Description
Cisco Meraki MX250 – A building block for SASE in a rack-mountable form factor
Large-branch, campus, or DC security and SD-WAN appliance for up to 2,000 users.
Highlights
- WAN: two 10 GbE SFP+, one USB (cellular failover)
- LAN: eight GbE RJ45, eight GbE SFP, eight 10 GbE SFP+
- 4 Gbps firewall throughput
- 1 Gbps site-to-site VPN throughput
- Supports up to 2,000 users
Features:
SD-branch cloud platform
- Unified management for security, SD-WAN, Wi-Fi, switching, MDM, and IoT
- Centralised management via web-based dashboard or API
- True zero-touch provisioning
- Smartphone-like firmware updates
Unified threat management
- Next-generation layer 7 firewall and content filtering
- Advanced Malware Protection (AMP) with Cisco Threat Grid
- Intrusion detection and prevention (IDS/IPS)
- Visibility of security events through an elegant security centre GUI
Cloud security
- Built-in SD-WAN connectivity to Cisco Umbrella global data centres
- Application prioritisation
- SSL decryption/inspection, data loss prevention (DLP), CASB
- Remote browser isolation, granular app control, SaaS tenant restrictions
Connectivity
- Layer 7 application optimisation over self-healing Auto VPN (SD-WAN fabric)
- Extension of SD-WAN fabric to hybrid clouds and Cisco Umbrella
- Support for native IPsecor Cisco Any Connect remote client VPN
- Instant wired fail over with added 3G/4G fail over via USB modem
Advanced analytics with ML
- Automatically applied Smart Thresholds to identify true app degradation
- At-a-glance performance of apps across the LAN, WAN, and app server
- Instant root-cause analysis of degradation with intelligent recommendations
- Status of multi-site uplinks in one view, including cellular
The Cisco Meraki MX are multifunctional security and SD-WAN enterprise appliances with a wide set of capabilities to address multiple use cases–from an all-in-one device. Organisations of all sizes and across all industries rely on the MX to deliver secure connectivity to hub locations or multi-cloud environments, as well as application quality of experience (QoE), through advanced analytics with machine learning.
