tab for upload requests or testing the tool while offline. Platforms built on this approach, such as ToolNova, offer 150-plus such tools with no accounts, watermarks, or file-size restrictions.

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ProgrammingDEV Community ·

Chinese LLMs Match or Beat GPT-5.5 on Tool Use, But Migration Is Not Plug-and-Play

As of August 2026, all five major Chinese LLM families — DeepSeek, GLM, Qwen, Kimi, and MiniMax — offer OpenAI-compatible tool-calling endpoints across 10 production variants. Benchmark testing on the BenchLM tool-use suite shows GLM-5.1 and MiniMax M3 scoring 70.1, surpassing GPT-5.5's 67.8, while Kimi K2.6 trails at 60.5. Despite surface-level API compatibility, meaningful differences persist in JSON schema fidelity, parallel tool-call handling, and streaming delta formats, meaning teams cannot migrate GPT-based agents with a simple configuration change. Router services like OpenRouter and Eden AI normalize transport-layer issues but do not resolve semantic or schema incompatibilities. Teams willing to build per-model adapters can achieve tool-use accuracy at or above GPT-5.5 levels at significantly lower cost.

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ProgrammingDEV Community ·

Developer Builds AI Agent Fleet to Detect Wildfire Risks on Power Grids Before They Ignite

A developer built Keystone, an AI-powered grid monitoring system, as a submission to the All Things Agentic Hackathon using Google Gemini and Google Cloud. Inspired by the 2018 Camp Fire — which killed 85 people and was traced to a faulty PG&E transmission line component that went unnoticed — Keystone continuously watches transmission infrastructure for developing failures. Unlike typical wildfire-AI tools that flag anomalies and stop, Keystone validates each finding using real engineering models, including the IEEE-738 thermal equation, and runs an adversarial critique agent to challenge results before any alert is raised. Once a risk is confirmed, the system autonomously notifies three peer organizations — a mutual-aid utility, a fire agency, and a grid balancing authority — simultaneously via the Agent2Agent (A2A) protocol, with the balancing authority's response able to block de-energization actions. The project aims to close the years-long gap between when a grid failure begins and when a human operator detects it, prioritizing accuracy over speed to maintain operator trust.

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