#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers
The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4].
https://github.com/panaversity/learn-agentic-ai
#ENS is rebounding from the support trendline of the descending channel, with the Ichimoku Cloud acting as a resistance barrier.
A decisive breakout above both the channel and the cloud would confirm bullish momentum.
#ENS/USDT analysis :
#ENS is currently in an uptrend, consistently reaching new highs while trading above the 200 EMA. The price is now retracing towards the 200 EMA and a significant support level. It is expected that the price will test this zone and rebound, which should support the continuation of bullish momentum and will lead to a retest of previous highs.
TF : 1D
Entry : $30.35
Target : $47
SL : $23.38
#ENS/USDT analysis :
#ENS is currently in an uptrend, trading above the 200 EMA. The price has recently bounced back from the 200 EMA, suggesting a continuation of its bullish momentum and potential testing of higher levels. For a long entry, it is advisable to wait for a retracement to optimize the entry point.
TF : 30min
Entry : $43
Target : $48
SL : $38