The workforce changed practically overnight last March, as millions of professionals quickly shifted to working from home. The global health crisis accelerated some trends that were already underway, and it looks like many of the changes are here to stay. In a recent Gartner survey, 82% of business leaders said they plan to maintain a partial work-from-home structure even after COVID-19 is no longer a threat.
For IT operations teams, that means improving visibility at the edge of networks is even more important. With a highly distributed workforce, network managers simply cannot guarantee quality of experience by monitoring the core of the network. How can you refocus your approach to gain better insight into what really matters? You need to acquire visibility at the edge, and apply intelligence and automation to ensure that it’s always delivering superior performance.
Informing a self-healing environment with AIOps
Insights begin with data, and the VMware SD-WAN™ platform collects data from multiple vantage points. It can also initiate self-healing based on the data it acquires, responding to network changes and guided by intent and business policies. For example, by continually measuring and analyzing the health of the tunnels it creates, initiate rapid responses to maintain network quality. If a tunnel issue arises, the SD-WAN can switch to another WAN link, adds redundancy, or leverages multiple paths in an innovative way. This kind of proactive behavior is based on local information that’s provided over a short period of time.
AIOps enabled by VMware Edge Network Intelligence™ can take these capabilities a step further, making self-healing more effective by pulling in global information over longer periods of time. For example, AIOps can incorporate not only data from the network, but from additional points between the client and application, including wireless devices, switches, network services, and SD-WAN edges, gateways and hubs. It can also acquire anonymized insights from other VMware SD-WAN enterprise networks. Together, this information can provide the context needed to help SD-WAN detect patterns—and locate the source of network problems faster and more effectively.
By using a larger data set, sampled over a longer period of time, AIOps can gain an additional level of metrics for analysis of each application’s performance individually. For example, with root cause-based analysis, the AIOps platform can determine a specific cause to any network problem—which is often the most time most time-consuming part of solving an issue.
Example: Solving Zoom problems
Suppose a branch office site is experiencing poor Zoom performance. To determine the root cause, the system might attempt to program the wireless LAN network itself, or determine that the issue can’t be mitigated in the WAN. Perhaps the Zoom performance issue is due to packets being dropped because of queuing inside the edge appliance or gateway. AIOps could discover the issue and recommend or even initiate a specific action of prioritizing Zoom traffic higher than other applications sent over the same link.
Another option could be to distribute traffic across multiple gateways, instead of sending all traffic to the same gateway. AIOps enables the system to go beyond simply stating that the WAN segment is faulty. It applies context and intelligent analytics to determine the specific root cause, and explicitly describe the issue. Simply reversing the root cause the system detected enables automated remediation.
Ultimately, organizations can maximize the value of their investment in SD-WAN by combining it with state-of-the-art AIOps capabilities—and gain the full insight at the edge they need to support today’s distributed workforces.
Learn to see more and do more at our webinar
Ready to learn more about how you can improve your visibility into the edges of your network? Join us at our free webinar, Ensuring Network Health with Edge Network Intelligence, for a live discussion featuring EMA Vice President of Research Shamus McGillicuddy, VMware experts, and VMware customers. They’ll explore top technology and business trends driving the importance of edge network intelligence, and what to look for in an edge network intelligence solution.
Register for our live online event, November 4 at 10:00 am Pacific time, or view it on demand.
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