Two weeks ago, a blog entitled Towards Machine Learning in Networking: Benefits Begin Now discussed machine learning in networking, and was based on a podcast given on the same topic. It was fun to have some discussion about what the next steps are, and how close we may be to networks that “machine learn” (ML) in the fullest spirit of AI.
The three most important words in the title of the above-referenced article are Towards, Benefits, and Now. Even the first steps you take towards collating and acting on network-provided information lead to operational improvements. I’ll explain why here, by taking a closer look at:
- The questions we ask of networks
- The data we collect to answer those questions
- How we can use visibility into this data as a “run time model” to confidently automate the network and other IT operations
- How Brocade’s visibility portfolio assists in transforming collected data into actionable analytics
First, let’s look at the questions being asked of data center networks:
- Why are these interfaces losing packets?
- Why is my Internet connection intermittent?
- Are the virtual network slices (VLANs, subnetworks) truly segregated and not vulnerable to broadcast storms?
- And, conversely, do subnetworks have ways to communicate when they need to?
Moreover, networks support users, applications, devices, access to backend systems, cloud services, etc. This is their reason for being. So related questions include:
- Are my users free from attacks? Even ones they “bring on themselves” (by being phished, for instance)?
- What about other endpoints, such as hosts, servers or applications?
- Can network data help identify ideal workload placement?
- Can reconfiguration optimize application performance?
The answers to these questions are in the data that networks themselves generate.
The Primacy of Collection
In order to understand the data center network and determine the best ways to improve its maintainability, you need to collect information. For instance, moving down the stack from the application to the hardware, you can gather information on traffic, topology, workloads, and devices (Table 1).
Table 1: Collectable Data to be Mined for Intelligent Automation
|Function or Object||Examples|
|Application Workloads||Workload identification – mapping virtual machines or software containers to servers and users|
|Control (Routing, Switching)||Interior (OSPF) and exterior (BGP) protocol state, as well as MPLS labels, multicast information, packet filters, etc.|
|Traffic (Data Plane)||sFlow, NetFlow, IPFIX, other SNMP MIB information such as interface counters|
|Device Inventory (Packet, Optical)||Chassis or fixed platforms, interface cards, optics, servers, etc.|
Collecting and storing this information, and being able to update it by executing a workflow is great. But each of these rows represents an individual view into the network, and any one by itself is quite limited.
This is not surprising because networks were not originally designed to provide actionable intelligence. The several decades of ping and traceroute being the main arrows in the network engineer’s quiver are a testament to this.
So we have correlated the gathered information into an abstracted view of the network in order to be able to automate with confidence.
The Network as Program; Automation as Compiler
The goal is to make things better by taking the network–the artifacts we have collected–and organizing them into a program. How could the entities in Table 1 comprise a program? They do not necessarily resemble code.
However, it doesn’t take too much imagination to see how they might. And in fact, it’s a norm for public cloud providers to treat infrastructure as code.
Furthermore, Brocade works with customers to create similar solutions suited to individual needs. These are later generalized into workflows and ultimately into automation suites and SDN applications.
The inputs and outputs to the “program” will be packets to and from every edge (Figure 1).
Figure 1: Inputs and Outputs to/from a “Network Program”
Packets (in the green arrows) will be:
- Generated by endpoints (users or applications)
- Traverse the “program” based on forwarding and filtering rules
- Physically make their ways as “flows”
- Across devices and cables
If the network is a program, the automation system (such as BWC or the Flow Optimizer) can be treated as a compiler, which processes the network as source code, and then can pass parameters into it in order to fix problems such as broken links or latency issues. Similarly, though with somewhat more difficulty, the “compiler” can find DDoS flows or identify threats.
And a very versatile “compiler” can also port outputs into systems in other domains, such as compute, storage, security, or applications.
How Does Brocade’s Visibility Portfolio Help?
Brocade focuses on hardware and software optimized for agility across all layers of the data center stack. Brocade Workflow Composer (BWC) automates the network lifecycle and integrates across IT domains for end-to-end workflow automation allowing enterprises to accelerate services delivery and improve availability.
In part, BWC accomplishes this by relying on actionable analytics, provided via data collected through the Insight Architecture and Visibility Services for pervasive network visibility that can be integrated with third-party analytics applications to improve SLAs.
Together, these capabilities deliver intelligent automation and dynamic remediation.
Call to Action
As we move towards more intelligent networks, and eventually those that can teach themselves to learn how to better provision and remediate themselves, there are many benefits that we will see at every step along the way.
To start now, you should look for solutions that provide intelligent, cross-domain automation, pervasive visibility, real-time analytics, and programmable platforms purpose-built for all places in the data center network.
Follow the links above or optionally consult the following videos for more insight into the importance of network visibility:
- The Routing Solution for the Digital Era: provides an example of the role of Splunk for analytics correlation
- Visibility with the Insight Architecture: discussed the use of TCPDump and Wireshark in the Guest VM of SLX platforms
Also, the following blogs from our community provide concrete examples of application or network remediation using visibility and automation:
- Visibility and Automation in Concert
- Using Visibility and Automation Together
- Unified Visibility Across the IT Stack
And as always, contact your Brocade Sales or SE representative for more information.