Bringing DevOps to the Edge: Managing Edge Devices at Scale

TL;DR: As more industries like retail, healthcare, and transportation use edge devices, managing them becomes a big challenge. By using DevOps principles—automation, security, and scalability—we can make managing edge devices easier. This post explains how DevOps is being used at the edge, with companies like Esper leading the way.

Why Managing Edge Devices Is Hard

With networks rapidly expanding through edge device proliferation, managing these devices is becoming more arduous. I had the opportunity to sit down with Sudhir Reddy, CTO of Esper, to discuss the growth in edge device deployments and how bringing DevOps, a process discipline normally associated with software development, could help solve a number of today’s edge challenges.

Esper concentrates on device management, in this case, enterprise edge devices distributed across a range of business locations. Great examples include airport kiosks displaying advertising or passenger information, restaurant POS systems or back-of-house displays, or even medical input systems targeted at patients and providers.

Previously, device management was a center-out motion with centralized servers and unsophisticated endpoints. But this model has given way to more engaging, sophisticated endpoints that must be responsive and interactive without relying on centralized updates. When staring down 50,000 or more endpoints in a network, central management is no longer tenable. Managing a dozen devices in a single restaurant might fit a centralized model, but a franchised model with thousands of worldwide locations in different time zones simply will not scale without some level of edge autonomy.

In this model, application and data become critical as organizations need to be able to view details from a high level across the whole system and drill down to the most granular details of a single device. Security, which is always at the top of mind nowadays, is essential when dealing with edge devices. Companies need to lock down edge devices in every way imaginable because most of these devices feature interfaces like USB that provide an entry point for attackers.

Edge devices are everywhere now: from airport kiosks to medical devices and retail checkout systems. These devices are important, but managing them—especially when there are thousands of them around the world—is really tough. Old ways of managing devices don’t work well because of time zones, network problems, and the large number of devices.

How DevOps Helps Manage Edge Devices

DevOps and edge computing can impact our daily lives in many real ways, helping make technology work better for us:

Real-Life Example – Smart Shopping in Retail Stores: Imagine a retail store using DevOps and edge computing for managing inventory. The store has dozens of smart cameras and IoT devices that track which items are picked up by customers. These devices gather data and send it to an edge device in the store that processes it in real time. If an item is running low, the system can automatically alert staff to restock it or even place an order for more supplies. DevOps practices help keep these systems updated and secure, ensuring that all devices work smoothly and the store can respond quickly to customer needs.

Real-Life Example – Healthcare Monitoring Systems: In a hospital, edge devices are used to monitor patients’ vital signs in real time. These devices send data to local servers to make quick decisions, like alerting nurses if there’s an emergency. DevOps makes sure that these edge devices are updated and secure, preventing any system failures. This means better care for patients, as any critical health issues are caught immediately, and the medical staff can react faster.

DevOps and edge computing are two transformative trends that significantly impact how organizations operate, enabling them to be more agile, responsive, and efficient. Here’s a breakdown of how DevOps and edge computing are changing organizational operations:

DevOps:

Accelerated Software Delivery: DevOps practices emphasize automation, collaboration, and continuous integration/continuous deployment (CI/CD). This leads to faster and more frequent software releases, reducing time-to-market and enabling organizations to respond quickly to customer needs.
Improved Collaboration: DevOps breaks down silos between development and operations teams. Collaboration is enhanced through shared responsibilities, increased communication, and cross-functional teams, leading to more efficient workflows.
Enhanced Quality Assurance: Automation of testing processes in the DevOps pipeline improves the quality of software. Continuous testing ensures that issues are identified and resolved early in the development process, preventing defects from reaching production.
Infrastructure as Code (IaC): IaC enables the automation of infrastructure provisioning and management. DevOps teams can define and manage infrastructure using code, leading to consistent and repeatable deployments.
Cultural Shift: DevOps is not just a set of tools; it’s a cultural shift. Organizations adopting DevOps prioritize collaboration, continuous improvement, and a customer-centric approach, fostering a culture of innovation and agility.
Monitoring and Feedback Loops: DevOps encourages the implementation of robust monitoring and feedback mechanisms. Continuous monitoring allows organizations to detect issues in real-time, gather performance insights, and make data-driven decisions for improvement.

Edge Computing:

Distributed Processing and Reduced Latency: Edge computing brings processing closer to the data source, reducing latency by processing data locally. This is crucial for applications that require low latency, such as IoT devices, augmented reality, and real-time analytics.
Scalability and Bandwidth Efficiency: Edge computing allows organizations to distribute computing resources across edge nodes, improving scalability and reducing the need for centralized data processing. This can lead to more efficient use of bandwidth and reduced network congestion.
Improved Reliability and Resilience: Edge computing can enhance system reliability by reducing dependence on centralized data centers. In scenarios where connectivity to a central data center is lost, edge devices can continue to operate autonomously.
Privacy and Compliance: Edge computing allows organizations to process sensitive data locally, addressing privacy concerns and complying with data residency regulations. This is especially important in industries like healthcare and finance.
Real-time Decision-Making: Edge computing enables real-time decision-making by processing data at the edge. This is critical for applications that require immediate responses, such as autonomous vehicles, manufacturing processes, and emergency response systems.
Support for Edge Devices: Edge computing accommodates the growing number of edge devices, such as sensors, cameras, and IoT devices. This enables organizations to harness the capabilities of these devices for data processing and analytics.

DevOps is usually used for software, but it can also be used to manage edge devices. It helps make sure they stay updated, secure, and working properly. By using DevOps ideas like automation and continuous delivery, companies can make edge device management more reliable and faster.

Key Benefits of Using DevOps for Edge Devices

Automated Updates and Configuration: DevOps helps automate updates and settings for edge devices. You can set a desired state for the devices and push updates to thousands of them, keeping everything working smoothly.
Better Security: Connected devices are at risk, so security is very important. DevOps allows for constant monitoring and security checks, which means issues are caught early—keeping kiosks, medical devices, or retail systems safe.
Scalability Across Locations: Managing a lot of edge devices in different places needs scalable processes. DevOps workflows help keep processes consistent and stable for both individual devices and large networks.

Esper: Leading the Way in Edge DevOps

Integration of DevOps and Edge Computing:

Automated Edge Deployments: DevOps practices can be extended to the edge for automated deployments. CI/CD pipelines can be adapted to deploy and manage applications on edge devices, ensuring consistency and reliability.
Infrastructure Management Across Edge and Cloud: DevOps teams can use IaC principles to manage both edge and cloud infrastructure, providing a unified approach to infrastructure management.
Edge Device Monitoring and Maintenance: DevOps principles of monitoring and maintenance can be applied to edge devices. Continuous monitoring ensures the health and performance of edge devices, while automated maintenance processes can address issues remotely.
Edge Application Lifecycle Management: DevOps practices support the entire lifecycle of edge applications, from development to deployment and monitoring. This ensures that edge applications are consistently updated, and issues are addressed promptly.

Many people associate DevOps with software, but the concepts espoused by DevOps are part of many disciplines beyond software development; DevOps is about workflows, processes, automation, and operationalizing change management and control. It’s more of a systemic framework than a coding paradigm, which is why areas outside of software development, like cloud infrastructure management, have raced to embrace DevOps principles. However, the device world has been slow to embrace DevOps, creating opportunities for companies like Esper. With DevOps in device management, tools like Esper can define the endpoint devices from a managed configuration profile and then deploy this desired state to all the endpoints worldwide. Most importantly, it can then maintain that state, enforcing security and preventing endpoint modification of either devices or applications.

With regulatory and compliance considerations top of mind in the face of cyber threats, businesses need the ability to not only protect these edge devices, but also report on them to either auditors or regulators. DevOps really simplifies this process.

Esper is a leader in using DevOps for edge device management. Their platform makes it easier for businesses to manage thousands of edge devices by focusing on automation, monitoring, and security. Some key features include:

Managed Configuration Profiles: Define a desired configuration and deploy it to all devices, making sure they stay compliant.
Continuous Monitoring and Feedback: Like DevOps for software, Esper uses real-time monitoring to catch problems before they get worse.
Automated Security and Compliance: Esper’s platform also helps meet regulatory needs by providing audit trails and automated compliance reports—helping industries like healthcare and transportation follow the rules.

DevOps and AI at the Edge

DevOps at the device level enables you to operate at scale, building pipelines, processes, and flows that enable applying policies, while still controlling deployment down to the device level. Since organizations already use DevOps with software, extending that process model to hardware makes perfect sense.

Looking forward, we’re seeing more artificial intelligence (AI) being deployed at the edge, where it can be more responsive to users. So, as organizations extend their DevOps to devices with a tool like Esper, they can also think about how this model will be extensible for them with AI.

AI is also being used more at the edge, powering things like healthcare tools and personalized retail experiences. Using DevOps for AI at the edge helps manage AI workloads better, keeping models updated and running smoothly. This means better performance, fewer risks, and faster rollouts.

Why DevOps for Edge Devices Is a Good Idea

The edge ecosystem is growing quickly, and old methods can’t keep up. DevOps helps by:

Automating repetitive tasks
Improving security with continuous monitoring
Scaling efficiently across different locations
Adapting quickly to changing business needs

Conclusion: The Future of DevOps at the Edge

As businesses rely more on edge devices, managing them becomes more complicated. DevOps is the solution, bringing automation, scalability, and security to device management—making it easier to manage everything from retail kiosks to AI-driven medical tools. Companies like Esper are showing what’s possible, and as AI at the edge grows, DevOps will be key to its success.

The future is bright for DevOps at the edge—it offers an efficient, secure way to manage the growing number of connected devices.