Head of Marketing & Customer Insight at Prosimo—enabling autonomous multicloud networking to deliver fast, secure & cost-optimized apps.
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Previously, I discussed the parallels between advancements in autonomous vehicles and autonomous networking. Autonomous networking can offer a path to IT and business alignment—including the C-suite, line of business, DevOps and security—that aims to simplify processes in a consistent and scalable way, which is needed for applications delivered through the cloud. It can enable operational efficiency and helps IT leaders and teams deliver application experiences that improve employee productivity and customer experiences.
Simultaneously, it can help networking and cloud teams to become more familiar with every part of the infrastructure, closing gaps in the skill sets of existing teams. Just as significant, autonomous networks can also help form consistent policies and recognize new patterns to ensure secure and reliable experiences. Here, we’ll look at the different levels of autonomous networks.
Level 1: Getting The Complete Picture
The first level of autonomy is understanding the entire enterprise IT environment and then assessing what can and should be automated. Traditional networking visibility tools often come with blind spots, especially as they relate to the application-specific views. It’s a prerequisite in today’s hyper-cloud environment that enterprises have complete end-to-end, real-time visibility across on-premises data centers, as well as both virtualized and cloud environments. Otherwise, enterprises will be guessing about issues that may arise outside their immediate purview. Getting the complete picture in real time helps shorten the time window to resolution.
Level 2: Building On Cloud-Native Constructs
The next level requires enterprises to set up a foundation that enables autonomy. Just as autonomous vehicles require a new platform, so does autonomous networking. Although enterprises are able to achieve some level of functionality with traditional networking tools, cloud-native computing has fundamentally changed how applications are delivered.
To be able to quickly and efficiently gain understanding in real time and take immediate action on applications that are cloud-delivered and interconnected by thousands of microservices, a networking platform built on cloud-native constructs is required. This can not only can help solve some of the challenges that enterprises are encountering today but also for the foreseeable future as more applications are delivered through the cloud.
Level 3: Orchestrating Across The Cloud With Consistency
Learning the native capabilities of the cloud can be daunting. So, having a cloud-native orchestration platform with a single management plane for today’s dynamic IT environment can be very helpful as enterprises grapple to gain control over on-premises data centers, into and across the cloud and increasingly at the edge.
Overcoming this challenge can ensure consistency across the connectivity layer such that IT teams need not burden themselves with thinking about the underlying connectivity technique. With a single integrated platform built on cloud-native constructs that can discover new applications in real time and understands interdependencies, enterprises could put the foundational layers in place to simplify networking and make it autonomous.
Level 4: Gaining Deeper Intelligence, Learning And Recommendations Tied To Business Outcomes
Level 4 is where the real magic starts to happen, as it brings enterprise networking one step closer to full autonomy. The underlying infrastructure leveraging ML-driven recommendations can understand applications and ingest all data from the network and application layers; it can also understand the environment these services are running.
Level 4 is where data leads to intelligent recommendations on how infrastructure can be changed to help provide different experiences for different applications. Although it still requires some human intervention to make changes after review, it can significantly reduce the scope of oversights and changes that operations teams often have to deal with at this stage.
Enterprises can understand and prioritize performance, risk tolerance and cloud spend management at this level. For example, at this level, you might receive a recommendation that if new users emerge in Australia, spinning up a new cloud region in Melbourne at $1,000 per month will improve performance by 50%. As these platforms are built on cloud-native constructs, they tend to be highly extensible and allow enterprises to expand with tools like Terraform to deepen the level of autonomy.
Level 5: Trusting The Recommendations With Full Network Automation
The future of autonomous networking is promising and exciting. Although full network automation is the dream of many, it will require further discussion, innovation and testing. What full automation could deliver is self-learning capabilities with the ability to understand issues before they impact end users and applications. It could also apply changes without any human intervention and create checks and balances against human error.
Similar to autonomous vehicles, enterprises could just specify which applications need to be delivered to which set of users and let the autonomous networks do the rest. This is possible today but requires enterprises to trust that the autonomy will be safe.
The Future Of Networking
Legacy networking had its time and place when applications and end users were static. But this approach doesn’t often scale with modern applications and complex IT environments. It still typically requires the manual stitching of disparate tools to understand interdependencies and leaves enterprises with an incomplete picture. With more applications moving to the cloud to support digital transformation, distributed workforces and innovation, businesses may want to consider autonomous networking as one way to help untether them from traditional IT restrictions and enable them to grow and innovate faster.
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