Exoscale VS cppq

• Data Privacy
  Exoscale is based in Switzerland, which has stringent data protection and privacy laws that benefit users seeking enhanced data privacy.
• European Presence
  Provides multiple data centers across Europe, which is beneficial for businesses needing to comply with data residency requirements.
• Scalability
  Offers scalable cloud solutions suitable for rapidly growing businesses or for handling variable workloads.
• User-Friendly Interface
  Designed with an intuitive interface that makes managing and deploying cloud resources easier for users.
• Performance
  Exoscale is known for high performance and reliability, which is crucial for business-critical applications.

• 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.

Exoscale - Automation Introduction

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• A developer's guide to deploy applications on Kubernetes

  IMPORTANT: I use the Scalable Kubernetes Service (SKS) from Exoscale (Switzerland) in the tutorial, but if you don't want to spend money on this, you can follow along with a local k3d cluster. Simply follow the instructions at the bottom... - Source: dev.to / over 3 years ago

• March Cloud Native Romandie Meetup

  Next Pierre-Yves Ritschard and Mathieu Corbin from Exoscale presented SKS, a Kubernetes as-a-Service, operating the user’s cluster on their behalf and taking care of the underlying infrastructure. - Source: dev.to / over 5 years ago

Tracking cppq since Nov 2022.