Navigating Cloud Complexity: Unifying Integration Solutions for Multicloud Environments

David S. Linthicum

Sponsored by Software AG.

Executive summary.

This paper clarifies how integration can help resolve cloud complexity and why there is an immediate need for effective integration solutions within enterprises. It explores the challenges of utilizing traditional systems when working with multiple cloud brands and categories of deployments, including private, public, and hybrid clouds, as well as different cloud types (i.e., SaaS, IaaS, and PaaS).

Other topics include the cost and talent implications of using multiple native cloud and non-cloud integration toolsets and the business issues around cloud complexity. Many enterprises, unfortunately, operate multicloud deployments with separate and disconnected operations across different clouds that include their own security, operations, and integration technologies. This siloed approach, which often leads to negative business value and the inability to change and scale core business systems, is a grave concern.?

To address these issues, we propose a unified solution that operates above the applications and clouds to provide a single, integrated platform for security, governance, and database development, with a focus on integration. This solution, with its emphasis on agility and adaptability, offers a beacon of hope in the complex cloud landscape. It introduces the idea of isolating volatility within a domain that is easy to modify, referring to the capability of the integration solution to adapt and withstand unforeseen changes, which are necessary to address the problem at hand.

Clouds and cloud integrations introduce complexities of their own. This paper provides strategies for overcoming these challenges and creating a more streamlined and well-integrated cloud environment. Enterprises need a comprehensive, adaptable, logical and physical architecture that can effectively manage multicloud environments while delivering agility and more value to the business.?

Some of the key conclusions reached in this paper include:

1. Enterprises face significant challenges due to multicloud complexity, which leads to inconsistent data answers and soaring complexities. This prevents effective data leverage and reduces business value.?
2. A comprehensive multicloud strategy provides organizations with greater flexibility, more cost-saving opportunities, improved reliability, and specialized access to various cloud services. Managing complexity requires direct integration.?
3. Unified integration solutions are crucial in managing cloud complexity and enhancing operational efficiency within multicloud environments. The investment can increase by 100 times in the first year and multiply by 5 in subsequent years.?
4. Organizations should implement adaptable integration strategies to manage cloud complexities and optimize performance. This objective requires a clear understanding of using the technology effectively, supported by a well-accepted strategy among stakeholders.?

Introduction

Cloud computing is now integral to operational efficiency and innovation in the modern business landscape. Due to the use of cloud computing and the need to leverage best-of-breed options from multiple cloud brands, the adoption of multicloud solutions has become a necessity. The use of multicloud deployments has ushered in a new era of complexity, which presents challenges for organizations looking to optimize their IT infrastructure. Although there are obvious advantages to using a multicloud approach, it brings challenges that must be addressed and overcome.?

The integration of diverse cloud platforms, including brands and types, each with its unique architecture, management, and security requirements, introduces operational challenges. This involves enabling interoperability between siloed cloud providers like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure, as well as with existing legacy systems, databases, and applications.?

Enterprises have realized that, in some cases, traditional systems like mainframes and commodity systems can provide better value than the cloud and have reverted to using them instead. However, more problems arise when working with outdated systems.

Integrating these different native technologies can introduce new challenges, particularly in managing both cloud and non-cloud assets. The consequences of using various native toolsets for integration are the creation of separate data sources, increased operational expenses, and limited scalability. The use of multiple integration technology stacks indicates that the entire integration framework is unnecessarily complex, and yet integration is crucial to minimize the complexities that come with using multiple clouds.?

Don’t forget that the main objective of integrating multicloud and heterogeneous (mixed) architectures is to reduce complexity and streamline operations, data flow, and applications across various cloud and non-cloud environments. Integration should simplify cloud complexity, enabling seamless communications and data accessibility across multiple systems. Agile and adaptable strategies can create a unified solution for addressing volatility and change in enterprise IT integration.

Let’s discuss the challenges and solutions related to managing cloud complexity.?

Evaluating Agility and Adaptability

The core value of IT is bound to both hard and soft values. Hard values are easy-to-measure tangible benefits such as cost savings and increased productivity. For instance, a company can reduce the cost of a sale by selling more through its website. Additionally, it can save money by using a shared public cloud service to reduce the cost of database usage.

Soft values such as agility and speed-to-market are more difficult to measure in terms of their business benefits. Even though they have clear and often significant value, it's hard for most enterprises to quantify them accurately. This often leads to soft values being overlooked despite being just as important, if not more so, as hard values. This oversight can be detrimental to the business to varying and sometimes catastrophic degrees.?

Some of the questions to help measure business agility (soft) business values may include:

1. How do current IT assets contribute to the enterprise’s agility? Identify the extent to which the enterprise’s technology supports rapid adaptation.?
2. How does the enterprise utilize IT assets to enhance hyperawareness and informed decision-making by leveraging real-time data analysis for proactive business strategies?
3. How do the enterprise’s current business processes and technological capabilities measure against industry benchmarks?
4. Assess the organization's IT assets to determine their capacity for fast execution.
5. Evaluate the IT assets' flexibility to embrace changes in technology and standards.

Of course, soft values have different levels of benefits depending on the business. Financial services companies can typically gain significant advantages from being agile because their market changes quickly, such as with the adoption of digital currency. However, a manufacturing company like a salt mining business may not reap the same benefits from agility if its market is relatively stable. However, most businesses desire and often require agility, and we must find ways to increase it.?

Complexity is the enemy of agility, especially in multicloud and heterogeneous IT infrastructures. It can hinder change by limiting the enterprise’s ability to alter data and application integration flows to support new and changing business processes.?

The relationship between agility and complexity and how they impact business value is depicted in Figure 1. The figure illustrates that, as complexity increases on the X-axis, agility decreases on the Y-axis, and vice versa. It is important to note that this figure is meant to represent the relationship between agility and complexity in general and not a specific problem domain. The more complex a system is, the less agile it becomes, which leads to reduced business value.?

Figure 1: The relationship between agility and complexity.

Addressing Volatility and Change

Various approaches can be explored to enhance resilience and adaptability while incorporating volatility to facilitate easier adaptations to evolving requirements and environments within a dynamic domain. Using a single stack technology for IT assets, such as security, operations, and integration, allows for easier changes to core services through a configuration layer.?

The main concept here is abstraction, a fundamental idea in computer science and software engineering. Abstraction involves simplifying complex systems by encapsulating their details while highlighting only the essential aspects. Simply put, we can deal with complex things using simplified representations (i.e., common APIs and common data flows) which make it easier for us to handle complex systems. Integration technology can provide these simplified representations.?

This method of dealing with complexity through abstraction is called “first conceptualization.” It involves creating a simplified conceptual model that emphasizes essential attributes while hiding unnecessary details. Data integration involves representing source and target systems using abstract representations to simplify their existence. This simplification makes it easier for integration engineers to leverage these systems without having to deal with native APIs and other underlying native aspects.

Consider data abstraction as a key attribute for dealing with complexity. Abstraction involves defining data types, structures, and operations without revealing the underlying implementation. Users can interact with data at a higher level, simplifying native systems.

Abstraction facilitates reuse by providing a clear interface and hiding implementation details. For instance, it allows for the reuse of data flows and adapter patterns, with these objects updated and improved centrally.?

Finally, abstraction deals with the concept of encapsulation. This is where an object's internal state is hidden, like being able to access the services of a container without having to manage its native functionality. Since the infrastructure services within each asset (such as a container) are encapsulated, understanding them is unnecessary. This reduces the need to deal with complexity in complex terms.?

Understanding the Unified Solution

So, let’s assume complexity is an unavoidable outcome of heterogeneity, including the use of multicloud and placing volatility into a single domain using abstraction. How do you approach these problems using a holistic solution? To address these issues, you need to understand how to create a unified solution.

Due to its inevitable complexity, a holistic solution that uses abstraction is necessary when dealing with heterogeneity. Integration is the most compelling priority for operations, security, and governance.

Here are a few core issues to address:

Selection of the domains and systems to view by means of abstraction. These can be leveraged by public clouds, mainframe systems, edge computing, AI, and other IT assets that produce or consume data or application behavior.?

Definition of the domains within an abstraction-oriented technology. For example, it's important to be able to define a system that involves public cloud providers, serverless systems, and even specific serverless application instances. This can be achieved through an integration solution that defines data flows and application behavior without requiring the integration engineer to understand the connected systems or native services in depth.

Assign data and application sources to domains and bind them to solution patterns. These solution patterns can be reusable integration flows, data mediation, semantic mediation, or other core services provided by integration technology. The idea is to save work by reusing the integration solutions across different domains and those domains across different systems. The benefit of integration technology is that it handles system details, freeing you from dealing with complex native services. This is the key to getting value from a unified solution.?

One common mistake is attempting to solve the issue of integrating all relevant systems and data sources by using multiple integration technologies. This becomes problematic when integrating technology to simplify complexity because each integration system becomes a separate IT service that requires management.?

Figure 2 illustrates this scenario. Specific integration technologies are assigned to each cloud in the top set of clouds, A, B, and C. Enterprises tend to choose integration technology from a particular public cloud provider, as it is often deemed the best option for use on that specific cloud and the path of least resistance to implementation.

Figure 2: An integration solution for each cloud and system versus an abstracted integration solution that spans all clouds and systems.?

Although the technology was initially implemented to fulfill a tactical requirement and integrated into a specific cloud, it ended up complicating the process with a unique set of approaches, development, features, and patterns inherent in each integration technology. Therefore, each technology requires specific skills, processes, and operations for each one in production. Again, more complexity hinders agility and business value.?

A standardized set of integration technology stacks used across all cloud providers would be more efficient. Including traditional systems, edge computing, and mobile computing in the standardized integration meta-architecture would also be ideal. This would result in a unified solution that can handle all integration services required across all platforms, data sets, applications, and core systems.?

Although it may appear to be an oversimplification of integration patterns, the concept is to utilize the abstraction, encapsulation, and mediation of the underlying systems that generate and consume data. Inter-platform application behaviors, such as APIs, should also be utilized to their full potential. The aim is to decrease the number of assets and redundant systems you deal with. This includes minimizing the number of integration technology stacks. Although you might need to use more than one system, depending on your specific requirements, the goal is to have the fewest integration technology assets possible to carry out integration operations. In other words, a minimum viable solution is preferred.

To further explain this, it’s helpful to focus on control planes and data planes.? The control plane is responsible for the decision-making aspects of integration management, including routing information, policy enforcement, and service management. It sets the rules for how data should be handled and routed. In contrast, the data plane directly processes and forwards data based on the control plane’s decisions. It manages the actual movement of data, ensuring packets are transmitted efficiently from origin to destination. This division enhances efficiency, allowing for specialized optimization of management and data handling, crucial for maintaining performance and reliability in complex integration domains like multicloud environments.

For instance, In webMethods.io iPaaS, control planes manage orchestration and resource coordination, while data planes handle actual data processing. This split architecture boosts scalability, as each plane operates independently, and enhances reliability by isolating faults in the data layer. ? Benefits include improved scalability, system reliability, and security across multicloud platforms. This framework allows for efficient integration management, quick updates, consistent policy enforcement, and optimized performance by localizing data tasks to reduce latency, fitting perfectly in complex, distributed cloud environments.

Conclusion

The integration of diverse cloud platforms, including legacy systems, ushered in a new era of complexity. It’s time for another shift in our approaches to dealing with IT complexity. We must address security, operations, governance, and integration to enhance agility and increase business IT asset value before complexity becomes a runaway train.?

Integration within highly heterogeneous landscapes aims to streamline operations, data flow, and applications in various cloud and non-cloud environments. Unified integration solutions will also address the challenges of agility and adaptability, which are directly related to the amount of business value derived from IT assets. It’s essential to prioritize hard and soft IT values, such as cost savings and productivity gains, alongside business benefits such as agility and speed-to-market.

Exploring a unified integration solution can help businesses simplify data handling, reduce complexity, and achieve operational resilience. This solution leverages abstraction, encapsulation, and standardized interfaces, which is quite different from the way enterprises currently approach integration.?

To streamline enterprise IT, it's important to normalize integration technology across multiple cloud providers, traditional systems, and edge computing. This will reduce redundant systems and the complexity caused by replicating work. Additionally, it's crucial to enhance data accessibility and ensure seamless communication to further improve efficiency.

Businesses can manage complexity more effectively by implementing updated integration strategies that incorporate key integration technologies. This includes improving agility and moving to a unified integration solution. By encapsulating validity into specific domains, we can reduce systemic complexities and foster adaptability to deal with any changes or expansions that the business requires.

About the Author

With over 30 years of experience in enterprise technology, David Linthicum is a globally recognized thought leader, innovator, and influencer in cloud computing, AI, and cybersecurity. He is the author of over 17 best-selling books, over 7,000 articles, and over 50 courses on LinkedIn Learning. He is the author of Enterprise Application Integration, which sets the standard for how data and application integration is defined. He is also a frequent keynote speaker, podcast host, and media contributor on digital transformation, cloud architecture, AI, and data and application integration topics.?

He drives new market offerings, service innovation, and thought leadership outreach, leveraging his extensive knowledge and experience in generative AI and cloud computing for business agility and growth. David is passionate about educating and empowering the next generation of cloud professionals, serving as an adjunct instructor for Louisiana State University and a mentor