IoT Is Pushing Us to the Edge, Literally
IoT Is Pushing Us to the Edge, Literally
See how cloud computing and IoT are meeting at the edge and the latest trends and developments in that space. We'll also examine challenges like latency and responsiveness.
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Imagine an Internet of Things (IoT)-enabled smart shoe that has the capability for workers to send or receive alerts while working in dangerous areas. The possibilities are just incredible. What we once dreamed of as future technology is now at our fingertips to create opportunities across workplaces and at home. As we see a proliferation of IoT devices, it's time for a wakeup call that we're heading to the plateau of productivity.
Previously, IT would pull one stream of data into one application, but now we're facing multiple streams into one application or even multiple applications. While companies are excited and ready for the advancements in IoT, It's unclear whether we're ready to move beyond the fledgling stage. IoT means that in a single environment, multiple devices with varying data models will be generating information that will need to be extracted and uniformly analyzed.
GSMA Intelligence predicts that there will be 25 billion connections to IoT globally in 2025. That's enough to push us to the edge-edge computing, that is.
Speaking of Edge Computing...
At the annual mobile industry extravaganza, Mobile World Congress (MWC), IoT was a headlining topic. The discussion lead by industry experts centered on the theme of how IT teams and businesses will be handling the data from IoT. The big answer seemed to be edge computing.
While cloud has spurred the development of IoT, it has run its course on acting as the primary location for storing and processing IoT data. Centralizing data is no longer efficient or even realistic when we're seeing latency-sensitive data processing become commonplace.
Instead, edge computing answers the newest IoT challenges by processing data at the network or infrastructure edge, near where it is created, to save bandwidth and storage and speed the time to get context from that data.
Reducing Latency and Increasing Responsiveness
Processing at the edge is supposed to reduce latency and make connected applications more robust and responsive, since it cuts out data round-trips to the cloud. But we're also placing a lot of trust in IoT devices and edge computing that aren't yet fully defined.
Although some organizations are beginning to deploy second-generation IoT and edge platforms that go beyond simplistic gateways for more sophisticated device management, there is still a larger focus on data management instead of the application.
As edge computing evolves, future applications will be built on a three-tier architecture of data sources, intelligence, and actionable insights. This is fundamentally different from the three-tier architecture of user interface, business logic, and databases that we formerly knew. Modern applications now will be structured around cloud, machine learning and fast data, and enterprises will need the resources to ensure that new approach won't slow down the rest of the ecosystem.
Visibility in Uncharted Waters
As IoT devices, edge computing and associated applications evolve to handle the massive influx of data, will there be enough visibility for the enterprise to handle any issues that arise? While new technology can be exciting and promise business agility, there are many points along the way where something can break, be misconfigured or become unresponsive because of outlying factors.
Now that both applications and data are decentralized, the requirements for monitoring the flow of information have changed. Before adopting an IoT data management strategy, consider a scalable monitoring solution that can map and monitor the entire enterprise network, end-to-end. Learn more about assessing your network before deploying new technologies in our guide.
Published at DZone with permission of Lea Rabinowitz , DZone MVB. See the original article here.
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