Mwiine Daniel
Cloud Engineer | IT Systems Admin
Kampala, Uganda
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Hey there! I’m Mwiine Daniel, a cloud enthusiast with a knack for all things tech. I’m a Certified Associate Cloud Engineer and a Google IT Support Specialist, which means I get to play around with cloud infrastructure and IT solutions while keeping things secure and running smoothly.
As a former Lead Organizer for Google Developer Groups (GDG) On Campus, I loved bringing tech lovers together, organizing events, and mentoring the next generation of developers. We were always learning and growing as a community, which keeps things exciting!
I’m all about Python, automation, and Linux—I seriously enjoy finding new ways to streamline tasks and build open-source solutions. Tech is my playground, and I’m constantly learning something new.
If there’s one thing that drives me, it’s the joy of sharing knowledge and helping others navigate the ever-evolving world of technology.
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Building and Deploying Applications Seamlessly with Google App Engine
Brief Description:
This session is designed for developers and tech enthusiasts who want to understand how to take an application from local development to live production with minimal infrastructure overhead. Google App Engine abstracts away server management, scaling, and monitoring, making it ideal for small startups, student projects, and enterprises looking for agility.
What to Expect:
1. Foundations of PaaS: Understand what Platform as a Service (PaaS) is, its pros and cons, and how it compares to other compute options like Compute Engine and Cloud Run.
2. App Engine Environments: Explore the differences between Standard (quick deployment, autoscaling, cost-efficient) and Flexible (custom runtimes, more control).
3. Step-by-step Live Demo: Watch a real-world example where a Python Flask web application is deployed in real-time, starting from gcloud app deploy.
4. Scaling Explained: Learn how App Engine scales from zero to millions of requests automatically and what quotas/free tier are available.
5. Built-in Tools: Monitoring with Cloud Logging & Cloud Monitoring, debugging issues, and rolling back versions.
6. Real-world Scenarios: Case studies on when to choose App Engine (startups, APIs, proof-of-concepts).
Basic Requirements:
1. A laptop with Python/Node/Java basics (if attendees want to try later).
2. A Google Cloud account (free tier is sufficient).
3. No advanced knowledge required — this is an entry-level introduction.
Building and Deploying Applications Seamlessly with Google App Engine
Brief Description:
This session is designed for developers and tech enthusiasts who want to understand how to take an application from local development to live production with minimal infrastructure overhead. Google App Engine abstracts away server management, scaling, and monitoring, making it ideal for small startups, student projects, and enterprises looking for agility.
What to Expect:
1. Foundations of PaaS: Understand what Platform as a Service (PaaS) is, its pros and cons, and how it compares to other compute options like Compute Engine and Cloud Run.
2. App Engine Environments: Explore the differences between Standard (quick deployment, autoscaling, cost-efficient) and Flexible (custom runtimes, more control).
3. Step-by-step Live Demo: Watch a real-world example where a Python Flask web application is deployed in real-time, starting from gcloud app deploy.
4. Scaling Explained: Learn how App Engine scales from zero to millions of requests automatically and what quotas/free tier are available.
5. Built-in Tools: Monitoring with Cloud Logging & Cloud Monitoring, debugging issues, and rolling back versions.
6. Real-world Scenarios: Case studies on when to choose App Engine (startups, APIs, proof-of-concepts).
Basic Requirements:
A laptop with Python/Node/Java basics (if attendees want to try later).
A Google Cloud account (free tier is sufficient).
No advanced knowledge required — this is an entry-level introduction.
Scaling Applications with Kubernetes: Load Balancing and Autohealing on GKE
Brief Description:
Applications in the cloud need to be resilient and capable of scaling up or down seamlessly based on user demand. In this session, we’ll explore how Kubernetes and Google Kubernetes Engine (GKE) simplify application scaling through load balancing and autohealing. You’ll learn how to build fault-tolerant systems that recover automatically from failures while efficiently distributing traffic across replicas.
What to Expect:
1. A step-by-step walkthrough of horizontal pod autoscaling (HPA) in Kubernetes.
2. How GKE load balancers work to distribute traffic across nodes and pods.
3. An introduction to readiness and liveness probes to keep your apps healthy.
4. Hands-on demonstration of autohealing in action (a failing pod being replaced automatically).
5. Best practices for optimizing workloads for performance and cost.
Basic Requirements:
1. Familiarity with containers and Kubernetes basics (pods, deployments, services).
2. A GCP account with billing enabled.
3. Installed tools: gcloud CLI, kubectl, and optionally Cloud Shell Editor.
4. Prior exposure to GKE clusters (creating one, deploying a simple app) will be helpful.
Simplifying Cloud Management: A Beginner's Guide to Infrastructure as Code with Terraform on Google
Welcome to an exciting journey into the world of Infrastructure as Code (IaC)—where managing cloud infrastructure becomes as easy as writing code! In this session, we’ll introduce you to the concept of IaC and show you how to use Terraform to take control of your Google Cloud resources in a way that’s simple, repeatable, and totally stress-free.
Have you ever found it tedious or confusing to manually create and configure cloud resources? Terraform is here to help! It allows you to define your cloud infrastructure with easy-to-write scripts, so instead of clicking around the Google Cloud console, you can automate the entire process with just a few lines of code. Imagine spinning up a virtual machine or deploying a database with one command—no more headaches or repetitive tasks!
We’ll guide you through creating your first Terraform configuration step-by-step. You’ll learn how to build, modify, and manage cloud infrastructure with confidence, all while getting hands-on experience along the way. And the best part? Terraform isn’t just about making things easier—it’s about automating deployments, ensuring consistency, and saving you a ton of time.
By the end of this session, you’ll understand the basics of Terraform and be ready to automate your Google Cloud infrastructure like a pro. Whether you’re new to cloud or just curious about how to make your cloud management smarter and faster, this session will show you how fun and empowering IaC can be!
Deploying AI Workloads on Google Kubernetes Engine (GKE)
In this session, we’re going to dive into the exciting world of running AI/ML workloads on Google Kubernetes Engine (GKE)—and trust me, it's not as complex as it sounds! Whether you're new to Kubernetes or just curious about how AI models can be deployed in the cloud, this session is designed to give you a hands-on, beginner-friendly introduction to both.
We’ll start by breaking down the basics of Kubernetes, giving you a clear understanding of what it is and how it works. Think of Kubernetes as the ultimate conductor for your cloud infrastructure, orchestrating all the moving parts so your AI workloads can perform flawlessly.
From there, we'll get practical by containerizing a simple AI/ML model—yup, we’re putting that model into a neat little box (or rather, a Docker container) so it can be deployed and run efficiently in a GKE cluster. Don’t worry if that sounds a bit intimidating; we’ll guide you through the steps, making sure everything’s easy to follow and fun to do.
Finally, we’ll bring it all together by deploying our AI model on GKE, showing you how Kubernetes can handle these workloads at scale, with minimal fuss. By the end, you’ll walk away with foundational knowledge of running AI workloads in the cloud, and who knows, maybe you'll be inspired to deploy your own AI projects in no time!
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Mwiine Daniel
Cloud Engineer | IT Systems Admin
Kampala, Uganda
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