Why Edge and IoT Demand a Unified DevOps Approach

Digital transformation touches every part of an enterprise—HR, finance, logistics, operations—but it is the IT function that must be the most responsive and agile. Applications are the primary vehicle through which business needs are met, which means delivering new deployments faster, with a consistent cadence, has become a strategic imperative rather than a nice-to-have.

Meeting that imperative typically involves a familiar set of modern practices:

• Containerized application packaging
• Iterative, pipeline-driven DevOps
• Microservice-based architectures
• Software-defined infrastructure
• Automation platforms for provisioning and configuration

These practices are well-understood for cloud and on-premise workloads. The challenge that edge computing and IoT introduce is extending the same discipline—continuous delivery, automated testing, rapid rollback—to environments that are physically distributed, resource-constrained, and often connected through intermittent or low-bandwidth links.

The Core Problem: Fragmented Development Methodologies

One of the most common mistakes enterprises make when expanding into edge or industrial IoT is treating those environments as entirely separate from their existing development pipeline. The result is two (or more) toolchains, two release cycles, and two sets of operational runbooks—multiplying complexity and slowing everything down.

A better model treats edge and cloud as different deployment targets for the same artifacts. Container images built and tested centrally can be deployed to edge nodes using the same orchestration tooling used in the data center. Continuous delivery pipelines can target edge clusters as just another environment, enforcing the same quality gates and rollout strategies.

This portability-first philosophy requires that the underlying platform be consistent across environments. That is where the choice of operating system, container runtime, and orchestration layer becomes critical.

Why Open Source Is the Only Practical Foundation

Proprietary stacks can introduce vendor lock-in that actively undermines portability. An application packaged for one vendor’s edge gateway may not run without modification on another vendor’s hardware—defeating the entire purpose of containerization.

Open-source software provides several structural advantages in this context:

• Portability: Open standards and open container formats (OCI) mean workloads are not tied to a specific vendor’s runtime.
• Security transparency: Open codebases allow the security community to audit, find, and fix vulnerabilities faster.
• Breadth of features: A large contributor ecosystem means edge-specific capabilities (hardware accelerator support, real-time kernels, LoRa/5G networking drivers) are developed and maintained by those closest to the hardware.
• Vendor independence: Organizations retain the ability to switch hardware vendors or cloud providers without rewriting their application layer.

SUSE’s Position in the Edge and IoT Stack

SUSE was among the first vendors to ship an enterprise Linux distribution, and it has extended that lineage into edge and IoT scenarios. The portfolio relevant to edge DevOps (as described in the original 2020 source material) includes several components:

SUSE Embedded Linux

An embedded Linux operating system designed for IoT and Industrial IoT (IIoT) devices. The goal is to provide a production-grade, security-hardened Linux foundation on resource-constrained hardware—the same kernel lineage that runs in the data center, adapted for the constraints of embedded and edge deployments.

SUSE CaaS Platform

A Kubernetes-based container-as-a-service platform that, per the source material, can be used to build and deliver applications targeting edge environments. Running Kubernetes-compatible orchestration at the edge allows teams to reuse the same deployment manifests, Helm charts, and CI/CD integrations they already use for cloud workloads.

Cilium-Based Advanced Networking

The source material references SUSE’s use of Cilium—an open-source project that provides eBPF-based networking, observability, and security for Kubernetes clusters. At the edge, network policy enforcement and east-west traffic visibility are especially important because edge nodes frequently operate in less-controlled network environments than a typical data center.

SUSE Cloud Application Platform

A platform-as-a-service layer (based on Cloud Foundry at the time of writing) that abstracts infrastructure details away from developers, enabling faster application delivery across cloud and on-premise targets.

Edge-Specific Technical Considerations

Several characteristics distinguish edge deployments from traditional data center or cloud workloads, and DevOps tooling must account for all of them:

Bandwidth and Latency Constraints

Edge nodes frequently sit on expensive or unreliable WAN links. Pushing every byte of raw sensor data to a central cloud for processing is economically and technically impractical at scale. Local pre-processing—filtering, aggregation, anomaly detection—reduces the volume of data that must traverse the WAN and enables real-time decision-making that a round-trip to the cloud cannot support.

Real-Time and Deterministic Requirements

Industrial, medical, and autonomous-vehicle applications often have hard real-time requirements. A general-purpose Linux kernel may need to be configured with real-time patches (PREEMPT_RT) or replaced with a real-time kernel variant to guarantee deterministic response times. Operating system choice matters here in a way it simply does not for a typical web application.

Remote Fleet Management

When a fleet of edge devices is spread across geographies—remote utilities, retail locations, transport hubs—manual updates are not a viable operational model. Automated over-the-air (OTA) update mechanisms, integrated with CI/CD pipelines, are essential for maintaining security and feature currency across the fleet without requiring on-site visits.

Machine Learning at the Edge

Running inference workloads locally—rather than sending data to a central ML service—reduces latency and bandwidth usage. Edge ML pipelines typically involve training models centrally (using aggregated data), then deploying optimized model artifacts to edge nodes where inference runs locally. Platforms that support GPU or neural processing unit (NPU) passthrough into containers simplify this workflow considerably.

In combination with communications technologies like 5G (low latency, high throughput) and LoRa (long range, low power), locally-running ML models can generate actionable insights from IoT sensor streams without a constant cloud dependency.

Applying DevOps Principles to Edge Deployments

The principles of DevOps translate to edge environments, though the implementation details differ:

Key Takeaways for DevOps Engineers

• Unify your pipeline. Resist the temptation to build a separate toolchain for edge. Treat edge nodes as deployment targets within your existing CI/CD system.
• Choose a portable base. An open-source, standards-compliant OS and container runtime reduces the risk of being locked into hardware or cloud vendor decisions made today.
• Design for disconnected operation. Edge deployments will lose connectivity. Applications, update mechanisms, and observability tooling must degrade gracefully and recover automatically.
• Account for real-time requirements early. Retrofitting real-time kernel support into a production edge deployment is painful. Understand latency requirements before selecting the OS layer.
• Automate fleet management from day one. Manual update processes that are acceptable for a handful of edge devices become untenable at hundreds or thousands. Build OTA update automation before the fleet scales.

Further Reading

For more detail on SUSE’s edge and IoT offerings, refer to the SUSE Edge Computing solutions page. For background on the Cilium networking project referenced above, see the Cilium project website. The original article appeared on TechHQ.

Why Cloud Certification Still Matters

Cloud computing has become a foundational skill for IT professionals. As organizations continue migrating workloads to platforms like Amazon Web Services (AWS) and Microsoft Azure, demand for engineers who understand cloud architecture, networking, compute, and storage services remains strong. Earning vendor-recognized certifications — or at minimum building documented, structured knowledge — is one of the most reliable ways to demonstrate competency to employers and clients.

The Complete 2020 Cloud Certification Training Bundle from Certs School packages 12 self-paced courses into a single offering aimed at beginners and intermediate practitioners who want structured coverage of AWS, Azure, Git, and Ansible.

What Is Included: All 12 Courses

The bundle covers a broad range of cloud and DevOps-adjacent topics. Here is a summary of each course:

Amazon Web Services (AWS)

• AWS Technical Essentials — Introduces core AWS concepts, terminology, benefits, and deployment models. A good starting point for anyone new to the AWS ecosystem.
• Introduction to Amazon S3 — Covers object storage fundamentals: buckets, permissions, versioning, and how S3 can store and serve large volumes of data at scale.
• Introduction to Amazon Route 53 — Explains AWS’s scalable Domain Name System (DNS) service, including how to register and manage domain names and route traffic.
• Introduction to Amazon EC2 — Walks through virtual compute instances: instance types, AMIs, security groups, and basic scaling concepts.
• AWS Solutions Architect Certification Training — Targets the AWS Certified Solutions Architect – Associate exam by covering architectural best practices, high availability, fault tolerance, and cost optimization on AWS.
• Amazon VPC Training — Explains Virtual Private Cloud networking: IP address ranges, subnets, route tables, internet gateways, and security groups.
• AWS Lambda Training — Introduces serverless computing on AWS, covering function creation, event triggers, execution roles, and IAM policies within Lambda.
• AWS Database Migration Service (DMS) — Describes how AWS DMS helps migrate on-premises or other-cloud databases to AWS with minimal downtime.
• AWS SysOps Associate — Covers operational topics aligned with the AWS Certified SysOps Administrator – Associate exam: deployment, monitoring, fault tolerance, and cost management.

Microsoft Azure

• Microsoft Azure Fundamentals — Introduces core cloud computing principles as implemented in Azure, suitable for professionals transitioning from AWS or starting their cloud journey on the Microsoft platform.

DevOps Tooling

• Git Training — Covers version control fundamentals using Git: installation, the three-stage workflow (working directory, staging area, repository), branching, file tracking, and working with remote repositories on GitHub.
• Ansible Foundations Training — Introduces Ansible 2.0 for configuration management and automation: playbooks, inventory, modules, and how to reduce manual operational overhead.

Who Is This Bundle For?

This bundle is best suited for:

• Entry-level IT professionals looking to build a broad cloud foundation before specializing.
• Sysadmins and infrastructure engineers who want structured AWS and Azure exposure alongside operational tooling like Ansible and Git.
• Developers who need a working understanding of the cloud services their applications run on.
• Certification candidates targeting the AWS Solutions Architect – Associate or AWS SysOps Administrator – Associate exams, who want guided preparation material.

Course Access and Completion Details

According to the original deal listing, the following terms applied at the time of purchase:

• Access duration: 1 year from the date of redemption.
• Completion certificate: Included for each course completed.
• Redemption deadline: Course codes must be redeemed within 30 days of purchase.
• Format: Self-paced online video instruction via Certs School.

A Note on Certification Validity

It is worth clarifying the distinction between a certificate of completion (issued by a training provider to confirm you finished their course) and an official vendor certification (such as AWS Certified Solutions Architect, issued by AWS after passing a proctored exam). This bundle provides the former. To earn official AWS or Microsoft certifications, candidates still need to sit and pass the respective vendor exams separately. The courses in this bundle are best used as preparation material toward those exams, not as a replacement for them.

Building on These Foundations

The course list reflects a practical combination: core AWS services (compute, storage, networking, serverless, database migration), an Azure introduction, and two DevOps tools (Git and Ansible) that are nearly ubiquitous in modern cloud workflows. For engineers who complete this material, logical next steps include:

• Sitting the AWS Certified Solutions Architect – Associate or AWS Certified SysOps Administrator – Associate exams through AWS’s official testing channels.
• Expanding Ansible knowledge into roles, Ansible Tower/AWX, and CI/CD pipeline integration.
• Pairing Git fundamentals with a CI/CD platform such as GitHub Actions, GitLab CI, or Jenkins.
• Pursuing the Microsoft Azure Fundamentals (AZ-900) exam as a formal entry point to the Azure certification path.

The original deal was sourced from the Neowin Deals store and was limited-time. Check current availability directly with Certs School or the Neowin Deals platform if you are interested in purchasing.

IT Organizations Are Being Redesigned From the Ground Up

Enterprises are fundamentally rethinking how IT operations are structured to better serve external customers. That shift is forcing a redefinition of many traditional job roles — and exposing a significant skills gap. According to a Forrester Research study by analyst Marc Cecere, many organizations report that they lack sufficient in-house expertise in analytics and data management, two capabilities that are becoming central to modern IT strategy.

The study examines how key IT roles will evolve over the next five to seven years from the time of publication (2017). Its conclusions remain highly relevant as the trends it identified — cloud adoption, automation, and DevOps normalization — have only accelerated since.

Three Core Takeaways from the Forrester Study

1. IT Headcounts Will Shrink Significantly

According to Cecere, “Automation, cloud, external services, and empowered business users will reduce the number of people needed in IT.” The trigger for visible headcount reductions, he argues, will be the retirement or re-engineering of large legacy system estates. Once organizations complete that migration work, the underlying operational workload that has historically required large IT teams will shrink substantially.

2. Remaining Roles Will Be More Strategic and Externally Focused

The roles that survive — architects, developers, and platform engineers — will look very different from their predecessors. “Many of the roles, such as architects and developers, will require increased business knowledge, consulting skills, and responsibilities that span the enterprise rather than a narrow functional area, technology, or business unit,” Cecere notes.

In practice, this means IT professionals can no longer operate as pure technologists working in isolation from business strategy. They must understand the customer outcomes their systems support and be capable of communicating across organizational boundaries.

3. Agile and DevOps Will Become the Default Delivery Model

“DevOps teams combined with agile methods will become the accepted means of building capabilities,” Cecere states. Rather than a niche practice or a transformation initiative, DevOps is expected to be the standard operating model for IT delivery — the baseline assumption rather than a competitive differentiator.

What Skills Will IT Professionals Actually Need?

The study’s most actionable message is directed at individual IT professionals: the time to reassess and upgrade your skills is now. With fewer total IT jobs available, positions will go to those who can clearly demonstrate business value. The most in-demand capabilities cited in the report include:

• Analytics and artificial intelligence — the highest-priority skill gap identified across organizations.
• Emerging technology specializations — including voice recognition, IoT, machine learning, and blockchain.
• Agile and DevOps methods — as process competencies, not just tool familiarity.
• Business knowledge and consulting skills — the ability to engage effectively with business stakeholders who are increasingly involved in IT decision-making.

“Specialization will be required in hot new technologies, including voice recognition, IoT, machine learning and blockchain, and methods such as agile and DevOps,” Cecere explains.

How Data and Analytics Roles Will Evolve

One of the more nuanced findings involves how data functions will be restructured. Cecere defines data and analytics roles broadly — covering data analysis, master data management, data integration, and data architecture — and predicts that these functions will become more segmented between business and IT units.

Rather than being centralized in a single data team, data experts will be aligned with specific business initiatives. Cecere describes this as a “major and minor” model:

“Machine learning, for example, requires people who know the algorithms, data and business purpose of the project. Business intelligence requires expertise in tools such as those from SAS, Microsoft or Tableau Software. These are different, but overlapping areas. To support these initiatives, data experts will have a major in tools and methods and a minor in initiatives such as machine learning, automation and business intelligence.”

— Marc Cecere, Forrester Research

This framing has practical implications for hiring and career development: deep specialization in one area combined with working knowledge of adjacent domains will be the expected profile for data professionals.

Automation Specialists Will Be a Dedicated Role

Cecere also identifies a growing need for dedicated automation specialists — a role distinct from developers or business analysts. These professionals will own end-to-end process automation, maintaining expertise in tools (the study cites UiPath and Pegasus as examples) as well as software engineering methods and the business processes being automated.

“Business and IT processes have been automated for as long as there have been organizations. Within IT this has been done by BAs, developers, engineers and numerous others. Future IT organizations will include automation specialists with knowledge of tools, such as UiPath and Pegasus, software engineering methods and business processes. These experts are dedicated to automating processes and keeping up to date with associated tools and techniques.”

— Marc Cecere, Forrester Research

Moving Toward a Multi-Sourced IT Environment

The organizational model itself is changing. IT departments are moving away from owning and operating internal assets — servers, data centers, custom applications — toward managing a portfolio of sourced services. Cecere describes this as a multi-sourced environment in which “their use of micro-services, contingent workers, cloud, and internal capabilities [are] recast as services.”

This shift places a premium on vendor management, service integration, and governance skills — capabilities that have not always been a focus of traditional IT career development.

What This Means for DevOps Practitioners

For engineers already working in DevOps, these findings validate the direction of the field while flagging areas to invest in:

• Data literacy is no longer optional. DevOps engineers who can instrument systems, analyze telemetry, and draw business-relevant conclusions from operational data will be significantly more valuable than those who cannot.
• Automation expertise is a career track, not just a task. Understanding the full lifecycle of automated workflows — from design to monitoring to continuous improvement — positions engineers for the specialist roles Cecere describes.
• Business context matters. DevOps practitioners who can articulate the business impact of their work and collaborate with product and finance stakeholders will be harder to replace than those who cannot.
• Platform and cloud skills remain essential. The move away from internal assets toward managed services reinforces the value of cloud-native expertise.

The broader message is straightforward: the IT roles that survive the coming automation wave will be those that add demonstrable, business-facing value. The time to build those capabilities is before the demand peaks — not after the restructuring begins.

The IT Profession Is Transforming

Constantly evolving technology is reshaping what it means to work in IT. Traditional, siloed roles — network administrator, storage administrator, systems administrator, database administrator — are being replaced by broader, more fluid responsibilities. The forces driving this change include the mainstream adoption of cloud computing, the rise of automation and machine-based technologies, and the spread of DevOps culture across the industry.

IT professionals who want to remain relevant must adapt. That means developing cross-functional skills, pursuing updated certifications, and learning how to communicate the business value of technology decisions to leadership — not just to peers on the technical team.

The Rise of the IT Generalist

The ability to rapidly learn new IT concepts and apply them in practice is becoming one of the most valuable attributes an IT professional can have. As workplaces grow more interconnected — through hybrid cloud environments, microservices architectures, and API-driven platforms — the rigid boundaries between IT disciplines are dissolving.

Deep expertise in a single technology is no longer sufficient on its own. Employers increasingly value professionals who can:

• Work across cloud, networking, storage, and application layers
• Bridge the gap between development and operations teams
• Understand containers and microservices, not just traditional infrastructure
• Translate technical decisions into business outcomes for non-technical stakeholders
• Act as IT liaisons between engineering teams and senior leadership

This is the profile of the modern IT generalist: solution-focused, adaptable, and capable of operating in hybrid and multi-cloud environments alongside automation tooling.

Automation and Machine-Based Technologies Are Changing Daily Responsibilities

Bots, intelligent monitoring systems, and automated workflows are taking over many of the routine, repetitive tasks that IT professionals once performed manually. Provisioning servers, applying configuration changes, monitoring system health, and responding to common alerts are all increasingly handled by automation tooling — from Ansible and Terraform to AI-driven observability platforms.

Rather than eliminating IT roles, this shift is elevating them. As automation handles lower-level operations, IT professionals move into more strategic positions:

• Evaluating and selecting automation tools that best fit the organisation’s infrastructure and security requirements
• Designing governance and oversight frameworks for machine-driven processes
• Advising leadership on which technologies to invest in and how to measure their return
• Owning security and monitoring for the automated pipelines and systems themselves

In practical terms, an IT professional who previously spent hours manually patching servers now needs to understand how to write and maintain the automation scripts — and audit them for correctness and security vulnerabilities.

DevOps Is No Longer Optional

DevOps is not a tool or a job title — it is a culture and a set of practices that brings software development and IT operations into a continuous, collaborative feedback loop. The core idea is that the teams who build software and the teams who run it should share ownership, share visibility, and work from a shared understanding of how the system behaves in production.

For IT professionals, adopting a DevOps mindset means:

• Participating in cross-functional teams rather than operating in isolation
• Treating infrastructure as code (IaC) using tools like Terraform, Ansible, or Pulumi
• Instrumenting and monitoring systems proactively, not reactively
• Contributing to CI/CD pipelines and understanding deployment processes
• Taking shared responsibility for the reliability and performance of production systems

Companies adopting DevOps practices see measurable improvements in deployment frequency, mean time to recovery, and overall software quality. IT professionals who can work within — and help build — these collaborative structures are in high demand.

Certifications and Continuous Learning Are Back in Focus

With new skill sets in demand, formal education and certification are re-emerging as important signals for employers. In particular, certifications related to the following areas are increasingly valued:

• Cloud platforms — AWS, Azure, and Google Cloud all offer structured certification tracks from associate to professional level
• DevOps and site reliability engineering (SRE) — including certifications from the DevOps Institute and platform-specific training
• Container orchestration — such as the Certified Kubernetes Administrator (CKA) and Certified Kubernetes Application Developer (CKAD)
• Security — with cloud-native and DevSecOps security disciplines growing rapidly in importance

Beyond formal certifications, IT professionals should build habits of continuous learning: following industry publications, participating in open-source communities, and regularly experimenting with emerging tooling in lab or sandbox environments.

IT Professionals Are Now Strategic Business Partners

Perhaps the most significant shift is cultural. IT professionals are no longer confined to the back room. They are active participants in business strategy — helping leadership understand what technology investments make sense, what risks need to be managed, and how digital infrastructure enables competitive advantage.

This requires not just technical fluency, but communication skills. An IT professional who can explain the cost-benefit tradeoffs of moving a workload to a managed Kubernetes service — in plain terms that a CFO or CTO can act on — is far more valuable than one who cannot bridge that gap.

The road map is clear: stay adaptable, invest in cross-disciplinary skills, build fluency in automation and cloud-native approaches, and learn to speak the language of the business. IT professionals who do this will not only survive the current wave of transformation — they will lead it.