Insights from a Rust Conference - Rustlab IT 2023
Rust, a programming language celebrated for its commitment to performance, reliability, and memory safety, has found substantial success in domains like kern...
Posts by Category
Coding
Kotlin coroutines and Java: How do they interoperate? - Part 2
This post continues what we have left off last time when migrating Java blocking codebase into Kotlin coroutine and how they interoperate with each other. To...
Measuring execution time in Spring Reactor Mono and Kotlin coroutine
I use Kotlin coroutine and Spring Reactor extensively for back-end development. Some challenges that I’ve encountered using those libraries are measuring ex...
Kotlin coroutines and Java: How do they interoperate? - Part 1
If we code with Kotlin, then Kotlin coroutine is a semi-obvious choice for asynchronous and concurrent programming. There are other alternatives, such as: ...
Transforming data class objects to Google BigQuery TableRow via reflection in Kotlin
I had a use case to transform multiple data classes into the Google BigQuery TableRow model. It is relatively straightforward if we have data classes with on...
Using Apache Beam vs other frameworks for bulk data processing
Apache Beam is a unified programming model for implementing batch and stream processing. It can run on multiple runners, such as Apache Flink, Apache Spark, ...
Data engineering
Transforming data class objects to Google BigQuery TableRow via reflection in Kotlin
I had a use case to transform multiple data classes into the Google BigQuery TableRow model. It is relatively straightforward if we have data classes with on...
Using Apache Beam vs other frameworks for bulk data processing
Apache Beam is a unified programming model for implementing batch and stream processing. It can run on multiple runners, such as Apache Flink, Apache Spark, ...
Machine learning
MLOps: exploring options on Google stacks
Running and maintaining a machine learning (ML) lifecycle on production is not an easy endeavor. Depending on the scale of our project, the activities can b...
Data science
MLOps: exploring options on Google stacks
Running and maintaining a machine learning (ML) lifecycle on production is not an easy endeavor. Depending on the scale of our project, the activities can b...