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Cloud Services / DevOps

4 Guidelines to Tame Your Hybrid Cloud Migration

Reduce the complexity and reap the value of migrating your applications to a hybrid cloud model with these strategies.
Nov 30th, 2023 8:00am by
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Featured image by Jacco Rienks on Unsplash.

The allure of migrating applications to a hybrid cloud model is fueled by the expanding business benefits it offers: cost savings, consistency and rapid deployment. Notably, Gartner projects a remarkable 21.7% surge in public cloud spending this year, largely attributed to these benefits. Nevertheless, the journey to successful hybrid cloud delivery is complex and often learned through challenges ranging from application failures to developer frustration and missed market opportunities. These issues arise when cloud transformation initiatives, which tend to focus on infrastructure migration, neglect to establish governance policies for continuous application delivery.

In this context and with more variables than ever to control, how do you avoid a classic case of “now what do we do?” when something goes wrong? The answer rests with a lifecycle approach to continuous app delivery that incorporates intelligence, automation, scalability, governance and security — elements that facilitate the seamless delivery of high-quality, reliable applications.

Challenges of Migrating and Delivering Applications in Hybrid Cloud Models

While the benefits of cloud transformation are undeniable, hybrid cloud models introduce a host of challenges. One central issue stands out: complexity. As David Linthicum, Chief Cloud Strategy Officer, Cloud Services, at Deloitte Consulting, says:

“… [hybrid cloud environments] often devolve into isolated clouds working in silos. When that happens, each cloud environment requires dedicated operational teams and procedures, which adds complexity, heterogeneity, inconsistent operations and security challenges.”

This complexity manifests in several ways that can get you stuck and jeopardize business value:

  • More microservices, more pipelines: As applications are broken down into microservices for optimal cloud utilization and faster delivery, multiple pipelines and tools emerge. This leads to inconsistency, redundancy and higher infrastructure demands. This can increase the risk of change failure and add extra stress to developers.
  • Legacy application maintenance: Running integrated legacy-to-cloud applications requires significantly more resources and team collaboration than might be anticipated. It is like rebuilding a modern city on top of an old infrastructure city, while ensuring that everything runs smoothly and nothing breaks. You will need to support both.
  • Skilled-talent shortage: Managing hybrid environments demands specialized expertise, making it challenging to find people with the right skillsets and prevent staff burnout. Improving developers’ experience without requiring them to know everything by giving them effective tools to minimize manual tasks can help reduce turnover and remove the need for specialized expertise while also increasing productivity.
  • Security and compliance flaws: Tool sprawl, security breaches and audit requirements present new challenges and increase the likelihood of failures, downtime and non-compliance fines. Deploying applications across hybrid environments introduces new security issues, such as cybercriminals exploiting vulnerabilities at the application level, performing code injections or launching tampering attacks, as well as the need to comply with regulations including Sarbanes-Oxley (SOX) or Health Insurance Portability and Accountability Act (HIPAA). All these considerations must be addressed throughout the software delivery process.
  • Increasing total cost of ownership (TCO): Managing frequent shifts among public cloud providers, the cost of fixing change failures and business outages are some examples of hidden costs that add up in the TCO. The more you shift, the more potential places for failure, especially if you do not coordinate the hundreds of tasks and automate the transition between cloud providers.

How to Get Unstuck

To make sure the work developers have done does not get stuck at deployment, organizations should make sure they have done the right work and asked the right questions in the following areas:

Check Your Ongoing Business Assumptions

Are the assumptions you had before transitioning to the cloud lining up with the current business trends and reality? In order to keep your CI/CD pipeline moving, it’s important to engage with cross-functional teams to identify improvements, new skillsets and other deployment requirements that are needed. According to the Accelerate State of DevOps 2023 report, simply “using cloud” provides mixed results. To help avoid that fate, consider whether you are prioritizing transforming applications to be cloud-ready rather than just using a lift-and-shift approach. Are you analyzing business outcomes when migrating applications or only measuring infrastructure costs? By continuously revisiting your cloud transformation approach, you can avoid just checking the “cloud box” but also prioritize its more long-term value benefits.

Connect Tools for Integrated Orchestration and Automated Processes

Does your organization have a clear understanding of the effort and resource availability needed to transform your applications to the cloud? How do you prioritize your cloud initiatives relative to everything else? Can you ensure your CI/CD pipeline and security tools and cloud management tools are ready for hybrid application deployment and monitoring with well-established orchestration and automated processes? The hundreds of tasks required to deploy applications to production provide multiple potential points of failure. Creating developer self-service options to facilitate onboarding new applications, automating release processes and spinning up new cloud environments could help alleviate developer requirements while minimizing the risk of production failure.

Neale Foulds, release and IT change manager from National Broadband Ireland, says, “If you do something three times, you have a strong argument for automating. We do things thousands of times, and we want a dependable, deterministic outcome every time.”

Always ask yourself, “What can be done to minimize manual hand-offs, scripting and reduce change failure in production?”

Deploy with Governance and Guardrails

Orchestration and automation success require solid security processes running in tandem. Establishing governance policies, quality checks and compliance with industry regulations can ensure precise execution to minimize business disruptions and liability risks. Organizations will not benefit from all the gains of developer productivity mentioned above if security and compliance guardrails are not in place. Questions to ask include: Do you have checks in place to verify the security of artificial intelligence (AI)-generated code? What are potential security flaws in release processes?

Use AI-Powered Analytics to Measure, Evaluate and Predict Risks

Analytics are ultimately the key that drives ongoing alignment to business value. The Accelerate State of DevOps 2023 report states, “Improvement work is never done. Find a bottleneck in your system, address it and repeat the process.”

AI provides a continual feedback loop on your dynamic environment to keep things working today, next month and next year. AI gives the business visibility into what is working well, not working or missing by analyzing historical results and making predictions based on that history. Using this data can help you predict what is realistic to deliver in the future and identify possible points of failure that may occur in cloud environments. Linking continuous feedback to managing your ongoing business assumptions will help you create a secure and streamlined process to transform and migrate applications to the cloud while avoiding risk and achieving business outcomes.


Ultimately, being able to focus on business benefits including innovation and market leadership, rather than the table stakes of delivery processes and infrastructure, requires leaning on the principles discussed above. These are the same core principles that software development and delivery leaders rely on across the software development lifecycle: efficiently managed teams, orchestration of complex application migrations and automated repeatable deployments to heterogeneous environments. The addition of AI-powered analytics adds the capability to systemically identify bottlenecks, improve efficiencies and predict risks of migration delays, change failure or compliance pitfalls.

Explore emerging trends and learn more about how to extract business value from hybrid cloud environments in our ebook: “Transform the Complexities of Hybrid Cloud into Business Advantages.”

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