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2019 Prediction: Enterprises Will Use AI to Replace VPNs with Micro-Perimeters to Optimize Hybrid Cloud Application Performance

Don Boxley
DH2i

Many enterprises are pursuing a hybrid IT strategy involving integrated on-premises systems and off-premises cloud/hosted resources. This pursuit will create application performance issues stemming from one key area: leveraging the public internet.

For enterprises the public Internet is both a boon and a danger. The public Internet's global reach offers an easy and cost-effective means for engaging large numbers of customers, regardless of location. However, using the public internet to connect users with business-critical workloads brings risks.

Businesses survive on speed. Customers don't like to wait, and each moment waiting has real revenue implications. Companies investing heavily in hybrid IT strategy around enterprise applications are making these investments to gain an edge, but these investments will only deliver a positive return if the applications are able to run at maximum performance allowed.

As an access path to the cloud, the performance of the public Internet can be limited by traffic and throughput impediments, which can impact the effectiveness of workloads right at peak load times. If enterprise applications struggle to deal with peak loads, this can result in the business suffering revenue loss, damage to their reputation and failing to meet the objectives of moving to a hybrid cloud strategy.

This performance issue can become even more severe as an organization seeks to improve network security by adding secure connectivity in order to reduce security exposure via the public internet by using traditional VPNs, which can cut throughput in half. But traditional VPN software solutions are obsolete for the new IT reality of hybrid and multi-cloud. They weren't designed for them. They're complex to configure, not performant, and they give users a "slice of the network," creating a lateral network attack surface.

A new class of purpose-built security software is emerging to eliminate these issues and disrupt the cloud VPN market. This new security software will enable organizations to build lightweight dynamic micro-perimeters to secure their application- and workload-centric connections between on-premises and cloud/hosted environments, with virtually no attack surface and without the performance issues of VPNs.

Because of the ease of use this new class of security software organizations will utilize at 1-2-3-100+ deployment strategy. That is, they'll deploy micro-perimeters for workload #1. Satisfied it meets the performance and security requirements, they'll deploy micro-perimeters for workload #2, and then deploy for workload #3. At that point, the organization will require micro-perimeters for every application, which could be 100s of workloads with thousands of users. This is the point organizations will turn to artificial intelligence (AI). This is where organizations will leverage their learnings in artificial intelligence to find products that can automate, manage and simplify the machine learning (ML) for each enterprise application's unique connectivity network to map out the optimal deployment of micro-perimeters. This deployment plan will enable organizations to aggressively implement micro-perimeters with the eventual goal of the AI engine deploying and updating micro-perimeters automatically.

Don Boxley is CEO and Co-Founder of DH2i

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2019 Prediction: Enterprises Will Use AI to Replace VPNs with Micro-Perimeters to Optimize Hybrid Cloud Application Performance

Don Boxley
DH2i

Many enterprises are pursuing a hybrid IT strategy involving integrated on-premises systems and off-premises cloud/hosted resources. This pursuit will create application performance issues stemming from one key area: leveraging the public internet.

For enterprises the public Internet is both a boon and a danger. The public Internet's global reach offers an easy and cost-effective means for engaging large numbers of customers, regardless of location. However, using the public internet to connect users with business-critical workloads brings risks.

Businesses survive on speed. Customers don't like to wait, and each moment waiting has real revenue implications. Companies investing heavily in hybrid IT strategy around enterprise applications are making these investments to gain an edge, but these investments will only deliver a positive return if the applications are able to run at maximum performance allowed.

As an access path to the cloud, the performance of the public Internet can be limited by traffic and throughput impediments, which can impact the effectiveness of workloads right at peak load times. If enterprise applications struggle to deal with peak loads, this can result in the business suffering revenue loss, damage to their reputation and failing to meet the objectives of moving to a hybrid cloud strategy.

This performance issue can become even more severe as an organization seeks to improve network security by adding secure connectivity in order to reduce security exposure via the public internet by using traditional VPNs, which can cut throughput in half. But traditional VPN software solutions are obsolete for the new IT reality of hybrid and multi-cloud. They weren't designed for them. They're complex to configure, not performant, and they give users a "slice of the network," creating a lateral network attack surface.

A new class of purpose-built security software is emerging to eliminate these issues and disrupt the cloud VPN market. This new security software will enable organizations to build lightweight dynamic micro-perimeters to secure their application- and workload-centric connections between on-premises and cloud/hosted environments, with virtually no attack surface and without the performance issues of VPNs.

Because of the ease of use this new class of security software organizations will utilize at 1-2-3-100+ deployment strategy. That is, they'll deploy micro-perimeters for workload #1. Satisfied it meets the performance and security requirements, they'll deploy micro-perimeters for workload #2, and then deploy for workload #3. At that point, the organization will require micro-perimeters for every application, which could be 100s of workloads with thousands of users. This is the point organizations will turn to artificial intelligence (AI). This is where organizations will leverage their learnings in artificial intelligence to find products that can automate, manage and simplify the machine learning (ML) for each enterprise application's unique connectivity network to map out the optimal deployment of micro-perimeters. This deployment plan will enable organizations to aggressively implement micro-perimeters with the eventual goal of the AI engine deploying and updating micro-perimeters automatically.

Don Boxley is CEO and Co-Founder of DH2i

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Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

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