Data is becoming increasingly essential to businesses globally, allowing for insights to be gathered around critical processes and operations. Over time, the traditional systems put in place to hold our data have become unsuitable for modern-day needs due to the continuous growth of data. Edge computing has emerged to reshape the current computing environment and allow data to be processed closer to where it’s being generated. Throughout this blog, we will be taking you through everything you need to know about edge computing, the advantages and disadvantages, and what Edge by Civo is all about.
Dinesh Majrekar, CTO at Civo, and Mark Boost, CEO at Civo, recently spoke at KubeCrash about the application deployments of old, cloud-native processes of today and edge native deployments of the future. Watch their session below to learn about the challenges we are about to face with an edge-first architecture and what we can do today to be ready.
What is edge computing?
Edge computing, which involves transferring application workloads from the cloud to remote sites, is typically characterised as computing technology that places computer resources as close as possible to the actual location of the user or the source of the data. It helps in reducing latency, which in return lessens the delay in the transmission of data helping in better communication between distant places. As a result of minimal latency, edge computing can facilitate IoT devices, smart homes/cities, automatic vehicles, robots, etc., much better than the traditional cloud model.
What are the advantages of edge computing?
Reduced latency is a major benefit of edge computing. There is little to no delay in the transmission of data as a result of reduced latency because it helps to shorten response time. The development of 5G technology, where the theoretical speed can reach 10 GB and the latency can be as low as one millisecond, is a perfect illustration of this. For edge devices, IoT applications, smart factors, etc., it produces enormous speed benefits.
Edge computing offers high performance since you may select the precise hardware you need based on your needs. In contrast, you will have few options when using cloud computing to define the precise gear you require for your project.
Lower bandwidth/data transfer costs
Low bandwidth is used by edge computing, which lowers the cost of data transfer. This occurs as a result of the extensive data processing that takes place at the edge location.
Edge computing allows you complete control over your own security, which is a huge advantage if you're adept at handling security. High security for your applications will be ensured by putting solid security policies in place.
Edge computing gives you data sovereignty, which is a further important benefit. You can determine the precise location of your data thanks to data sovereignty. In some clouds, you could worry about where your data is stored during backup or whether it might inadvertently end up in the incorrect place. But, if you use edge computing, you can be sure that once data is placed at the edge, it will remain there.
What are the disadvantages of edge computing?
We are accustomed to using cloud models today that are based on operational expenses. As a result, monthly expenditures are made in accordance with demand. However, deploying expensive hardware, which could cost a lot of money, is a responsibility that comes with edge computing. Edge computing requires a significant capital expenditure, making it a Capex-heavy transition from the current approach.
Security becomes your responsibility
We are used to giving cloud service providers control over the network and physical layers of security. If you're deploying at the edge, you are now responsible for your own security.
Additional management & maintenance
Depending on what your company does and how you use IoT devices, you could end up managing thousands of devices at scale. This becomes challenging when it comes to upgrades and patches.
Unable to scale on-demand
In the cloud, you have almost an infinite number of resources, allowing you to take advantage of things such as auto-scaling. When deploying at the edge, you might be limited by a finite capacity that’s deployed. This means you have to handle scale and gain access to new hardware quickly.
As more compute-focused workloads are running at the edge and discarding data, data loss can occur more frequently. If you are not sending the data to the cloud or storing it at the edge, there is a risk of losing data. This means that when deploying at the edge, you need to monitor the data you keep and discard.
What are some challenges of edge computing?
One of the main challenges of edge computing is getting deployments working. The architecture of edge computing is complex and extensive and as a result, it might give considerable challenges to end users.
Hardware and software management at scale
Managing hardware and software according to the needs of your business can be a challenge when using edge computing. Hardware and software resources are expensive and limited and as a result, one may face difficulty managing them in proportion.
Another challenge while using edge computing is managing the deployment pipelines for rolling out the changes during an upgrade. This is due to the possibility of handling thousands of devices at once, which might make it difficult to roll out changes during an upgrade.
Design for intermittent access
Suppose you are using a self-driving car that needs communication: In a city, it can do so with reliable 5G and 4G connectivity, but in a desert environment, it won't have access to either. Therefore, you must create an edge processor and application that can go for extended periods of time without being online and then, when it does, be able to upload data, download containers, and perform software updates.
Day 2 Operations
Day 2 operations focus on operational issues to keep an edge system running. Delivering patches or full upgrades to large deployments becomes challenging as some edge sites can be in a remote location and do not have internet connectivity. New upgrades need to be tested and verified which causes delays before rolling out and poses challenges to day 2 operations.
Explore Edge by Civo
Managing your software and operations at the edge can be a challenge, especially when Kubernetes is required.
Edge by Civo simplifies this process by using CivoStack: Our own custom-built software stack designed for hosting and maintaining Kubernetes at scale, with a focus on simplicity, security and the very best developer experience.
Your team can easily manage and interact with Kubernetes using Civo's web interface, API, CLI, and industry-standard automation tools, such as Terraform, Pulumi and Crossplane.
Request a demo today and try out Edge by Civo here.