Stretching The Silver Lining: 6 Benefits of Edge Computing for DevOps

Software service delivery used to be simple. You had your servers, endpoints (usually PCs), and some network gateways on the way, and it was all very slow to deploy, update, and use. In 2023, software development and deployment processes dramatically accelerated with DevOps strategies and cloud-native architectures delivered using Kubernetes. 

But faster and shorter development cycles don’t always translate to a better user experience or lower operational costs, and the reason for that can be purely geographic – where the data meets your apps. Enter edge computing. Statista estimates that by the end of 2023, over 50% of IT infrastructure will be deployed at the edge. 

But what exactly is considered “edge,” especially in cloud-native applications? And how do DevOps practices apply to edge computing in a way that produces measurable positive business outcomes?

Edge computing in DevOps: where are we now?

Before discussing the intersection of DevOps and edge computing, it’s essential to define each of the terms and why integrating them presents a challenge.

DevOps is an established and widely adopted agile software development practice that “shifts left” the building and management of all software development operations. Not entirely IT and not software engineers, DevOps engineers are tasked with meeting the platform and environment needs of developers while ensuring day two operations run smoothly for users. All while trying to stay on budget and automate repetitive tasks across platforms and services. So, let’s just say, not the easiest of jobs. 

Edge computing is a type of architecture that entails storing and processing data closer to where it is produced rather than in a centralized data center or public cloud, thus lowering network latency and reducing network resource consumption.

But where does edge computing start, and where does it end? It could be at the edge of the cloud or in a regional data center; perhaps the edge is a micro-data center with a 5G antenna on the roof of a farm or some old dusty data center in a closet in a hospital. It could also be a dedicated edge server, a gateway, or even a smart device in someone’s pocket. The answer is complicated and highly dependent on the type of applications and services you deliver and their intended target audience.

The Cloud-to-Edge Virtual Plane

From a DevOps perspective, and in an everything-as-code world, one of the ways to approach the challenges of edge computing and reap its benefits is to see the distributed and hybrid infrastructure as a cloud-to-edge data plane.  

By unifying cloud and edge resource consumption under a single control plane, you can employ automation and AI to adapt your workloads to the best location, deploy additional instances, and optimize data availability according to business needs and budget constraints.

With Control Plane, your codified infrastructure becomes geo-optimized for superior performance at lower operational costs. It’s simple: our DNS intelligent router connects each user request to its nearest server. If one server isn’t running correctly, the request is related to the second closest healthy workload, so your app’s performance is always optimal. You have complete workload portability between hybrid, public, and private clouds.

6 Benefits of Edge Computing for DevOps

Applying DevOps principles to edge computing is, in many ways, inevitable. It is the only cost-effective way for businesses to solve the challenges engrained in managing the increasingly complex infrastructure of interconnected edge applications and ensuring they perform according to user expectations. Let’s break them down:

1. Availability & Resilience

Service failure isn’t an option. It optimizes end-to-end system performance when applications and services can run anywhere and interact with other services on other platforms. In addition, your codified infrastructure can enable failover at the edge, deploying unbreakable workloads even if some edge resources are unavailable. 

If one workload fails, user requests are served by the second nearest healthy workload. If a whole cloud fails, that’s not the end-all-be-all either. With the help of multi-cloud management tools, you can also move your workloads to another cloud to avoid any service disruption. Control Plane ensures 99.999% availability – meaning that your services will be fully up and running 99.999% of the time (an average of less than 6 minutes downtime per year). 

2. Performance & Latency

A seamless user experience always starts with low latency. Your users don’t have another second to spare before they get confirmation that a payment went through or that they won their online game. And this applies to any industry – whatever users want; they want it now. 

By bringing computation close to the data source and reducing the physical distance between the server and the user, edge computing allows faster processing and response times (think real-time), optimizing your app’s performance. 

3. Optimized Costs

Let’s address the elephant in the room, shall we? Cloud costs are challenging to track, and this lack of control affects many businesses’ operations. By running your workloads closer to the edge, your data is processed locally, and only relevant data is sent to the cloud for further processing. This filtering capability enables you to reduce the costs of data transfers to the cloud and to free up cloud resources for other tasks. 

Going one step further in your cost savings journey, solutions like Control Plane’s Capacity AI enable you to only pay for the computing resources you use. You can scale up and down as needed, and app usage is billed by millicores (one-thousandths of CPU core) and megabytes of memory. 

4. Extra Security 

Security is an increasing concern for cloud-based businesses, especially those that run an extensive cloud infrastructure. And there is no wonder why, as 39% of companies suffered at least one data breach in their cloud environment last year.

Edge computing offers an additional layer of security by segmenting your virtual and physical data centers. It isolates, at least in part, the data and apps at the edge of your infrastructure, preventing breach escalations. With a codified hybrid edge computing infrastructure, DevOps teams can apply specific threat detection measures to different edge nodes according to the sensitivity of the data they store and process.

5. Improved Regulatory Compliance 

As of 2023, 157 countries worldwide have data privacy laws in place, with the EU’s GDPR serving as an example for many other regulations. Local data privacy regulations are versatile and rapidly evolving, so compliance is an ongoing challenge. Plus, some regulatory frameworks require you to keep sensitive data within certain geographics, which can be a challenge if data from across the globe needs to travel to one data center to be processed and stored. 

Because data is processed and stored locally with edge computing, you can keep the data within the geography required by law. Plus, you don’t need to transmit data over public networks, reducing the risk of data breaches and making DevSecOps implementation much more straightforward. 

6. Elastic Scalability & Flexibility

Edge computing enables distributed computing while maintaining the scalability and ease of cloud computing deployment. With DevOps at the helm of compute resource allocation and management, you have much more flexibility and reduce the load on your core data servers. 

Unlike static, on-prem servers, cloud functionality extended to the edge can let you automatically and effortlessly scale resource consumption up and down according to end-user activity. You can also port or clone workloads throughout your distributed edge cloud according to the geographic source of the traffic.

7. Reduced Maintenance & Management Overhead

One component that enables the hybridization of cloud services and promotes the adoption of edge computing is containerization technologies, specifically Kubernetes. Its flexible architecture and self-healing capabilities make Kubernetes the natural cloud-native technology for processing data at the edge. Moreover, its ability to run applications across multiple clouds and different providers’ infrastructures enables performance optimization and increased reliability.

For organizations employing containerization technologies in their CD workflows, self-service orchestration should be a familiar DevOps concept. Developer-friendly Kubernetes orchestration tools that make it a breeze to create, manage and decommission platform-agnostic containers.

Frictionless DevOps to the Edge with Control Plane

Imagine a world in which developers effortlessly introduce containerized workloads anywhere they want in the organizational cloud-to-edge plane. Consider what your developers can do with a single platform that provides a standard and familiar interface for managing application deployment across the edge, the public cloud, and owned data center, all while balancing optimal performance for end-users and minimizing cloud expenses for your business. You can stop imagining now.

Just a few years ago, tools like Control Plane were the hope and dream of DevOps practitioners and developers. Today, infrastructure complexity doesn’t need to impact developer productivity and innovation. With Control Plane, you can combine the services, regions, and computing power of AWS, GCP, Microsoft Azure, and any other public or private cloud to provide developers with a flexible yet unbreakable global environment for building and scaling backend apps and services. Wanna see how that’s possible? Request a demo here.