One of the key advantages of cloud services versus on premise deployments is the wide range of purchasing options and pricing models. While it’s an attractive advantage, it can be complicated for organizations to determine the best blend of service pricing models. The ability to define the organization’s blend of purchasing strategies and display the target versus actual performance is critical for optimizing cloud cost management efforts.
MQTT is a machine-to-machine communication protocol. Devices publish messages to a broker under specific topics, and other devices subscribe to those topics to receive information. It’s popular because it doesn’t take up a lot of bandwidth, so IoT devices with limited network connectivity can use it. MQTT works because of brokers. Each device sending and receiving data can communicate with potentially millions of other devices while only connecting to one broker.
Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week we’re exploring the ‘hidden’ environmental impact of our data-driven world.
The Internet of Things (IoT) describes devices with sensors and computational ability which let them collect, exchange, and act on data. IoT is a broad category that includes uses from smart home thermostats to industrial manufacturing equipment. Sensor data is time series data, and IoT is a common use case for InfluxDB because it can handle the huge amounts of data IoT sensors create.
Cloud spend — which research shows makes up 51% of IT budgets — is a prime candidate for company cost savings initiatives with the potential to make a huge difference in gross margins. It’s also an area that has grown dramatically in the last few years due to digital transformation and a rise in cloud demand during the pandemic.
This article was originally published in The New Stack and is reposted here with permission. Hundreds of billions of sensors produce vast amounts of time series data every day. The sheer volume of data that companies collect makes it challenging to analyze and glean insights. Machine learning drastically accelerates time series data analysis so that companies can understand and act on their time series data to drive significant innovation and improvements.
Learn how to deploy InfluxDB Cloud’s Native Collectors with Kepware and The Things Network. Did you hear about the new feature that just dropped to InfluxDB Cloud? Native Collectors! Starting with MQTT. There will be plenty of content to get you started with Native Collectors. So this blog series covers connecting two popular IoT-based platforms to InfluxDB Cloud using native Collectors. One Enterprise use case and one industrial use case.
An enterprise IT company hosted a large industry event that drew attendees from all around the globe, including key technology leaders. Organizers knew that their IT offerings needed to be top notch to ensure attendees were happy when it came to event experience. The event application allowed attendees to browse and register for sessions at the event. So, organizers needed to be able to identify issues in real-time and fix them quickly.