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Network Automation

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.

Simple NAPALM Use – A Python based abstraction layer multivendor support capable. Part of screen scraping solution.

Ansible ConfigMgmt / Jinja2 Templates – Part of a CLI automation system solution which can be called sophisticated screen scraping. via SSH. No on-device agent or service.

Salt / NAPALM Logs – Event driven network automation. This is also a CLI automation solution and can be part of screen scraping from network device perspective. Event driven by NAPALM logs.

Netconf or Restconf with YANG – Connectivity is via Netconf/Restconf (JSON/XML) while configuration is via YANG data modeling available on device (which is a service on device).  Not screen scraping or CLI automation as YANG is a data modeling language providing service and can be used to extract and push state at device.

SDN based Cisco ACI like: Northbound Rest API on APIC controller and Southbound OpFlex with an OpFlex agent on device. On device Policy Element abstraction service.

Good reference links for exploring of the above:

Ansible + Jinja2 Option:

https://networkotaku.wordpress.com/2017/10/24/network-configuration-templates-with-ansible-and-jinja2/

Salt + NAPALM Abstraction Option:

https://ripe76.ripe.net/presentations/17-RIPE76_-Event-driven-network-automation-and-orchestration.pdf

https://mirceaulinic.net/2017-10-19-event-driven-network-automation/

https://my.ipspace.net/bin/list?id=xNetAut181#SALT

Links for Restconf + YANG Option:

https://networkop.co.uk/blog/2017/02/15/restconf-yang/

https://networkop.co.uk/tags/ansible-yang/

https://packetpushers.net/podcast/pq-show-116-practical-yang-network-automation/

Links for SDN Style Cisco ACI – Like:

https://wiki.opendaylight.org/view/OpFlex:Opflex_Architecture

https://www.cisco.com/c/en/us/solutions/collateral/data-center-virtualization/application-centric-infrastructure/white-paper-c11-731302.html

https://www.cisco.com/c/en/us/td/docs/switches/datacenter/aci/apic/sw/2-x/rest_cfg/2_1_x/b_Cisco_APIC_REST_API_Configuration_Guide/b_Cisco_APIC_REST_API_Configuration_Guide_chapter_01011.html

 

An automated multi-tenant data center network is an increasingly desired end goal for large and small organizations including providers. Servers that house the CPU, RAM and Hard Disk resources are serving traffic for applications they host. These servers need connectivity among themselves within the data center and also towards the outside world.

At first an organized set of CPU/RAM/HD Servers are connected to a network device. This happens in a Data Center rack and the network device is a ToR, a Top of Rack switch.  Another similar set of servers is connected to another Top of Rack network device. Multiple such sets of servers/network device pods are then linked together. The incumbent way to do this would be to make a leaf-spine Clos fabric. The layer of network devices connecting the servers are the leaf layer and the layer of network devices that is connecting these leaf nodes is the spine layer.

Hardware is thus laid out in a 2-stage or 3-stage Clos fabric and then we need to lay out a logical control plane to pass traffic. Applications on the Server CPU/RAM/HD will talk to each other within the DC which is east-west traffic or to the outside world which can be called north-south traffic.

Depending on the type of application east west traffic could be higher but north south traffic is always present.

Moving bits from a server to any other location is the networks job. These bits could be a compute hosting virtual machine’s bits or a ‘Serverless’ cloud application’s bits but they  go somewhere and are moving. They are moved by the network layer regardless of what resides on the servers.

How many layers of protocols and software are required to provide for an automated multi-tenant data center network which can connect servers, host applications and provide east-west/north-south connectivity ?

In the Networking Components blog post some basic networking components were listed out in a different construct: Network Device, Protocols, Protocol Messages, Addresses, Lookup tasks, Identity Tags, Filters & Actions, Network Over Network ( Overlay) Appended Information, Network + Network , Network Inside Network Device, Control and Data Plane.

In the Event-Driven Network Automation blog automation details were described.

The below will make some use of the networking components and event-driven network automation blog posts.

At first you need Addresses appended onto payload bits to ascertain endpoints and exchange traffic. How many layers of addresses will be required to connect the servers to each other over a fabric? In a full mesh structure the networking layer is small/direct and less addresses are required. In a Clos Leaf-Spine-Leaf fabric there needs to be multiple layers of addresses required.

A packet/frame structured bits data structure is switched across multiple nodes. In terms of Addresses Ethernet MACs are used for Layer 2 connectivity between servers NICs and ToR ports. The server could also have an IP Address of its own and be performing Layer 3 communications.

One server connected with one leaf could send an IP packet to another server connected with another leaf (Server<>Leaf<>Spine<>Leaf<>Server). As parts of the Control Plane of laying out the fabric the leaf and spine network devices will have IP addresses of their own which will speak to each other and send Control Plane Protocol Messages. What this infers is that there will be present 2 layers of IP communications. One between the network nodes themselves and one between the servers. This infers the requirement to have an IP address pushed on to another IP address in a tunnel type structure where from one network device to another (e.g. leaf to leaf via spine) the packet is routed based on Outer IP Addresses and the inner address is used by the server. Therefore some packets will require an addressing structure such as IP|Eth|IP|Eth. The IP Tunnel will span from a Leaf to another Leaf via the Spine, therefore the tunnel endpoints are at the Leaf switches. (Server-IP<encapsulation>Leaf-IP<>via Spine <>Leaf-IP<decapsulation>Server-IP)

We have multiple combinations of communications to deal with in multiple layers of the networking stack.  Leaf-Local L2, Leaf-Local L3, Leaf-Spine, Leaf-Spine-Leaf L2, Leaf-Spine-Leaf L3.  All this calls for multiple domains. A ‘Local’ Link Layer Domain, A Local Network Layer Domain, A Distant Network Layer Domain, A relatively distant Link Layer Domain. A link layer domain could be an L2 VLAN/broadcast domain or a bridge domain and a network layer domain could be a local VRF or a wider-spanning IP-in-IP domain level routing instance.

… A routed layer has IP addresses at two endpoints and an Ethernet link has MAC addresses at two end points. A virtual machine of a tenant in a server can have both an IP address and a MAC address. There could also be a single virtual machine having multiple subnets IPs behind the same MAC address ethernet link. This virtual machine is an endpoint and is this is what the network layer needs to provide connectivity to. Therefore we could say that an endpoint requires at least 2 tables at the network device it is connecting to. An IP Routing table and a MAC table. An ARP table is also required for Inter-Layer discovery. There is also the Leaf-Spine-Leaf IP-in-IP tunnel we spoke about which adds another layer of overlay Routing Table. In addition an outer IP to inner IP socket-style mapping function will be required which is another table (L4 Socket of Outer IP to Inner IP).

Discovering the places of destination-address lookup-actions happening in a network always helps discover the kind of networking happening.

So a Leaf-Local L2 frame (a server sends to another server connected to the same leaf) would be switched locally with the local bridge domain/mac table. A Leaf-Local L3 packet would be routed by the local VRF. A Leaf-Spine-Leaf Packet would be mapped to the relevant far-end leaf tunnel endpoint and a tunnel endpoint IP would be pushed on it; it would then be tunneled/IP routed across the spine to the destination leaf; the destination leaf would then look at the socket-style mapping table of the destination endpoint; it would then pass onto the final destination endpoint.

While the Leaf-Local communications can be handled within the network device by tables, mappings and local lookups, it is obvious that when crossing the spines and reaching for a far end leaf there is a need for a control plane to communicate the far end addresses and mappings. A Protocol to exchange the distant leafs addresses and mappings which establishes the control plane for traffic to be switched and routed between leafs across the spines. There is a spine in the middle and the leafs are not directly connected. A Control Plane to distribute addresses and mappings.

There is a choice here.

For this Leaf-Spine-Leaf addresses exchange & inner/outer mappings population we could use a distributed, nuke-tolerant, internet style packet layer protocol OR instead use an SDN style central controller to do the thinking and push/program the network devices with all the addresses and mappings. The devices need to be populated with far end addresses and mappings and both will achieve this goal.

Our topic is an Automated Multi-Tenant Data Center Network and the automation part of the name is supported by the SDN style.

Why ?

The reason is that any distributed, nuke-tolerant, internet style protocol inherently requires independent configurations on all networking nodes which then enable the devices to start communicating. While an SDN controller is a single configurations point which pushes the configs onto the devices. This means that from an automation standpoint you will be either automating the configurations of hundreds of devices or an SDN controller. Configuring all devices in a large data center fabric independently is difficult to automate while managing the automation of an SDN controller or even levels of SDN controllers is easier.

This Data Center will need to speak to the outside world too.

This means that there will be a border functionality which will provide L3 and L2 reachability to the outside world. i.e. Ethernet L2 connectivity; VLANS or bridge domains, extended from a server in a leaf to a border node leaf and onwards to an outside world L2 construct, say an MPLS L2VPN.

Similarly an L3 VRF extension  where a set of routes of an endpoint/server/tenant are stretched onto a border node leaf’s VRF via say MP-BGP style RD/RT mechanism where they are further extended onto an outside world MPLS L3VPN via a PE-CE routing protocol. (Tenant-Routes|VRF|MP-BGP|VRF| VRF-PE <> CE|Outside World).

Our topic also contains the word Multi-Tenant which means that in the case of L3 Multi-tenancy a legacy MPLS L3VPN style VRF/MP-BGP mechanism will be needed per tenant per VRF.

A similar mechanism is required for connecting two or multiple such large data centers between themselves. So “Endpoint<>Leaf<>Spine<>Border-Leaf<>|Infra-Link|<>Border-Leaf<>Spine<>Leaf<>Endpoint” communications are then possible. For L3 VRFs/MP-BGP can provide separation and ensure multi-tenancy for this Inter-DC comms.

When required some border leafs will obviously connect to routers which speak eBGP to the outside world. Other Autonomous Systems over Transit and Peering connections. These routers will have the global routing table and will gateways to the rest of the world. The PE-CE communications mentioned above for VRF stretching can be Static/OSPF/EIGRP/BGP.

To run this Automated Multi-Tenant Data Center lets not forget an overarching Orchestration software residing atop it providing a GUI mechanism into the wide array of options, tools, clogs and combinations to enable tenants Intra-DC, Inter-DC and outside-world communications.

Event Driven Network Automation is a term used to describe what large scale NetOps teams are doing to scale, deploy and manage networking infrastructure.

YAML data formatting and Jinja2 templating with Python glueing and executing.

Ansible/YAML and Netconf/API for configuration, execution operations.

Event Generation using SNMP/Telemetry/BGPMon.

BGPMon looks like it could be used to check up on changes in a Routed Core with BGP based Leaf-Spine Clos Fabric.

Zero Touch Provisioning – ZTP is best suited for quickly bringing up new devices.

An Orchestration-style GUI layer custom made for every domain in the network would definitely be required as well for various aspects of NetOps.

There can be human driven network automation but there can also be event driven network automation which can be termed as ‘closed loop’ with rule based actions defined by humans.

The events driven, closed loop, rule-based-actions execution layer would then be managed by humans. This layer would be evolving and to manage it there would be a requirement of necessary data structuring and scripting skills in addition to being mindful of what the impact is on the network layer (DC or WAN, both).

References:

https://mirceaulinic.net/2017-10-19-event-driven-network-automation/

https://ripe76.ripe.net/presentations/17-RIPE76_-Event-driven-network-automation-and-orchestration.pdf

Network Automation: Template Configurations with Jinja2 and YAML

https://packetpushers.net/back-journey-network-automation-introduction/

https://packetpushers.net/back-journey-network-automation-part-1-zero-touch-provisioning/

https://packetpushers.net/back-journey-network-automation-part-2-ansible/

https://www.ipspace.net/Building_Network_Automation_Solutions