Add IP Fabric screenshot placeholders for documentation
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@@ -20,7 +20,7 @@ The distinction that matters most, coming from a monitoring background, is that
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That distinction is exactly why it slots into the "topology as source of truth" layer of the AIOps stack described in the blog series: an agent that needs to reason about the network needs this structured state before it needs metrics.
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[[CAPTURE: IP Fabric dashboard overview]]
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## How discovery and snapshots work, at a high level
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@@ -32,7 +32,7 @@ IP Fabric works from two core concepts: discovery and snapshots.
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That snapshot model is what makes several of the use cases below possible: because history isn't discarded, questions like "what changed since yesterday" have a direct answer instead of requiring you to have thought ahead and set up your own diffing.
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[[CAPTURE: snapshot list / discovery settings screen]]
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## Use cases
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@@ -42,7 +42,7 @@ This is the use case that started it all for me, and the one referenced directly
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For my EVPN/VXLAN lab, that means I have an always-current answer to "what's connected to what" without trusting my own memory or an out-of-date diagram. This is the layer an AI agent would need to query first, before anything else, if it's going to reason correctly about the network — which is the whole point of the "blind agent" problem from the blog series: an agent working off stale topology data is confidently wrong, not cautiously uncertain.
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[[CAPTURE: IP Fabric topology diagram of the lab]]
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### Intent checks
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@@ -50,7 +50,7 @@ Intent checks are rules you define once, things like "no unused VLANs," "STP roo
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This is where IP Fabric moves from "descriptive" (what's out there) to "normative" (is what's out there correct). It's a natural fit for the standardization principle I keep coming back to in the blog series: intent checks are a way to enforce naming and configuration consistency automatically, instead of relying on a human to notice drift.
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[[CAPTURE: intent check results table, colored pass/fail]]
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### Path lookup
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@@ -58,7 +58,7 @@ Given a source, a destination, and optionally a protocol/port, IP Fabric simulat
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This turns "why can't this host reach that host" from a multi-device, multi-`show`-command investigation into a single query. It also validates security posture: a path lookup will tell you if an ACL or firewall rule blocks traffic somewhere along the way.
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[[CAPTURE: path lookup diagram between two lab hosts]]
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### Snapshot comparison
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@@ -66,7 +66,7 @@ Because every discovery run is preserved as its own snapshot, IP Fabric can diff
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This is the practical answer to "what actually changed," which is normally the hardest question to answer after an incident. Instead of reconstructing a timeline from memory or from scattered change tickets, the diff is already sitting there.
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[[CAPTURE: snapshot diff view showing added/removed items]]
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### Programmatic access: Python SDK and MCP server
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@@ -76,4 +76,4 @@ More relevant to the AIOps angle of the blog series: IP Fabric also ships an [MC
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I haven't wired this up on my lab yet; that's future work, and future sections here.
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[[CAPTURE: MCP server tool list or example agent query]]
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