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GitOps has already transformed how we think about infrastructure: declarative, auditable, and version-controlled. But as infrastructure-as-code (IaC) adoption grows and systems become more complex, even GitOps can feel overwhelming.

Enter the next wave: AI-powered GitOps. By integrating large language models (LLMs) into our CI/CD pipelines, infrastructure management becomes not …

Rebase and merge are not rival moral systems. They create different commit graphs, and the useful choice depends on who already depends on the history. Choose the shape that makes collaboration, debugging, and recovery boring—not the one that wins an argument in a pull request.

The graph is the …

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 …

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 …

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 …

Count lines of code by language with cloc, tokei, and Git-aware exclusions so generated files, dependencies, and vendor code do not distort your repository metrics.

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …