ZondaYang

技能樹亂點的 Software engineer / reverse engineering enthusiast

[ZondaYang @ZondaYang]

agent-Interlude intercepts the traffic between an AI coding agent (Claude Code, Codex)

https://t.co/5JvvJd4m08

#Codex #Claude #analyze

[ZondaYang @ZondaYang]

Using claude has make me to speed up to implement what I want to build for long time ago

Multi-platform SRE ChatOps bot
https://t.co/NeHGRrdyUt

#SRE

[ZondaYang @ZondaYang]

Coffee break for the AI ​​agent — because even agents need rest!

take care Agent's health together

https://t.co/t8DVmRDSfy

#Claude #Codex #Skill

[ZondaYang @ZondaYang]

@GOATS_immortal Goats

[GOATS 🐐 @GOATS_immortal]

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[ZondaYang @ZondaYang]

@Goats_memecoin UQBUlC-4LiHgrkoJUmqPfPBrEWUr_XxMtP-vEczBgNhUQD-a

@pikaso_me screenshot this

[Narra @narralayer]

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[ZondaYang @ZondaYang]

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[ZondaYang @ZondaYang]

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[ZondaYang @ZondaYang]

Blaster goes Pew Pew Pew! 🔫 The first and only place to trade, earn, and launch tokens on @Blast_L2!

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[BLASTER 🔫 @BlasterSwap]

Blaster is ready to Blast!

We are stepping into the @Blast_L2 Big Bang Competition and announcing the Early Access Airdrop - Phase One!

https://t.co/9sq2m3CLI0

[ZondaYang @ZondaYang]

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[Wen Exchange @wen_exchange]

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[sysxplore @sysxplore]

20 Linux administration tips and tricks to help you excel in a DevOps career:

[ZondaYang @ZondaYang]

這個小玩具寫了一段時間了，真的不錯用，感覺最好用的功能是自動幫忙偵測是什麼壓縮格式，然後幫忙解壓縮，還是逐層哦，例如：.tar.gz ，可以自動幫忙解完兩種，是不是很方便阿，目前還有點 bug ，有些檔案會遺留，再來找時間修好他，先分享出來看看大家覺得如何～https://t.co/7jeeraVJJB

[sysxplore @sysxplore]

7 Layers of the OSI Model vs TCP/IP Model visual guide:

[ZondaYang @ZondaYang]

自己寫了一個 live-reload 的 watchdog ，目前功能是依據設定要監控的資料夾有發生什麼樣的 event，以重新執行 cmd ，心目中還有其他想要的功能，之後會陸續補上
https://t.co/5lm3HuBQkw

[Bilgin Ibryam @bibryam]

Applying Domain-Driven Design and Clean/Onion/Hexagonal Architecture to MicroServices

https://t.co/WTuSSFJDJh

[Dr Milan Milanović @milan_milanovic]

𝗗𝗲𝘀𝗶𝗴𝗻 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁

Design patterns can be divided into three main types:

𝟭. 𝗖𝗿𝗲𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀

These design patterns deal with object creation mechanisms, trying to create objects in a manner suitable to the situation.

Important patterns in this group are:

𝗙𝗮𝗰𝘁𝗼𝗿𝘆: This pattern allows delegating the instantiation logic to factory classes. The Factory Method creates objects without exposing the instantiation logic to the client.

𝗦𝗶𝗻𝗴𝗹𝗲𝘁𝗼𝗻 The Singleton pattern ensures that a class has only one instance and provides a global point of access to it. It's useful when exactly one object is needed to coordinate actions across the system.

𝟮. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀

These patterns deal with the composition of classes and objects that form larger structures.

Important patterns in this group are:

𝗔𝗱𝗮𝗽𝘁𝗲𝗿: This pattern works as a bridge between two incompatible interfaces. It wraps an existing class with a new interface to become compatible with the client's interface.

𝗙𝗮𝗰𝗮𝗱𝗲: The Façade pattern provides a unified interface to a set of interfaces in a subsystem. Façade defines a higher-level interface that makes the subsystem easier to use.

𝗗𝗲𝗰𝗼𝗿𝗮𝘁𝗼𝗿: This pattern dynamically adds/overrides behavior in an existing method of an object. This pattern provides a flexible alternative to subclassing for extending functionality.

𝗣𝗿𝗼𝘅𝘆: The Proxy pattern provides a surrogate or placeholder for another object to control access to it. In its most general form, a proxy is a class functioning as an interface to something else.

𝟯. 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀

These patterns are specifically concerned with communication between objects and how they interact and distribute work.

Important patterns in this group are:

𝗖𝗼𝗺𝗺𝗮𝗻𝗱: The Command pattern encapsulates a request as an object, thus allowing users to parameterize clients with queues, requests, and operations.

𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲 𝗠𝗲𝘁𝗵𝗼𝗱: This pattern defines the program skeleton of an algorithm in a method called template method, which defers some steps to subclasses.

𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: The Strategy pattern defines a family of algorithms, encapsulates each one, and makes them interchangeable. Strategy lets the algorithm vary independently from clients that use it.

𝗢𝗯𝘀𝗲𝗿𝘃𝗲𝗿: This pattern defines a one-to-many dependency between objects so that all its dependents are notified and updated automatically when one object changes state.

#technology #softwareengineering #programming #techworldwithmilan #developers

[Alex Xu @alexxubyte]

IBM MQ -> RabbitMQ -> Kafka ->Pulsar, How do message queue architectures evolve?

🔹 IBM MQ
IBM MQ was launched in 1993. It was originally called MQSeries and was renamed WebSphere MQ in 2002. It was renamed to IBM MQ in 2014. IBM MQ is a very successful product widely used in the financial sector. Its revenue still reached 1 billion dollars in 2020.

🔹 RabbitMQ
RabbitMQ architecture differs from IBM MQ and is more similar to Kafka concepts. The producer publishes a message to an exchange with a specified exchange type. It can be direct, topic, or fanout. The exchange then routes the message into the queues based on different message attributes and the exchange type. The consumers pick up the message accordingly.

🔹 Kafka
In early 2011, LinkedIn open sourced Kafka, which is a distributed event streaming platform. It was named after Franz Kafka. As the name suggested, Kafka is optimized for writing. It offers a high-throughput, low-latency platform for handling real-time data feeds. It provides a unified event log to enable event streaming and is widely used in internet companies.

Kafka defines producer, broker, topic, partition, and consumer. Its simplicity and fault tolerance allow it to replace previous products like AMQP-based message queues.

🔹 Pulsar
Pulsar, developed originally by Yahoo, is an all-in-one messaging and streaming platform. Compared with Kafka, Pulsar incorporates many useful features from other products and supports a wide range of capabilities. Also, Pulsar architecture is more cloud-native, providing better support for cluster scaling and partition migration, etc.

There are two layers in Pulsar architecture: the serving layer and the persistent layer. Pulsar natively supports tiered storage, where we can leverage cheaper object storage like AWS S3 to persist messages for a longer term.

Over to you: which message queues have you used?

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[Javarevisited @javarevisited]

10 System design concepts you should learn.
1. Caching
2. Sharding
3. load-balancing
4. replication
5. fault-tolerance
6. high-avaibility
7. Performance
8. scalability
9. Performance
10. Indexing
learn more on DesignGuru - https://t.co/1cnctTTdSY