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Autonomous Networks

Two edge computing specifications are present.

Facebook OCP’s CG-OpenRack-19 and LinkedIn’s Open19.

They provide for Rack Layouts, Compute, Storage and Networking.

Networking for CG-OpenRack-19 is copied below. The servers sleds in the pictures appear to be single homed as per the colors. It would be interesting find out which protocol handles the Active Active state of the multi homed Compute and Storage Sleds if that is at all present.

OpenRack-19

Given here

Open19 gives 100G bandwidth capabilities and some details are on its website.

5G’s edge ultra low latency requirements would could require edge solutions and it would be interesting to see how things play out ahead.

This also brings to mind SD-WAN because these edge racks will be at least connected in a large WAN.

Google’s B4 is one of its software defined inter data denter WAN solution. Google’s Espresso is its peering edge solution. Espresso links into B4 domain via B2. This link has the details of Espresso as shared by the Google team.

 

Google-Espresso-B4.JPG

Google is not employing an army of networking engineers to run these because they are software defined and programmed bots will probably be doing operational tasks. To operate this network there are Site Reliability Engineers though.

Here is one public job advertisement that relates as to what an SRE is expected to be like:

We have reliable infrastructure and can spin up new environments in a couple of hours. Automate everything so there is more time for exploring and learning. Foster the DevOps mindset

What are our goals?
  Internationalisation
  Deploying multiple data centers
  Deploying every 5 minutes
Requirements
  Experience with Java or JavaScript in a Dockerised environment
  Linux Engineering/Administration
  Desire for improving processes
  Have a passion and most importantly, a sense of humour
Tech Stack (you DO NOT need experience in all of these)
  Kubernetes + Docker
  Terraform + Ansible
  Linux
  Kotlin + NodeJS
  ELK stack
  AWS

This is obviously an SRE for the servers side and the application enablement side of things. If there is a large software defined edge network like Espresso and a large Edge-to-DC network like B2 and a large software defined inter-DC network like B4 you will need a different SRE.

Here is Google’s version of a Site Reliability Engineer Job.

Job description
Minimum Qualifications

BS degree in Computer Science or related technical field involving coding (e.g. physics or mathematics), or equivalent practical experience.
3 years of experience working with algorithms, data structures, complexity analysis and software design.
Experience in one or more of the following: C, C++, Java, Python, Go, Perl or Ruby.

Preferred Qualifications

Systematic problem-solving approach, coupled with effective communication skills and a sense of ownership and drive.
Interest in designing, analyzing and troubleshooting large-scale distributed systems.
Ability to debug and optimize code and automate routine tasks.

About The Job

Hope is not a strategy. Engineering solutions to design, build, and maintain efficient large-scale systems is a true strategy, and a good one.

Site Reliability Engineering (SRE) is an engineering discipline that combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google’s services—both our internally critical and our externally-visible systems—have reliability and uptime appropriate to users’ needs and a fast rate of improvement while keeping an ever-watchful eye on capacity and performance.

SRE is also a mindset and a set of engineering approaches to running better production systems—we build our own creative engineering solutions to operations problems. Much of our software development focuses on optimizing existing systems, building infrastructure and eliminating work through automation. As SREs are responsible for the big picture of how our systems relate to each other, we use a breadth of tools and approaches to solve a broad spectrum of problems. Practices such as limiting time spent on operational work, blameless postmortems and proactive identification of potential outages factor into iterative improvement that is key to both product quality and interesting and dynamic day-to-day work.

We can see that Google’s SRE Job Ad is all software along with large scale distributed systems requirements.

Now if we note this extract from the Wikipedia SD-WAN article:

“With a global view of network status, a controller that manages SD-WAN can perform careful and adaptive traffic engineering by assigning new transfer requests according to current usage of resources (links). For example, this can be achieved by performing central calculation of transmission rates at the controller and rate-limiting at the senders (end-points) according to such rates”

and we also note this extract:

“As there is no standard algorithm for SD-WAN controllers, device manufacturers each use their own proprietary algorithm in the transmission of data. These algorithms determine which traffic to direct over which link and when to switch traffic from one link to another. Given the breadth of options available in relation to both software and hardware SD-WAN control solutions, it’s imperative they be tested and validated under real-world conditions within a lab setting prior to deployment.”

We see Algorithms.

Its clear that there are different algorithms running these Software Defined networks (Google’s software defined Espresso, B2, B4 and Jupiter). These algorithms automate, kick in and optimize. Google becomes a large scale distributed system with various algorithms here and there. While Software Architects and Software Engineers will have developed these algorithmic nodes and programmed them into network devices/servers an SRE is the human who will operate the system. A team of SREs.

One aspect of Networking protocols is that they are for a multi-vendor, multi-enterprise and multi-domain environments. They provide simple consensus to connect two or more different network devices.

To take a merchant silicon network device like OCP’s Wedge and OCP style servers and make one large network like Google out of it will require software engineering to remake the NOS (Network Operating Systems) part at least. There will be atleast a Meta-NOS, somewhat running on top of a typical NOS which would handle the SDN – software defined algorithms. In addition to the SDN controllers talking to this Meta-NOS. Multiple layers of SDN controllers will be talking to each other and you can call this a network protocol or an SDN algorithm but it will be part of distributed systems software architecture and it will be programmed in place by software engineers.

Large Scale Distributed System on Merchant Silicon Hardware – Software Defined Meta-NOS – SDN Controllers – Hierarchical SDN Controllers – Algorithms.

Sounds like a Program Management task instead of PMP scale Engineering Project Management task. You will need Mathematicians to sit with Network Architects, Distributed Systems Architects and Software Architects. The Mathematicians will do give the algorithms. They will be important too.

Fun times.

Terabit scale networking requires better Consensus.

Autonomous Networks and Autonomic Networking can be renamed as solving Consensus Dynamics.

Wikipedia States (Nov’ 2018):

“Consensus dynamics or agreement dynamics is an area of research lying at the intersection of systems theory and graph theory. A major topic of investigation is the agreement or consensus problem in multi-agent systems that concerns processes by which a collection of interacting agents achieve a common goal. ”

To note again it is an ‘intersection of systems theory and graph theory’.

Lets not forget that mathematically communications networks are Graphs. An OSPF/ISIS network is a weighted directed graph where the costs & metrics are the weights, the network devices are vertices and the ethernet L2 links are directed edges.

Furthermore, to note again that ‘ a collection of interacting agents achieve a common goal’. In networks the common goal can be to enable end to end, host to host connectivity over a vast network. TCP and UDP.

Interesting times ahead for Terabit scale networks. Keeps the fun alive in network engineering.

References:

https://en.wikipedia.org/wiki/Consensus_dynamics

https://cs.fit.edu/~msilaghi/papers/EncyclopAI07.final.pdf