If you work in network peering and interconnection, you probably remember when we first introduced the PeeringDB integration to Kentik Portal a few years ago. That integration gave network teams easy access to up-to-date information about an Autonomous System's (AS) network footprint, peering relationships, and interconnection opportunities, directly within Kentik.

Now, we're taking that integration a step further with Kentik AI Advisor.

AI Advisor can now incorporate PeeringDB's extensive interconnection data into its AI-powered investigations and analysis, bringing valuable peering intelligence directly into the investigative process.

Let's take a closer look at what's new and what it means for you. 

PeeringDB 101

For peering and interconnection teams, PeeringDB is an essential resource for understanding where networks operate, how they interconnect, and under what conditions they're willing to exchange traffic.

This community-maintained directory provides detailed information about registered Autonomous Systems (ASNs), including:

• Data center presence: The facilities where networks have a physical presence, helping teams identify opportunities for private network interconnects (PNIs).
• Internet Exchange (IX) participation: The exchanges where networks are present, including their peering IP addresses, enabling teams to identify public peering opportunities and establish BGP sessions.
• Peering policies: The requirements and conditions under which networks are willing to establish interconnection relationships.

These insights inform a wide range of strategic and operational decisions, from evaluating inbound peering requests and identifying potential PNI partners to selecting the best Internet Exchanges for localized traffic exchange. They also help teams identify shared facilities for interconnection, minimize unnecessary backhaul costs, and determine where transit providers can efficiently deliver connectivity to prospective customers.

But PeeringDB is only one piece of the interconnection puzzle.

Developing an effective peering strategy also requires understanding what's actually happening across your network. That means analyzing traffic volumes, source and destination ASNs, traffic paths, and the types of connectivity carrying that traffic, whether public peering, private interconnection, or IP transit.

Equally important is understanding your network's current state. Do you already have BGP peering sessions established with a potential partner? Which routers and interfaces are involved? These answers often require consulting monitoring systems, routing data, and device configurations alongside PeeringDB.

Traditionally, bringing these data sets together has required network teams to move between multiple tools, manually correlate information, and piece together the insights needed to make informed interconnection decisions.

That's where Kentik AI Advisor changes the equation.

Kentik brings together the critical data needed to inform peering and interconnection strategies, and AI Advisor can now put that information to work:

1. Unified access to critical network intelligence: Kentik combines PeeringDB interconnection data, traffic telemetry enriched with connectivity classifications, and router configuration context.
2. AI-powered, cross-domain investigations: AI Advisor can reason across these data sources, connecting interconnection opportunities with actual traffic behavior and network configuration.
3. Investigations tailored to your network: With Custom Network Context (aka AI Advisor's claude.md) and AI Runbooks (aka AI Advisor's Claude Skills) teams can guide AI Advisor using their network-specific knowledge, operational practices, and established investigation workflows.

Here's the great news moving forward: 

1. Kentik collects all of this information: PeeringDB, Connectivity Type-enriched Traffic telemetry, Router Configuration
2. Kentik's AI Advisor has access to it and can reason with it
3. You can mix and match reasoning across these datasets using the guided context you have provided in both Custom Network Context (aka AI Advisor's claude.md) and AI Runbooks (aka AI Advisor's Claude Skills)

The net result is now AI Advisor can tackle complex, multi-layer peering and interconnection questions that previously required significant manual investigation, helping network teams evaluate opportunities, optimize connectivity decisions, and turn network intelligence into action.

Let's explore how you can put AI Advisor to work as an AI-powered teammate for peering and interconnection management.

The Basics: PeeringDB Intelligence in AI Advisor

AI Advisor can now automatically tap into PeeringDB's extensive interconnection data as part of its investigations. Using context-aware triggers, AI Advisor invokes a dedicated PeeringDB sub-agent when relevant, accessing detailed information about Autonomous Systems (ASNs), Internet Exchanges (IXes), and data center facilities. It can retrieve and analyze this information independently or combine it with other data sources and tools through multi-step investigations.

Here's a look at some of what AI Advisor can do with PeeringDB data:

• Identify shared interconnection opportunities: Find Internet Exchanges and data center facilities where any two or more ASNs have a common presence, or explore the complete IX and facility footprint of any individual ASN.
• Discover and compare Internet Exchanges: Identify IXes in a specific city, region, or country and compare them based on attributes such as member count, open peering policies, and aggregate member port capacity. AI Advisor can also locate IXes and facilities within a specified geographic radius.
• Explore network presence and peering policies: Identify which ASNs are present at a particular IX or facility, filtering by criteria such as peering policy, contractual requirements, and available peering IP addresses.
• Retrieve peering connection details: Look up an ASN's ports and IP addresses at specific Internet Exchanges to support interconnection planning.
• Access peering policies and contacts: Retrieve relevant NOC and peering contact information, traffic ratio requirements, peering policy URLs, and other published interconnection requirements.

And that's just a starting point. Whenever AI Advisor invokes the PeeringDB sub-agent, users can inspect the underlying tool calls and retrieved data through the View Details side panel, providing transparency into the information used to inform its analysis.

These capabilities are valuable even for standalone queries. Rather than switching between Kentik Portal and PeeringDB to look up network footprints, peering policies, or interconnection details, users can access that information directly through AI Advisor, keeping their investigations in one place. 

In the next sections, we'll look at combining this data with other datasets in AI Advisor to demonstrate power user use cases!

Putting AI Advisor to Work: Advanced Peering and Interconnection Use Cases

Accessing PeeringDB data through AI Advisor is valuable on its own, but the real power comes from combining that intelligence with Kentik's broader network telemetry, device configurations, and operational context.

Let's explore how AI Advisor can bring these data sources together to streamline complex peering investigations, identify interconnection opportunities, and support more informed peering decisions.

Understand Existing BGP Peering Sessions

Before evaluating new interconnection opportunities, it's important to understand the peering relationships already established across your network. For devices monitored by Kentik NMS, AI Advisor can retrieve information about existing BGP sessions to help determine whether you're already peering with a particular ASN and understand the current state of those relationships. Similar information can also be obtained through router configurations when devices are enrolled in Kentik's Config Backup capability, or by executing show commands directly on supported devices with Command Access enabled.

Combine Traffic Intelligence with PeeringDB Data

Kentik regularly synchronizes PeeringDB data, including the IP address ranges associated with Internet Exchanges. This information helps enrich customer flow telemetry with additional interconnection context, making it easier to analyze traffic based on source and destination ASNs and connectivity attributes.

Consider a common peering optimization scenario: How much IP transit traffic could you potentially shift to direct interconnection if your network established a presence at Equinix Ashburn?

With Kentik Data Explorer, experienced users can investigate this opportunity by applying filters to identify traffic currently traversing transit links that may be eligible for alternative interconnection.

But what if you don't know which filters to apply or aren't familiar with Data Explorer? Simply ask AI Advisor.

AI Advisor can bring together traffic analysis and PeeringDB intelligence to help identify potential interconnection opportunities without requiring users to manually construct the underlying queries.

Fast forward: towards an AI-powered Peering Manager

Identifying potential transit offload is only the first step. A peering manager also needs to determine which networks to approach, where interconnection makes sense, and what information is needed to initiate a peering relationship.

Continuing our Equinix Ashburn example, AI Advisor can help translate the analysis into an actionable plan, identifying prospective peering partners and providing the relevant interconnection details needed to pursue those opportunities.

This helps bridge the gap between identifying an optimization opportunity and taking the next steps toward implementing it.

Streamline Peering Request Evaluations with AI Runbooks

Now consider another routine responsibility for peering managers: evaluating inbound peering requests. When another network requests a peering relationship, the evaluation typically involves several steps:

1. Analyze traffic: Examine traffic volumes and patterns exchanged with the requesting ASN, including inbound and outbound traffic ratios.
2. Evaluate interconnection options: Review the requesting network's PeeringDB footprint to identify shared Internet Exchanges or data center facilities.
3. Apply peering policies: Assess whether the request meets established requirements, such as minimum traffic thresholds, traffic ratios, and geographic criteria.
4. Determine eligibility: Evaluate the findings against your organization's peering policies to determine whether the request should be approved.
5. Prepare next steps: Document the decision and outline the actions required to establish a BGP peering session at an agreed-upon location.

Traditionally, this process requires peering managers to move between multiple tools, manually correlate data, and apply internal policies before reaching a decision.

With AI Advisor and AI Runbooks, much of that multi-step evaluation process can be automated.

AI Runbooks allow network teams to define repeatable investigation workflows using natural-language instructions, giving AI Advisor a structured process to follow when evaluating peering requests.

For a deeper introduction to this capability, check out our recent webinar, Transforming Network Operations with AI Advisor. To get started, simply define the steps of your peering evaluation process in an AI Runbook.

Here's an example of a basic Peering Evaluation Runbook. While it can be expanded and customized to reflect more sophisticated policies, it demonstrates how AI Advisor can orchestrate an investigation across multiple data sources.

In this example, the Runbook instructs AI Advisor to first query Kentik Data Explorer to analyze the requesting ASN's traffic profile over the past seven days. It then evaluates common Internet Exchange and facility presence using PeeringDB data and checks the findings against predefined peering requirements, including minimum traffic thresholds.

Rather than requiring a peering manager to execute each step independently, AI Advisor follows the defined workflow to build a cohesive, evidence-based evaluation.

AI Advisor can also dynamically invoke the appropriate Runbook based on the context of a user's prompt, making it possible to initiate the process with a simple natural-language request. When a Runbook is invoked, AI Advisor indicates that it's following the defined workflow, providing visibility into the steps guiding its investigation.

Build Your Own AI-Powered Peering Workflows

The peering request evaluation example is just one of many ways to put AI Advisor and AI Runbooks to work. By defining repeatable procedures tailored to your network, peering policies, and operational priorities, you can equip AI Advisor to tackle a wide range of interconnection planning and optimization tasks.

Here are two more examples of what's possible:

Optimize Interconnection to Reduce Transit Costs and Improve Performance

Create an AI Runbook that evaluates interconnection opportunities in a specific country or region to identify ways to reduce IP transit costs, localize traffic exchange, and improve network performance. For example, the Runbook could instruct AI Advisor to:

• Analyze traffic to and from ASNs in the target geography.
• Identify Internet Exchanges with the greatest overlap among those networks.
• Evaluate potential data center locations based on network presence and interconnection opportunities.
• Recommend strategic locations for expanding your network's interconnection footprint.

Audit Existing Peering Relationships to Identify Optimization Opportunities

Not all optimization opportunities require establishing new peering relationships. Sometimes, you may already have a peering session with a network but still exchange a portion of your traffic with that ASN over paid transit. An AI Runbook could help uncover these inefficiencies by:

• Identifying top inbound and outbound ASNs reached through existing IX or PNI peering connections.
• Analyzing the distribution of traffic exchanged with those ASNs across transit, public peering, and private interconnection.
• Flagging networks where traffic continues to traverse transit despite an existing peering relationship.
• Investigating the relevant prefixes and routing behavior to identify potential opportunities to shift traffic onto established peering connections.
• Generating a documented report of findings that can be shared with peering partners to support further investigation and optimization.

These are just a few examples of how AI Advisor can help turn complex, multi-step peering investigations into repeatable, AI-powered workflows.

Now it's your turn.

Whether you're evaluating new peering partners, optimizing interconnection costs, or auditing existing relationships, AI Advisor gives you the tools to build workflows around your network's unique requirements.

What will you build with your AI-powered peering teammate?