Customer Success Story: Peak Signals
Peak Signals has implemented the entire TICK Stack (Telegraf, InfluxDB, Chronograf, and Kapacitor) to monitor communications equipment in their shop lab to gain absolute visibility of equipment status to technicians working through complex problem scenarios. Telegraf and InfluxDB are used in microwave telecommunications mock-up labs for analysis and training purposes and are installed “in-rack” with simulated network core and edge equipment.
InfluxDB, a purpose-built time series database, then ingests SNMP data from Telegraf from the microwave equipment directly. This data is displayed using Chronograf, allowing “at-a-glance” status information to be read directly from the equipment’s SNMP Agents. Peak Signals also uses NodeMCU devkits to feed analog voltage levels into InfluxDB, as well as monitoring and trending dry contacts.
Peak Signals has found that InfluxDB has a high ingest rate and integrates well with other tools. Their team enjoys the ability to hack/cobble together a functional performance-monitoring data historian with familiar tech on multiple single boards, allowing immense flexibility in spinning up and knocking down testing environments. Peak Signals now has the ability to integrate Kapacitor and use it to downsample data, driving a look towards the presence of the stack at the network edge. This allows them to showcase the possibility of using MQTT for telemetry transport in Alaska where bandwidth doesn’t come cheap.
Ben Ruel, Technician for Peak Signals, uses InfluxDB in both a professional and personal setting. He recommends the products whether it’s small projects (like a homeschool weather station project with his daughter), medium-sized project (like monitoring several on-board parameters on commercial and recreational boats), or much larger projects (like proof-of-concept enterprise-wide network status monitoring for disparate communications gear). He likes that there’s a robust support community available for just about every use case and recommends diving in headfirst and using the InfluxData Sandbox as a guide.