Security Policy / Rule Generator
Build a firewall rule (and matching NAT, if needed) and get vendor-native CLI syntax for Palo Alto, Juniper SRX, Cisco ASA, Fortigate or Checkpoint.
Rule Parameters
policy-rule.conf
Set your rule parameters and pick a vendor, then click Generate config.
Firewall Policy Management — Audit & Cleanup
Best practice checklist for keeping a rule base clean, plus the vendor command to find unused/shadowed rules. Uses the vendor selected above.
| Practice | Why it matters |
|---|---|
| Least privilege / specific over broad | Scope source, destination, and service as tightly as possible — avoid "any/any/any" rules. |
| Naming & description convention | Every rule should say who requested it, what it's for, and when to revisit it. |
| Rule order review | General rules above specific ones create shadowing — most specific/most-hit rules should sit higher. |
| Logging enabled on every rule | Silent allow/deny rules are unauditable; enable logging (incl. deny rules) for forensics. |
| Scheduled recertification | Rules tied to a decommissioned project/person should expire — review on a fixed cadence (e.g. quarterly). |
| Remove unused/zero-hit rules | Every extra rule increases attack surface and troubleshooting time — prune what nothing matches. |
| Change control & peer review | Rule changes go through a ticket + second reviewer before push, with a rollback plan. |
rule-audit-commands
Click Generate to see the audit/cleanup commands for the vendor selected above.
NAT Generator
Source (dynamic/PAT), static 1:1, and destination NAT / port-forwarding across vendors.
NAT Rule Parameters
nat-rule.conf
Choose a NAT type and vendor, then click Generate config.
Access Control Generator
Lock down management-plane access (SSH/HTTPS/API) to trusted admin subnets, and build generic ACLs / address-object based access rules.
Management Access Control
Generic ACL Builder
access-control.conf
Generate a management ACL and/or a generic ACL — both append to this panel.
Secure Connectivity — Remote Access VPN
Client-based remote access: GlobalProtect, AnyConnect, Fortigate SSL-VPN, Checkpoint Mobile Access, Juniper remote access.
Remote Access Parameters
remote-access-vpn.conf
Set parameters and pick a vendor, then click Generate config.
Network Segmentation Designer
Define security zones/VLANs (e.g. Trust, DMZ, Guest, IoT, Servers) and generate the zone/interface bindings plus a default-deny inter-zone policy per vendor.
Segments
Default recommendation: deny all inter-zone traffic by default, then add narrow allow rules per required flow (see Policy tab). Keep Guest/IoT isolated from Trust and Servers unless explicitly required.
segmentation.conf
Add segments above, then click Generate config.
Site-to-Site IPsec VPN Generator
Enter the peer and IKE/IPsec parameters once, then generate matching config for any supported vendor.
Tunnel Parameters
Phase 1 (IKE)
Phase 2 (IPsec)
vpn-tunnel.conf
Fill in tunnel parameters and pick a vendor, then click Generate config.
Zscaler Proxy / ZIA Config Generator
Generate a PAC file, a GRE or IPsec tunnel to the Zscaler cloud, and pull up ZCC / ZIA troubleshooting steps.
PAC File Generator
proxy.pac
Generate to preview the PAC file JavaScript.
GRE / IPsec Tunnel to ZIA
gre-to-zia.conf
Set ZEN and internal IPs, then generate.
Zscaler Troubleshooting Cheat Sheet
| Check | Where | Command / URL |
|---|---|---|
| Confirm client is connected & forwarding to ZIA | Zscaler Client Connector | ZCC tray icon → Advanced → View Logs / VPN Adapter status |
| Verify egress IP is a Zscaler cloud IP | Browser | https://ip.zscaler.com |
| Confirm PAC file is being applied | Browser | chrome://net-export or check proxy settings |
| Check tunnel/health status (GRE/IPsec) | ZIA Admin Portal | Administration → Cloud & Branch Connector → Locations / VPN Credentials |
| Test connectivity to ZEN | Router/firewall CLI | ping/traceroute <ZEN IP>, show crypto isakmp sa / show interface tunnel |
| Validate authentication (SAML) issue | ZIA Admin Portal | Administration → Authentication → check IdP metadata / clock skew |
| App fails only via Zscaler, works direct | ZCC | Add domain to PAC bypass or SSL Inspection bypass list |
| Check ZCC connectivity to cloud | ZCC CLI (Windows) | "C:\Program Files\Zscaler\ZSATrayManager.exe" -e (export logs) |
| Verify ZPA App Connector status | ZPA Admin Portal | Administration → App Connectors → check connection state & version |
| Confirm SSL inspection cert install | Endpoint | Check Zscaler root CA is trusted in OS/browser cert store |
Common fixes: PAC not applying → check WPAD/GPO push; latency → confirm nearest ZEN via https://config.zscaler.com; app breakage → add to SSL/PAC bypass rather than disabling the whole client.
Routing & Switching Generator
Static routes, OSPF, BGP and VLAN/trunk configs across Cisco IOS/IOS-XE, Cisco Nexus (NX-OS), Juniper, Arista EOS, Aruba (AOS-CX), and the routing-capable firewall platforms.
Static Route
OSPF
BGP
MPLS
LDP label distribution, RSVP-TE traffic-engineered tunnels, or an L3VPN (VRF + MP-BGP) — the building blocks of an MPLS core/edge.
VLAN & Trunk (switching)
VoIP / IP Telephony
Voice VLAN + QoS trust for switch access ports, plus SIP/RTP handling (ALG, inspection, QoS marking) for the routing-capable firewalls — dual-stack (IPv4 + IPv6 SIP/RTP) aware.
voip.conf
Set the voice VLAN and SIP trunk details, then generate.
Mesh Networks
Wireless mesh backhaul between APs/routers — 802.11s (WPA3-SAE mesh), proprietary mesh (e.g. easy-mesh-style controller systems), or routed mesh protocols like OLSR / B.A.T.M.A.N.-adv for outdoor / IoT mesh links.
mesh-node.conf
Pick a mesh protocol and node role, then generate.
routing.conf
Choose a vendor above, fill parameters, and generate any of the sections.
SD-WAN Configurator
Dual-WAN SLA-based path selection: define the two circuits, the SLA thresholds, and which traffic class should follow them.
sdwan-policy.conf
Pick a vendor above, set the SLA thresholds, then click Generate config.
Network Connectivity Test simulated
Visualize the path between two networks and get a simulated test readout (ping / TCP handshake / traceroute / policy verdict). This is illustrative — run the real commands from the Troubleshooting tab to verify on an actual device.
Set source/destination and click "Run connectivity test" to see the path and results.
Troubleshooting Assistant
Pick a vendor and a symptom — get an ordered list of diagnostic commands to run.
diagnostic-sequence.txt
Select a vendor and an issue type above.
General Command Cheat Sheet by Vendor
All-Domain Troubleshooting Quick Reference
First checks for the most common issue in every domain this tool covers — jump to that tab's own generator/cheat-sheet for vendor-specific commands.
| Domain | Common issue | First check |
|---|---|---|
| Policy | Traffic unexpectedly blocked | Policy lookup / rule-match test (see Policy tab) — check for a broader deny rule matching earlier in the rulebase |
| NAT | Connectivity works internally but not through NAT | Confirm the translated address is actually reachable and the NAT rule order isn't shadowed by a more specific rule |
| Access Control | Admin/API access denied from an expected host | Verify the management-plane ACL includes the source IP and the correct service/port |
| VPN | Tunnel won't establish or flaps | Check Phase 1/2 proposal match and MTU/fragmentation (see VPN tab troubleshooting sequence) |
| Secure Connectivity | TLS/cert errors on a managed connection | Check certificate expiry and chain-of-trust on both ends |
| Segmentation | Two VLANs that should be isolated can reach each other | Check for an overly-broad "any-any" rule or a route leaking between VRFs/zones |
| Zscaler | User can't reach an internal app via ZPA | Confirm the App Connector is up and the access policy includes the user's group |
| Routing & Switching / MPLS | Route flapping or an LSP won't stay up | Check IGP adjacency stability on the underlying interface before suspecting BGP/MPLS itself |
| CCTV | Camera stream missing or NVR storage full | Confirm camera network reachability (ONVIF/RTSP ports) and audit recording mode vs. retention policy |
| IoT / IIoT | Device offline or publishing garbage data | Confirm it's still on its isolated VLAN and reachable from the broker/gateway; check for firmware drift |
| Wi-Fi & Cellular | Client can't roam or keeps dropping | Check RF overlap/channel plan and whether 802.11r/k/v is enabled on the SSID |
| Smart Home | Automation didn't fire | Confirm the device is still joined to its mesh network and the hub-to-device segmentation rule allows the needed port |
| Mesh Networks | Node dropped off the mesh or picked a bad path | Check hop count vs. configured max, and RSSI/link quality to the parent/neighbor node before suspecting the routing protocol |
| ISP Networks | Upstream BGP session down or route-flapping | Check peer interface/link state first, then BGP hold-timer expiry and prefix-limit teardown in the peering config |
| Satellite Networks | Link degraded or dropped (rain fade) | Check ACM MODCOD step-down events on the modem before assuming a hardware fault — most Ku/Ka outages are weather |
| Space Networks | Inter-satellite link lost or handover failed | Confirm the contact window/pointing schedule matched actual orbital position — most "ISL down" events are a missed acquisition window, not a fault |
| Data Center Networks | EVPN-VXLAN tenant traffic not forwarding | Verify the VTEP/loopback is reachable in the underlay before checking the overlay — EVPN can't build if BGP underlay peering is down |
| Cloud Networks | Peered/transit VPC can't reach the other side | Check route tables on both sides — peering doesn't auto-propagate routes, they must be added explicitly |
| AI Data Center Networks | Training job throughput collapsed | Check for PFC pause storms / ECN marking spikes on the rail leaf — congestion control misconfiguration is the most common cause, not the GPUs themselves |
| CDN | Stale content served after an update | Confirm the purge actually matched the cache key (including query-string components) rather than just the path |
| Sensor Networks | Node reporting stopped | Check battery/duty-cycle first, then confirm it hasn't fallen out of mesh range or been orphaned by a routing-table change |
| Interplanetary Networks | Bundle never arrived | Check whether the contact window it was scheduled on actually opened — a missed contact, not a lost bundle, is the usual cause given custody transfer |
| Deep Space Communications | Telemetry dropouts or low SNR | Confirm antenna pointing/tracking against the current ephemeris — a stale pointing solution looks identical to a link fault at these distances |
| Internet / Interplanetary Internet | Earth-side traffic not bridging to the space side | Confirm the gateway's earth0↔space0 bridge is actually translating flows to bundles, not just routing IP toward a dead-end interface |
Automation Generator
Ansible playbooks and Python (Netmiko) scripts for common day-2 operations, plus a backup scheduler.
Ansible Playbook
Python (Netmiko) Script
automation.yml
Choose a vendor and generate a playbook or script.
Nightly Backup Scheduler (cron + shell)
Pick a schedule preset (or write a custom cron expression), then generate the crontab entry and retention cleanup job.
backup-cron.sh
Set the 5 fields (or a preset) and the command, then click Generate crontab.
Cross-Domain Automation Snippets
Pick any domain covered by this tool and get a representative automation snippet (Ansible / Python / Terraform / API script / Node-RED) for that domain's most common day-2 automation task.
cross-domain-automation.yml
Pick a domain and scope, then click Generate snippet.
Automation Maturity Model (applies across every domain above)
| Level | What it looks like |
|---|---|
| 0 — Manual | CLI/GUI changes by hand, no version control, tribal-knowledge runbooks |
| 1 — Scripted | Ad-hoc scripts (Python/Netmiko, shell) run manually for repetitive tasks like backups |
| 2 — Orchestrated | Ansible/Terraform playbooks in source control, run on-demand with peer review |
| 3 — Pipelined (CI/CD) | Changes flow through a CI/CD pipeline with automated validation/linting before push |
| 4 — Closed-loop / self-healing | AIOps detection (see AIOps tab) automatically triggers a remediation playbook, with human approval or full auto-remediation for low-risk actions |
AIOps & Intelligent Automation
Simulated AI-assisted network operations — machine learning, automated monitoring, anomaly detection, predictive analysis, automated remediation, and root-cause analysis — plus how the same intelligent-automation stack extends into MLOps, Robotic Process Automation (RPA), and physical robotics: building robots, ROS/ROS2, robot fleet management, predictive robot maintenance, and autonomous systems like drones and vehicle robots (AMRs/AGVs).
Simulated AIOps Insight Generator simulated
Pick a symptom and a platform — get a mock AI-style insight report (anomaly, correlated signals, probable root cause, recommended remediation). This is a template for illustration, not a live model.
ai-insight-report
Pick a symptom and platform, then click Generate AI insight.
AIOps Pillars
The six capabilities that make up "AIOps" as used across this tool and the industry.
| Pillar | What it does |
|---|---|
| Machine Learning | Learns normal baselines from historical telemetry (traffic, logs, sensor/robot data) instead of relying on fixed thresholds, and improves as more data is collected. |
| Automated Monitoring | Continuously collects and correlates telemetry across devices, links, applications, and — in an intelligent-automation shop — RPA bots and robot fleets, without manual polling. |
| Anomaly Detection | Flags statistically significant deviations from the learned baseline (latency spikes, flapping, drift, a bot failing mid-run, a robot's motor current trending abnormally) before they become outages. |
| Predictive Analysis | Projects trends forward — circuit saturation dates, component wear curves, storage exhaustion — so action happens before failure, not after. |
| Automated Remediation | Executes a pre-approved fix (failover a circuit, restart a bot, quarantine a device, pause a robot for service) automatically or with one-click human approval. |
| Root Cause Analysis | Correlates signals across layers to point at the underlying cause rather than the symptom — see the generator above for a worked example. |
AIOps Techniques & Concepts
| Concept | What it means in practice |
|---|---|
| Intent-based networking (IBN) | Describe the desired outcome (e.g. "keep VoIP under 150ms") and the system translates it into device config and continuously verifies it. |
| ML-based anomaly detection | Baseline normal traffic/telemetry patterns, then flag statistically significant deviations instead of relying on static thresholds alone. |
| Closed-loop automation | Detection → diagnosis → remediation happens automatically (e.g. auto-failover a circuit, or auto-restart a stalled RPA bot) with a human approving or auditing after the fact. |
| Digital experience monitoring (DEM) | Synthetic transactions from branch/user vantage points measure real application experience, not just link up/down. |
| NLP-driven configuration | Natural-language request → generated vendor config, the same pattern this tool uses for policy/VPN/routing generation. |
| Predictive capacity planning | Trend WAN/link utilization — or robot battery/component wear — forward to flag what will fail or saturate before it actually does. |
Where AI Shows Up in These Platforms Today
| Vendor | AI / AIOps offering |
|---|---|
| Cisco / Meraki | Meraki's built-in AI-powered network insights, Catalyst Center AI Assurance, and ThousandEyes for digital experience monitoring. |
| Juniper | Mist AI with the Marvis Virtual Network Assistant — conversational root-cause analysis across wired/wireless/SD-WAN. |
| Fortinet | FortiAI and FortiGuard AI-based threat/anomaly detection embedded across the Fortinet Security Fabric. |
| Palo Alto | Precision AI embedded across NGFW/Prisma products, plus Cortex XSIAM for AI-driven SOC operations. |
| Checkpoint | ThreatCloud AI for threat prevention, plus Infinity AI Copilot for natural-language policy assistance. |
| Aruba (HPE) | Aruba Central AIOps — client health scoring and root-cause suggestions across wired, wireless, and SD-WAN. |
| Ubiquiti | UniFi Network's built-in AI-based client/RF insights and anomaly highlighting in the Network app. |
| AWS IoT | AWS IoT Device Defender — fleet-wide behavioral anomaly detection for IoT/IIoT device telemetry. |
| Azure IoT | Azure IoT Hub + Azure Digital Twins with anomaly detection pipelines (Azure Stream Analytics / ML). |
| Google Home / Nest | On-device and cloud ML for presence/activity-based automation suggestions in the smart-home ecosystem. |
These are the vendors' actual product lines as of this writing — check each vendor's site for current capabilities and licensing, since AI feature sets move quickly.
MLOps — Operationalizing the Models Behind AIOps
AIOps insights are only as good as the ML models feeding them. MLOps is the discipline that gets those models built, deployed, and kept accurate over time.
| Stage | What happens |
|---|---|
| Data collection & labeling | Telemetry (NetFlow, syslog, sensor/robot data, RPA run logs) is aggregated, cleaned, and labeled with known-good/known-bad outcomes. |
| Feature engineering | Raw telemetry is turned into model inputs — rolling averages, rate-of-change, error-rate ratios, retry counts. |
| Model training & validation | Candidate models are trained on historical data and validated against held-out incidents to check they actually predict/detect correctly. |
| Model registry & versioning | Approved models are versioned and stored (e.g. MLflow, SageMaker Model Registry, Vertex AI) so any deployed model is traceable and reproducible. |
| CI/CD for models | Automated pipelines test, package, and roll out a new model version the same way application CI/CD ships code. |
| Serving / inference | The model runs against live telemetry — in the cloud, at the edge, or on-device (e.g. inference running on a robot's onboard compute for real-time obstacle avoidance). |
| Monitoring & drift detection | The model's own accuracy is monitored; when real-world data drifts from training data, it's flagged for retraining — this is MLOps applying AIOps-style monitoring to itself. |
| Retraining loop | New labeled data (including corrected false positives/negatives from AIOps or robot incidents) feeds back into training the next model version. |
In short: MLOps builds and maintains the models; AIOps is one of the biggest consumers of those models in an operations context.
MLOps Pipeline Generator simulated
Describe the model use case — get a tailored MLOps pipeline plan (data sources, model type, tooling, monitoring/retraining cadence).
mlops-pipeline-plan.txt
Describe the use case, pick a deployment target, then generate.
Robotic Process Automation (RPA)
Software "bots" that automate repetitive, rules-based digital work by driving existing applications the way a human would — clicking, typing, reading screens, moving data between systems.
| Aspect | Detail |
|---|---|
| What it automates | High-volume, repetitive, rules-based tasks: data entry, invoice processing, ticket triage, report generation, form-to-system data transfer. |
| RPA vs AIOps | AIOps automates IT operations decisions (detect/diagnose/fix infrastructure); RPA automates business-process execution across applications. They compose well: an AIOps alert can trigger an RPA bot to open a ticket, gather diagnostics, or roll back a change. |
| Intelligent Process Automation (IPA) | RPA + AI/ML (OCR, NLP, classification models) so bots can handle unstructured input — reading a scanned invoice, classifying a support email — not just fixed-format screens. |
| Popular platforms | UiPath, Automation Anywhere, Microsoft Power Automate, Blue Prism. |
| Orchestration | A central orchestrator schedules bots, manages credentials/queues, and reports run status/failures — the same fleet-management pattern used for physical robots below. |
| Good RPA candidates | High volume, low exception rate, stable UI/system, clear rules, currently done manually by people copying data between systems. |
RPA Bot Workflow Generator simulated
Describe the manual process — get a bot workflow outline, exception handling plan, and a rough time-saved estimate.
rpa-bot-workflow.txt
Describe the process, pick a platform, then generate.
Robotics & Physical Intelligent Automation
Where "intelligent automation" leaves the screen and moves into physical space.
| Category | Definition | Example |
|---|---|---|
| Physical Robotics | The hardware layer — chassis, actuators, motors, manipulators/end-effectors, sensors, power system — that lets software act in the physical world. | An industrial arm, a mobile base, a drone airframe. |
| Robotic Process Automation (RPA) | The software-bot form of automation described above — included here because "RPA" and "physical robotics" are often confused despite automating different layers (digital work vs. physical work). | A bot that reconciles invoices between two ERP systems. |
| Autonomous Robots | Robots that sense, plan, and act without step-by-step human control — they perceive their environment, make navigation/task decisions, and execute, only escalating exceptions to a human. | An AMR (autonomous mobile robot) routing itself around a warehouse floor. |
| AI-Powered Robots | Robots whose perception/decision-making is driven by ML models (computer vision, reinforcement learning, LLM-based task planning) rather than fixed scripted behavior. | A picking robot that visually identifies and grasps novel SKUs it wasn't explicitly programmed for. |
| Robot Fleet Management | The orchestration layer coordinating many robots at once — task allocation, traffic/collision management, software/OTA updates, remote monitoring, and dashboards. | A warehouse operations center tracking 200 AMRs in real time. |
| Predictive Robot Maintenance | Applying AIOps-style ML to robot telemetry (motor current, vibration, battery cycle health, joint error rates) to schedule service before a component fails, instead of on a fixed calendar or after breakdown. | Flagging a wheel motor whose current draw is trending upward for maintenance next week. |
Robot Fleet Health & Predictive Maintenance Report simulated
Enter a fleet size and type — get a simulated fleet-health snapshot with predictive-maintenance flags, the same AIOps loop applied to physical robots.
robot-fleet-report.txt
Set fleet size/type, then generate.
How to Build a Robot — From Concept to Deployment
The stack a robot needs, roughly bottom-to-top, whether it's a small hobby project or an industrial fleet unit.
| Step | What it covers |
|---|---|
| 1. Define the mission | What task, in what environment, at what duty cycle/payload — this drives every hardware choice that follows. |
| 2. Mechanical design | Chassis/frame, drivetrain or airframe, manipulator/end-effector if needed; material and form factor for the operating environment. |
| 3. Actuation | Motors (DC, brushless, servo, stepper) and motor controllers/ESCs sized for the required torque, speed, and payload. |
| 4. Power system | Battery chemistry/capacity (or tethered/PoE power), voltage regulation, and — for fleets — a charging/swap strategy. |
| 5. Sensing | Proprioceptive (IMU, wheel/motor encoders, current sensors) and exteroceptive (LiDAR, depth/RGB cameras, ultrasonic, GPS/RTK) sensors for state estimation and perception. |
| 6. Compute platform | Onboard compute sized for the workload — microcontroller (real-time control loops) plus, for perception/AI, an SBC or GPU module (e.g. Jetson-class) running the higher-level stack. |
| 7. Middleware | A robotics framework — typically ROS or ROS2 (see below) — to move sensor/control data between processes and reuse existing drivers, planners, and tools instead of writing everything from scratch. |
| 8. Perception & localization | SLAM (simultaneous localization and mapping), sensor fusion (e.g. an extended Kalman filter combining IMU + wheel odometry + GPS), and object/obstacle detection. |
| 9. Planning & control | Path/motion planning (global route + local obstacle avoidance) and the low-level control loops that turn a planned path into motor commands. |
| 10. Safety systems | Hardware E-stop, safety-rated speed/force limiting, geofencing, watchdog timers, and a fail-safe behavior (stop-in-place) if communication or sensing is lost. |
| 11. Communications | How the robot talks to the network — Wi-Fi/cellular for AMRs, RF telemetry links for drones — see the Autonomous Systems table below for the connectivity design. |
| 12. Simulate before you deploy | Validate navigation, manipulation, and edge cases in simulation (Gazebo/Ignition, NVIDIA Isaac Sim, Webots) where failures are free. |
| 13. Field test & iterate | Controlled real-world trials, log everything (rosbag or equivalent), and feed failures back into the perception/planning stack. |
| 14. Fleet operations | Once one robot works, add fleet management, OTA software updates, remote monitoring, and predictive maintenance (see the Robot Fleet Management row above) to run many. |
Robot Build Planner simulated
Describe the mission — get a tailored build plan (chassis, sensing, compute, comms, safety) following the 14-step stack above.
robot-build-plan.txt
Describe the mission, pick an environment, then generate.
Robot Hardware, Chips & Circuit Fundamentals
The silicon underneath everything above — what actually sits on a robot's circuit boards.
| Category | Examples | Role |
|---|---|---|
| Microcontroller (MCU) | STM32 (ARM Cortex-M), ESP32, RP2040 | Runs hard-real-time control loops — motor commutation, sensor polling — where jitter isn't acceptable. |
| SoM / SBC compute | NVIDIA Jetson Orin, Raspberry Pi CM4/CM5, Qualcomm Robotics RB-series | Runs perception, planning, and the ROS2 stack — everything that isn't hard-real-time. |
| AI accelerator / NPU | Google Edge TPU, Hailo-8, Jetson's on-die NPU, Intel Movidius | Offloads neural-network inference from the CPU for real-time vision, grasp planning, or speech. |
| Motor driver IC | TMC5160/2209 (stepper), DRV8323 (BLDC/FOC gate driver) | Converts logic-level commands into the high-current waveforms that actually drive a motor. |
| Power management IC (PMIC) / BMS | TI BQ-series, Analog Devices LTC-series | Regulates and protects the battery, and generates the multiple voltage rails a robot needs from one pack. |
| Sensor ICs | MEMS IMU (BMI088/ICM-42688), force/torque ASICs, capacitive/piezoresistive tactile arrays | Convert a physical quantity (motion, force, touch) into a digital signal the compute stack can read. |
| Communication transceivers | CAN-FD transceiver, EtherCAT ASIC, UWB radio, BLE/Wi-Fi module | Move data between distributed boards across the robot's body, and to the outside world. |
PCB Assembly & Packaging Methods — SMT, THT, COB & Beyond
How a chip actually gets attached to a board, and which method fits which part of a robot.
| Method | How it works | Where it fits in robotics |
|---|---|---|
| Through-Hole (THT) | Component leads pass through drilled holes and are soldered on the opposite side. | High-current connectors, terminal blocks, and parts needing real mechanical strength (battery terminals, motor leads). |
| Surface-Mount (SMT/SMD) | Packaged components sit directly on copper pads and are reflow-soldered. | The default for almost every modern robot board — MCUs, passives, sensor ICs. |
| Chip-on-Board (COB) | A bare, unpackaged die is glued directly to the PCB, wire-bonded to the board's pads, then sealed under a "glob-top" epoxy blob instead of a plastic package. | Extreme space-constrained nodes — a tactile-sensor array in a humanoid fingertip, an LED-matrix "face" board — anywhere board space and package height are both scarce. |
| System-in-Package (SiP) | Multiple bare die (a compute chiplet, memory, an RF chip) are bonded together inside one package before it ever reaches the PCB. | Compact SoMs where several chips need to behave as a single part on the board. |
| Flip-chip | The die is flipped face-down, its solder bumps connecting directly to the PCB/package without wire bonds. | High pin-count, high-speed parts (advanced SoCs) where wire-bond inductance would ruin signal integrity. |
| 2.5D / 3D chip stacking | Multiple dies are stacked vertically or side-by-side on a silicon interposer, connected through-silicon vias (TSVs). | Chiplet-based compute modules — the emerging way to pack a CPU + NPU + memory into one robotics compute package. |
| Flex / rigid-flex PCB | A polyimide flexible circuit replaces or joins rigid FR4 sections. | Routing across a robot's joints (shoulder, elbow, wrist) without a wire harness, or wrapping electronics onto a curved surface. |
Chip-on-Board (COB) in more detail — three steps: die attach (the bare die is glued face-up to the board), wire bonding (fine gold or aluminum wires connect the die's bond pads to the PCB's pads), then glob-top encapsulation (an epoxy dome protects the exposed die and wires). It gives the lowest possible height/footprint and a short thermal path straight into the board, at the cost of being hard to rework and needing bare-die supply and tighter (near clean-room) process control than standard SMT.
Robot Hardware & PCB Design Generator simulated
Describe any design — a humanoid, a hexapod, a delivery drone, whatever — and get a tailored chip stack, PCB/board architecture, an assembly-method plan (including where COB makes sense), a build sequence, and a few forward-looking directions for that design.
robot-hardware-pcb-plan.txt
Describe the design, pick an assembly method, then generate.
PCB Component Assembly / Disassembly Preview simulated
Auto-updates from the assembly method chosen above — a rotatable 3D view of a representative board showing where each component sits, with an exploded view to see how it comes apart (and back together).
PCB Design Generator simulated
Name a single board (not the whole robot) — get a concrete BOM with reference designators, a net list, a layer stack-up, DRC guidance, and an ASCII top-down silhouette.
pcb-design.txt
Name the board, pick an assembly method, then generate.
Robot 3D Design Preview simulated
Pick any robot type — get a rotatable 3D block model of it, built live in the browser (drag to rotate, scroll to zoom, no external files).
ROS / ROS2 — Robot Operating System
The de facto middleware for robotics software — not an OS in the traditional sense, but a set of libraries, tools, and conventions for building robot software as communicating processes.
| Concept | What it means |
|---|---|
| Node | A single-purpose process — e.g. a camera driver, a path planner, a motor controller — that does one job and communicates with other nodes. |
| Topic | A named, typed, many-to-many publish/subscribe data stream (e.g. /scan for LiDAR data) — the primary way nodes share continuous data. |
| Service | A synchronous request/response call between nodes (e.g. "recompute the global path now") for one-off operations rather than a continuous stream. |
| Action | A long-running, goal-oriented request (e.g. "navigate to this waypoint") that reports feedback and can be canceled mid-execution. |
| Parameter | Runtime-configurable values (max speed, sensor thresholds) a node reads without a code change or rebuild. |
| Package | The unit of software reuse/distribution — a bundled set of nodes, configs, and launch files for one capability (e.g. a LiDAR driver package). |
| Launch file | Starts and configures a whole set of nodes together as one runnable system, instead of starting each node by hand. |
| tf (transform tree) | Tracks the geometric relationship between every coordinate frame on the robot (base, sensors, arm joints) over time, so any point can be translated between frames. |
| URDF | An XML format describing the robot's physical structure (links, joints, sensor mounts) used for simulation, visualization, and the tf tree. |
| ROS1 vs ROS2 | ROS2 replaces ROS1's central master with a DDS-based decentralized discovery layer, adds real-time and multi-robot support, and has a built-in security model (DDS-Security) — ROS1 reached end-of-life and new projects should start on ROS2. |
| Common tooling | RViz (3D visualization), Gazebo/Ignition (physics simulation), MoveIt (manipulation planning), Nav2 (autonomous navigation stack), rosbag (record/replay sensor data for testing). |
Network angle (this tool's focus): ROS2's DDS discovery is multicast-based by default, so multi-robot or robot-to-basestation links usually need dedicated VLANs/SSIDs, multicast allowed, and QoS/latency budgets similar to the VoIP guidance in the Routing & Switching tab — treat a robot cell as its own segmented network the same way the IoT/IIoT and Smart Home tabs segment those devices.
ROS2 Node & Topic Architecture Generator simulated
Describe the robot/task — get a plausible ROS2 node graph, key topics/actions, a launch-file skeleton, and the recommended stack (Nav2 / MoveIt2 / PX4).
ros2-architecture.txt
Describe the robot/task, pick a distro, then generate.
ROS Programming Generator simulated
Describe what the node should do — get real, runnable starter code (a Python or C++ node, package.xml, build file, and a launch/run snippet) tailored to the topic/action pattern for that kind of robot.
ros_node.py
Describe the node, pick language/distro, then generate.
Autonomous Systems: Drones & Vehicle Robots
| System | Connectivity & network design |
|---|---|
| Drones (UAVs) | A command-and-control (C2) telemetry link (typically 900MHz/2.4GHz/5.8GHz RF, or cellular for BVLOS), GPS/RTK for positioning, onboard companion computer for vision/autonomy, geofencing enforced in software, and Remote ID broadcast for regulatory compliance. |
| Drone swarms | Mesh or hub-and-spoke RF between units for coordination, with a ground-station link for oversight; latency and packet loss budgets are far tighter than typical Wi-Fi/cellular assumptions. |
| AMRs (autonomous mobile robots) | Indoor Wi-Fi roaming (802.11r/k/v — same fast-transition need as the Wi-Fi & Cellular tab) between APs as the robot moves through a facility, on a segmented VLAN/SSID separate from IT traffic. |
| AGVs (automated guided vehicles) | Often wired/fixed-path with simpler connectivity needs than AMRs, but still typically isolated on their own VLAN with a safety-rated E-stop network independent of the data network. |
| Autonomous road vehicles | V2X (vehicle-to-everything: V2V, V2I, V2N) over cellular-V2X or DSRC for situational awareness beyond onboard sensors, plus cellular backhaul for fleet telemetry and OTA updates. |
| Common thread | All of these need a safety-rated fail-safe (stop-in-place on link loss), a segmented network boundary from corporate/IT traffic, and telemetry feeding back into the predictive-maintenance and fleet-management loop described above. |
Autonomous System Connectivity & Safety Planner simulated
Pick the system type and describe the environment — get a tailored connectivity, positioning, fail-safe, and compliance plan.
autonomous-system-plan.txt
Pick a system type, describe the environment, then generate.
AIOps Coverage Across All Domains
How the anomaly-detection → root-cause → remediation loop applies to every domain in this tool.
| Domain | Typical telemetry | AIOps focus |
|---|---|---|
| Policy / NAT / Access Control | Hit counts, session tables, log volume | Unused/shadowed rule detection, anomalous-source blocking suggestions |
| VPN / Secure Connectivity | IKE/IPsec SA state, rekey timing, jitter | Predictive tunnel-instability detection (see MTU/fragmentation template above) |
| Segmentation | Inter-VLAN flow logs, drift diffs | Config-drift detection, east-west anomaly flagging |
| Zscaler / SSE | Cloud proxy logs, ZIA/ZPA telemetry | Anomalous SaaS access patterns, policy-gap suggestions |
| Routing & Switching / MPLS | IGP/BGP state, LSP status, interface counters | Flap correlation, LSP instability root-causing (see template above) |
| CCTV | Storage utilization, per-camera bitrate/frame-drop | Storage-exhaustion forecasting, stream-degradation triage |
| IoT / IIoT | Publish frequency, payload distribution, register values | Behavioral anomaly detection, device quarantine suggestions |
| Wi-Fi & Cellular | RSSI/SNR, retry rate, roaming events, APN failover state | RF-plan suggestions, failover-flap detection |
| Smart Home | Automation execution logs, device online/offline state | Automation-failure triage, mesh-network health scoring |
| RPA / Intelligent Process Automation | Bot run logs, exception rate, queue depth, execution time | Stuck/failed bot detection, exception-pattern root-causing, auto-retry/auto-restart |
| Robotics / Autonomous Systems | Motor current, battery cycle health, vibration, link RSSI, localization confidence | Predictive component maintenance, fleet-wide connectivity anomaly detection, task-allocation optimization |
CCTV / IP Camera Config Generator
Camera network provisioning, NVR/VMS recording profiles, and a camera-VLAN firewall rule across Axis, Hikvision, Dahua, Uniview/generic ONVIF and Cisco Meraki MV.
Camera Network / ONVIF Provisioning
NVR / VMS Recording Profile
cctv-provision.conf
Choose a vendor above, fill parameters, and generate.
Camera VLAN Segmentation Rule
Isolate the camera VLAN so cameras can only reach the NVR/VMS server and the internet for firmware/cloud backup — not the corporate LAN.
cctv-segmentation.conf
Set the fields and click Generate segmentation rule.
Common CCTV / ONVIF Ports & Notes
| Port / Protocol | Purpose |
|---|---|
| TCP 80 / 443 | Camera web UI / ONVIF device management (HTTP/HTTPS) |
| TCP 554 | RTSP stream negotiation |
| UDP 5353 | mDNS / device discovery on the local segment (should not cross VLANs) |
| TCP 3702 | WS-Discovery (ONVIF camera discovery) |
| UDP 37000-65535 (vendor-specific) | RTP media stream ports — check vendor docs for the exact range |
| TCP 8000/8899 (Hikvision/Dahua) | Proprietary SDK/mobile-app port — restrict to the NVR only |
Best practice: cameras live on an isolated VLAN with no direct internet inbound, no lateral access to user/server VLANs, and firmware updates pulled through the NVR/VMS or a controlled proxy.
IoT & IIoT Generator
Device provisioning and protocol configs for consumer/enterprise IoT (MQTT, AWS IoT Core, Azure IoT Hub) and industrial IIoT (Modbus TCP, OPC-UA), plus an IoT VLAN segmentation rule.
Device / Broker Provisioning
IIoT Polling (Modbus TCP / OPC-UA)
iot-provision.conf
Choose a platform above, fill parameters, and generate.
IoT/IIoT VLAN Segmentation Rule
IoT and IIoT devices should never sit on the corporate/user VLAN — isolate them and only allow the specific flows they need (broker/gateway/historian).
iot-segmentation.conf
Set the fields and click Generate segmentation rule.
Common IoT / IIoT Protocol Ports
| Port / Protocol | Purpose |
|---|---|
| TCP 1883 / 8883 | MQTT (plaintext / TLS) |
| TCP 502 | Modbus TCP (industrial control — should never be internet-facing) |
| TCP 4840 | OPC-UA |
| TCP 5683 / 5684 (UDP) | CoAP (plaintext / DTLS) |
| TCP 8443 / 443 | AWS IoT Core / Azure IoT Hub HTTPS device endpoints |
| TCP 102 | S7comm (Siemens PLC) — segment and restrict tightly |
IIoT/OT protocols (Modbus, S7comm, DNP3) generally lack authentication — the network segmentation and firewall boundary is the security control, not the protocol itself.
Wi-Fi & Cellular Network Generator
SSID/WLAN profiles across Cisco Meraki MR, Cisco Catalyst/WLC, Aruba, Ubiquiti UniFi and FortiAP, plus a cellular WAN failover (APN) config for LTE/5G routers.
SSID / WLAN Profile
Cellular WAN Failover (LTE/5G)
wifi-profile.conf
Choose a vendor above, fill parameters, and generate.
Wi-Fi & Cellular Troubleshooting Quick Reference
| Symptom | Likely cause / first check |
|---|---|
| Clients stuck on 2.4GHz | Band steering disabled or 5GHz coverage hole — check RF/AP placement |
| Slow roaming / drops between APs | 802.11r/k/v (fast transition) not enabled, or mismatched power levels between APs |
| RADIUS auth failures | Shared secret mismatch, NAS-IP not whitelisted on RADIUS server, or clock skew (EAP-TLS cert validity) |
| Cellular failover not triggering | Track object / IP SLA not actually monitoring the right target, or threshold too lenient |
| High cellular data usage | Failover flapping (primary WAN unstable) — check primary link stability before blaming the APN |
Smart Home System Generator
Automation rules and device-network configs for Home Assistant / Zigbee2MQTT / Matter-Thread ecosystems, plus a smart-home VLAN segmentation rule.
Automation Rule (trigger → condition → action)
Device Pairing / Network Join
smarthome.yaml
Choose a platform above, fill parameters, and generate.
Smart Home VLAN Segmentation Rule
Keep consumer smart-home devices off the main household/user network — most have weak update hygiene and shouldn't be able to reach laptops, NAS, or work devices directly.
smarthome-segmentation.conf
Set the fields and click Generate segmentation rule.
ISP / Carrier Network Config Generator
Upstream BGP peering, RPKI origin validation, and subscriber-edge provisioning (PPPoE / DHCP / static) across the major carrier-grade platforms.
Upstream BGP Peering
isp-bgp-peer.conf
Set ASNs and peer IP, then generate.
Subscriber Edge Provisioning
isp-subscriber-edge.conf
Pick an access method and generate.
Peering & RPKI Quick Reference
| Concept | Note |
|---|---|
| IX peering | Public peering over an internet exchange fabric (route-server) vs. private PNI for high-volume pairs |
| RPKI ROA | Route Origin Authorization ties a prefix to the AS allowed to originate it — validate at the edge, don't just log |
| Prefix-list / max-prefix | Always cap max-prefix per peer session to prevent a leak from taking down the router's RIB |
| IRR filtering | Build peer prefix-lists from IRR/RPSL (bgpq3/bgpq4) rather than hand-maintaining them |
| CGNAT (subscriber edge) | 100.64.0.0/10 shared address space (RFC 6598) is the standard CGNAT pool range, not RFC1918 |
Satellite Network Config Generator
VSAT / earth-station link parameters and remote-site provisioning across the major satellite hub/modem platforms.
Earth Station / Modem Link
sat-earth-station.conf
Set band/modulation/slot, then generate.
Remote Site Provisioning
sat-remote-site.conf
Set the site ID and LAN subnet, then generate.
Space Networks Config Generator
Inter-satellite link (ISL) backbone and ground-station handover planning for LEO/MEO/GEO constellations.
Inter-Satellite Link (ISL)
isl-node.conf
Pick a constellation/crosslink type, then generate.
Ground Station Handover
ground-handover.conf
Set the ground station and thresholds, then generate.
Data Center Network Config Generator
Leaf-spine (Clos) EVPN-VXLAN fabric underlay/overlay and MLAG/vPC + DCI configs across the major DC switching platforms.
Leaf-Spine EVPN-VXLAN Fabric
dc-fabric-leaf.conf
Set fabric size and VNI, then generate.
MLAG / vPC + DCI
dc-mlag-dci.conf
Set peer-link and DCI transport, then generate.
Cloud Network Config Generator
VPC/VNet + subnet layout and cross-network peering/transit across the major public clouds.
VPC / VNet & Subnets
vpc-network.tf
Set CIDR/region, then generate.
Peering / Transit
vpc-peering.tf
Set the peer CIDR and transit method, then generate.
AI Data Center Network Config Generator
Rail-optimized, non-blocking GPU cluster fabrics (RoCEv2/InfiniBand) with lossless RDMA tuning for large-scale training clusters.
Rail-Optimized GPU Fabric
ai-fabric-plan.conf
Set node count and transport, then generate.
RDMA / Lossless QoS Tuning
ai-rdma-qos.conf
Set PFC/ECN parameters, then generate.
CDN Config Generator
Edge caching rules and Anycast/WAF edge policy across the major content delivery platforms.
Edge Caching Rule
cdn-cache-rule.conf
Set origin/path/TTL, then generate.
Anycast / WAF Edge Policy
Pick a WAF mode and rate limit, then generate.
Sensor Network Config Generator
Low-power wireless sensor node provisioning and gateway/mesh routing across LoRaWAN, Zigbee, Thread/6LoWPAN, and BLE mesh.
Sensor Node Provisioning
sensor-node.conf
Pick a protocol, then generate.
Gateway / Mesh Routing
sensor-gateway.conf
Set the gateway ID and broker, then generate.
Interplanetary Network (DTN) Config Generator
Delay/Disruption-Tolerant Networking — Bundle Protocol (BPv7) nodes and contact-graph routing plans for links spanning light-minutes to light-hours.
Bundle Protocol (BPv7) Node
dtn-node.conf
Set the IPN node/service number, then generate.
Contact Plan Entry (CGR)
contact-plan.txt
Set the contact window and OWLT, then generate.
Deep Space Communications Config Generator
CCSDS telemetry/command frame parameters and link-budget/one-way-light-time planning for Deep Space Network-class links.
Link Budget & Timing
deepspace-link.txt
Set distance/band/rate, then generate — one-way light time is computed from distance.
CCSDS Telemetry / Command Frame
ccsds-frame.conf
Set SCID/VCID/frame type, then generate.
Internet / Interplanetary Internet Gateway Generator
Configure a terrestrial Internet edge/WAN uplink, then bridge that TCP/IP network to the DTN-based Interplanetary Internet (Solar System Internet) — gateway node config plus the IPN addressing scheme reference.
Internet Edge / WAN Uplink (dual-stack)
internet-edge.conf
Set the uplink options, then generate.
Internet Reference — protocols, transition mechanisms & routing hygiene
| Concept | Note |
|---|---|
| DNS | Resolves names to addresses; run a recursive resolver or forward to a public one (1.1.1.1, 8.8.8.8, 9.9.9.9), and prefer resolvers that also answer AAAA for dual-stack clients |
| DoH / DoT | DNS-over-HTTPS / DNS-over-TLS encrypt resolver queries — worth enabling on the edge firewall's own DNS client and considering for LAN clients |
| NTP | Clock sync is a prerequisite for TLS certificate validation, log correlation, and routing-protocol authentication timestamps — never skip it |
| CGNAT | If the ISP hands out a private/shared address (100.64.0.0/10) instead of a routable public IPv4, inbound port-forwarding won't work — IPv6 (which is rarely CGNATed) is the usual workaround for inbound reachability |
| IPv6 transition — DHCPv6-PD | The ISP delegates a routed prefix (e.g. /56) to the WAN router, which then sub-delegates /64s to internal VLANs — the standard "real" way to get LAN-wide IPv6 today |
| IPv6 transition — 464XLAT / NAT64+DNS64 | Lets an IPv6-only access network reach the legacy IPv4 Internet by synthesizing AAAA records and translating at a gateway — common on mobile/cellular networks |
| IPv6 transition — 6to4 / Teredo / 6rd | Older automatic tunneling mechanisms for reaching IPv6 over an IPv4-only path; mostly superseded by native dual-stack or DHCPv6-PD, but still seen on legacy gear |
| NPTv6 | IPv6 equivalent of NAT, but a 1:1 prefix translation (no port overload like PAT) — used sparingly, since IPv6's address abundance means most sites just route instead of translating |
| RPKI / ROA | Cryptographically attests which AS is authorized to originate a prefix; enable Route Origin Validation on the Internet edge/transit router to drop invalid (hijacked/misconfigured) BGP announcements |
| IXP (Internet Exchange Point) | A shared fabric where many networks peer directly, cutting latency/cost versus routing everything through transit — relevant once you're running your own AS/BGP |
| Anycast | The same IP is announced from multiple locations; BGP/IGP routes each client to the topologically nearest instance — how public DNS resolvers and CDNs achieve low latency globally |
| TLS / HTTPS | Modern Internet traffic is expected to be encrypted end-to-end; terminate/inspect only where policy requires it, and keep certificates and cipher suites current |
| MTU / PMTUD | PPPoE (1492), various tunnel overlays (IPsec, GRE, VXLAN) and IPv6 (which forbids in-path fragmentation) all shrink the usable MTU — black-holed Path MTU Discovery is a classic "some sites work, some don't" symptom |
| BCP38 / Source-address validation | Filter or uRPF-check traffic leaving the network so that spoofed source addresses can't be used for DDoS reflection/amplification — good practice for anyone announcing routes to the Internet |
Earth ⇄ IPN Gateway Node
ipn-gateway.conf
Set interfaces/node number, then generate.
IPN Addressing Reference
| Concept | Note |
|---|---|
| node.service | IPN scheme address, e.g. ipn:27.1 — node 27, service 1 (analogous to IP:port, but store-and-forward, not end-to-end) |
| Bundle Protocol (BPv7) | RFC 9171 — the interplanetary-internet equivalent of IP; bundles hop store-and-forward across disrupted links |
| No end-to-end TCP | Round-trip times of minutes-to-hours make TCP's ACK/retransmit model unusable beyond a single hop — DTN uses custody transfer instead |
| Gateway role | Translates terrestrial TCP/IP traffic into bundles at the Earth-side edge, and back to TCP/IP for any Earth-bound destination |