Observing the Edge helps ensure greater productivity and efficiency

Modern IT environments are highly complex, becoming increasingly complex with each passing day. 

Made up of a massive web of applications, databases, and devices across infrastructures that can stretch across the world, these IT ecosystems are becoming more intricate as organisations turn to technology in their pursuit of improved productivity and efficiency. 

There is little doubt that digital transformation and the shift to cloud computing have been at the forefront of positive business change. Especially as enterprises look to increase scalability and ensure employees have access to their work environments regardless of location. 

But this change is not without problems. Any reliance on technology must be managed against increased security concerns as data moves between devices, geographies, and platforms. 

Moving to the cloud is critical to business transformation…but it is not without risk

One of the consequences is that it has led to latency – or  a delay in the time it takes for data to be moved from point to point. Slow data transmission can lead to slow response times and delays in accessing critical information or performing essential tasks. 

It can also act as a brake on productivity because employees have to wait longer for applications or systems to respond. And if the latency affects customer-facing applications, it can tarnish the user experience and – if left unchecked - potentially damage business growth.  

While the shift to the cloud has been fundamental to business transformation, it has resulted in the breakdown of the network perimeter as devices connect to company networks, applications, and data via the cloud. That’s why IT networking teams often deploy virtual machines, which can introduce packet delays if they exist on separate networks. 

This may be done to alleviate network congestion and load balancing while improving traffic routing as part of a host of measures to ensure efficient data transmission for optimal performance.

But it is not without risk. And in the worst case, virtual machines can leave IT teams with slower environments and without tools to understand the issue clearly – or  how to fix it. 

Moving to the edge 

To get around this problem, the industry has turned to edge computing, a distributed computing model where data processing and storage are moved closer to the network's “edge.” Devices such as Internet of Things (IoT) gateways, smart displays, and sales terminals have sufficient memory and computing power to process data rather than send it back to a central server in the cloud. 

One of the standout benefits of edge computing is faster data processing. Simply put, moving data processing to the edge – or  as close to the devices generating the data as possible – helps  increase the speed at which data can be processed. 

Edge computing can offer significant advantages in scenarios where IT pros face networking limitations and time-sensitive processing. It can effectively reduce bandwidth requirements for enterprises by minimising long-distance communication between servers or central hubs – and  the devices receiving information. 

This can help to decrease latency and optimise bandwidth usage. Moreover, it can provide greater flexibility as data processing occurs closer to its source, enabling computing processes to adapt to necessary changes swiftly.

While edge computing has successfully addressed many challenges associated with cloud migration, it has also introduced new obstacles that enterprises must overcome. For instance, adopting edge computing requires a more distributed infrastructure, which adds complexity to company IT environments. The vast amount of data generated by a network of distributed devices can make comprehending the information being produced challenging. 

Observability brings visibility to the edge

Thankfully, observability offers a solution to help enterprises gain the efficiency of edge computing without losing visibility. It’s a concept in IT systems and software engineering that allows users to gain insights and understand the internal workings of a system by providing visibility into its internal state, performance, and behaviour through monitoring and analysis of various data sources.

It does this by analysing massive amounts of information across an entire IT environment and pinpointing the causes of outages or performance issues. It also generates actionable insights to resolve these problems quickly – something that is critical to understanding complex IT environments. 

Observability also allows IT teams to maintain ongoing availability and reliability by identifying bottlenecks in the network, troubleshooting problems, and optimising system performance. 

And it does this by providing single-pane-of-glass visibility into the enterprise and giving teams real-time information. 

With observability, organisations can better monitor network traffic, identify potential security threats, detect anomalies, and optimise system performance. Not only can this help to reduce downtime, improve security, and ensure high availability and reliability, it allows teams to see and understand the edge computing systems in their network and work to resolve issues quickly. 

Edge computing is one of the most effective models for companies to adopt. When deployed in tandem with observability, teams can better understand and address potential issues quickly and efficiently. And by combining edge computing with observability, there’s little doubt enterprises can increase productivity and efficiency.