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DueWeekly Tech: 10-02-2025 to 23-02-2025

Feb 23, 2025, 13 min read

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Hi @all, we are back again with brand new session of dueweekely tech, this series will cover for you about the how the growth of technologies field via couple of blogs and let’s find out what you got with me. Cheer and have good experience

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Architecture

1. TechTarget - What is multi-tenancy (multi-tenant architecture)?

2. Viblio - Multi-tenacy vΓ  kiαΊΏn trΓΊc database cho hệ thα»‘ng multi-tenacy

  • These two of version about Multi-Tenacy in English and Vietnamese, that will show you about how we can structure and design a new pattern for your project serving multiple tenant instead of only one.
  • Pros/Cons when you use this architecture and which one you should choose or not to easier give you advice for choosing options

Career

1. Blog - When to Stay, or Leave a Job as an Engineering Manager

  • Blog talk about the real cases of engineer that face up with triangle important things of work: Pay - Work - People
  • Give you the vision about Engineer Manager could drop job with high salary because of missing once of stuffs and guide you what you should choose or think twice when making decision for new jobs
  • Helpful for who want to leave a job and find out a new place to keep continuous pursuit more career goals

Cloud

1. Medium - How I Stopped Cloud Security Breaches (5 Azure Features Every DevOps Engineer Must Use)

  • Learn about multiple methods for protecting your Azure Resources and Cloud, you can imagine about landscape when you use one of these implementations for enhancing your secure of Azure
  • Give you what effective and efficiency of these techniques with attaching scenario, solution and use cases for easier approaching

Containerization

1. Dev.to - Comparison of Alpine, Slim, Stretch, Buster, Jessie, and Bullseye Linux Distributions

2. Medium - Alpine, Slim, Stretch, Buster, Jessie, Bullseye β€” What are the Differences in Docker Images?

  • These articles take around how to distinguish between multiple types of Docker container. If you are work with containerization, you will have clear information about suitable distributions to make decision.
  • Information about each types, how to use and when to use that container. It really helpful when you try to optimize your docker image size and help your product pull/push more efficiently

3. Medium - Docker pros are shrinking images by 99%: The hidden techniques you can’t afford to miss

4. Medium - 13 Docker Cost Optimizations You Should Know

  • Two articles cover about how we can optimize cost and resources spending for building and storing Docker Images
  • List a couple of methods and strategies for efficiency implementation and write Dockerfile, you can prevent a lots of stuff mistake and happy with result when you try to apply these one
  • If you first start with Docker, you should learn these strategy for becoming modern docker builder in best ways as well.

Data Engineer

1. Blog - Open Source Data Engineering Landscape 2025

  • This blog is truly massive because that one cover a lot of stuff related into Data Engineer, what things you should be figured out in nowadays to tackle with daily changing in DataWorld
  • Note for your about multiple opensource for using and depend on many topics, pretty detail and you will happy to get more information from their
  • If you wanna see what activity in data field, go for it and you will learn a lot for sure

2. Medium - Filtering Streaming Data with Apache Spark, Reading with Druid, and Dashboarding with Superset

  • Article will demonstrate how to filter streaming data using Apache Kafka, for 10,000 users and 1,000,000 processes and consumed and processed usingΒ three Kafka brokers. Next, Use Apache Spark for streaming filtering these data into different topics and use Apache Druid and Apache Superset to analysis and visualization data transform.
  • Walkthrough step by step to help you cover stories to retrieve the result set in top of session and that’s pretty clear and truly helpful if you curious what things he does.
  • Help you find out many keywork, mindset and strategies for implementing for your own data pipelines and one more thing, this article collects actual many open-source which truly interesting

3. Medium - Building an End-to-End Data Lake ELT Pipeline using Modern Data Stack

  • Article helps you build E2E ELT Pipeline with couple of new technologies in Data field, such as DBT, Iceberg, Trino and Airflow
  • This one help you combine ELT into workflow orchestration with Airflow, attach with step by step to build this progress and provide useful information who want to earn and get more advise to implement ETL/ELT for yourself

Developer

[1. Medium - Blazing fast Python Docker builds with Poetry πŸƒ](# Blazing fast Python Docker builds with Poetry πŸƒ)

  • This article cover how we can optimize the docker build for Python project used Poetry as package management. It’s providing multiple strategy and scenarios for your implementation
  • This one will help you to reduce the build time as first, remove the odd things in docker image like cache as second and give you a lot of advice to boost the build time with integrating buildkit of docker, really helpful and interesting

2. Blog - What is the N+1 Query Problem and How to Solve it?

3. FreeCodeCamp - What is an ORM – The Meaning of Object Relational Mapping Database Tools

4. Viblo - Object Relational Mapping

  • Help me to approach theory about ORM (Object-Relational Mapping) in technologies. If you work in this technologies field, you will meet this technique at least one time or daily used, Do you know about that ?
  • These blogs deliver information about ORM, technologies and tools usually use for each languages which act ORM in your project, such as Prisma, Entity Framework, SQLAlchemy, …
  • It opens for new problem should be taken and solved by any organization who use ORM for their application, It called N+1 Query
  • Tunning and help you figure out Pros/Cons of ORM and what should we do when choose to use ORM or RawSQL. Think what you will be trade off and received, that pretty cool and adaptive for your learning

Kubernetes

1. Medium - Mastering Ingress Strategies for AWS EKS: ALB vs. Istio vs. NGINX

  • Collection of methodology for publishing your traffic into Internet inside Cluster with Gateway and Ingress, such as AWS ALB, Istio, Nginx
  • Attaching with each type, you will have manifest for guiding configuration, give you reason and pros to choose that service for your project
  • Hanging out if you want to learn about basic things inside Kubernetes and its’s pretty clear for approaching

2. Medium - Mastering Kubernetes: A Comprehensive Guide to Cluster Architecture, Upgrades, and Maintenance

  • Go through the Kubernetes Architecture, you can scrape a bit information about Kubernetes components but It’s just brief
  • BTW, This article guide you about migrate, backup and update the new version for your Kubernetes cluster, but remember it sets only for cluster using kubeadm via apt package
  • There are many ways for another selfhost cluster, such as k3s, rke2, k0s, …

3. Medium - How Do We Mitigate Memory Leak in Kubernetes with a One-liner Commit

  • Author tells about insane story of real events with production when spike memory and It turns your service into error state. This is journey him or his team dive into system, tunning and find the reason why
  • Couple of techniques to tunning memory leaking with application, especially with Kubernetes, It always problems of this technology and we can deal with that one
  • Sharing though in this article and that’s really helpful and well-being for who want to learn and explore more about functionality in Kubernetes and Techniques related to detect memory leak

4. Medium - Picking the Right Messaging Broker for Kubernetes at Scale

  • Useful article to help you reach to popular Message Broker in technologies field, such as Kafka RabbitMQ AWS SNS / SQS Pulsar
  • Explain use cases and what pros/cons of each option for easier choosing when you want to bring that technology into your project

MLOps

1. Medium - A Guide to MLOps with Airflow and MLflow

  • Provide you how to buiild DataOps and MLOps workflow with airflow and MLflow, role of them in your project
  • Explain and suggest tool for each step, you can explore more about MLOps process, including explanation about Airflow, MLflow and Kedro
  • Give example with real scenarios of orchestration system

2. Astronomer - Use MLflow with Apache Airflow

  • If you wanna learn how combination Mlflow and airflow for orchestrating workflow of ML model, this one should be for your
  • Guiding you how to implementation step by step, what library used and what is landscape for doing such things like this. After that, you can imagine how the MLflow and airflow interact with each others

3. Astronomer - Predict possum tail length using MLflow, Airflow, and linear regression

  • This one is real case scenarios of ML Engineer to build model and orchestration and management that via Mlflow and airflow, that combination is truly massive and pretty cool for exploring
  • Attach with step by step for implementation, source code for more inspect

4. Medium - Automating ML Workflows: Webhooks in Databricks with MLflow

  • Give the solution for automation workflow of ML via webhook, kinda clearly strategy and useful implementation
  • Blog cover and give you step by step from training to send your model to registry with combination between Databricks and MLflow

5. Medium - Real-Time Model Inference with Apache Kafka and Flink for Predictive AI and GenAI

  • Introduce multiple theories of AI/ML and how we can train and deploy model to inference, list couple of inference types and give advantage and disadvantage of each one, it will help you image which way you should follow up.
  • Point you to hot topics nowadays, GenAI and PredictiveAI, try to covey the problems and uses case when you resolve this problems. For sure, you will have some keywords and you can explore more about this problems
  • Learn how to Flink and Kafka act the role in the GenAI problem and what should we get after combination these technologies for your implementation with GenAI (e.g: Remote Model Inference with Kafka, Flink and OpenAI, Embedded Model Inference with Kafka, Flink and TensorFlow)

6. Medium - Machine Learning Operations (MLOps) For Beginners

  • Explain for you about MLOps, what kinda wrong when you first meet and help you imagine what MLOps can do for AI/ML Project
  • Have project for practicing and combine with AWS cloud for helping you learn more about strategy, theories and process in MLOps, such as DVC, MLflow, AWS ECS and Evidently AI

7. JFrog ML - 5 Best Open Source Tools to Build End-to-End MLOps Pipeline in 2024

  • Explore the way to build E2E MLOps pipeline with combining between these tools, they separate into categories and easier for your approaches, really helpful
  • Express the idea for changing from traditional strategy into MLOps with more efficiency
  • Give you more information about opensource, which best and what thing you should or can implement for project

8. Medium - End-to-End MLOps Pipeline using MLFlow (Part-1)

9. Medium - End-to-End MLOps Pipeline using MLFlow (Part-2)

10. Medium - End-to-End MLOps Pipeline using MLFlow (Part-3)

  • Learn how to use MLFlow to implement E2E MLOps as AI Engineer
  • Attaching and stitch with you for walkthrough into each process of MLOps implementation

11. Medium - ML workflow with Airflow, MLflow and SageMaker

  • Learn and how to build E2E ML workflow with airflow, mlflow and AWS such as sagemaker
  • Have example and illustration for imagine what step you should follow up inside with workflow strategy

12. LakeFS - MLflow Model Registry: Workflows, Benefits & Challenges

  • Introduce about MLflow and what feature you can do with this platform
  • Kinda same with official documentation but if you wanna try to read more brief version, I think this article should be for you, dawg
  • But if you have time, you should read and explore more information in MLflow - Official Documentation, pretty sure you can have more techniques for playing with Mlflow for sure

13. Databricks - MLOps workflows on Databricks

14. Databricks - LLMOps workflows on Databricks

  • Two article of Databricks which cover for you lots of information about MLOps and LLMOps and you can be easier for approaching
  • Introduce couple of tools and process of Databricks platform for each process, maybe you can familiar with Delta Lake or Mlflow
  • BTW MLOps and LLMOps is building for full compatibilities platform which integrate lots of process into one, like DevOps, DataOps, ModelOps and LLMOps , that what can do via Databricks - Data Intelligence Platform and Data Lakehouse

Technologies

1. Medium - Top 16 DevOps Tools for 2025: (Excellent for SREs, Too!)

  • Collections of really helpful tools for DevOps engineer in 2025, you can imagine you this tools for your work and reduce the workload, that’s pretty cool
  • About some candidates in this list actually aware by myself, include Harness, Dash0, Crossplane, Nix & NixOS, Zitadel, …

2. Debizium Blog - Incremental Snapshots in Debezium

  • Blog cover about how to incremental snapshot and what useful you get from this action
  • Put on legacy solution and new way to approach, explain with detail step by step and why we should we incremental snapshot

3. Gartner Community - Which is the best strategy to create the initial snapshots of a transactional database with millions of entries when using Debezium and Kafka Connect?

  • Discussion topic about why we should change init to when_needed in Debezium as Kafka Connector for handling million of entries
  • Give you bit solution and methodology for optimizing your debezium and good for handle high workload as well.

4. Dev.to - 20 Open Source Tools I Recommend to Build, Share, and Run AI Projects

  • Collections of really helpful for you to approach and reach to almost of concept of AI, you will have couple of keywords and knowledge about what some theories and how we can use opensource to tackle with that one
  • If you wanna find new technologies to learn, keep go in because that one for your

5. Confluent - KRaft: Apache Kafka Without ZooKeeper

  • Introduce new techniques and technologies to replace Zookeeper in combo with Kafka, It’s help reduce the complex when operate with Zookeeper than KRaft
  • List some features of KRaft, architecture to help you figure out how that work and small demo already attached with article to help explore.
  • This open way for next gens of Kafka and that’s relate with KIP-500, go check it out at Preparing Your Clients and Tools for KIP-500: ZooKeeper Removal from Apache Kafka

6. ClickHouse - ClickHouse Keeper: A ZooKeeper alternative written in C++

  • Another technology can used for replacing Zookeeper, In good way because this one is component of huge platform and technologies as OLAP Database - ClickHouse.
  • This blog covers about motivation, advantages and development of ClickHouse Keeper, It essential emphasized more efficiency, quick and less memory than Zookeeper, Upto 46 times
  • This one provide a lot of information and illustration for your exploring and express a feature of Keeper and the benchmark with impressive result.

7. VNPT Cyber - Zookeeper: BΓ­ quyαΊΏt thuαΊ§n hΓ³a dα»― liệu vΓ  thα»‘ng trα»‹ thαΊΏ giα»›i phΓ’n tΓ‘n!

  • Vietnamese Blog of VNPT Cyber write about Zookeeper, What is it, architecture and how Zookeeper actual work as coordination service in distribute system. Read more about concept of Zookeeper in English
  • Give you couple of comment and review about Pros/Cons of Zookeeper
  • Have quick demo session to guide you how to run Zookeeper in your environment

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