Meraki wireless networks and security camerasare deployed in large numbers of retail outlets, hotels, campuses, and enterprises. Meraki wireless networks connect many business-critical devices, including Point-of-Sales devices, and provide internet connectivity to visiting customers. The Meraki camera provides reliable security with local and remote live viewing capabilities from Meraki cloud hosted dashboard. Both are very easy to deploy, configure, and manage via a centralized cloud management dashboard.

Meraki wireless access points and security cameras, beyond their basic functionalities, also provide valuable insight into foot traffic and behavior patterns of users. Meraki Access point collects user location information from nearby smart devices, enabling location-based analytics.

Meraki camera utilizes a powerful onboard processor to analyze video and provides valuable foot traffic insights by detecting persons using computer vision. Location insights provided by these Meraki devices enables businesses to provide better customer engagements, increase retail store traffic, and drive revenue. Meraki network location analytics and camera analytics are exposed to business owners via an easy to use Meraki dashboard.

As Meraki wireless network is enabling core business capabilities, monitoring of network health and maintaining low network latency becomes very critical to the operations team. Meraki Wireless Health features simplifies monitoring and root cause analysis of issues for all connected clients from the Meraki health dashboard. The dashboard provides a snapshot view for 1 hour, 12 hours, 1 day, and 1-week durations, along with various drill down capabilities to help identify issues.

Rich APIs for location analytics, health, and camera

Meraki pre-built dashboards for location analytics, camera analytics, and health monitoring are very useful and sufficient for many organizations. But some organizations have more advance use cases and want to retain granular data for longer periods of time. Historical data from Meraki, when combined with other business related data like Point-of-Sale, can provide very useful business insights. To enable these advanced use cases Meraki also supports rich APIs for location analytics, health, and camera analytics. These data sets can help business solve complex use-cases like:

• How much do foot traffic and sales increase during promotions?
• What is typical queue size on cash registers during specific hours of day?
• How many devices successfully connected (or failed to connect) to the network in specific locations throughout the business?

Merakibeat Plugin collects data from the Meraki API and stores it in an analytics database

The DevNet and Meraki teams worked together to create the Merakibeat plugin, data pipeline, and reporting dashboard based on open source technologies like Elastic Beats, Elasticsearch, and Kibana. The Merakibeat plugin enables consumption of data from Meraki wireless health, location analytics, and camera API, and stores this data in an analytics database like Elasticsearch.

Key open source components for data pipeline include:

• Elastic Beats is an open source platform for data shipper. The lightweight beats agent sends metrics to Elasticsearch. Beats is very flexible framework that supports pluggable input-output plugins.
• Merakibeat is a DevNet community contributed input plugin that can write data to any of the Beats supported output data sources like Elasticsearch, Kafka, MongoDB, Redis etc. (complete list)
• Elasticsearch is an analytics data store that saves historical data for further analysis and reporting.
• Kibana is a visualization tool for Elasticsearch, that enables creating custom reports and dashboards.
• Business metrics, like point-of-sale data, can also be ingested into the same analytics datastore to enable data analysis of business metrics, network health, and location analytics.

The DevNet team, working with Meraki engineers, developed a custom Beats plugin and reference data pipeline for Meraki APIs. This Merakibeat plugin has three sub modules