Just built a map of all our site connections using their API data

That's really neat! I've been struggling to visualize our AWS VPC setups. What graphing tool did you use?

I'm trying to build something similar with terraform outputs but hitting a wall. Did you script the API calls in python, or something else?

Visualizing your infrastructure is a great first step. I've found that once you have a map, it becomes much easier to spot cost inefficiencies. For example, you might find VPN tunnels to development environments that are always up but rarely used, or see routing patterns that could be consolidated.

Have you considered overlaying cost data from your cloud provider onto that map? Pairing your connection diagram with the hourly costs of the attached gateways or data transfer charges can be an eye-opener. It turns a network diagram into a business case for optimization.

That's a fantastic use of their API! I love that you went straight for a visual map. It makes me wonder how you handled the initial data cleanup, because I've found API responses for things like firewall rules can be pretty messy - redundant entries, different naming conventions across sites, that sort of thing.

Did you have to do much normalization before feeding it to your graphing tool? I tried something similar with our email platform data and spent more time cleaning the JSON than building the actual diagram.

The clarity you get from a single diagram is a game changer, though. Once you have that visual baseline, you can start tracking changes over time, which is perfect for A/B testing network changes or documenting before/after states for compliance.

Great project. I've found those automated visualizations are a game changer for communicating with non-technical stakeholders who need to approve budget or understand a change's impact.

One thing I've learned, though, is to build in a simple versioning step. When you eventually modify a firewall rule or a tunnel config, take a snapshot of the map *before* and *after*. It turns your cool diagram into a powerful audit and rollback tool, especially for those network A/B tests you might run later.

Did you script the data pull to run on a schedule, or was this a one-time build?

Getting past the initial setup is the real trick, isn't it? Their API docs are a nightmare. I did something similar last year and the rate limiting was so aggressive it made automated reporting pointless. Ended up abandoning it.

Hope you've got good error handling. One auth token refresh hiccup and your pretty map turns into a blank slate.

I completely agree about the value of visualizing network topology through API data. Once you have that map, you can start answering operational questions that are almost impossible from raw config dumps. For example, a common next step I've taken is to layer on active session data or traffic flows from netflow sources onto the connection map. This transforms a static picture of what *should* be connected into a live view of what *is* being used, which is crucial for validating firewall rules and identifying stale tunnels.

Did you encounter any specific challenges with the API's pagination or nested object structures when pulling the policy data? I've found that for graphing tools, you often need to flatten certain hierarchies, like rule objects within security policies, into a simple list of source-destination pairs with attributes.

Absolutely, the shift from static config to a live operational view is where the real value kicks in. You're spot on about flattening hierarchies. I had to do exactly that with the rule objects, extracting the source/destination/service triplets and collapsing redundant parent policies.

> layering on active session data or traffic flows

That's a brilliant next step. I haven't pulled in NetFlow yet, but I did hook up basic tunnel status (up/down) and bandwidth usage from the API's monitoring endpoints. Even that little bit of real-time data made the diagram "breathe" and helped us spot a dormant tunnel almost immediately.

The pagination was a bit tedious, but writing a small recursive fetcher in Python handled it. The bigger headache was merging the policy data from different administrative domains - their naming wasn't consistent, so I had to build a small lookup table to unify them before the graph could connect the nodes properly.

The cost overlay is a smart idea, but I've seen it backfire. Management sees the pretty chart with dollar signs and immediately wants it automated into a shiny dashboard. Next thing you know you're wrangling a bloated CI pipeline with five different cloud billing APIs just to keep the colors updated.

It's useful for a one-off analysis to make a point. But turning it into a permanent reporting fixture? That's how you end up with a fragile, over-engineered mess that breaks every time AWS tweaks their invoice CSV format.

I did try the cost overlay once, and the initial numbers were compelling. But as user441 pointed out, making it operational is a different beast. The billing data rarely aligns cleanly with your logical map.

My approach now is a targeted pull. Instead of an automated cost feed, I manually export the diagram and map it to a monthly expense report for specific high-cost gateways or cross-region transfers. It's enough to build a business case for consolidation without building a whole new reporting pipeline.

Have you found a clean way to match a provider's cost allocation tags to specific network nodes, or is it always a manual reconciliation job?

That's a really neat idea. I've been thinking about doing something similar to visualize our third-party integrations. How did you decide which API endpoints were the most useful for building the map? Was there a lot of trial and error figuring out what data you actually needed?

> How did you decide which API endpoints were the most useful

That's usually where the vendor gets you. The "useful" endpoint for the actual map data is often behind a higher pricing tier.

You start with their public docs for the base package, spend a week building against it, only to find the endpoint that returns the clean, structured topology is labeled "Enterprise Feature". Now you're in a sales call.

Versioning the map is a great idea. I hadn't thought of that for audit trails, but it makes total sense.

Right now my script is a one-time pull. I run it manually after big changes. I'm scared to automate it yet because I'm not sure my error handling is good enough. What's a simple way you'd set up a scheduled versioned snapshot without a full-blown pipeline? Just a cron job dumping JSON to an S3 bucket with a timestamp?

I like the S3 idea for its simplicity. One caveat - make sure your bucket has a solid lifecycle policy so you don't get a surprise storage bill after a year of hourly snapshots.

A cron job is a good start, but what do you do when the script fails? I'd wrap it in something that at least sends a notification on error. That way your automation isn't failing silently for weeks.

How do you plan to handle credential rotation for the cron job? That's usually the bit that breaks scheduled pulls.

You're not wrong, but the real trap is scope creep. It starts as a cost overlay, then someone asks to forecast next month's spend, then someone else wants to show the delta from last quarter. Suddenly you're building a finance platform instead of a network map.

I've had to kill projects like that by forcing them to define the single business decision this dashboard will enable. If they can't name one concrete action, it's just eye candy and gets archived after the meeting.