#cplusplus#cache#cpp#database#fibers#in_memory#in_memory_database#key_value#keydb#memcached#message_broker#multi_threading#nosql#redis#valkey#vector_search
Dragonfly is a modern in-memory data store compatible with Redis and Memcached, offering up to 25 times higher throughput and better cache efficiency while using up to 80% fewer resources. It scales well with larger servers, supports many Redis commands, and features a unique, memory-efficient cache and fast snapshotting. Dragonfly provides low latency, high performance, and is easy to configure with familiar Redis options. Its design ensures atomic operations and efficient resource use, making it ideal for fast, cost-effective cloud applications needing real-time data access and high scalability. This means you get faster, more efficient caching and data handling with minimal changes to your existing setup[5][2][4].
https://github.com/dragonflydb/dragonfly
http://aiohttp.readthedocs.io/en/stable/web.html#aiohttp-web-websockets
In order to implement a #web_server, first create a #request handler.
A request handler is a coroutine or regular function that accepts a Request instance as its only parameter and returns a Response instance:
#aiohttp#asyncio
from aiohttp import web
async def hello(request):
return web.Response(text="Hello, world")
Next, create an Application instance and register the request handler with the application’s #router on a particular HTTP method and path:
https://github.com/aio-libs/aiohttp/blob/master/docs/web_reference.rst
Server Reference
#asyncio#aiohttp#Request#BaseRequest#Server#client#Router#Resource
#typescript#ai_gateway#gateway#generative_ai#hacktoberfest#langchain#llama_index#llmops#llms#openai#prompt_engineering#router
The AI Gateway by Portkey lets you connect to over 1600 AI models quickly and securely through one simple API, making it easy to integrate any language, vision, or audio AI model in under two minutes. It ensures fast responses with less than 1ms latency, automatic retries, load balancing, and fallback options to keep your AI apps reliable and scalable. It also offers strong security with role-based access, guardrails, and compliance with standards like SOC2 and GDPR. You can save costs with smart caching and optimize usage without changing your code. This helps you build powerful, cost-effective, and secure AI applications faster and with less hassle.
https://github.com/Portkey-AI/gateway
YouTube Issues and Economic Updates
🔧 Users in Russia report ongoing issues with YouTube, marking another decrease in platform traffic, as confirmed by Google.
📊 The Russian Communications Ministry (RKN) plans to acquire data on user attempts to access blocked sites, though it already collects some relevant data.
⚙️ The Ministry of Economic Development aims to increase processing limits to enhance labor market flexibility amid personnel shortages.
📈 Predictions suggest the information security market in 2024 could grow by 30% to reach 593 billion rubles, though other estimates are lower.
📺 Yandex is negotiating with Haier, TCL, and Huawei for the installation of its OS on all their TVs supplied to Russia.
💰 AI search engine Perplexity successfully raised $500 million at a valuation of $9 billion, a significant increase from its earlier valuation of $1 billion.
🇺🇸 In the US, an investigation has been initiated against TP-Link over national security concerns, as they hold 65% of the domestic router market.
#YouTube#RKN#EconomicDevelopment#MarketGrowth#InformationSecurity#Yandex#Perplexity#Funding#TPLink#NationalSecurity#Russia#TechNews#AI#Router#Television#DataPrivacy#UserExperience#TrafficIssues