Top 5 Ways Cloud Providers Can Solve the Challenge of Data Gravity

Steven Zolman
Jul. 13,2023 | Cloud Azure AWS GCP


While cloud adoption has been growing rapidly since before the pandemic, in recent years, there are signs of a slowdown in the overall rate of growth. Several factors contribute to this trend:

  1. Price shock: As client organizations migrated their workloads to the cloud, they often underestimated the costs involved. While the cloud offers scalability and flexibility, it is not always the most cost-effective option, particularly for certain types of workloads. Some clients experience price shock when they receive their cloud bills, especially if they haven't properly optimized their resources, realized the implications of data movements, or fully understood the pricing models.                  See NET(net)'s recent blog on this topic
  2. Workload suitability: Not all workloads are well suited for cloud deployments. Certain applications, such as those with high data transfer requirements, performance-sensitive workloads, or compliance-sensitive workloads, may be more cost-effective or better managed on-premises. Client organizations are realizing that a one-size-fits-all approach to the cloud may not be optimal, leading them to repatriate certain workloads back to on-premises environments.
    See NET(net)’s recent blog on this topic
  3. Complex Migration Challenges: Migrating existing applications and workloads to the cloud can be a complex and resource-intensive process. Client organizations often face challenges in rearchitecting or refactoring their applications, dealing with data migration, ensuring security and compliance, and managing dependencies. These challenges can lead to delays and difficulties, causing some organizations to repatriate workloads instead of fully embracing the cloud.  See NET(net)’s recent blog on this topic
  4. The Nascent Nature of Cloud Cost Optimization Services: Despite the ability to analyze cloud workloads and empirically demonstrate more cost-effective countermeasures (many with outright engineering benefits), cloud cost optimization has not been able to stem the tide of eventual workload repatriations back on-premises when it comes to mitigating cost overruns resulting from the challenges enumerated above, among others. This is partly due to culture challenges and points of organizational friction between FinOps and DevOps, often resulting in a stalemate regarding potential changes that can result in cost savings, with the tie going to the engineers who are able to ‘tech-splain’ their rationality in such a way that makes it difficult for the bean counters to argue the merits of the counterpoints. Imagine a financial expert trying to explain the engineering benefits and cost advantages of bamboo (as compared to steel) with a room full of construction workers. It's unlikely that even the most compelling arguments about tensile strength will convince them to switch from rebar. Galileo got ridiculed for suggesting the earth revolved around the sun. Darwin was considered absurd to suggest the theory of evolution. Nikola Tesla was laughed at for suggesting power could be transmitted wirelessly. It’s not all that different for FinOps teams today when talking to DevOps teams about cost-savings ideas.  See NET(net)’s recent blog on this topic

Introduction – Data Gravity

If cloud solution providers want to reverse the recent trend of workload repatriation, one of the critical challenges they will have to solve is that of Data Gravity. Data Gravity and the associated costs of data egress can be a significant challenge. Workloads that involve large amounts of data transfer out of the cloud may face high egress charges, making it more cost-prohibitive to keep those workloads in the cloud.

As a result of these and other factors, some of which are illuminated above, there is a trend that reflects a growing recognition that the cloud is not a one-size-fits-all solution and that a hybrid approach, combining on-premises infrastructure with the cloud, may be more suitable for certain workloads.

  • Editor’s Note: It's important to note that while repatriation is occurring in some cases, overall cloud adoption continues to grow, albeit at a potentially slower rate. Cloud providers are actively working to address these challenges by refining their pricing models, enhancing their services for specific workload types, and providing tools and solutions to facilitate workload migration and management.

The industry is evolving, and client organizations are gaining a better understanding of how to optimize their cloud strategies to balance cost, performance, and compliance requirements.

Data Gravity is a significant challenge when it comes to cloud adoption and cost optimization. Data Gravity refers to the concept that as data accumulates and grows, it becomes increasingly difficult and expensive to move that data between different locations (including from a client data center to a cloud provider or between cloud providers, or even to different regions within the same cloud provider). The higher the Data Gravity, the more challenging it becomes to migrate or distribute data.

Data egress charges are a serious cost concern when moving large amounts of data out of a cloud provider's network. These charges can potentially make it cost-prohibitive for certain applications, especially those that have significant data transfer requirements.

Below, we have outlined the top 5 approaches cloud solution providers and/or client organizations should take to address the challenge of data gravity and mitigate the impact of data egress charges:

  1. Data locality: Cloud providers should establish data centers in various regions globally, allowing client organizations the ability to store and process their data closer to where it is generated. This reduces the need for data transfer over long distances, minimizing data egress charges.
  2. Edge computing: Cloud providers should invest in edge computing infrastructure, bringing computing resources closer to the edge of the network where data is generated. This enables processing and analysis of data locally, reducing the need for frequent data transfers back and forth between central cloud regions.
  3. Hybrid and multi-cloud strategies: Many client organizations are adopting hybrid and multi-cloud strategies to distribute their workloads and data across multiple cloud providers or a combination of cloud and on-premises infrastructure. This approach helps mitigate data gravity by reducing dependence on a single provider and enabling more efficient data movement between environments.  See NET(net)’s eBook on Multi-Cloud Strategies
  4. Data transfer services and pricing models: Cloud providers are introducing services and pricing models that aim to reduce data egress charges. For example, some providers offer data transfer services specifically designed to streamline large-scale data transfers, often with reduced or discounted pricing compared to standard egress charges.
  5. Data optimization and compression: Techniques such as data compression, deduplication, and intelligent data tiering can help reduce the overall data volume and optimize storage costs. By minimizing the amount of data that needs to be transferred, organizations can mitigate the impact of data egress charges.

While data gravity and associated costs remain a challenge, cloud providers are actively working on solutions to address these issues. It's important for client organizations to evaluate their data transfer requirements, consider data residency needs, and explore the available options provided by cloud providers to optimize costs and minimize the impact of data egress charges. In addition, client organizations should carefully consider on-premises solutions, as well as those that utilize hybrid and/or multi-cloud management technologies.


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