DEV Community: Robert Coffie

[Boost]

Robert Coffie — Sun, 05 Oct 2025 14:12:59 +0000

Introduction to Live Streaming Architecture

Robert Coffie ・ Oct 5

#infrastructureascode #cloud #kafka #aws

Introduction to Live Streaming Architecture

Robert Coffie — Sun, 05 Oct 2025 14:12:33 +0000

Live streaming architecture is the backbone that makes it possible to deliver real-time video and audio from a broadcaster to viewers around the world. Behind every smooth live stream lies a carefully designed system of components that capture, process, distribute, and play media across devices and networks.

This blog post will take you on a journey through the complete live streaming workflow. We'll pull back the curtain to explore the five core components that make it all possible, following the path of the stream:

Input Source/Capture→Encoder→Media Server→CDN→Player/Audience
By the end of this article, you won't just know what live streaming is, but you'll have a technical understanding of how it works, from the moment the camera captures a scene to the millisecond it appears on your screen.

1. The Starting Line: Input Source and Capture.

Every live stream starts with capturing the source—the raw video and audio that make up the broadcast. Without a reliable way to bring these signals into your streaming setup, there’s nothing to encode, process, or deliver. This is where capture devices come in.

What Is a Capture Device?
A capture device is usually a piece of hardware (though sometimes software can serve the same role) that takes video and audio from an external source—such as a gaming console, professional camera, or even another computer—and makes it usable for your streaming workflow. Once connected, the device feeds that signal into your PC or directly to the internet so you can broadcast or record it.

Video Capture
On the video side, cameras are the most common input sources. Depending on the setup, this could be:

A broadcast camera for professional production.
A webcam for casual streaming.
A smartphone camera for quick, mobile broadcasting.

Cameras capture a sequence of images, or frames, at a certain rate (for example, 30 frames per second). These frames form the moving picture you see in a live stream.

Audio Capture
For audio, microphones do the heavy lifting. They convert sound waves—your voice, music, or any ambient noise—into digital audio samples. These samples are then synced with the video to create the full streaming experience.

2. Compressing the Stream: The Encoder.

Once your video and audio have been captured, the next critical step in live streaming is encoding. Raw media files are massive and uncompressed, which makes them impossible to deliver smoothly across the internet. This is where a media encoder comes into play.

What Is an Encoder?
An encoder is a tool—either hardware-based or software-based—that converts raw video and audio into a compressed digital format optimized for streaming. By shrinking file sizes without destroying quality, encoders make it possible for viewers to watch your live stream in real time, without endless buffering.

Most encoders output in streaming-friendly codecs such as H.264 (AVC) or H.265 (HEVC), which balance quality and efficiency.

Types of Encoders

Software Encoders
Software encoders are applications you install on your computer. They use your machine’s CPU or GPU to process video and audio, giving you flexibility and customization options. Software encoders are ideal for creators who want control over scenes, overlays, alerts, and transitions.
Popular examples:

OBS Studio
Streamlabs
vMix
Wirecast
XSplit

Hardware Encoders
Hardware encoders are dedicated physical devices built solely for the purpose of encoding. Because they don’t rely on your PC’s resources, they’re more reliable for professional workflows and reduce performance strain on gaming or production machines. These devices often connect directly to your camera or capture card and stream straight to your platform.

Popular examples:

Teradek Vidiu
LiveU Solo
AJA HELO
Elgato 4K60 S+

3. The Central Hub: The Media Server (Origin).

In the live streaming pipeline, the media server is the crucial middleman that makes it all work. While capture devices and encoders prepare the stream, the media server ensures that the content is processed, adapted, and delivered smoothly to audiences worldwide.

Think of it as the traffic controller of live streaming—it receives incoming video, reshapes it for different needs, and distributes it in the right formats to every viewer, no matter their device or internet speed.

Key Functions of a Media Server

Ingest
The first job of a media server is to receive the encoded stream from the source. This step, called ingest, is often carried out using protocols such as RTMP (Real-Time Messaging Protocol) or SRT (Secure Reliable Transport). Once ingested, the media server prepares the stream for further processing.

Transcoding
Not every viewer has the same device, screen resolution, or internet connection. That’s where transcoding comes in. The media server takes a single encoded video and converts it into multiple versions—for example, 1080p, 720p, and 480p. This ensures that whether someone is watching on a high-speed desktop connection or a slower mobile network, the stream adapts to their conditions.

Why Media Servers Matter
Without a media server, a live stream would be a single, rigid feed—too large for some viewers, incompatible with others. The media server bridges this gap, transforming one raw input into multiple optimized outputs, ready for large-scale distribution over CDNs and ultimately into streaming players.

In Short:
The media server is the backbone of live streaming, taking in your encoded feed, shaping it into adaptable formats, and sending it out so every viewer can watch smoothly.

4. Scaling Globally: The Content Delivery Network (CDN).

Once your live stream has been captured, encoded, and processed by the media server, the next challenge is getting it to viewers around the world—quickly and reliably. This is where a Content Delivery Network (CDN) steps in.

What Is a CDN?
A CDN is a globally distributed network of servers, often called edge servers or points of presence (PoPs). Instead of relying on a single central server to deliver your stream, CDNs store or cache copies of video segments on these edge servers located across different regions.
When a viewer hits play, the CDN delivers the stream from the server closest to their location. This reduces buffering, lowers latency, and ensures consistent quality—even when thousands or millions of people are tuning in at once.

How CDNs Work in Streaming

The media server acts as the origin, preparing video segments.
The CDN replicates those segments across its global network.
Viewers are automatically connected to their nearest edge server, rather than a distant origin server.

This design keeps streams fast, reliable, and scalable—whether your audience is local or worldwide.

Why CDNs Matter
Without a CDN, every viewer would need to pull video directly from the origin server, creating bottlenecks and massive delays. With a CDN, streams are distributed intelligently, making live content available on-demand at scale with minimal interruption.

In shot:
CDNs are the delivery backbone of live streaming, ensuring that no matter where your audience is located, they receive the broadcast smoothly and without lag.

5. The Final Mile: The Player and the Audience.

Every live stream ends where it matters most—with the viewer. After passing through capture devices, encoders, media servers, and CDNs, the video finally reaches its destination: the player.

What Is a Player?

A player is the end-user application—either a standalone app or an embedded component in a website or platform—that receives, decodes, and displays the live stream on a viewer’s device. Whether it’s a browser, mobile app, smart TV, or gaming console, the player is the interface between the streaming system and the audience.

The Final Step in the Chain

Players are responsible for turning compressed digital streams back into smooth video and audio playback. They also manage critical functions like:

Decoding → converting formats like H.264 or H.265 into watchable video.
Buffering → ensuring smooth playback even if network conditions fluctuate.
Adaptive Bitrate Streaming (ABR) → automatically adjusting quality (1080p, 720p, 480p) to match a viewer’s internet speed.
User controls → play, pause, volume, captions, and sometimes interactivity like chat or reactions.

Why Players Matter

The player is the audience’s window into your stream. No matter how advanced the backend architecture is, if the player fails to deliver a seamless, responsive experience, the viewer will notice. A reliable player ensures that your live stream isn’t just delivered—but also enjoyed.

The player is the final and most visible stage of the live streaming pipeline. It’s where all the behind-the-scenes technology comes together to bring real-time video to life for audiences around the world.

Wrapping Up: The Live Streaming Pipeline

Live streaming might feel instant to viewers, but behind the scenes, it relies on a series of steps working seamlessly together:

Capture – Cameras and microphones record raw video and audio, often passed through capture devices.
Encoding – Encoders compress this raw data into streaming-friendly formats like H.264 or H.265.
Media Server – The stream is ingested, processed, and transcoded into multiple versions to suit different devices and internet speeds.
CDN (Content Delivery Network) – A global network of edge servers distributes the stream efficiently to viewers around the world.
Player – Finally, the player on a user’s device decodes and displays the stream, turning all the behind-the-scenes technology into a smooth viewing experience.

In short:
live streaming architecture is a chain where each link matters. From capture to playback, every stage plays a role in ensuring that what the broadcaster sends is delivered to the audience reliably, in real time, and in the best quality possible.

Multipass Unlocked: Effortlessly Spin Up Ubuntu VMs in Seconds!

Robert Coffie — Thu, 13 Mar 2025 03:02:19 +0000

I recently stumbled upon Multipass, an open-source project by Canonical, and I'm absolutely smitten! As a developer who loves tinkering with Linux instances, particularly when learning Ansible, this tool has been a breath of fresh air.

Multipass allows me to create and manage multiple Ubuntu instances right within my native shell, all without the need for virtual machines or complex setup processes. It's like having a mini-cloud on my machine!

For example, let's say I wanted to learn how to use Ansible to automate system configuration across multiple hosts. I can spin up three Ubuntu instances in seconds using Multipass:

$ multipass create -n instance1 -i amd64 -c 2048 -m 4096
$ multipass create -n instance2 -i amd64 -c 2048 -m 4096
$ multipass create -n instance3 -i amd64 -c 2048 -m 4096

Once they're up and running, I can SSH into each instance with a single command:

$ ssh user@<instance1-ip-address>

This simplicity not only saves time but also makes the learning process more enjoyable!
If you're a developer or Linux enthusiast looking to streamline your workflow, give Multipass a try and let us know what you think!
Link to the documentation: Multipass Documentation

Unveiling the Magic: How Terraform Works Under the Hood to Manage Your Infrastructure as Code

Robert Coffie — Sat, 22 Feb 2025 15:08:47 +0000

I talked about Infrastructure as Code (IaC) in my last piece. Since I am the project manager, team lead, and junior developer on my portfolio project, I thoroughly examined it and chose to use the IaC approach to build each side project. Since I do the majority of my deployments in Azure, this led me to explore some of the infrastructure as code tools like Azure Resource Manager and Azure Biceps. Yes, given how common AWS is, some people utilize Azure like me.

Biceps became my go-to IaC tool until I discovered Terraform. In this post, I will explain how Terraform works under the hood to provision infrastructure.

What is Terraform

Terraform is an open-source infrastructure as code tool developed by HashiCorp for customizing and deploying your infrastructure. Terraform allows you to describe both cloud and on-premises resources in human-readable configuration files that you can version, reuse, and share.

Why Terraform

I loved Azure Biceps, but the major reasons I chose Terraform were multi-cloud capabilities, declarative configuration, and a large community.

Multi-Cloud Support
Terraform works with AWS, Azure, Google Cloud, and many other providers.
Facilitates hybrid and multi-cloud deployments.
Declarative Configuration
Uses a declarative approach where you define the desired state, and Terraform ensures infrastructure matches it. This reduces complexity to imperative provisioning tools.
Large Community & Ecosystem
Terraform has Extensive community support and a growing ecosystem of providers and modules, with an
Active development and contributions from HashiCorp.

How Terraform Works

Under the hood, Terraform works by following a structured process to deploy infrastructure based on the configuration files you write. These files describe the desired state of your infrastructure, and Terraform ensures that your actual infrastructure matches this state.

Let’s break down how Terraform works under the hood to deploy infrastructure:

To interact with different cloud platforms or services, Terraform uses providers. Providers are plugins that act as a bridge between Terraform and the APIs of cloud platforms or services.

Providers are responsible for understanding API interactions and exposing resources for a specific cloud or service. Each provider corresponds to a cloud platform (e.g., AWS, Azure, GCP) or a service (e.g., Kubernetes, GitHub).
When you write your configuration file, the Terraform form provider communicates with the cloud providers to which you deploy your resources by translating it into a language the Cloud API understands to create, update, delete, and manage infrastructure resources.

The Terraform community have already written thousands of providers to manage many different types of resources and services. You can find all publicly available providers on the Terraform Registry, including Amazon Web Services (AWS), Azure, Google Cloud Platform (GCP), Kubernetes, Helm, GitHub, Splunk, DataDog, and many more.

Examples of Terraform Providers:

Azure:
- Proivder: azurerm
- Used to manage Azure resources like virtual machines, storage accounts, and networks.
- Example:

provider "azurerm" {
  features {}
}

resource "azurerm_resource_group" "example" {
  name     = "example-resources"
  location = "East US"
}

AWS:
- Provider: aws
- Used to manage AWS resources like EC2 instances, S3 buckets, and IAM roles.
- Example:

provider "aws" {
  region = "us-east-1"
}

resource "aws_instance" "example" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"
}

Google Cloud Provider(GCP):
- Provider: google
- Used to manage GCP resources like Compute Engine, Cloud Storage, and BigQuery.
- Example:

provider "google" {
  project = "my-gcp-project"
  region  = "us-central1"
}

resource "google_storage_bucket" "example" {
  name     = "example-bucket"
  location = "US"
}

Terraform providers are plugins that enable communication with cloud platforms or services.
Each provider is configured with credentials and settings specific to the platform.
Examples include azurerm for Azure, aws for AWS, google for GCP, and
others like Kubernetes and GitHub.

By using providers, Terraform abstracts the complexity of interacting with different cloud APIs, making it easier to manage multi-cloud or hybrid infrastructure.

Key Terraform Actions Under the Hood:

1.Initialization (terraform init)
Providers and Modules: When you first initialize your Terraform project using terraform init, Terraform Core downloads the necessary provider plugins for the specific services you want to use (e.g., AWS, Azure, GCP); it downloads and installs any modules referenced in your configuration. This sets up the working directory to prepare for execution.

2.Plan (terraform plan)
State File: When you run terraform plan, Terraform compares the current state of your infrastructure (stored in the terraform.tfstate file) to the desired state defined in your configuration files.
Dependency Graph: Terraform builds a dependency graph of all resources defined in your configuration. This helps Terraform understand the correct order in which resources should be created, modified, or destroyed based on dependencies (e.g., a virtual machine needs a network to be created first).
Execution Plan: Terraform then generates an execution plan. The plan details what resources will be created, modified, or deleted, and in which order. The plan is generated by comparing your configuration against the current state of your infrastructure. The execution plan is displayed for you to review and approve.

3.Apply (terraform apply)
Resource Creation/Modification: When you run terraform apply, Terraform executes the changes outlined in the plan: Terraform communicates with the cloud providers (e.g., AWS, Azure, GCP) using the appropriate provider plugins. Each provider has its own API that Terraform interacts with. Terraform sends API requests to the cloud provider’s API to create, modify, or delete resources according to your configuration. For example, if you're creating an EC2 instance on AWS, Terraform sends a request to the AWS API to launch the instance with the desired specifications (e.g., size, region, tags).
State File Update: As resources are created or modified, Terraform updates the state file (terraform.tfstate) to reflect the actual state of the infrastructure. Terraform relies on this state file to track provisioning, ensuring consistency for future runs.
Providers’ Role: Each provider is responsible for interacting with a specific infrastructure or service, using its own API. For example, the AWS provider interacts with the AWS API to provision resources like EC2 instances, VPCs, S3 buckets, etc. The Azure provider interacts with the Azure Resource Manager (ARM) API to provision resources like virtual machines, networks, etc.
Resource Dependencies: Terraform ensures that resources are created or modified in the correct order based on their dependencies. For instance, a virtual machine depends on a network to exist before it can be created.

4.Resource Change and Idempotency
Terraform ensures idempotency, meaning that running terraform apply multiple times with the same configuration should yield the same result. If nothing has changed in your .tf files, Terraform won’t re-create the resources. It will simply confirm that the infrastructure is already in the desired state. If the configuration has changed, Terraform will calculate the minimal changes required to bring the infrastructure in sync with the new configuration and apply those changes.

Terraform Workflow

1.Write:
Write Configuration: You define your desired infrastructure state in .tf files using HCL.
Initialize Terraform (terraform init): Initializes the project and downloads necessary providers and modules.

2.Plan (terraform plan):
Terraform compares the desired state (in your configuration) with the actual state (from the state file). It creates an execution plan to show which changes will be made (create, update, or delete resources).

3.Apply (terraform apply):
Terraform sends API requests to the cloud providers (AWS, Azure, etc.) to create, update, or delete resources as defined in the plan. Terraform updates the state file to reflect the changes made to the infrastructure.

Summary

Under the hood, Terraform is a tool that manages your infrastructure by defining the desired state in configuration files, comparing it to the current state (through the state file), and then applying changes by communicating with cloud provider APIs. The process involves initialization, creating execution plans, applying changes, and updating the state file to keep infrastructure consistent across different runs. The core logic ensures that Terraform operates in a consistent, idempotent way, always aiming to bring your infrastructure to the desired state.

The IaC Revolution: How Automating Infrastructure Can Save You Time and Money

Robert Coffie — Sat, 08 Feb 2025 11:46:38 +0000

I made the decision to start diving into cloud computing around three months ago.
My curiosity led me to the term "Infrastructure as Code," or IaC.
There is always something fresh and buzzing about this tech field, so at first I assumed it was just something new that everyone was trying to get on.
I chose to board the IaC bandwagon since I was seeing so much about it whenever I read best practices.

If there's something I don't understand, I ask ChatGPT to explain it to me like a 7-year-old. When I asked ChatGPT to explain IAC to me like a 7-year-old, the response I received is seen below.

All right! Let's say you want to construct a cool spaceship out of a large box of LEGO pieces. You could simply begin assembling the pieces one at a time, but what if you eventually want to construct the same spaceship again? Remembering how you did it the first time could be challenging!
Similar to that manual, Infrastructure as Code (IaC) is used to develop computer systems in the cloud. You use things like servers, databases, and networks in place of LEGO blocks. Additionally, you write the instructions in a unique computer language (similar to a cloud recipe) rather than on paper.

As someone who finds automation fascinating, when I read ChatGPT's description, automation was the first thing that came to mind. I made up my mind that I wanted to know more about IaC.

What Infrastructure as Code (IaC)

In the simplest form, infrastructure as code is the managing and provisioning of IT infrastructure through code instead of manual processes.
This allows engineers to automate the deploying, updating, and destroying of environments rather than setting them up manually.

How Infrastructure as Code (IaC)

Resources, including servers, databases, networks, and storage, are managed using declarative or imperative setups in Infrastructure as Code (IaC). These configurations specify how resources should be produced, modified, and eliminated in an automated and repetitive manner. These configuration files can be created in Python, Java, and Go, and they can be kept under source control with commits made for every modification to the code.

Approaches to Infrastructure as Code (IaC)

Infrastructure as code (IaC) can be approached in two ways: declaratively or imperatively.

Imperative Approach

An imperative approach to Infrastructure as Code (IaC) involves writing step-by-step instructions to provision, configure, and manage infrastructure. Unlike the declarative approach, where you define the desired end state, in imperative IaC, you specify how to reach that state.

Declarative Approach

Benefits on Infrastructure as Code (IaC)

Infrastructure as Code (IaC) is a key concept in modern DevOps and cloud computing practices. Here are some of its main benefits:

Consistency and Repeatability - IaC ensures that the same configuration is applied every time an environment is created, reducing human error and ensuring consistency across different environments.
Version Control - Since infrastructure configurations are stored as code, they can be versioned just like application code. This allows teams to track changes, revert to previous versions, and understand the history of configurations.
Automation and Efficiency - IaC enables the automation of infrastructure provisioning and management. This reduces the time and effort required to set up environments, leading to increased productivity and faster deployment cycles.
Scalability - IaC allows organizations to scale their infrastructure up or down based on demand easily. By using code to define infrastructure, it's easier to replicate and scale environments.
Documentation - Infrastructure as Code serves as documentation for your infrastructure setup. The code itself provides a clear and up-to-date description of the infrastructure, making it easier for new team members to understand and for teams to troubleshoot issues.
Cost Management - By automating the provisioning and de-provisioning of resources, IaC helps manage costs more effectively. Resources can be scaled down or terminated when not needed, reducing unnecessary expenditure.
Testing and Validation - With IaC, infrastructure can be tested and validated just like application code. This allows teams to identify and fix issues before they affect production environments.
Collaboration - IaC promotes collaboration among teams by using the same tools and processes as application development. This leads to better communication and alignment between development and operations teams.
Disaster Recovery - IaC makes it easier to recover from disasters by allowing teams to recreate environments quickly and accurately. This ensures minimal downtime and faster recovery times.

IaC is crucial for organizations looking to leverage modern Cloud and DevOps practices and achieve greater agility, reliability, and efficiency in their infrastructure management.

Infrastructure as code (IaC) Tools

There are several popular Infrastructure as Code (IaC) tools that you can use to automate and manage your infrastructure. Here are some of the most commonly used ones:

Terraform - Terraform by HashiCorp is a widely used IaC tool that supports multiple cloud providers and services. It uses declarative language to define and provision infrastructure
AWS CloudFormation - AWS CloudFormation is an IaC service provided by Amazon Web Services. It allows you to define and manage AWS infrastructure using JSON or YAML templates.
Azure Resource Manager (ARM) - Azure Resource Manager (ARM) is a service by Microsoft Azure that enables you to define and manage Azure resources using templates written in JSON.
Google Cloud Deployment Manager - Google Cloud Deployment Manager allows you to define and manage Google Cloud resources using YAML, Python, or Jinja2 templates.
Ansible - Ansible by Red Hat is a configuration management and automation tool that can also be used for IaC. It uses YAML files called playbooks to define the desired state of the infrastructure.
Chef -Chef is a configuration management tool that uses a Ruby-based DSL to define infrastructure as code. It automates the configuration, deployment, and management of infrastructure.
Puppet - Puppet is another configuration management tool that uses declarative language to define the desired state of the infrastructure. It automates the provisioning and management of resources.
Pulumi Pulumi is a modern IaC tool that allows you to define infrastructure using general-purpose programming languages like TypeScript, Python, and Go. It supports multiple cloud providers.
Kubernetes YAML - For containerized applications, Kubernetes uses YAML files to define and manage the desired state of the cluster and its resources.

These tools have their strengths and are suited for different use cases. The choice of tool often depends on the specific requirements of your project and the cloud provider you are using.

Infrastructure as Code (IaC): Why Use It?

Infrastructure as Code (IaC) is a game-changer for cloud computing, DevOps teams, and organizations as a whole. For cloud environments, IaC ensures scalable, consistent, and automated infrastructure management, reducing manual configurations and deployment errors. DevOps teams benefit from improved collaboration, faster deployments, and seamless CI/CD integration. Engineers gain efficiency by defining infrastructure through code, enabling rapid provisioning and minimizing operational overhead. For companies, IaC leads to cost savings, enhanced security, and greater agility in responding to business needs. By adopting IaC, organizations can future-proof their infrastructure, streamline operations, and drive innovation in an increasingly digital world.