Global Mesh Computing


In today’s rapidly evolving digital landscape, traditional paradigms of system architecture and security are being put to the test. The demand for more flexible, resilient, and scalable systems is growing, prompting us to reconsider long-standing concepts and methodologies.

The digital world we are moving towards requires an environment where the current perimeter paradigm undergoes a profound transformation. The rigidity of conventional systems needs to give way to a more dynamic, adaptive model. This model would be defined by loosely coupled nodes using the publish-subscribe model, with different versions coexisting synchronously, mirroring the principles of technologies like Bittorrent with its millions of nodes.

In this emerging landscape, stateless workloads are becoming the norm, reducing the need for rigid, inflexible clustering. As a result, we are moving towards a world where consistency isn’t a universal attribute but something that can be customized to each workload’s specific requirements.

This custom approach to consistency can be accomplished with the help of workload sidecars. Operating in parallel with the main workload, sidecars offer the flexibility to manage different types of consistency for different workloads. For stateless workloads, they can ensure eventual consistency, promoting a more distributed and resilient approach to handling data. For stateful workloads, they can enforce strong consistency, ensuring that all replicas of data are synchronized, thus maintaining data integrity and reliability.

Most importantly, this approach eradicates the need to limit scalability. The sidecar-based model allows to scale without compromising consistency, thus preserving integrity and performance while catering to the diverse needs of various workloads.

Security is also a critical aspect that needs reconsideration. By incorporating workload identity into userland sockets—a technique known as slirp4netns—security is strengthened through mutual authentication and continuous authorization of workload-to-workload communications. This method strictly adheres to zero-trust principles and provides a level of security and traceability that traditional approaches cannot achieve.

The roles of traditional schedulers are also evolving from centralized entities into decentralized, topic-based algorithms. Likewise, APIs need to adapt to ensure that legacy workload manifests can be reused, guaranteeing compatibility with existing ecosystems. Such adjustments will ease the transition from the current architecture to the more dynamic, adaptable model we envision.

However, the vision of the future is not without its challenges. Shifting from a centralized scheduler to a decentralized, topic-based algorithm will require considerable changes in how we manage and deploy systems. The complexity of creating a system that can adapt to changes proactively will be substantial. Moreover, the practicality of implementing such a system on a large scale remains to be seen. Nonetheless, these challenges are not insurmountable, and the potential benefits could be transformative.

This vision may seem radical today, but it’s precisely these kinds of bold ideas that drive innovation and reshape the world. Innovation happens when we challenge established norms. As we move forward, it’s crucial to foster discussions about the future of system architecture and security, pushing the boundaries of what we currently believe is possible.