CircuitWall Consultancy

Expertise. Innovation. Success

About Me

My name is Andrew Wu, lives and works in Stockholm Sweden.

I am a Big data and Machine learning engineer with ten years plus experiences. My knowledge including (but not limited to):

  • General application development
  • Big data & Machine learning
  • Cloud technologies (public and private)

Contact me if you need a hand or advices, and you are welcome to add me to your Linkedin contact.

Big data & Machine learning

Technologies supporting big data and machine learning like hadoop are more than 10 years old. If you think big data is a buzz word, then you are falling behind.

Big data and machine learning is about three things in my mind:

  • Ability to fetch and store large number of data.
  • Ability to analyze big data efficiently.
  • Ability to use the data and empower your business.

Key competences and Technologies

  • Big data
    • Apache Storm, Flink, Spark
    • Apache and Confluent Kafka
    • Cassandra, Riak databases
  • Machine Learning
    • Python, Tensorflow, Keras, Scikit
    • Evolution Algorithm
    • Realtime recommender system
    • Deep learning

Cloud technologie

Alright, “Cloud” is a real buzz word. Some people understand is the cloud drive, on-demand virtual machines, or the stuff floating on the sky… I say cloud is all those combined with out the floating stuff of course.

Key competences and Technologies

  • AWS EC2 & VPC
  • Cloudfoundry

General Application Development

Ten years plus of professional experience taught me how to build maintainable service with performance. I deliver any part of a service, mainly focused at backend.

Key competences and Technologies

  • Java SE/EE Spring, Springboot (10 years)
  • Python 3 (2 years)
  • Golang (2 years)
  • Javascript, CSS
  • MySQL, MongoDB, Riak


Performance, probably THE reason people choose kafka. But the definition of word performance is different between different use cases mainly two forms: latency and throughput. Understand your bottleneck To understand latency between each request, it is important to understand what are the ingredient of your latency. Monitoring Tuning Kafka cluster side Client side

The multi-datacenter topic come up usually because of two reasons: Your business now expanded into another part of the world. You need reliability more than pure performance (to some degree). I will skip the single DC setup here, as you can read upon in basically any kafka introduction documents. When comes to multi-datacenter setup there are, in my opinion, there are three major aspects during normal operations and when disaster strikes to consider: Read More…

As a consultant, it is hard to say “I don’t know”. With only very limited knowledge of Kafka, I started working as DevSecOps a few months ago on a large Kafka(confluent) installation for a bank. I am writing this from my own perspective on the key takeaways after working and tuning this multi-dc setup. There will be topics that you feel important that is not covered here, please let me know so I can improve this. Read More…