This blog is part of the “Branch of the Future” series where we take a closer look at the four key tenets that next-generation SD-WAN and SASE provide to deliver a branch network that is digital-first, secure and powered by the latest AI/ML innovations.
Artificial intelligence (AI) is a prominent force driving innovation and transformation. Businesses everywhere are relying on AI to enhance operations and achieve better business outcomes. In the realm of cybersecurity and SD-WAN in particular, AI has huge potential to revolutionize IT operations and improve efficiency.
In today's digital landscape, IT organizations are expected to do more with less and avoid costly downtime.
By 2023, 40% of I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity with greater agility and scalability.
The move to a highly distributed workforce has created a new generation of challenges for IT teams. These challenges hinder IT teams from delivering optimal performance:
Gartner estimates IT downtime can cost organizations up to $5,600 per minute on average. Plus, there’s another problem.
Legacy networks often rely on disparate products and separate management systems. This makes it impossible for IT staff to correlate, prioritize and analyze issues quickly. More importantly, the lack of a common data lake limits the ability to automate day 2 operations with AI/ML techniques.
SD-WAN has fundamentally transformed how networks work. With monitoring capabilities at the user, branch, and application level, SD-WAN collects crucial network and performance data to take forwarding and prioritization decisions. This presents an ideal foundation for implementing AI-driven automation—thanks to its modern analytics capabilities.
The wealth of SD-WAN generated data can be used to detect, diagnose, and remediate issues fast. While SD-WAN analytics primarily address concerns at branch edges, it is essential to recognize that the network extends far beyond branches. It also encompasses users, data centers, clouds, and applications.
This evolution has led to the widespread adoption of Secure Access Service Edge (SASE) solutions that consolidate networking and security functions into a single cloud offering, which makes integration of AI capabilities simpler and more seamless.
In contrast, legacy SD-WAN solutions often offer mix-and-match options, which can impede the smooth implementation of AI automation.
Observability and AIOps (Artificial Intelligence for IT Operations) play crucial roles in enhancing the effectiveness of AI-powered operations.
The right solution will leverage the latest advancements in observability and AI/ML built natively to help customers:
By embracing observability and AIOps, organizations are in a far better position to mitigate risks, simplify ops, and address network anomalies proactively.
Prisma SD-WAN offers deep visibility into performance scores at the site, circuit, and application level that is intelligently computed using trend analysis leveraging AI and ML and shared as insights. These insights highlight recommendations and key incidents that IT administrator need for anomaly identification, troubleshooting, and resolution of issues.
Additionally, these insights provide proactive incident reporting that empowers IT staff to implement the right measures like allocating more bandwidth to circuits and fine-tuning business policies to avoid performance degradation to avoid any outages across the enterprise.
Prisma SD-WAN granular visibility into branch and application performance.
With unified data (which is necessary for applying the full potential of AIOps), Prisma SD-WAN makes discovering network anomalies quick and easy, using:
AI/ML offers organizations and IT teams improved automation, observability, increased productivity and reduced MTTR. Learn more about how AI/ML is powering next-gen SD-WAN and SASE for the branch. Watch our on-demand virtual event.