Catalyst Center: Troubleshooting and Zero Trust Deployment

Introduction

Imagine arriving at work on Monday morning only to discover that your Catalyst Center is stuck in maintenance mode after a weekend upgrade, your inventory shows dozens of devices in an unmanaged state, and your security team is demanding better endpoint visibility across the campus. These are not hypothetical problems. They are the everyday reality for network engineers managing enterprise infrastructure, and mastering Catalyst Center troubleshooting is the skill that separates a reactive firefighter from a proactive network architect.

Cisco Catalyst Center, formerly known as Cisco DNA Center, is the central management and automation platform for enterprise campus networks. It handles everything from device inventory and software image management to network assurance and policy-based segmentation. As organizations pursue Zero Trust security models, Catalyst Center also serves as the orchestration engine for endpoint visibility, network segmentation through SD-Access, and trust-based access control.

This article provides a comprehensive, hands-on guide to troubleshooting the most common Catalyst Center issues and deploying a Zero Trust workplace strategy. You will learn the platform's underlying architecture, essential CLI commands for diagnosing problems, step-by-step procedures for resolving inventory, provisioning, SWIM, assurance, and upgrade failures, and a complete walkthrough of the Zero Trust journey from endpoint discovery to threat containment.

What Is the Catalyst Center Architecture?

Before you can troubleshoot any system effectively, you need to understand how it is built. Catalyst Center is a microservices-based platform running on dedicated hardware appliances or in the cloud.

Hardware Generations

Catalyst Center runs on two hardware generations:

Generation	CPU Cores	Base Platform
DN2	44, 56, or 112 cores	Cisco UCS 220/480 M5
DN3	32, 56, or 80 cores	Cisco UCS 220 M6

The platform runs Linux Ubuntu (18.4.1 LTS or 18.4.6 LTS) as the base operating system. On top of this, a layered architecture provides container orchestration, managed services, and network applications.

Microservices Stack

The Catalyst Center architecture has evolved across releases. In release 2.3.3.x, the stack used Maglev v1.7/1.8 with Kubernetes v1.18.15 and Docker 19.3.9 for container orchestration. Starting with release 2.3.7.x, the stack transitioned to MKS with Kubernetes v1.24.4-cisco and Containerd v1.6.6, replacing Docker as the container runtime.

The managed services layer includes:

Database as a Service (DBaaS): MongoDB (upgraded from 4.2.11 to 4.4.13), PostgreSQL, and Redis
Messaging Queues: RabbitMQ (upgraded from 3.8.3 to 3.13.3) and Kafka
Clustering Services: GlusterFS and Zookeeper
Monitoring: InfluxDB (replaced by Prometheus in later releases) and Grafana
API Gateway: Kong for northbound API access

The network applications sit at the top of the stack and include Automation (the "fusion" appstack), Assurance (the "ndp" appstack), Platform APIs, AI Network Analytics, and Endpoint Analytics.

Key Microservices Terminology

Understanding Kubernetes terminology is essential for Catalyst Center troubleshooting:

Term	Definition
Container	A lightweight, standalone, executable package that includes code, runtime, system tools, libraries, and settings
Pod	A group of one or more containers with shared storage and network
Namespace	A mechanism for isolating groups of resources within a single cluster
Service	A Kubernetes abstraction defining a logical set of Pods and a policy for accessing them
Node	A VM or physical computer serving as a worker machine in the cluster

An appstack maps to a Kubernetes namespace and acts as a virtual cluster. For example, the "fusion" namespace handles Automation, while the "ndp" namespace handles Assurance. Services within each namespace represent logical groupings of pods. The "inventory" service manages inventory collection, while "postgres" stores the collected inventory data.

Single Node vs. Three Node Cluster

Catalyst Center can operate as a single-node deployment or as a three-node cluster. The three-node cluster provides a high availability framework that reduces downtime due to failures with near real-time synchronization across nodes. Pods are always placed on a node, but pods within a namespace are spread across nodes for resilience.

Pro Tip: When troubleshooting in a cluster setup, remember that a service might be running on any of the three nodes. The Grafana Inventory Dashboard is most useful in XL or cluster setups where multiple inventory instances exist across nodes.

How Do You Access the Catalyst Center CLI for Troubleshooting?

The Catalyst Center provides two distinct command-line interfaces, each serving a different purpose. Understanding when to use each is critical for effective troubleshooting.

SSH Access

Connect to the Catalyst Center CLI using SSH on port 2222:

ssh maglev@<Catalyst_Center_IP> -p 2222

Note that the CLI username and password are separate from the web UI credentials. The CLI uses the "maglev" user account.

Maglev Commands

The maglev commands are Python wrapper scripts for the Kong API interface. They are primarily used for managing and monitoring system packages. Key maglev commands include:

maglev system_update progress
maglev system_updater update_info
maglev package status

Magctl Commands

The magctl commands are the primary tools for monitoring and troubleshooting system services and containers. Many commands and their output are similar to kubectl. Here are the essential magctl commands every network engineer should know:

Check overall appstack status:

magctl appstack status

Retrieve service logs:

magctl service logs -r <service-name>

For example, to view inventory manager logs:

magctl service logs -r inventory-manager

View the last N lines of a service log:

magctl service logs -r <service-name> | tail -n N

Follow live logs in real time (equivalent of tail -f):

magctl service logs -rf <service-name>

Soft restart a service (restarts the container only):

magctl service restart <service-name>

Hard restart a service (deletes and recreates the pod):

magctl service restart -d <service-name>

Warning: A hard restart deletes the pod and recreates it. This means all non-persistent storage and in-container application data will be lost. Use hard restarts only when a soft restart does not resolve the issue.

Display configuration and current status of a service:

magctl service status <service-name>

Display stateful information about a service:

magctl service display <service-name>

Full Log Options

The magctl service logs command supports extensive options for filtering and formatting:

magctl service logs --help
Options:
  -o, --output [json]    Print log records in json
  -m, --mins TEXT        How many minutes in the past to search for logs
  -r, --raw              View raw log files
  -c, --container TEXT   Show logs for this container
  -t, --timezone TEXT    View logs in selected timezone (e.g., America/Los_Angeles, Asia/Calcutta)
  -f, --follow           Follow logs when using --raw
  -p, --previous         Show logs from previous running instance of service
  -t, --tail INTEGER     Lines of recent log file to display (defaults to -1, showing all)
  -a, --appstack TEXT    AppStack on which to perform the operation

Catalyst Center Troubleshooting: Inventory and Device Sync Issues

Inventory is the foundation of Catalyst Center. It performs data collection via SNMP, CLI, or NETCONF, reports reachability and manageability status, and converts collected data into database objects. Without a healthy inventory, automation capabilities like upgrading, provisioning, RMA, and running commands cannot function.

Inventory Sync Enhancements (Release 2.3.x.x Onwards)

Starting with release 2.3.x.x, several improvements were introduced to inventory sync:

Memory optimizations: Shorter sync times, especially for scaled setups, and prevention of out-of-memory crashes
Reprioritization of sync tasks: SNMP trap flooding no longer starves other priority syncs
Visibility into sync errors: Eliminated vague "Partial Collection Failure" messages
Grafana Inventory Dashboard: Added additional visibility and troubleshooting capabilities

Troubleshooting Step-by-Step: Device in Unmanaged or Error State

Step 1: Check the device management status.

Open the Inventory page and look at the device status column. Devices will show one of three states: errors present, sync in progress, or successfully managed.

Step 2: Investigate the error details.

Click on the error message for more details. The interface displays a "Reason and Suggested Actions" menu along with the affected application name. Check for configuration changes that could have caused the issue, including config drift or device CLI changes to SNMP, AAA, HTTPS, NETCONF, or certificates.

Step 3: Check the reachability column.

Status	Meaning
Reachable	Reachable via all mandatory protocols
Ping Reachable	Reachable via ICMP only
Unreachable	Unreachable via all mandatory protocols

Step 4: Validate credentials.

Select the device in Inventory, choose "Edit Device" from the Actions menu, and click "Validate" to verify credentials.

Step 5: Check device reachability from Catalyst Center.

If the device is Unreachable, use the Command Runner:

traceroute <IP address>
ping <IP address>
ping6 <IP address>

If the device is Ping Reachable only, test SNMP connectivity:

snmpget -v <version> <IP address> -c <community> <OID>

Test NETCONF connectivity:

ssh -p 830 <username>@<IP address>

Step 6: Force a manual resync.

Select the device in Inventory and click the resync button to manually force a resync.

Step 7: Check service logs.

View inventory service logs via the Grafana Inventory Dashboard or directly from the CLI using the magctl commands described earlier.

Step 8: Verify firewall rules.

Ensure no firewall is blocking the necessary inbound and outbound ports between Catalyst Center and the managed devices.

When Does Inventory Sync Occur?

Understanding inventory sync triggers helps identify why a device may fall out of sync:

Initial addition: Discovery, Inventory Add, CSV Import, PnP, or LAN Automation
Automatic periodic sync: Every 24 hours by default
Event-based sync: Triggered by SNMP traps for link up/down, config change, or AP-related events
Manual sync: From the Inventory Dashboard via Actions > Inventory > Resync Device
REST API triggered: Credential updates or requests from features like SWIM and Provisioning
Minimal syncs: Take approximately 20% to 50% of the time of a regular sync, depending on the scale of interfaces or APs

Catalyst Center Troubleshooting: Provisioning Failures

Provisioning is the process of pushing configuration to network devices. There are four main types of provisioning in Catalyst Center:

Initial Provisioning: Authentication templates (Closed, Open, Easy Connect), network settings (AAA, DNS, NTP)
Fabric Provisioning: Border, Control Plane, and Edge node roles, Virtual Networks, LISP, VXLAN, BGP, redistribution
Host Onboarding: L2 VLANs, L3 anycast SVIs, IP address pools, CTS (TrustSec policy plane), IPDT (Device Tracking)
Configuration Template Provisioning: Templates based on device family, type, and tags

The Provisioning Workflow

When you initiate a provisioning request, the system follows a multi-step workflow:

Step 1: A REST API call goes to the provisioning-service, which creates a task via the task-service
Step 2: The orchestration-engine starts the provisioning workflow
Step 3: The spf-service validates the Composite Fabric Settings (CFS), and the spf-service-manager generates the device configuration
Step 4: The network-validation service performs pre-checks
Step 5: The network-programmer pushes the configuration to the device

When provisioning fails, identify which step failed and check the relevant service logs using:

magctl service logs -r provisioning-service
magctl service logs -r orchestration-engine
magctl service logs -r spf-service-manager
magctl service logs -r network-programmer
magctl service logs -r network-validation

Catalyst Center Troubleshooting: SWIM (Software Image Management)

SWIM handles upgrading and patching the operating systems on switches, routers, firewalls, and other networking devices. It operates through four main areas in the Catalyst Center UI.

SWIM Workflow Overview

Area	Function
Design > Image Repository	Import and store images and patches (SMU), mark images as Golden, import the ISSU Compatibility Matrix
Inventory (Software Images)	Provision software images (Distribution + Activation), check update status, perform readiness checks
System > Settings	Configure up to 3 external image distribution servers, change protocol order
Workflows (Image Update)	Plan multiple device upgrades with flexible device ordering (release 2.3.7)

SWIM Pre-checks

Before distributing or activating images, SWIM performs several pre-checks:

Startup configuration check
Config register value
Flash memory availability
File transfer protocol verification
Service entitlement validation

Supported file transfer protocols include HTTPS, SCP, and SFTP (for WLC).

Change in Operation from Release 2.3.x

Starting with release 2.3.x, the SWIM operation changed:

Distribution copies images to flash and performs install preparation:

install add file <Image Name>
ap image pre-download

Activation completes the installation:

install activate <image name>
install commit

Common SWIM Issues and Solutions

Issue 1: Image information has not been updated in the repository.

Common causes include connectivity problems (firewall blocking access to OCSP/CRL URLs for SSL/TLS certificate revocation checks) or missing Cisco.com credentials. Ensure the following URLs are accessible:

http://ocsp.quovadisglobal.com
http://crl.quovadisglobal.com/*
http://*.identrust.com

Also verify that Cisco.com account credentials are configured in Settings or the Image Repository window with proper permissions to download software images.

Issue 2: Unsupported image or compatibility matrix error.

This error indicates the image is invalid for the target device. Verify the image against the compatibility matrix.

Issue 3: Distribution or activation failure.

For distribution and activation issues:

Verify the device is Managed and Reachable
Click "Needs Update" to check status or rerun the Readiness Check
Click "See Details" for a detailed view of the image provisioning status, including enhanced visibility into each step
Common failures include insufficient flash space and device misconfiguration

Use the SWIM Grafana Dashboard to view key logs and a summary of all devices within a selected timestamp. You can also filter service logs for a specific device from the dashboard.

Catalyst Center Troubleshooting: Assurance and Health Scores

Assurance provides end-to-end visibility and insights across your entire network infrastructure, covering clients, access points, switches, WLCs, WAN, and cloud applications.

Common Assurance Issues

The three most frequently encountered assurance issues are:

No device health score: The device is not reporting any health data
Low device health score: The device is reporting degraded health
No application health: Application telemetry is not being collected

Health Score Investigations

For switches, click on the time graph to identify the parameter affecting the health score. Starting with release 2.3.7, a telemetry status indicator helps you quickly determine whether telemetry data collection is working properly.

For access points, similarly click on the time graph to find the parameter causing a low score. The telemetry status is also available for AP health.

For WLCs, health score details are accessible through the same interface with dedicated parameters for wireless controller performance.

Telemetry Status Dashboard (Release 2.3.7.x Onwards)

The Telemetry Status Dashboard is a powerful troubleshooting tool introduced in release 2.3.7.x. Click on "Telemetry status" to open this dashboard. Key behaviors:

If the telemetry status is not good, checks are executed automatically every 6 hours
Checks are executed for switches, routers, and WLCs

Assurance System Data Flow

The Assurance system collects data from multiple sources:

Network telemetry data flows from routers, switches, WLCs, and sensors via SNMP, NetFlow, Syslog, and streaming telemetry.

Contextual data comes from ISE (via pxGrid), DNS, AAA, DHCP, topology, inventory, location, policy, and IPAM.

This data flows through collectors into a distributed message broker (Kafka), then to an analytics engine with pipelines powered by Apache Flink for real-time analytics. The processed data is stored in Redis and Elasticsearch and served via APIs to the UI.

Required Assurance Settings

Device-specific settings (Provision > Inventory):

Manageability state must be Managed
Reachability state must be Reachable
Device must be assigned to a site
For Application Health: choose Telemetry from the Actions menu and click "Enable Application Telemetry"

Site-level settings (Design > Network Settings > Telemetry):

Catalyst Center must be set as the SNMP trap server, Syslog server, and NetFlow collector
For wired client assurance: enable "Cisco Catalyst Center Wired Endpoint Data Collection At This Site"
For wireless assurance: enable "Wireless Telemetry"

Network Reasoner Tool (Release 2.3.5.x Onwards)

The Network Reasoner runs a sequence of machine reasoning steps that verify various Assurance configurations and settings on both the network devices and the Catalyst Center itself.

To use it:

Navigate to Tools > Network Reasoner > Assurance Telemetry Analysis
Choose a device and click Troubleshoot
Review the results, which include detailed checks for switches, WLCs, and other devices

Starting with release 2.3.7.x, you can also launch the Network Reasoner directly from Assurance > Network > Device 360.

Force Configuration Push for Telemetry

If telemetry configurations need to be re-pushed to a device:

Select the device(s) in Inventory
Choose "Update Telemetry Settings"
In the popup, select "Force Configuration Push"
Click Next to proceed

AI Analytics Troubleshooting

AI Analytics leverages advanced machine learning techniques and a cloud learning platform. The most common issue across all TAC service requests is cloud connectivity failure.

The feature must be enabled in Settings > External Services and requires outbound HTTPS (TCP 443) access to the cloud hosts. AI Analytics features include AI Network Analytics (Network Heatmap, Baseline Dashboard, AP Performance Advisories) and AI Enhanced RRM.

Starting with release 2.3.5.x, cloud connectivity checks are performed automatically. For CLI-based troubleshooting across all versions:

magctl appstack status

Look for the ai-network-analytics namespace and verify the kairos-agent service is running. Check service logs for cloud connectivity messages:

magctl service logs -a ai-network-analytics kairos-agent

Successful connectivity will show "cloud is reachable" and "request succeeded" in the logs. Errors like "unable to resolve FQDN" indicate DNS or connectivity issues.

Catalyst Center Troubleshooting: Software Upgrades

Catalyst Center software upgrades are one of the most critical and potentially disruptive operations. Understanding the process and knowing how to troubleshoot failures can save hours of downtime.

Pre-Upgrade Checklist

Before starting any upgrade:

Ensure a healthy backup exists
Verify hardware health
Open all required ports on the firewall
Run pre-checks using the Validation Tool (release 2.3.5.x onwards) or AURA (releases 1.2.8 to 2.3.5.x)
Use Google Chrome as the recommended browser
Verify the target release and upgrade path (N-2 supported)
Check network device compatibility (especially for SDA)
Confirm DNS resolution to https://www.ciscoconnectdna.com:443

Pro Tip: There is no option to switch back to an earlier release once the upgrade has started. Always take a backup and validate readiness before proceeding.

Firmware Requirements

Ensure the Cisco IMC firmware version matches the supported version for the target Catalyst Center release. The Validation Tool can automatically verify this for you.

Simplified Upgrade Process (Release 2.3.x.x Onwards)

The upgrade process was simplified in release 2.3.x from three compulsory steps to two compulsory and one optional:

Aspect	Release 2.2.x and Below	Release 2.3.x Onwards
Target Release Selection	Latest patch or next available (confusing)	Multiple options with a clear single dropdown
Compulsory Steps	3 steps: Update System, Download Apps, Update Apps	2 steps: Download All, Install All
Pre-checks	None in workflow	Added as part of workflow (before steps 1 and 2)
Maintenance Mode	From Step 1	From Step 2 only

Step 1: Download -- Click "Download Now" to download both System and Application packages simultaneously. The Catalyst Center is not locked during this step. System packages download first, and you can monitor the overall download percentage.

Step 2: Install -- Click "Install Now" to install all packages. The UI enters maintenance mode at this point.

Step 3 (Optional): Install optional application packages for the release.

Monitoring the System Upgrade

Use the following commands to monitor upgrade progress:

maglev system_update progress

This displays the installed version, currently processed version, current phase, update progress percentage, and phase details.

For more detailed status information:

maglev system_updater update_info

The system upgrade consists of three major phases:

Phase A: Preparation (0% to 31%)

0-6%: Maintenance mode activation, system update hooks download and installation, catalog server and system updater upgrade
7-30%: Download packages to all nodes in the cluster
31%: Applications are shut down

Most upgrade-related field issues occur during this preparation phase.

Phase B: Upgrade (32% to 94%)

This phase includes multiple sub-phases:

System memory requirements check for "/" and "data" partitions, NTP service verification, old file cleanup
Linux Kernel, Docker/Containerd, and Kubernetes upgrade
Maglev Server and its services upgrade (Kong, RabbitMQ, GlusterFS, MongoDB, Cassandra)
Certificate refresh and cluster health check
In a cluster, nodes are upgraded one at a time
Restarts typically occur after Linux Kernel upgrade and after Kubernetes upgrade

Phase C: Post Upgrade (95% to 100%)

System upgrade completes and the application upgrade begins.

Troubleshooting Upgrade Failures

When the system upgrade fails, check these log files:

magctl service logs -r system-updater
cat log/maglev-node-updater-<IP-Addr>.log
cat log/maglev-hook-installer.log

The systemd services responsible for upgrading Linux and Kubernetes are maglev-node-updater and maglev-hook-installer.

For application upgrade failures, check:

magctl service logs -r <affected-application>
magctl appstack status
maglev package status

The maglev services responsible for application upgrades are workflow-worker and maglev-server.

Post-Upgrade Verification

After a successful upgrade, run the Validation Tool again with all validation sets. Starting with release 2.3.7.7, a summary of the most recent upgrade with timestamps is available directly in the UI.

Catalyst Center Health Monitoring and Troubleshooting Tools

System 360

System 360 is the primary dashboard for monitoring your Catalyst Center deployment. It provides visibility into services, resource utilization, and system logs. The Cluster Tools section provides additional capabilities for multi-node deployments.

Self-Monitoring Mode

Starting with release 2.2.x, Catalyst Center displays a banner at the top of the screen when one or more services are down. Click the banner to view which services are affected.

From release 2.3.5.x onwards, hardware health monitoring was added. This detects issues like power supply failures and disk/RAID failures with detailed status information.

AURA Health Checker Tool (Release 1.2.8 to 2.3.5.x)

AURA covers health, scale, and upgrade readiness checks across all use cases:

Simple deployment: copy one executable file to the Catalyst Center and execute it
Uses only pre-installed libraries and software
Only input required: Catalyst Center passwords
Generates a PDF report and zipped log file automatically
Not intrusive: only database reads, show commands, and API calls
Execution time: less than 15 minutes per node; SDA checks depend on scale (approximately 30 minutes for 30 SDA devices)

Validation Tool (Release 2.3.5.x Onwards)

The Validation Tool provides on-demand Catalyst Center health checks directly from the UI. It validates NTP synchronization, DNS resolution, valid internal certificates, catalog server settings, memory requirements, proxy settings, and known software bugs.

RADKit Remote Support

RADKit (Remote Access Diagnostic Kit) provides a secure, temporary, interactive, and remote way for support engineers to access the Catalyst Center:

Secure: Cisco SDL process approved, data encrypted, outbound connection only
Temporary: Customer authorizes access for a fixed time slot (24 hours by default)
Interactive: Access to both UI and CLI for log collection, command execution, and troubleshooting
Remote: All activities tracked on the Catalyst Center

Starting with release 2.3.7.6, RADKit supports secure SSH connectivity without username/password, read-only CLI access for maglev and magctl commands, and access to the Catalyst Center ESXi.

RCA Bundle Collection

Root Cause Analysis bundles can be generated from the CLI:

magctl service logs -r <service-name>

RCA files are stored in /data/rca/ (release 2.3.x and above). Starting with release 2.3.7.6, RCA bundles can be created and viewed directly from the UI, including both general and application-specific bundles.

Audit Logs

Audit logs capture all critical events and activities on the Catalyst Center. Up to 1,000,000 notifications are maintained regardless of type and stored for one year. Five filters are available: Date, Message Severity, User ID, Log ID, and Description. Logs can also be exported to an external syslog server.

Microservices Reference for Troubleshooting

Knowing which microservices are involved in each function helps you target your log collection:

Function	Key Microservices
SWIM	swim, network-design, network-programmer, kong
Inventory	inventory-manager, postgres, dna-maps-service, kong
Upgrades	catalogserver, workflow-worker, system-updater, kong
Provisioning	provisioning-service, orchestration-engine, spf-service-manager, network-programmer, network-validation
LAN Automation	onboarding-service, connection-manager, network-orchestration, inventory-manager
ISE Integration	pki-broker, network-design, ise-bridge, kong
PnP	onboarding-service, connection-manager, inventory-manager

How Does Catalyst Center Enable a Zero Trust Workplace?

Zero Trust is often misunderstood. It is not just a firewall, endpoint security product, or ZTNA solution. In the context of the campus network, Zero Trust means converging networking and security to meet modern business demands. Security needs to be integrated in the network, not bolted on top of it.

The challenges driving Zero Trust adoption are clear: workers connecting from everywhere causing loss of access control, more interconnected environments expanding the attack surface, multi-cloud reality creating gaps in visibility, and rapid innovation introducing sophisticated threats.

The Zero Trust Journey Map

Catalyst Center provides a built-in Zero Trust Journey Map that organizes the path into three pillars:

Endpoint Visibility: Discover, label, profile, and group endpoints
Network Segmentation: Deploy macro and micro segmentation through SD-Access
Trust Monitoring: Detect spoofing, vulnerabilities, and threats; take containment actions

The journey map tracks your progress across these areas and provides a visual status of where your deployment stands.

Prerequisites for the Zero Trust Journey

The following components are required:

Component	Requirement
Catalyst Center	Release 2.3.7 with Cat9000 switches in managed state
Catalyst 9000	Release 17.12 with DNA Advantage License
ISE	Release 3.2 with ISE Premier License

ISE Integration: The Foundation

ISE is the essential partner for Catalyst Center in the Zero Trust journey. The integration provides three main capabilities:

Client Assurance: Network access devices handle AAA requests for users, devices, and IoT things
Network Access Control: ISE provides access control policies and endpoint authentication/posture status
Context Sharing: ISE and Catalyst Center exchange endpoint visibility information, trust policies, and workload status via HTTPS REST API and pxGrid

Catalyst Center uses an intent-based deployment model where network devices inherit properties of profiles and settings associated to their site. AAA server configuration is automated through the site hierarchy with inheritance, eliminating manual per-device configuration.

Catalyst Center Zero Trust: Endpoint Visibility with AI Endpoint Analytics

One of the biggest challenges in enterprise networks is the proliferation of unmanaged devices. The ratio of managed to unmanaged endpoints can be as high as 1:5. Unmanaged endpoints are difficult to patch, most vulnerable to cyber attacks, and cannot use secure authentication mechanisms like 802.1X because they lack a supplicant.

Without 802.1X, endpoints fall back to MAC Authentication Bypass (MAB), which requires a MAC address database and assigns default authorization policies for unknown MACs. This is inherently insecure because MAC addresses can be spoofed.

AI Endpoint Analytics Architecture

AI Endpoint Analytics in Catalyst Center addresses this by aggregating data from multiple sources to rapidly reduce the unknowns:

Network telemetry probes from the network infrastructure
DPI-based fingerprinting using Deep Packet Inspection via the SD-AVC agent on Catalyst 9000 switches
ML Analytics for machine learning-based classification
CMDB Connector for importing data from configuration management databases
Onboarding tools for administrative endpoint registration

Multifactor Classification (MFC)

Endpoint Analytics classifies endpoints using four independent label categories:

Device type: Printer, Laptop, Smartphone, CT Scanner
Hardware manufacturer: Apple, GE, Samsung, Globex Corp
Operating system: MacOS 10.14.6, Windows 7, Linux, Android 9.0
Hardware model: MacBook Pro, Galaxy S8, Optima CT540

MFC results are shared bidirectionally between Catalyst Center and ISE, enabling sophisticated authorization policies based on endpoint identity.

Deep Packet Inspection Classification

For complex devices that cannot be identified through standard ISE probes alone, Endpoint Analytics uses deep packet inspection. The SD-AVC agent on Catalyst 9000 switches analyzes Layer 7 traffic to identify application protocols and device characteristics. This provides first-packet classification that goes beyond the Layer 3 and Layer 4 analysis of traditional ISE profiling.

Machine Learning for Unknown Endpoints

When ML analytics encounters unknown endpoints, it groups them into clusters based on shared attributes. Administrators can then label these clusters (for example, "These are Coffee Machines" or "These are Smart Watches"), and the AI learns these new labels. Through the Connected Catalyst cloud service, these labels can be crowdsourced across global Catalyst Center deployments, improving accuracy over time.

Enabling Endpoint Analytics

Required configuration steps:

Enable CBAR on Catalyst 9000 devices via Provision > Services > Application Visibility (enabled by default on C9K during site assignment in release 2.3.7)
Enable Enhanced ISE Integration using the Day 0 Interactive Setup workflow for bidirectional EA attribute sharing
Enable Catalyst Center AI Analytics in System > Settings > Cisco AI Analytics, including Endpoint Smart Grouping, AI Spoofing Detection, and cloud data storage location selection

After setup, verify that all required configurations show "enabled" status under Policy > Endpoint Analytics > Manage Configurations.

Catalyst Center Zero Trust: Network Segmentation with SD-Access

SD-Access provides the network segmentation layer for Zero Trust, delivering multi-level segmentation through a solid underlay with a flexible overlay.

SD-Access Architecture

The SD-Access architecture separates the forwarding plane from the services plane:

Underlay Network: Control plane based on IS-IS
Overlay Network: Control plane based on LISP, data plane based on VXLAN, policy plane based on TrustSec

Fabric Roles

Three main roles establish the SD-Access overlay:

Control-Plane Nodes: Map system managing endpoint-to-device relationships
Fabric Border Nodes: Connect external L3 networks to the SD-Access fabric (typically core devices)
Fabric Edge Nodes: Connect wired endpoints to the fabric (typically access or distribution devices)

LAN Automation for Underlay Deployment

LAN Automation leverages PnP to automatically configure the underlay, including routed interconnections, Loopback0, IS-IS routing protocol, and hostnames. It is prescriptive and requires starting from a seed device.

Multi-Level Segmentation

SD-Access enables both macro and micro segmentation:

Macro segmentation uses Virtual Networks (VNs) to create isolated routing domains. For example, an Employee VN, IoT VN, and Guest VN provide complete isolation enforced by firewall policies at the border.

Micro segmentation uses Security Group Tags (SGTs) within each VN. SGTs are 16-bit tags assigned to endpoints that enable topology-independent access control. Groups like Employees, Contractors, Cameras, and Printers can have granular permit/deny policies between them.

To verify group-based policies on a fabric edge switch:

show cts role-based permissions

Authentication Templates

Catalyst Center provides templates for each phase of authentication policy rollout:

Open: Visibility only, network access always authorized
Low-Impact: Visibility and limited access before authentication
Closed: No access before authentication, full visibility and control

Authorization Enforcement Options

Beyond basic RADIUS Accept/Reject, three enforcement mechanisms are available:

Method	Description
Security Group Tags	16-bit SGT assignment enabling topology-independent group-based access control
Dynamic VLANs	Per-port, per-domain, or per-MAC VLAN assignment
Downloadable ACLs	Per-endpoint access lists pushed from ISE

Group-Based Policy Analytics

Catalyst Center provides Group-Based Policy Analytics that displays real traffic flows between security groups. This tool aggregates data from Endpoint Analytics MFC, ISE Security Groups, Secure Network Analytics host groups, and network flow information. It shows the ports and protocols used for communication between specific groups, enabling you to create accurate allow-list policies.

Catalyst Center Zero Trust: Trust Monitoring and Threat Containment

The final pillar of the Zero Trust journey is continuous trust monitoring and automated threat containment.

Trust Score

The Trust Score assesses the trustworthiness of each endpoint on the network, with values ranging from 1 (low trust) to 10 (high trust). Trust scores are influenced by both positive and negative factors:

Positive influences (increase trust score):

Secure authentication (e.g., 802.1X with EAP-TLS)
Posture compliance via Cisco Secure Client

Negative influences (decrease trust score):

Impersonation attacks (MAC spoofing, attribute spoofing)
Insecure software interfaces
Unauthorized clients behind NAT
Endpoints accessing low-reputation IP destinations (detected via Talos threat intelligence)

Trust scores can be viewed under Policy > AI Endpoint Analytics > Overview and are available as an attribute in ISE authorization policies.

AI Spoofing Detection

AI Spoofing Detection identifies concurrent instances of the same MAC address, which indicates a spoofing attack. Trigger criteria include:

Endpoints connected on the same or different switches
Detection based on traffic when the endpoint appears at the same time across switchports
Detection when an endpoint transitions from one port to another more than 4 times and sends traffic

Adaptive Network Control (ANC)

ANC provides four actions to mitigate risks:

Action	Effect
Quarantine	Move the endpoint to a quarantine Security Group
Shut Down	Shut down the switchport where the endpoint is connected
Port Bounce	Cycle the switchport where the endpoint is connected
Re-Authenticate	Demand the switch to restart the authentication process

Quarantine and Shut Down actions do not require a permanent authorization policy, while Re-auth and Port Bounce actions do.

Trust-Based Authorization in ISE

By combining Trust Scores with Endpoint Analytics attributes, you can create dynamic ISE authorization policies. For example, an HP Printer with a trust score of 6 or higher receives the Printer SGT, while the same printer with a trust score below 6 is placed into a Quarantine SGT. On any change of trust score, an automated RADIUS Change of Authorization (CoA) forces re-authentication with the new trust score value.

Talos Threat Intelligence Integration

Catalyst Center pulls IP reputation data from Talos via the Connected Catalyst cloud service. Application telemetry enabled via NetFlow on network devices detects unauthorized connections to low-reputation sites, indicating anomalous behavior. Mitigation is possible through ISE using Adaptive Network Control APIs.

Frequently Asked Questions

What is the difference between Cisco DNA Center and Catalyst Center?

Catalyst Center and Cisco DNA Center are the same product. The rebranding from DNA Center to Catalyst Center began with release 2.3.7 as part of the simplified branding for the Cisco Catalyst product stack. Both product names can be used interchangeably during the transition.

How often does Catalyst Center sync with managed devices?

By default, Catalyst Center performs an automatic periodic inventory sync every 24 hours. Additionally, event-based syncs are triggered by SNMP traps for link up/down events, configuration changes, and AP-related events. Minimal syncs, which take 20-50% of the time of a full sync, are used when only partial data needs refreshing. Manual syncs can be triggered at any time from the Inventory page.

What should I do if Catalyst Center is stuck in maintenance mode after an upgrade?

First, SSH into the Catalyst Center CLI on port 2222 and check the upgrade progress using maglev system_updater update_info. Look at the current state, sub-state, and progress percentage. Check the system-updater logs with magctl service logs -r system-updater for specific error messages. If the system upgrade completed but application upgrades failed, use maglev package status to identify the failing package, and then check that specific application's logs.

What licenses are needed for Zero Trust deployment with Catalyst Center?

To deploy the full Zero Trust workplace with Catalyst Center, you need Catalyst 9000 switches running IOS-XE 17.12 with the DNA Advantage license, ISE release 3.2 with the ISE Premier license, and Catalyst Center release 2.3.7. The DNA Advantage license is required for SD-Access fabric features and AI Endpoint Analytics, while ISE Premier is needed for advanced profiling, posture assessment, and pxGrid context sharing.

How does AI Endpoint Analytics detect spoofed endpoints?

AI Spoofing Detection identifies concurrent instances of the same MAC address across the network. It triggers when an endpoint with the same MAC appears simultaneously on the same or different switches and sends traffic, or when an endpoint transitions between ports more than four times. This detection goes beyond simple MAC-based identification by using deep packet inspection and multifactor classification to verify that the device attributes match what is expected for that endpoint type.

What is the difference between a soft restart and a hard restart of a Catalyst Center service?

A soft restart using magctl service restart <service-name> restarts only the container within the existing pod. This preserves any non-persistent data within the pod and is generally safe. A hard restart using magctl service restart -d <service-name> deletes the entire pod and recreates it, which means all non-persistent storage and in-container application data is lost. Always try a soft restart first and only use a hard restart when necessary.

Conclusion

Catalyst Center troubleshooting requires a systematic approach grounded in understanding the platform's microservices architecture. From the CLI commands that give you direct visibility into service health, to the Grafana dashboards that surface inventory and SWIM insights, to the Validation Tool and Network Reasoner that automate diagnostic checks, the platform provides a rich set of tools for identifying and resolving issues across inventory, provisioning, SWIM, assurance, and upgrades.

On the security side, Catalyst Center's Zero Trust capabilities transform the campus network from a flat, trust-everything environment into a segmented, continuously monitored infrastructure. The journey from endpoint discovery through AI Endpoint Analytics, to network segmentation via SD-Access, to trust monitoring with spoofing detection and Talos integration, provides a complete framework for workplace security.

The key takeaways to remember are: use System 360 to monitor your Catalyst Center services, resources, and logs; leverage Grafana dashboards for inventory and SWIM troubleshooting; use the Network Reasoner and Validation Tool for assurance diagnostics; monitor upgrades with maglev CLI commands; and follow the three-pillar Zero Trust journey of endpoint visibility, network segmentation, and trust monitoring.

To deepen your understanding of these topics and gain hands-on experience with Catalyst Center operations, explore the CCNP Enterprise certification courses available at NHPREP. Mastering these troubleshooting and security deployment skills will prepare you for both certification exams and real-world enterprise network management challenges.