Bhanu Singh* says organisations need to integrate their edge ecosystems to become part of centrally managed IT operations management systems.
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Edge computing is growing quickly, but IT operations need to evolve as well to effectively monitor and manage new devices, sensors, applications and data.
Growing enterprise edge ecosystems should integrate and become part of centrally managed IT operations management (ITOM) systems.
Edge computing is hard to define and is running high on the hype scale.
But research and surveys continue to indicate that this trend of processing data where it’s collected for better latency, cost savings and real-time analysis is an innovation with legs.
There will be 75 billion Internet of Things (IoT) devices by 2025, according to Statista.
According to Spiceworks’ 2019 State of IT report, 32 per cent of large enterprises with more than 5,000 employees are using edge computing, and an additional 33 per cent plan to adopt it this year.
Tied to the growth of edge computing is the advent of 5G wireless: 51 operators globally will start 5G services by the end of the year, according to Deloitte Global research from 2019.
The major cloud companies are also investing in the edge.
The AWS Local Zones service allows single-digit latency connecting to computing resources in a metro environment, while Microsoft offers the Azure Stack Edge appliance and Google Cloud IoT is a “complete set of tools to connect, process, store and analyse data both at the edge and in the cloud”.
Benefits of the edge
We’ve read plenty about the business benefits from edge computing: oil rig operators need to see critical sensor data immediately to prevent a disaster, marketers want to push instant coupons to shoppers while in the store, video security monitoring can catch a thief in the act and medical device alerts can ensure patient safety.
Edge computing may save IT money on cloud and network bandwidth costs as data volumes keep exploding and the need to store every data point becomes harder to justify.
There are also implications for IT management and operations.
Local processing of high-volume data could provide faster insights to manage local devices and maintain high-quality business services when seconds make a difference.
Today, IT operations teams are inundated with data from thousands of on-premise and cloud infrastructure components and an increasingly distributed device footprint.
Only an estimated 1 per cent of monitoring data is useful, meaning it provides indications of behaviour anomaly or predictions about forthcoming change events.
With edge monitoring, we can potentially program edge-based systems to process and send only that small sliver of actionable data to the central ITOM system, rather than transmitting terabytes of irrelevant data daily to the cloud or an on-premise server where it consumes storage and computer power.
The job of filtering out the highly contextual data on the edge can support real-time decisions for successfully running IT operations at speed and scale — regardless of what combination of on-premise, public cloud or private cloud infrastructure is in place.
At the same time, IT operations will need to lead when it comes to minimising the risk of edge technology from a performance, security and privacy perspective.
IT operations realities for edge computing
Edge-specific security needs are still unknown: Edge devices are often small and infrequently designed with security in mind.
More than 70 per cent of edge devices don’t mandate authentication for third-party APIs, and more than 60 per cent don’t encrypt data natively.
So, the attack surface in IoT and edge environments is now larger, and less secure.
This is particularly worrisome when considering edge devices that collect personally identifiable information such as email, phone numbers, health data or financial formation such as credit card data.
Edge monitoring tools are immature: Organisations need platforms that can instantly monitor and analyse edge-generated data.
Increasingly, billions of connected devices will be communicating machine-to-machine, and the addition or subtraction of connected devices will be possible at an unprecedented scale.
The ability to manage large volumes of connected devices and the information being exchanged between them will be critical.
5G acts as the unifying technology, bringing the flow of information and the density of scale.
We will see an influx of innovation in edge monitoring in the coming years.
New environments call for new rules: As organisations move more data and application assets to edge computing environments, IT will need to devise new policies and thresholds for central processing and alerting of all this data.
Applying AI-based automation is essential here, as manual efforts will have zero chance of keeping up with the volume of data filtering, analysis and response.
We are entering the age of nano satellites.
These edge devices will transform the future of agriculture, energy, mining, transportation and finance due to their capabilities for sending insightful data in real-time to customers.
IT operations will have its work cut out to properly manage this evolving edge infrastructure.
DevOps processes will become even more paramount: If you haven’t already realised that DevOps is taking over software development and IT management, just wait for when edge goes mainstream.
There will be no other way to manage change and deployments of edge technology without the agile, continuous integration and continuous delivery methodology of DevOps.
It will be imperative for IT operations to adopt DevOps practices and tools to manage, monitor and deploy edge resources.
IT operations is at a crossroads, determining how much of the past is still relevant and how much they will need to change to adapt to a distributed, hybrid cloud world that will soon include edge as a fundamental pillar of their digital strategy.
Security, machine intelligence and DevOps will be crucial areas of expertise for IT operations teams looking to maximise the benefits from the edge.
* Bhanu Singh is SVP at OpsRamp.
This article first appeared at devops.com.
