Introduction
The network is the backbone of every enterprise. It is critical to the organization’s overall performance, yet there are many elements that need to be monitored to ensure it’s functioning properly. AIOps (Artificial Intelligence for Operations) is the next-generation technology that can enhance user experiences and help organizations in gaining deeper insights into their networks.
What is AIOps?
Artificial intelligence in operations (AIOps) is a network management approach that uses artificial intelligence and machine learning to improve operational efficiency. AIOps takes advantage of the latest AI technologies to automate processes, making it easier and faster for IT teams to troubleshoot problems when they arise.
It’s no surprise that the adoption of AIOps has skyrocketed in 2019—companies are hungry for technology advancements that will allow them to maximize user experience while reducing costs. Networking vendors are responding by offering solutions that combine multiple technologies, including real-time analytics, automated configuration changes, and self-healing algorithms.
Importance of AIOps In Network Management and Cloud Performance
AIOps is the next generation of network management. AIOps uses machine learning to automatically detect and resolve problems as they occur, which not only helps you to identify issues in real time but also fix them before they affect users.
AIOps can improve network performance across your entire network by making sure that there are no bottlenecks or other issues slowing down traffic. It also provides better reporting on how well your network is performing at any given moment, allowing you to take action if necessary.
One of the biggest trends in cloud computing is the adoption of artificial intelligence and machine learning. These technologies have been around for a while, but they are now becoming mainstream in many industries. AI in networking operations is also becoming a reality, and we are seeing more and more network devices with AI capabilities. This will lead to better performance, security, automation, and service assurance for enterprises.
AI-based Systems Now Reaching Across Enterprise and Service Provider Networks
From an initial focus on core network systems, there is now a deepening investment in AI-based systems across both the enterprise and the service provider space. The use cases for AI are numerous, with some of the more prominent ones including:
- Service Quality Monitoring & Improvement — A large percentage of customers use their mobile devices as a primary means of accessing content and performing business functions. As such, it is imperative that service providers ensure high-quality user experience over these connections by identifying problems quickly and proactively taking steps to resolve them before they escalate into customer churn or financial losses.
- Network Security Detection & Prevention – Endpoints have become increasingly vulnerable due to sophisticated attacks from hackers who find new ways to break security measures. These attacks can be detected through advanced analytics which can monitor endpoint behavior patterns (e.g., abnormal traffic volume) to identify malicious activity before it happens; this technology can also be used as part of an overall defense strategy against cyber threats at large scales (i.e., across multiple customers).
- Automated Orchestration – According to IDC research, businesses will spend about $1 trillion annually on IoT-connected devices by 2022—which translates into thousands upon thousands of devices being added every year! To keep up with this demand requires organizations to make investments in automation tools capable of not only monitoring but also managing these devices efficiently while ensuring consistent performance levels across all networks regardless of whether they’re old legacy infrastructure or newer fiber optic cables used as part of 5G networks worldwide.
How AIOps Improve Service Assurance?
The fundamental purpose of AIOps is to provide a better user experience. This is done by improving and optimizing the network’s performance and ensuring that it can support all of your users’ needs.
AIOps improves service assurance by offering insights into the health of the network and its components, as well as the ability to proactively predict potential issues before they occur. With AIOps, you can track performance data over time, identify potential bottlenecks, and automatically take action based on what you determine is needed.
In addition, AIOps can be used for capacity planning so that you have an accurate idea of how much bandwidth is needed for peak usage times. This way, you can plan ahead and make sure that there is enough capacity available for your business needs.
SD-WAN and AIOps Coming Together
SD-WAN is a technology that helps enterprises connect their branch offices to the cloud. SD-WAN uses a virtualized network overlay to provide secure, reliable, and scalable access for branch devices.
When used in conjunction with AIOps, SD-WAN can improve network performance by offering insights into both the user experience and network conditions within the organization’s cloud environment. In addition to providing an improved user experience for end users, this combination can also help IT operations teams reduce costs associated with maintaining on-premises data centers.
How is AI-driven SD-WAN Helping Businesses?
Traditional SD-WAN can be difficult to navigate, especially for the average user. For example, a remote employee may have difficulty setting up VPN connections or configuring DNS settings in order to access your network. Additionally, complex IT processes like provisioning new sites and adding new users often require extensive time and cost on management’s part.
The combination of AI and SD-WAN will help improve the user experience by automating these tasks. For example, AI has been shown to predict network issues before they occur based on what it observed in historical data; this will allow IT teams to proactively monitor networks while simultaneously reducing costs associated with managing multiple locations across diverse environments.
Similarly, AI can be used as an intelligent assistant for end users who are trying their best to troubleshoot problems themselves by removing some of the guesswork involved with diagnosing and repairing common issues through automation tools such as chatbots or virtual assistants (VAs).
SD-WAN Enhanced User Experience With AIOps
By ensuring the best possible connection, both in terms of speed and latency, to the applications that users rely on, SD-WAN can help improve an enterprise’s user experience. This is especially important for businesses that want to deliver a better user experience to their customers or employees.
Here are some of the best user experiences that can be achieved based on Juniper’s AI-Driven SD-WAN powered by Session Smart:
- Agility – Faster deployment, higher scale, dynamic optimization, boundary-free routing from client to cloud
- Performance – 60% Latency Reduction Less overhead, more scalability, dynamic optimization. Enables hitless voice and video calls.
- Visibility and Insights – 30-40% Less Support and MTTR Costs
- Reduced Cost – 30-50% Bandwidth 75% Headend Infrastructure
- Security – Zero-trust model: Authentication + Encryption + Segmentation. SASE-based policy and routing built-in.
- Simplicity – No tunnels, no overlays, no more hardware-centric networking
A network as a service provider can help in setting up an AI-driven SD-WAN for enterprises. Blue Chip, an IT consulting and networking service provider in Los Angeles has expertise with AI-driven SD-WAN with the use of AIOps.
Enterprise AI Driven Networking
Enterprise Network Goals
Today, businesses are more connected than ever before. And as companies continue to grow, their network infrastructure also needs to evolve. Businesses need enterprise-grade networks that are fast, reliable, secure, and cost-effective.
Enterprise AI-driven networking is the next evolution of the enterprise network infrastructure. By adopting this new approach to networking, enterprises can improve productivity, simplify operations, drive excellent user experience, and reduce costs.
Essential Elements of Business-Critical Networks
- Optimized For Assured Experiences
- Proactive AI-driven operations and support
- Open and programmable cloud
AI and Machine Learning Optimize Network Performance by Improving The User Experience.
AIOps is helping network administrators improve their users’ experience by optimizing network performance. The ability to quickly detect, troubleshoot and resolve issues has been the cornerstone of AIOps since its inception, but now with AI and machine learning, this capability has become even more powerful. With the addition of AI and ML-driven analytics capabilities, AIOps platforms are able to provide a more personalized user experience by detecting and responding to issues in real-time.
AI and machine learning optimize network performance by helping you get the most from your existing infrastructure and resources, so you can focus on what matters most: creating better customer experiences.
Benefits Driving AIOps Adoption
- Reduce network management costs.
- Improve network performance.
- Enhance business outcomes.
- Increase customer satisfaction and retention, which leads to increased revenue, market share, and profitability.
AIOps can also improve employee productivity by removing manual processes, reducing the number of tickets required to be resolved by IT teams (which improves efficiency) while at the same time freeing up staff resources for more strategic work such as preparing data center operations for a cloud migration or automating your next big deployment project – all done through automation!
Conclusion
As AIOps adoption continues to grow, network enterprises will realize the value AI-driven SD-WAN provides in improving service assurance. By adopting AIOps, network enterprises can take their service assurance efforts to the next level by leveraging AI-driven SD-WAN. The key benefits are expected to be realized through improved end-user experience and reduced operating costs.
