Google’s Vendor Lock-In and Cloud Computing

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Table of Contents

Understanding Vendor Lock-in
The Reality of Vendor Lock-In
The Impacts of Vendor Lock-In
Google Cloud Services and Lock-In
Reference List

Understanding Vendor Lock-in

Since cloud computing became a necessity for companies involved in big data management, vendor lock-in has become a significant risk. However, little is known about the existence of the problem. To understand Google’s position in regard to cloud computing vendor lock-in, it is vital to gain a comprehensive view of the topic. Several researchers have attempted to explain the vendor lock-in challenge in an easy-to-grasp format to assist IT professionals and businesspersons, in making informed decisions.

Although many authors have approached the concept from different perspectives, they all recognize that the need for data storage solutions and the lack of sufficient research into the area are the major reasons behind the escalating challenge. Sjoerdstra (2016), in his article on dealing with vendor lock-in, begins by defining it as the dependence on a supplier by a customer. The dependence can arise from contractual agreements of perceptions by the client that the supplier offers an unparalleled solution. The latter, according to Straford (2020), has been the dominant claim over which cloud service providers have ridden, resulting in customer manipulation and a growing lock-in. In addition, Straford (2020) underscores that some vendors have used false claims to woe clients into adopting their services, only to realize that none of the promised solutions are provided. Changing from an initial provider to another one becomes challenging and nearly impossible following different product operations.

Although little focus has been paid to design parameters, the lock-in risk among cloud computing customers can best be understood from a technical lens. Opara-Martins et al. (2014) approach the issue from a design perspective, underscoring that the adoption of cloud computing solutions has been tied to specific service providers by virtue of their product designs. In view of this, Opara-Martins et al. (2014) allude that the lock-in problem can only be attacked from a product development point. Google has risen as a cloud service provider partly due to its product designs that feature three main solutions SaaS, PaaS, and IaaS. Customers depending on these solutions may find it hard to achieve the same level of satisfaction from other vendors, remaining tied to Google.

The benefits associated with cloud service products have also stood out as contributing factors to vendor lock-in. In their analysis, Różańska and Kritikos (2019) argue that on-demand resource allocation and deployment are among the chief benefits that clients have come to associate with cloud service solutions. As the industry is still developing, users have not grasped the idea that the same benefits can be obtained from other vendors except the ones they adopted at first. These elements describe explicitly the vendor lock-in problem giving insight into its existence, impacts, and a platform on which Google cloud services can be evaluated.

The Reality of Vendor Lock-In

Vendor lock-in has been shown to exist in the business world following an in-depth analysis of business trends, particularly the emergence of e-business. Cordella et al. (2011) focus their attention on the performance of e-businesses, revealing the significant roles of vendor lock-in in shaping the industry. The authors focused their attention on how the vendor lock-in problem arose in the business sector and the key players in it. In their analysis, Cordella et al. (2021) reveal that as business people are struggling to understand the entire online operations concept, cloud computing vendors are busy tailoring their products to supply not only the much-needed resources but also limit the data migration options available for users.

The need to migrate from one cloud service to another and the risks involved therein have been studied to reveal the existence of vendor lock-in and unveil the potential solutions therein. Opara-Martins (2017) looked into cloud Saas migration in light of the available options for migration and revealed that cloud service providers have made it quite challenging for users to switch vendors. From his analysis, Opara-Martins (2017) realized that not much attention had been paid to the technical aspects of cloud service operations, such as portability and interoperability. Evidently, most vendors, including Google, have made their products with limited portability. Körner (2020) adds to this topic by underscoring that non-portability has enabled vendors to manipulate users into remaining hooked up to their services despite high costs. If one tries to migrate to another service provider, high migration costs are involved due to the interoperability challenges.

Cloud computing has become vital for businesses to operate online, a factor that has been utilized by cloud service providers to create opportunities for lock-in. Shinwari et al. (2018) analyze the factors that have enabled the existence and thriving of vendor lock-in with respect to cloud computing. He feels that the core concept of cloud computing is “pay for what you use,” which implies individuals pay for the services that CSP provides, such as incoming and outgoing bandwidth for data transfer, as well as the storage capacity your data takes up in CSP’s data centers. This simple rule can keep a customer tied to a vendor; if they switch CSPs, they should first retrieve all their data from the prior CSP, for which they pay, and then upload it to a new one, which is an additional cost (Shinwari et al., 2018). Cost implications, alongside the newness of cloud computing, as alluded to by Körner (2020), make up the most viable reasons for vendor lock-in. As the volume of data involved grows, the problem escalates.

Some cloud vendors don’t charge their clients for incoming bandwidth, which might lead to large data uploads and lock-in when it’s time to download everything. Another concern is the migration fee, which is charged to clients for moving their data to the new CSP as specified in the contract (Shinwari et al., 2018). This migration cost could be significant because they charge per unit of data rather than per GB, which raises the migration cost if the data is large in bulk. Due to such concerns, the cost of data transmission plus relocation becomes unaffordable for the consumer, who is thus locked in with the vendor.

From the standpoint of existing cloud computing challenges, overcoming the Lock-in risks involved calls for a deeper understanding of its taxonomy. Opara-Martins (2018) develops a taxonomy-based solution model for the lock-in risks encountered within the cloud computing environment by moving from the basics of its existence to three main elements; interoperability, portability, and security. The first two elements have also been researched by Lisdorf (2021) in his analysis of vendor lock-in profiles. In his evaluation, Lisdorf (2021) approaches the topic by unveiling five major distinctive factors differentiating available cloud-computing vendors; product packaging, vision, end-user target, cloud focus, and customer orientation. Linking with Opara-Martins’ (2018) evaluation, these authors imply that cloud service providers have intentionally designed their products with a specific target- lock-in. Therefore, Google’s cloud solutions and the risks involved can be understood in light of the company’s focus and product packaging.

The Impacts of Vendor Lock-In

One of the significant areas of influence by vendor lock-in has been the business environment. Therefore, it is imperative to unveil how cloud service vendors have affected enterprises through their product designs and operations that have resulted in a near-total dependence on specific service providers. Ahn and Ahn (2020) conducted an empirical study to determine how enterprises’ willingness to implement cloud-based solutions is influenced by some aspects of the business-innovation link, including vendor lock-in. Organizations are interested in enterprise resource planning (ERP) conversions from an established on-premise technique to a cloud-based system to improve the sustainability of corporate operations. The authors used the technology-organization-environment, innovation diffusion theory, and the concept of innovation resistance paradigms to conduct a comprehensive analysis (Ahn and Ahn, 2020). Organizational culture, the expectations and benefits accrued, regulatory system, trialability, and vendor lock-in all had a substantial impact on the desire to adopt cloud-based ERP, according to the empirical investigation.

On the same note, small-scale (SMEs) and large-scale enterprises (LEs) have faced significant challenges in their adoption of cloud-based solutions. Haddara et al. (2022) researched the cloud-ERP adoption limitations and revealed that although SMEs and LEs have found the cloud an invaluable element for their operations and sustainability, the dependence created by service providers has inflicted the corporations with significant operational challenges. Business revenue losses and lack of flexibility are among the issues noted by Haddara et al. (2022). The challenges extend into the procurement field, whereby suppliers and procurers tend to be bound in a lock-in that significantly limits the procurement process. Duraj (2017) evaluates IT procurement efficiency in light of vendor lock-in and records that a lack of proper documentation keeps the procurer dependent on the supplier for source codes, infrastructure, and data solutions. Notably, this connection inhibits the IT procurer from having exclusive product rights that would enable them to switch vendors.

Similarly, quality assurance has been noted as a significant problem facing cloud service users. While analyzing test as a service (TaaS), De Oliveira et al. (2017) noted that the main challenges limiting the efficiency and quality of TaaS are associated with the lack of standardization in the cloud service solutions industry. Evidently, poor configuration and management of tests have led to customer dependence on vendors in a lock-in that had significantly lowered the application extents of TaaS cloud solutions. Initial customer experiences with cloud service providers have been cited as viable explanations for why they remain in unproductive and negative experiences. Fliess and Volkers (2019) studied the influence of customer expectations and experiences on vendor lock-in and recorded that many customers dwell on the good experiences they had while ignoring the changing elements such as efficiency. Google established itself by providing solutions to the pressing problem of data access. Over time, customer dependence on Google cloud services has raised concerns warranting research into the issue.

Google Cloud Services and Lock-In

Google has dominated the cloud service industry, competing against Microsoft. Although it offers attractive packages, several researchers have found that the company maximized its market control to create a lock-in environment that has bound customers from seeking other solutions. Andročec and Vrček (2018) evaluated the resolution of cloud data and found that many of the available vendors have limited data migration and resolution. AlTwaijiry (2021) confirms that cloud providers face a slew of data migration issues due to standardization problems. Andročec and Vrček (2018) argue that clients should carefully select a cloud service, existing cloud storage solutions, and features to minimize the risk of data transfer complications in the cloud environment. It’s recommended to stay away from vendor-specific features that are not supported by other cloud providers.

Available cloud service providers differ in their product designs, calling for an evaluation of each to determine the vendor lock-in risks present. While comparing Google, Microsoft, and Salesforce, Andročec and Vrček (2018) reveal that Google has had the most significant lock-in challenge among the three cloud service providers. Looking at the large number of customers relying on Google cloud services, it can be concluded that the company intentionally omitted crucial documentation and standardization procedures to maintain the client dependence witnessed.

As IoT applications expand, the choice of a cloud service provider presents significant challenges to clients. Ucuz (2020) researched Google Cloud, Microsoft Azure, and Amazon web services, confirming that despite the fact that these platform explanations are thorough, users frequently have difficulty deciding which of the three platforms to use. In addition to operability, security has been cited as a significant factor leading to vendor lock-in. Sarker (2022) revealed that the choice of a cloud database is largely dependent on the security features embedded. At this point, Google has used its security measures through infrastructure and source codes to keep customers tied to its operation, as revealed by Finta (2022). In essence, the literature reveals that from the definition of vendor lock-in and the impacts of supplier dependence on business operations, Google is moving towards a total lock-in that will significantly affect customers.

Reference List

Ahn, B. and Ahn, H. (2020). Factors affecting intention to adopt cloud-based ERP from a comprehensive approach. Sustainability, 12(16), p.64-66.

AlTwaijiry, A. (2021). Cloud computing present limitations and future trends. ScienceOpen Preprints.

Andročec, D. and Vrček, N. (2018). Ontology-based resolution of cloud data lock-in problem. Computing & Informatics, 37(5), pp. 1231-1257.

Cordella, A., Martin, A., Shaikh, M., & Smithson, S. (2011). Management and innovation of e-business, Undergraduate study in Economics, Management, Finance and the Social Sciences (University of London International Programmers)

De Oliveira, R.R., Martins, R.M. and Simao, A.D.S. (2017). Impact of the vendor lock-in problem on testing as a service (TaaS). In 2017 IEEE International Conference on Cloud Engineering (IC2E), pp. 190-196.

Duraj, A. (2017). Vendor lock-in in IT procurement. (Bachelor thesis, Charles University)

Finta, G. (2022). Mitigating the effects of vendor lock-in in edge cloud environments with open-source technologies. Digital Scientific Archive

Fliess, S. and Volkers, M. (2019). Trapped in a service encounter: Exploring customer lock-in and its effect on well-being and coping responses during service encounters. Journal of Service Management, 31(1), pp. 79-114.

Haddara, M., Gøthesen, S. and Langseth, M. (2022). Challenges of Cloud-ERP Adoptions in SMEs. Procedia Computer Science, 196, pp. 973-981.

Körner, N. (2020). Institutionalized cloud clients: A description of SaaS vendor lock-in avoidance measures in organizations (Bachelor’s thesis, Lund University).

Lisdorf, A. (2021). Cloud vendor profiles. Cloud Computing Basics, pp. 95-108.

Opara-Martins, J., Sahandi, R. and Tian, F. (2014). Critical review of vendor lock-in and its impact on adoption of cloud computing. In International Conference on Information Society (i-Society 2014), pp. 92-97.

Opara-Martins, J. (2017). A decision framework to mitigate vendor lock-in risks in cloud (SaaS category) migration. (Doctorate Thesis, Bournemouth University).

Opara-Martins, J., 2018. Taxonomy of cloud lock-in challenges. Mobile Computing-Technology and Applications. IntechOpen.

Różańska, M. and Kritikos, K. (2019). Good bye vendor lock-in: Getting your cloud applications multi-cloud ready. In Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion, pp. 171-173.

Shinwari, N.A., Nasrullah, A.S., Sharma, N. and Noida, G. (2018). Vendor lock-in situation in cloud computing. International Journal of Creative Research Thoughts (IJCRT) 6(2), PP. 703-707.

Sarker, S. (2022). Choosing a cloud database solution for managing AEM survey datasets. Preview, 2022(216), pp.38-40.

Sjoerdstra, B. (2016). Dealing with vendor lock-in (Bachelor’s thesis, University of Twente).

Straford, A. (2020). Lock vendor rapped over ‘false claims’. Biometric Technology Today, 2020(5), pp.3-3.

Ucuz, D. (2020). Comparison of the IoT platform vendors, Microsoft Azure, Amazon Web Services, and Google Cloud, from users’ perspectives. In 2020 8th International Symposium on Digital Forensics and Security (ISDFS), pp. 1-4.

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