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**Apache Kafka 4.0 Details:** | |
* **Cloud-Native Focus:** The primary theme of Kafka 4.0 is its continued evolution towards being more cloud-native (from video). | |
* **ZooKeeper Removal (KIP-500):** | |
* ZooKeeper has been fully removed and deprecated (from video) | |
* KRaft is now the standard for metadata management, offering improved scalability and resilience (from video). | |
* This change simplifies cloud deployments by eliminating a component that posed networking challenges (from video). | |
* **KIP-848: New Consumer Rebalance Protocol** |
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# -*- coding: utf-8 -*- | |
""" | |
N8N-Inspired AI Automation Workflow Builder using Streamlit and LangGraph | |
""" | |
# Subscribe to the Deep Charts YouTube Channel (https://www.youtube.com/@DeepCharts) | |
import streamlit as st | |
import uuid | |
import os | |
import re |
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* **Titans** are a new Transformer architecture with RNN memory. | |
* **RNNs** have limitations like vanishing gradients, limited memory, and sequential dependency. | |
* **Titans** address these limitations by combining RNNs and Transformers. | |
* **Addressing RNN Limitations:** Titans aim to overcome the shortcomings of Recurrent Neural Networks (RNNs), such as: | |
* **Vanishing/Exploding Gradients:** Difficulty in training deep RNNs due to unstable gradient flow. | |
* **Limited Memory:** RNNs struggle to capture and retain information over long sequences. | |
* **Sequential Computation:** Processing information sequentially limits parallel processing capabilities. | |
* **Key Innovation: Neural Long-Term Memory:** | |
* Titans incorporate a dedicated neural module for long-term memory. |
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https://marketplace.visualstudio.com/items?itemName=liviuschera.noctis |
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mongodb | |
time series | |
Copped Collection -> fixed and retrieve insertion order, high throughput | |
Use Custom Collection -> rules for string comp letter case and assent marks | |
Clustered Collection -> stores ordered by used defined cluster key |
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https://betterprogramming.pub/tracing-in-spring-boot-3-webflux-d432d0c78d3e | |
logging.pattern.level: "trace_id=%mdc{traceId} span_id=%mdc{spanId} trace_flags=%mdc{traceFlags} %p" | |
https://spring.academy/guides/microservices-observability-reactive-spring-boot-3 | |
---------------- | |
https://azizulhaq-ananto.medium.com/how-to-handle-logs-and-tracing-in-spring-webflux-and-microservices-a0b45adc4610 | |
@Component |
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cmd -cur_console:n | |
powershell -cur_console:s1TVn | |
bash -cur_console:s1THn |
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https://www.dynatrace.com/news/blog/distributed-tracing-with-w3c-trace-context-for-improved-end-to-end-visibility/ | |
https://engineering.dynatrace.com/open-source/standards/w3c-trace-context/ | |
https://aloisreitbauer.medium.com/trace-context-and-the-road-toward-trace-tool-interoperability-d4d56932369c | |
https://stackoverflow.com/questions/76620276/use-both-b3-and-w3c-trace-formats-in-trace-propagation-between-spring-boot-2-3 |
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java -jar wiremock-jre8-standalone-2.35.jar --port 9999 | |
ls -> __files and mappings folders | |
wiremock recorder -> | |
localhost:9999/__admin/recorder/ | |
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AWS CloudWatch | |
βββ Metrics | |
β βββ Custom Metrics | |
β βββ EC2 Metrics | |
β βββ RDS Metrics | |
β βββ ELB Metrics | |
β βββ Lambda Metrics | |
β βββ S3 Metrics | |
βββ Alarms | |
β βββ Actions |
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