For businesses in the early stage of their ventures, proving that they have the expertise and technical know-how when it comes to cloud technology can be difficult. An acceleration toward digitization due to COVID-19 and an increasingly crowded cloud market, dominated by the big players, means that simply shouting about your skills in cloud engineering and DevOps isn’t enough to get noticed.

Joining forces with expert brands and entering into endorsement partnerships can propel your business by loading it with seasoned expertise. Accreditation, if you can achieve it, can give you a stamp of approval and reassurance to prospects that you have the relevant knowledge to support their digital transformation efforts. Collaborating with industry leaders on skills accreditation programs is a great way to demonstrate your capabilities and gives clear goalposts to work to when it comes to building and learning.

So, how do businesses achieve this status, and what are the long-term benefits of the process?

What does it take to become a trusted AWS Partner?
At AND Digital, we have achieved our accreditation as an AWS DevOps Competency Partner. A lot of hard work and investment has gone into building the technical skills required to reach such a high standard – logging and evidencing every action your team takes is no mean feat. From beginning to end, the course took around 6 months. The process begins with researching and selecting which specific AWS Competency your team is interested in achieving. It’s important to understand which AWS Competency your business is most suited to – so doing your homework is key. From there, there’s a lot of work to evidence, certificates to achieve, and reviews to undergo. Becoming an accredited AWS Partner brings a multitude of benefits to your brand, so is well worth the investment.

Top tips for the accreditation process:
Create detailed accounts of your work: To become a certified AWS DevOps Competency Partner, businesses need to evidence four case study examples, two public and two private. As such, we found it useful to bring in a tech writer who consolidated all our notes and observations throughout. We began with a technical exploration from the team to understand the best case studies to put forward, our work had to be clearly evidenced with strong examples and the documents to back it up which took a considerable amount of time to pull together. Maintaining clear and detailed accounts of previous work can prevent any delays. This information is firstly analyzed by AWS to check that it met the specific requirements before being passed on to be examined by a team of external auditors, so every detail counts when it comes to showcasing your work.

Prepare the marketing team: As part of the process, businesses are required to have certain marketing collateral in place across their website to aid with lead generation For the AWS DevOps Competency designation, we needed to evidence three technical blogs – businesses applying for the certification need to ensure that the content best reflects their expertise in the given AWS Competency. Once the accreditation is finalized, the collaboration should be displayed on the site. Even if a business is tech agnostic, demonstrating your skills in a particular type of cloud engineering is highly valuable to your brand and AWS is a respected cloud platform to use.

Advance technical training in the workplace: Having members of the team qualified in cloud engineering is another requirement of accreditation. For DevOps, we needed eight people in the team to have achieved their associate certifications and four pros. To fulfill this requirement and ensure that we’re on top of our game when it comes to cloud training, we’ve invested in third-party tools, provided access to LinkedIn Learning programs, and give our people additional time off from client-facing work to prepare for their exams. Building and learning in tandem is the fabric of our culture, and a similar approach would benefit any company looking to achieve cert status.

The benefits
Being able to showcase a close association with a major player such as AWS opens up a number of doors for smaller businesses. Operating within this kind of business ecosystem provides the opportunity to demonstrate a business’ DevOps and technical skills to an enormous global audience which can drive new business conversations and drive quality leads. Confirmation that your business is a trusted partner for a major cloud organization will ensure that prospects have confidence in your capabilities and you’re taken seriously as a technical player in the market. Building confidence within your teams and supporting them in their learning is an investment that will pay off in dividends.

At AND, we can automate platforms in as little as one hour, whilst other organizations can take almost eight weeks to complete the process – it’s something we’re really proud of, and working alongside AWS as an accredited AWS DevOps Competency Partner gives us a springboard to talk about our work and engage with other players in the market. The accreditation is a fantastic talking point and definitely gets you noticed in the cloud community – plus, you will be taken more seriously as a partner.

Investment in cloud tech as a key for the future
As businesses everywhere begin to operate in an increasingly digitized environment, technical skills and cloud expertise are a necessary investment for any business. Working towards coveted industry accreditations whilst prioritizing skills training, in the long run, is imperative. It’s a competitive, buoyant market for cloud engineers and DevOps at the moment; opportunities are at their fingertips and if they aren’t being fulfilled by their current work, they’re likely to look elsewhere. Investment in training and nurturing growth in this way breeds loyalty. For a company to thrive technically, it needs to host a wide range of diverse talent and be able to retain it. Learning opportunities should always be the key focus.

The shortage in this talent means it’s critical to advance the business’s cloud expertise by pursuing recognition from major global players, providing advanced training and certification opportunities for people will ensure long-term talent retention whilst making the business a leader in cloud engineering which is pivotal for long term success.

The cloud is becoming an increasing part of our lives, integrated throughout many aspects. Our phones sync photos of family and friends with the cloud, as well as an ever growing list of contacts.

Gaming consoles ensure that we don’t lose achievements from the hours spent. Even in offices, our software offers the option to back up to the cloud.

This technology is capable of so much more than simply providing backup – it is driving digital transformation, economic growth and job creation. The cloud has become an essential tool for organisations of all shapes and sizes, from government to corporate, from conglomerate to startups.

Not only that, the cloud is accessible for all and considerably more cost effective than on-site data centres, with the ability to scale up and scale down according to need – and thus suitable for every size of business and budget.

At tipping point
Spending on traditional, non-cloud, IT infrastructure is on the decline but still accounts for the majority – 57.2 per cent – of total spending on IT infrastructure. There are a number of benefits to utilizing the cloud, including the ability to scale up and scale down, which provides a cost-effective solution.

However, the benefits are so much beyond initial investment as a solid RoI (return on investment) is provided in a variety of areas.

With increasing complexity of local data residency and governance – as the region increasingly becomes a mature market – businesses of all shapes and sizes can meet compliance needs in a cost-effective manner. What’s more, the cloud can achieve the broadest compliance, security, privacy and certification standards with the most effective prevention and mitigation measures in the industry.

The cloud has applications for every level as it drives digital transformation for governments, organizations and startups, enabling them to better engage their customers, empower employees, optimize operations and transform their products and services.

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During the course of this year, we have seen how remote work has been enabled by the cloud, with communication apps and remote capability of devices providing an office from home. We’ve also seen how frontline workers have kept hospitals up and running and staffed grocery stores’ engage in curb-side pick-ups

The cloud has better connected these workers with corporate offices, digitize manual processes, equipping them with the right devices, and all on a foundation of security.

This technology provides an empowering capability, accelerating innovation by enabling companies to adopt AI, machine learning and other innovative technologies. This provides an in-reach option for start-ups and SMEs, providing increased competitiveness.

Instant connection
The cloud also enables organizations to immediately connect with IT resources. With the data centre migrated out, there is no need to wait for hardware deployment or procurement as this is part of the cloud service.

In the UAE there are now two Microsoft Cloud data centers, which integrate into a broader network across more than 60 regions. This is greatly aiding the entrepreneurial spirit that has long driven forward the UAE business environment, driving digital transformation, economic growth and job creation.

More customers in the Middle East can move with confidence to the cloud. We have particularly seen this come to light during the pandemic, where many businesses have experienced a response and recovery journey, with a first taste of cloud technology through business continuity.

Businesses will find they become even more competitive as they continue a digital transformation journey to reimagine their ways of working and empowered by the cloud.

“DevOps is not about what you do, but what your outcomes are.” That observation, attributed to Gene Kim — author of The Phoenix Project and a widely recognised voice in the DevOps community — cuts to the heart of a persistent problem: organisations adopting DevOps practices without clearly defining what success looks like.

DevOps enables faster delivery throughout the software development lifecycle, but speed is only valuable when it produces real, measurable results. When the end goal drifts out of focus, teams end up automating for automation’s sake, chasing the wrong metrics, and building pipelines that deliver little actual value. Below are five common mistakes that derail DevOps initiatives — and practical guidance on avoiding them.

1. Measuring the Wrong Things

A widespread misconception is that DevOps is fundamentally about automating everything. Automation is an important enabler, but it is not the destination. The harder question is: once you have automated, are you actually delivering better outcomes?

Metrics like deployment frequency and mean time to repair (MTTR) are useful indicators, but they do not, on their own, confirm that your team is delivering value to the business or to customers. Counting deployments without connecting them to customer outcomes is roughly as meaningful as counting lines of code.

Before you can measure improvement, you need a baseline. That requires defining what value means for your organisation and for each individual deliverable. Common value metrics include:

• Story points delivered to production — tracking actual throughput, not just work in progress
• Revenue impact — comparing outcomes before and after a feature ships
• Customer satisfaction scores — NPS, CSAT, or direct support ticket trends
• Lead time for changes — the time from code commit to production, as a proxy for pipeline efficiency

A cautionary example: it is possible for a team to spend 18 months “doing DevOps” — running standups, building pipelines, writing tests — without shipping a single change to production. That is process without outcome. DevOps is a means to an end; if it produces zero value, it is not fulfilling its purpose.

2. Neglecting Environment Stability

Pre-production environments are one of the most overlooked weak points in a delivery pipeline. An automated pipeline depends on code being built and deployed consistently across development, test, staging, and production environments. When those environments are fragile, unreliable, or poorly configured, teams spend their time diagnosing environment failures instead of fixing application defects.

Randy Bias popularised the “pets versus cattle” analogy for servers: pets are named, hand-maintained, and mourned when they fail; cattle are interchangeable and replaced without sentiment. The same logic applies to environments. If an environment is a unique, hand-crafted snowflake that only one person knows how to fix, it is a liability. Environments must be standardised, reproducible, and disposable.

Practical requirements for stable environments:

• Infrastructure as Code (IaC) — environments should be defined in version-controlled scripts (Terraform, Ansible, CloudFormation, etc.) so they can be rebuilt on demand
• Complete, consistent data — test data should be managed as carefully as application code
• Validated automation — if a piece of automation fails even 5% of the time, it introduces noise that makes it impossible to trust test results
• Isolation — no environment should be singular; if it cannot be replaced, it is a single point of failure

When the environment is unstable, you are gambling with the whole pipeline.

When a pipeline failure occurs in an unstable environment, the root cause is hard to isolate — it could be the code, the data, the middleware, the environment configuration, or any combination. Developers get pulled away from feature work to triage infrastructure problems, compounding the productivity loss.

3. Allowing Disconnected Toolchains to Fragment Teams

DevOps is as much a cultural and organisational practice as it is a technical one. A fragmented toolchain is often a symptom — and a cause — of fragmented teams. When planning, development, testing, release, and operations groups each operate their own tools with no integration between them, information silos form and handoffs break down.

Each group will always have its own domain-specific language and priorities. The goal is not to force everyone to use identical tools, but to ensure those tools are interconnected so that work flows smoothly across team boundaries:

• Planning initiatives (epics, user stories) should map visibly to development and testing work
• Test results and quality gates should be surfaced in release pipelines, not siloed in a separate QA dashboard
• Operational changes (infrastructure updates, configuration changes) should be tracked alongside application changes in a unified audit trail

Toolchain integration is not just a convenience — it is a prerequisite for the visibility and shared accountability that DevOps depends on.

4. Underestimating the Complexity of Hybrid Delivery

Modern software delivery rarely happens in a single, uniform environment. Most organisations operate in a hybrid world across multiple dimensions:

• Hybrid methodology — combining waterfall governance with agile delivery and DevOps automation
• Hybrid infrastructure — workloads split across on-premises data centres, public cloud, private cloud, and edge
• Hybrid geography — globally distributed teams working across time zones and regulatory boundaries
• Hybrid architecture — monolithic applications coexisting with microservices and serverless functions

Ignoring this complexity does not make it go away. A DevOps approach that works for a single cloud-native application may fail entirely when applied to a team managing legacy on-premises systems alongside a cloud migration. Organisations need tooling, processes, and governance models that explicitly account for hybrid delivery — otherwise improvements in one part of the delivery chain will be cancelled out by friction in another.

5. Automating the Wrong Things — Ignoring the Theory of Constraints

Eliyahu Goldratt’s Theory of Constraints offers a directly applicable lesson for DevOps: any improvement made anywhere in the system other than at the bottleneck is an illusion. If your deployment pipeline is blocked by a slow manual approval step, speeding up your build process will not improve overall throughput — work will simply pile up faster at the constraint.

This means that automating something just because it is automatable can be a waste of effort. The right question is: what is the actual bottleneck preventing value from reaching customers? That is where automation energy should be directed first.

Equally important: if a process is poorly designed, automating it does not fix it. It makes the bad process faster and harder to change. Organisations that automate confusing workflows end up with confusing automation. The sequence should be:

1. Identify the constraint
2. Simplify or redesign the process
3. Automate the improved process
4. Measure the outcome against the baseline
5. Repeat

Key Takeaway: Outcomes First, Automation Second

DevOps is not a synonym for automation. It is a philosophy of continuous, measured improvement across the entire software delivery lifecycle — from ideation through to production. The practices, tools, and cultural changes that DevOps demands are only worthwhile if they are anchored to clearly defined outcomes.

To avoid the traps described above:

• Define what value means before measuring it
• Invest in environment stability as a foundation for reliable automation
• Integrate toolchains to keep teams aligned
• Design processes and tooling that handle hybrid delivery explicitly
• Apply the Theory of Constraints — fix bottlenecks, not non-issues

When the end goal stays clearly in view, DevOps delivers on its promise. When it does not, organisations are left with faster, more automated ways of producing the wrong results.

The Shift from Infrastructure-Based to Application-Based Operations

For most of computing history, running a business meant running your own hardware. Server rooms, cooling systems, UPS units, and dedicated IT staff were simply the cost of doing business. That model is changing rapidly. Cloud computing — at its core, the delivery of computing resources over the internet by a third-party provider — has matured from a niche cost-cutting measure into a foundational element of modern enterprise architecture.

The transition isn’t just about moving files offsite. It represents a fundamental shift: instead of managing infrastructure, teams can focus on managing and improving the applications and services that drive business value. The operational model changes from reactive maintenance to proactive development.

Why Businesses Are Moving to the Cloud

1. Eliminating the Physical Footprint

On-premises server infrastructure carries significant hidden costs beyond the hardware itself: physical floor space, power consumption, cooling systems, redundant backup hardware, and the staff required to maintain all of it. As real estate costs rise in commercial centers, dedicating large portions of office space to server rooms becomes increasingly hard to justify financially.

Cloud providers achieve economies of scale that no individual business can match. Hyperscale data centers spread those infrastructure costs across thousands of customers, making enterprise-grade compute and storage accessible to organizations of all sizes.

2. Scalability Without Capacity Planning Guesswork

Traditional on-premises servers have hard limits. If you need more storage or compute, you order hardware, wait for delivery, rack and stack it, and configure it — a process that can take weeks. Cloud infrastructure scales on demand, often in minutes. This elasticity means businesses no longer need to over-provision for peak load or risk under-provisioning during growth periods.

3. Supporting a Distributed, Remote Workforce

Cloud-hosted applications and data are accessible from any location with an internet connection. This is not a minor convenience — it fundamentally changes how teams collaborate and how software is deployed. Instead of installing and updating software on each individual endpoint, cloud-based applications can be accessed through a browser or lightweight client, updated centrally, and rolled out instantly across an entire organization.

For DevOps teams specifically, this means:

• CI/CD pipelines accessible to geographically distributed teams
• Shared development environments that eliminate “works on my machine” problems
• Centralized logging, monitoring, and alerting accessible from anywhere
• Faster onboarding — new developers can access full environments without manual workstation setup

4. Security and Regulatory Compliance

Data protection regulations — including GDPR in Europe and a growing number of regional equivalents — place significant obligations on businesses to store, process, and protect personal data appropriately. Major cloud providers invest heavily in compliance certifications (SOC 2, ISO 27001, FedRAMP, HIPAA, and others) and offer built-in tools for encryption, access control, audit logging, and data residency.

For many small and mid-sized businesses, achieving equivalent security posture with on-premises infrastructure would be prohibitively expensive. Cloud platforms make enterprise-grade security controls accessible and auditable.

Important caveat: Cloud providers operate on a shared responsibility model. The provider secures the underlying infrastructure; the customer is responsible for securing their data, identity and access management, and application configuration. Misconfigured cloud storage buckets remain one of the most common causes of data breaches.

Where Cloud Services Are Heading

The next phase of cloud evolution moves beyond simple compute and storage. Several converging technologies are reshaping what cloud platforms can do:

Machine Learning and AI at the Platform Level

Cloud providers are embedding machine learning capabilities directly into their platforms. Services like managed ML training, inference APIs, and AI-powered operations tools (AIOps) are making it possible for engineering teams without dedicated data science resources to build intelligent features into their products. Anomaly detection, predictive scaling, and automated incident response are increasingly standard offerings.

Edge Computing

Not all workloads benefit from centralized cloud processing. Latency-sensitive applications — industrial IoT, autonomous vehicles, real-time video analytics — increasingly require compute to happen closer to where data is generated. The cloud is expanding outward through edge computing nodes, enabling hybrid architectures where processing happens at the edge but management, orchestration, and data aggregation remain centralized.

Software-Defined Networking and Infrastructure as Code

Cloud-native networking removes the dependency on physical network hardware and configuration. Combined with Infrastructure as Code (IaC) tools like Terraform and Pulumi, entire network topologies can be defined, versioned, tested, and deployed programmatically. This brings the same rigor and repeatability to infrastructure that DevOps practices brought to application code.

Cloud Enablement: Getting There Safely

Migrating to the cloud is not simply a matter of lifting and shifting existing workloads to virtual machines. Poorly planned migrations can increase costs, introduce security gaps, and cause performance regressions. Cloud enablement services — consulting, assessment, architecture design, migration planning, and ongoing managed operations — help organizations navigate the complexity.

A structured migration engagement typically includes:

• Discovery and assessment: Cataloging existing workloads, dependencies, and data flows
• Migration strategy: Determining which workloads to rehost, replatform, refactor, or retire
• Architecture design: Designing target-state cloud architecture aligned with security and compliance requirements
• Migration execution: Moving workloads in phases with validation at each stage
• Disaster recovery and backup: Ensuring recovery point and recovery time objectives are met
• Ongoing operations: Monitoring, cost optimization, patching, and incident response

For small and mid-sized businesses without large internal IT teams, partnering with an experienced cloud services provider can significantly reduce the risk and time-to-value of a cloud migration.

Key Takeaways for DevOps and Engineering Teams

• Cloud adoption is accelerating across organizations of all sizes, driven by cost, agility, and workforce flexibility.
• The operational model shifts from managing hardware to managing services — DevOps practices align naturally with cloud-native architectures.
• Security in the cloud is a shared responsibility; teams must actively configure and audit their own controls.
• Emerging capabilities — AI/ML services, edge computing, and software-defined infrastructure — are expanding what cloud platforms can do.
• Successful migrations require planning and phased execution; lift-and-shift alone rarely delivers the expected benefits.

Originally referenced from CIO.com — The Future of Cloud Services.