My workspace

  Disclaimer: this post is not a usual technical article. If you are not interested, you can skip it. I just want to share a few recent moments with my readers. After several months of work, the  print  edition of my book  Generative AI with Local LLM  has reached a new milestone — the cover design for the print version is now complete. This edition is a translated version of the original book and is planned for publication through  BomBora Publisher  in  Eastern Europe . The publisher has adapted the content specifically for  non-technical readers , making the material more accessible while keeping its practical focus. The translation and adaptation process took about eight months and included multiple rounds of review, proofreading, and refinement to ensure clarity and quality. The book is designed to help readers understand and apply generative AI through practical and accessible methods. It emphasizes clarity, simplicity, and real-world a...

 After a long period of time, I am moving to my new address  https://www.shamimbhuiyan.ru/   The new site is designed to provide a better experience with easier navigation, updated content, and more resources for exploring AI and related topics. If you've been following my work, be sure to bookmark the new address for future updates. Feel free to explore and let me know what you think!

Our new book (my 3rd book), Getting Started with Generated AI, is now available on both Leanpub and Amazon Kindle . While writing this book, we focused on two key goals: providing a simple, practical roadmap and maintaining a good balance between theory and hands-on practice. We also emphasize the use of local LLM inference for study and developing agents for personal use—something that has become much more affordable with the release of Llama 3.2. By the end, we highlight an important message: "You don't need to be a machine learning expert to learn Generative AI." If you're interested in learning more about Generative AI, take a look at the book. We've published 30% of the book as a sample chapter for you to explore. As always, your comments and suggestions will be highly appreciated!

Recently I was involved into a project for replicating data from PostgreSQL to Datalake. I heard about PostgreSQL logical data replication a few years ago and found a few hours to play with the Change data capture fuction of these popular database. Today's blog is all about PostgreSQL logical replication with a few fragments of code to test the functionality.  Change data capture is an architecture design principle that allows us to capture the recently data changed into the database in realtime. The changes could be any DML operations: Insert, update, delete.  TThere are a few charactaritics of CDC as follow: Logical replication uses publish-subscribe model. Subscriber pulls the data from the publication they subscribe to and manipulate the data. Only commited transactions on WAL archive (transaction log file) will be return by the CDC. CDC will return on orderd form how they commited on the database. Logical CDC doesn't impact on database performance. From the PostgreSQL v15...

Apache Ignite  is built on JVM and not a set-it-and-forget-it system. So, like other distributed systems, it requires monitoring for acting on time. However, Apache Ignite provides a web application named Ignite Web Console to manage and monitor the cluster, but it's not enough for system monitoring. You can also use JConsole/VisualVM for monitoring an individual Ignite node and a small number of Ignite nodes. Monitoring an Ignite cluster over 5 nodes by VisualVM or JConsole is unrealistic and time-consuming. Also, JMX does not provide any historical data. So, it is not recommended for production environments. Nowadays, there are a lot of tools available for system monitoring. The most famous of them are: Nagios Zabbix Grafana In this article, we cover the Grafana for monitoring Ignite clusters and provide step-by-step instructions to install and configure the entire stack technology. Grafana  is an open source graphical tool dedicated to query, visualize,...

Any technology, no matter how advanced it is, will not be able to solve your problems if you implement it improperly. Caching, precisely when it comes to the use of a distributed caching, can only accelerate your application with the proper use and configurations of it. From this point of view, Apache Ignite is no different, and there are a few steps to consider before using it in the production environment. In this article, we describe various technics that can help you to plan and adequately use of Apache Ignite as cutting-edge caching technology. Do proper capacity planning before using Ignite cluster. Do paperwork for understanding the size of the cache, number of CPUs or how many JVMs will be required. Let’s assume that you are using Hibernate as an ORM in 10 application servers and wish to use Ignite as an L2 cache. Calculate the total memory usages and the number of Ignite nodes you have to need for maintaining your SLA. An incorrect number of the Ignite nodes can become a b...

If you're just starting with this great open source framework, don't worry, we're here to help. Check out this great resource to help get you going. If you are running Apache Ignite for the first time, you might face some difficulties. You have just downloaded Apache Ignite, run it a few times, and got some issues. Mostly, these problems are solved in a similar fashion. Therefore, I decided to create a checklist, which provides recommendations to help you avoid issues in the development environments. 1. Configuration Files When Ignite starts in standalone mode by executing the ignite.sh|bat file, Ignite uses the $IGNITE_HOME/config/default-config.xml configuration file. In this situation, to connect to the specified node from the Visor command line console, you should choose the default-config.xml file from the configuration file list. Most of the time, the default- config.xml file is the first file in the list. You have to run the following command to execute an Ig...