Introduction to eBPF and Cilium
Imagine being able to run programs directly at the core of your operating system—right within the kernel. There's no need to imagine, though, because Extended Berkeley Packet Filters (eBPF) make this possible. eBPF allows you to execute functions safely and securely within the Linux kernel. While it
Build and push Docker images to AWS ECR using Github Actions
Finding Docker as part of the deployment cycle when building modern applications is nothing new. This wide acceptance of Docker stems from the problem it solves—limited stress about the OS where your application will be deployed. Docker containers provide a consistent environment, ensuring your application behaves the same way
Hands-On Guide to Distributed Tracing: Encore vs OpenTelemetry
Let's say you're managing an application with multiple moving parts, like an e-commerce app. In this application, you have services such as user authentication, product catalog, payment processing, order management, etc. Each of these services is deployed across different servers and potentially even different regions for
Introduction to Multi-Cluster Deployment in Kubernetes
When starting out with Kubernetes, you've probably used a single cluster architecture. This architecture is easy to set up and allows you to enjoy the benefits of scaling and deploying your applications. If you've used this setup for a long time and on much larger projects,
Overview of the Apple M1 chip architecture
The M1 chip is Apple's first processor for Macs. Since its release in November 2020, it has shaped Apple's product lineup and set a new standard for what consumers can expect from their devices. Although the world has moved past M1 technology, it's still
Is Apache Kafka a Database?
Well, no. Apache Kafka isn't a database. It's a real-time event streaming platform. However, Kafka's ability to retain data in a durable and replicated manner does give it some database-like properties, which can be helpful in specific scenarios. In this article, I intend to
How Does Real-Time Data Streaming Work in Kafka?
Producing and processing real-time data are two sides of a coin. Imagine you run a company that continuously generates a steady stream of data that needs to be processed efficiently. Traditional solutions for handling this data using Kafka's producer and consumer APIs can be bulky because of the
Schema Evolution in Kafka
While applications are producing and consuming messages to and fro Kafka, you'll notice that new consumers of existing topics start emerging. These new consumers (applications) might have been written by the same engineers who wrote the original producer of those messages or by people you don't
