latest posts

  • Using kbld to Rapidly Iterate on Kubernetes Deployed Apps

    When creating applications that extend or interact with Kubernetes, there are times when it's necessary to deploy and develop against a real K8s cluster. While Kubernetes makes it trivial to apply and roll out new changes, the building and pushing new dev Docker images for your application can be a rigamarole. On top of that, you also have to remember to configure the imagePullPolicyfor your containers to Always. Fortunately, there is a tool that can help solve all of these problems: kbld. The kbld CLI (pronounced "k build") assists with all things around image building and pushing for Kubernetes.

  • Leaving Breadcrumbs

    This post is going to be a bit meta. I'm going to write a bit about why I take notes publically and, to a lesser extent, blog in general. I started posting to this blog six years ago for kind of a lame reason. I had purchased the `downey.io` domain name and had no clue what to do with it! My earliest content is reflective of that lack of intentionality. Nowadays, I primarily write for three reasons: to cement my own understanding of a subject, to create content where there is none, and to leave digital breadcrumbs for myself and others to find in the future.

  • Desired State Versus Actual State in Distributed Systems

    It was once acceptable — and even expected — for web services to go down for maintenance or when under heavy load. Today, however, services are measured in the number of nines of availability they provide. A single server no longer cuts it. One way to achieve higher availability is by running countless copies, or replicas, of our services across geographies. Now, though, we've got ourselves a distributed system to wrangle! In this post we touch on the CAP theorem and the concept of Desired vs Actual State in distributed systems.

  • 2020 Goals

    When it comes to goals and self-improvement, I have a nasty habit of being over-ambitious and over-committing myself -- as evidenced by the piles of technical books and unused yoga equipment cluttering my apartment. In this post I describe what goals, both technical and otherwise, that I will focus on for 2020.

  • Reflections on Kubecon 2019

    A little over a week ago, I had the privilege of attending Kubecon in San Diego. It was an amazing experience, if not just a tad overwhelming in attendance and scale. It was a lot to take in -- and also a lot of fun! Now that I've had a bit of a break, I've had a chance to revisit my notes. In this post, I'll jot down a few of my takeaways from the conference.

  • Simplify Kubernetes App Deployments With Cloud Native Buildpacks and kapp

    In recent years the Kubernetes wave has taken the software world by storm. And for good reason. Kubernetes makes it easy for developers to build robust distributed systems. It provides powerful building blocks for deploying and managing containerized workloads. This makes it an enticing platform for the sprawling microservice "apps" of today. In this post we'll look at simplifying app deployments on Kubernetes with Cloud Native Buildpacks and kapp.

  • Completing Georgia Tech's Online Master of Science in Computer Science

    I applied to Georgia Tech's Online Master of Science in Computer Science (OMSCS) program back in September 2015. One of my friends was applying and encouraged me to apply as well. So I did, not really knowing what I was getting myself in to. I was accepted and took my first class, Software Development Process in Spring 2016 -- right as I was moving out to California. Now, three and a half years later, it's over. I've graduated and completed the Computing Systems specialization while working full time! Now I want to take the time to look back and reflect on my experiences in the program.

  • Finding Max Flow using the Ford-Fulkerson Algorithm and Matthew McConaughey

    The max flow problem is an optimization problem for determining the maximum amount of 'stuff' that can flow at a given point in time through a single source/sink flow network. A flow network is essentially just a directed graph where the edge weights represent the flow capacity of each edge. The 'stuff' that flows through these networks could be literally anything. Maybe it's traffic driving through a city, water flowing through pipes, or bits traveling across the information superhighway. This post walks through how to use the Ford-Fulkerson to determine the max flow of a network.

  • The Helman and JáJá List Ranking Algorithm

    In one of our labs in Georgia Tech's Intro to High Performance Computing course, we had to explore the parallel computing problem of list ranking. List ranking is essentially just traversing a linked list and assigning each node a "rank", or distance from the list's head. This post explores two parallel algorithms for list ranking -- Wylies's and Helman-Jájá.

  • Learning to build an Operating System in Rust via CS140e

    I first found out about Stanford's experimental Rust-based Operating Systems course via the GATech OMSCS Slack. I was intrigued by the fact that the course combined two of my favorite topics: the Rust programming language and Raspberry Pis. Now that I've hit a bit of a lull, having just wrapped up grad school for the semester, I've finally had a few cycles to spare and really dig in to the material in Stanford's CS140e.

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