The “Internet of Things” or IoT is the inter-networking and instrumentation of physical devices—everything from streets, cars, factories, power grids, ice caps, satellites, clothing, phones, microwaves, milk containers, planets, human bodies. It is an exciting area of tech, where industry experts estimate that there will be more than 30 billion connected IoT devices by 2020. In an IoT Architecture, data about these devices are collected with the help of various technologies in order to gain real-time insights to facilitate automation. Current market examples include home automation (also known as smart home devices) to control and automate lighting, heating, air conditioning and household appliances, infrastructure management to monitor and control urban and rural solar panels, railway tracks, and wind-farms and manufacturing, where monitoring and control can optimize plant safety and security as well as extend into asset management thus allowing for predictive maintenance that drive efficiencies and maximize reliability.
Because of this, the Internet of Things creates an opportunity to measure, collect and analyze an ever-increasing variety of behavioral statistics. That being said, data is central to any IoT implementation, and depending on the application, there could be high data acquisition requirements which in turn lead to high storage and heavy data processing requirements.
This paper reviews how an IoT Data platform fits in with any IoT Architecture to manage the data requirements of every IoT implementation. It is based on the learnings from existing IoT practitioners that have adopted an IoT Data platform using InfluxData. These clients have a range of solutions–from home automation (thermostat monitoring & management), to infrastructure management (solar panel monitoring and control) to manufacturing (equipment monitoring & control) as well as environmental management (green wall monitoring & control).
These learnings will help IoT adopters avoid the common pitfalls current clients faced in their journey to developing their IoT solution.
Track and graph your Aerospike node statistics as well as statistics for all of the configured namespaces.
Knowing how well your webserver is handling your traffic helps you build great experiences for your users. Collect server statistics to maintain exceptional performance.
Collect and graph performance metrics from the MON and OSD nodes in a Ceph storage cluster.
Use the Dovecot stats protocol to collect and graph metrics on configured domains.
Easily monitor and track key web server performance metrics from any running HAProxy instance.
Gather metrics about the running Kubernetes pods and containers for a single host.
Collect and act on a set of Mesos statistics and metrics that enable you to monitor resource usage and detect abnormal situations early.
Gather and graph metrics from this simple and lightweight messaging protocol ideal for IoT devices.
Gather phusion passenger stats to securely operate web apps, microservices & APIs with outstanding reliability, performance and control.
The Prometheus plugin gathers metrics from any webpage exposing metrics with Prometheus format.
Monitor the status of the puppet server – the success or failure of actual puppet runs on the end nodes themselves.