Posted on in programming
If you’ve ever participated in a heated pull request debate, you’ve probably encountered the age-old dilemma: Should we rebase or merge? While this question often sparks opinions based on team culture or aesthetics, there’s a more technical layer that rarely gets discussed — what’s really happening inside …
Posted on in programming
Source Code Management (SCM) has evolved dramatically over the past few decades. What started as simple file versioning systems has transformed into sophisticated platforms integrating AI-driven automation, security, and collaboration features. From the days of CVS and SVN to the dominance of Git and the rise of AI-powered development, this …
Posted on in system_administration
When working with Google Cloud Storage (GCS) via gsutil, most file operations
run smoothly. However, occasional cryptic error messages may appear that leave
you scratching your head. One such error is:
Semaphore released too many times MiB] 99% Done
CommandException: 1 files/objects could not be copied/removed.
make: *** [Makefile …Posted on in programming
In a previous article, we
explored how to count lines of code by language using tools like cloc. While
cloc and similar tools are convenient, sometimes you may prefer to avoid
additional dependencies and rely solely on standard Unix utilities. Maybe you’re
working in a minimal environment, or you …
Posted on in programming
Understanding the composition of a codebase can provide valuable insights: Which languages dominate the repository? Where might maintenance efforts be concentrated? Counting lines of code by language is a common task when assessing project complexity, preparing for audits, or reporting progress in multi-language environments.
In this article, we’ll explore …
Posted on in programming
When working with large Bazel code repositories, it’s not always clear how targets are distributed across directories. Understanding how many targets each top-level directory contains can help gauge complexity, identify hotspots, or guide refactoring efforts.
While Bazel itself doesn’t have a direct command to provide a “count of …
Posted on in programming
Over the course of this series, we’ve explored how to build client/server applications with Thrift and Protobuf/gRPC in three different programming languages: Java, Rust, and Python. We started with Thrift, implementing a Java server and Python client, then added Rust into the mix. Next, we recreated a …
Posted on in programming
We’ve now built similar RPC setups using Thrift and Protobuf/gRPC in Java and Python. Following the pattern established with Thrift, let’s integrate Rust into our Protobuf/gRPC ecosystem. Rust’s performance and safety features make it a popular choice for high-performance back-ends, and this exercise will show …
Posted on in programming
In our previous articles, we explored Thrift and demonstrated how to build cross-language systems with Java, Python, and even integrated Rust. Now, let’s turn our attention to Protobuf and its companion RPC framework, gRPC.
Protobuf (Protocol Buffers) focuses primarily on defining your data structures and ensuring efficient, compact serialization …
Posted on in programming
In the previous article, we built a simple Thrift-based client/server application where the server ran on Java and the client ran on Python. Now, let’s take things a step further by introducing a third language: Rust. Rust’s emphasis on performance and safety makes it an intriguing choice …
Posted on in programming
In our first article, we introduced Thrift and Protobuf and laid out our plan to build cross-language client/server applications. Now, it’s time to dive into a hands-on example with Thrift. In this article, we’ll define a simple service using Thrift’s IDL, implement a server in Java …
Posted on in programming
Modern distributed systems often span multiple programming languages, architectures, and runtimes. As services grow in complexity and scale, developers turn to powerful serialization frameworks and RPC (Remote Procedure Call) mechanisms that streamline inter-service communication. Two such technologies, Thrift and Protobuf, have emerged as popular solutions.
This article sets the stage …
Posted on in programming
As modern distributed systems become increasingly complex, developers rely on efficient, language-agnostic communication mechanisms to ensure seamless interactions between services. Two popular solutions for defining data structures and enabling efficient communication are Thrift and Protobuf. Both originated at tech giants—Thrift at Facebook and Protobuf at Google—and both aim …
Posted on in programming
Open source projects thrive on collaboration, transparency, and reliability. As contributors from around the world work together, ensuring consistent and reproducible builds becomes crucial. Hermeticity plays a vital role in achieving this consistency. In this article, we'll explore best practices for implementing hermeticity in open source projects, helping maintainers and …
Posted on in programming
Achieving hermeticity in software development brings numerous benefits, such as reproducibility, reliability, and security. However, implementing hermetic builds in large codebases can be a daunting task. In this article, we'll explore the common challenges developers face when striving for hermeticity in complex or legacy systems and provide practical solutions to …
