k3sup VS cppq

• Simplicity
  k3sup simplifies the process of setting up a lightweight Kubernetes cluster by providing an easy-to-use CLI tool, reducing the manual effort involved.
• Speed
  It significantly speeds up the installation of k3s by automating many of the steps, allowing users to get a cluster up and running quickly.
• Portability
  k3sup is compatible with various environments, including Raspberry Pi, virtual machines, and cloud services, offering flexibility in deployment.
• No Overhead
  Since k3sup installs k3s without any additional overhead, it maintains the lightweight nature of the k3s distribution.
• Open Source
  Being open source, k3sup allows developers to contribute to its development and adapt the source code to suit their specific needs.

Possible disadvantages

• Limited to k3s
  k3sup is specifically designed for k3s and may not be suitable for users who need to work with larger Kubernetes distributions or have specific deployment requirements not covered by k3s.
• Basic Features
  While k3sup simplifies setup, it might lack some of the advanced features that more robust, full-featured Kubernetes management tools provide.
• Community Support
  As a smaller, community-driven project, k3sup may not offer the same level of support and resources as more established Kubernetes tools.
• Limited Automation
  Although k3sup automates the installation of k3s, further configuration and management of the cluster after setup may require additional scripting or manual intervention.
• Dependency on SSH
  k3sup relies on SSH for remote connections, which means it requires proper SSH setup and permissions, potentially complicating configurations for some users.

• Lightweight C++ implementation
  cppq is written in modern C++ and designed to be a minimal, efficient task queue library, making it a good fit for performance-sensitive applications where the overhead of scripting language runtimes is undesirable.
• Redis-backed reliability
  Built on top of Redis as the message broker, cppq benefits from Redis's persistence, atomic operations, and wide adoption, giving the queue system durability and the ability to survive process restarts.
• Inspired by proven design (asynq)
  The library's architecture mirrors the popular Go asynq task queue, so it inherits a well-thought-out API design for task enqueueing, retries, and worker processing patterns that have already been validated in production systems.
• Native integration for C++ projects
  For teams already working in a C++ codebase, cppq allows adding background job processing without needing to introduce a separate service written in another language (like Go or Python), simplifying the technology stack.
• Open source and inspectable
  Being open source on GitHub, developers can review the source code, modify it for custom needs, and contribute improvements, which offers transparency not available with closed-source queueing solutions.

Possible disadvantages

• Limited maturity and battle-testing
  Compared to established task queue libraries like Sidekiq, Celery, or asynq itself, cppq is a newer and smaller project with less real-world production usage, which may translate into undiscovered bugs or edge cases.
• Smaller community and ecosystem
  Because it has far fewer users and contributors than mainstream task queue systems, finding community support, third-party tutorials, or pre-built integrations is more difficult.
• Documentation gaps
  As a smaller project, cppq may have less comprehensive documentation compared to major task queue frameworks, requiring developers to read source code directly to understand advanced features or edge-case behaviors.
• C++ build and dependency complexity
  Using cppq requires managing C++ build toolchains and dependencies (such as a Redis client library), which can be more cumbersome than installing a package via pip or npm in other ecosystems.
• Fewer built-in features and tooling
  cppq likely lacks the extensive ecosystem tooling of more mature queues, such as web-based monitoring dashboards, extensive metrics/observability integrations, or advanced scheduling features found in more established solutions.

No analysis of k3sup yet.

I - Pi & Kubernetes with k3s, k3sup, arkade and OpenFaaS

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• How do you archive your side hobby projects?

  I recommend learning docker first, then pick a vps host from vpsbenchmarks, then use k3sup to deploy a kubernetes cluster on that, then follow a getting-started kubernetes tutorial from there. You'll also want to buy a domain name with... Source: over 3 years ago

• What do you use as a kubernetes base?

  I just installed k3s yesterday using k3sup on 6 VMs (3 masters, 3 workers) each with 2GB RAM ( limited by the actual RAM on hardware, for now ) with Ubuntu 22.04 as the base OS. Source: over 3 years ago

• What's a cheap way to setup your own Kubernetes cluster locally or remote?

  k3s installed with k3sup, longhorn for storage, kube-vip for API VIP, and MetalLB for service load balancer using local subnet, and of course Rancher. Source: over 3 years ago

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Tracking cppq since Nov 2022.