Introduction
Businesses across the spectrum have embraced the mainstream trend of cloud computing, lured by its myriad advantages. Cloud computing promises a dynamic, scalable environment that enhances operational efficiency and is friendly to the bottom line. Yet, it’s not without its fair share of complexities. Companies grapple with issues such as data integration, security, and the delicate balance of governance and compliance in this digital realm.
To address these challenges, many businesses are adopting a multi-cloud strategy, which involves using a combination of multiple cloud storage environments from different cloud providers and on-premises storage.
What is Multi-Cloud Data Management?
Multi-cloud data management is the oversight of data and application workloads across multiple cloud environments, facilitated by tools that provide cross-cloud visibility, control, and security. It organizes large volumes of data and distributes it among different volumes, file shares, or object storage buckets, to avoid over-reliance on one cloud platform. It uses a single interface, or “pane of glass” for viewing and managing the data across all clouds.
Types of Cloud Environments
There are three main types of cloud environments that businesses can use:
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Public cloud
A public cloud is a cloud service that is offered by a third-party provider over the internet. Examples of public cloud providers are Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), etc. Public clouds offer high scalability, availability, and cost-effectiveness, but they also pose some risks such as data breaches, vendor lock-in, and regulatory compliance issues.
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Hybrid cloud
A hybrid cloud is a combination of public cloud and on-premises data centers. It allows businesses to leverage the benefits of both worlds while mitigating the drawbacks. For example, a business can use a public cloud for non-sensitive workloads and an on-premises data center for sensitive workloads. A hybrid cloud also enables data portability and workload mobility across different environments.
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Multi-cloud
A multi-cloud is a combination of several public clouds and on-premises data centers. It allows businesses to diversify their cloud portfolio and avoid vendor lock-in. For example, a business can use AWS for compute services, Azure for database services, GCP for analytics services, and an on-premises data center for backup services. A multi-cloud also enables optimal performance and cost optimization by choosing the best cloud service for each workload.
Advantages of Multi-Cloud Data Management
Multi-cloud data management offers many advantages for businesses, including:
| Improved performance | By distributing data across multiple clouds, businesses can reduce latency and improve response time for their applications and users. They can also leverage the best features and capabilities of each cloud service for their specific needs. |
| Increased reliability | By using multiple clouds, businesses can avoid downtime and data loss due to failures or outages of a single cloud provider. They can also implement backup and disaster recovery strategies across different clouds to ensure business continuity. |
| Enhanced security | By using multiple clouds, businesses can reduce the risk of cyberattacks and data breaches by diversifying their attack surface. They can also apply different security policies and controls for different types of data and workloads across different clouds. |
| Reduced costs | By using multiple clouds, businesses can optimize their costs by choosing the most cost-effective cloud service for each workload. They can also avoid vendor lock-in and negotiate better prices and terms with different cloud providers. |
Data Sovereignty and Policy-Based Control
One of the main challenges of multi-cloud data management is data sovereignty, which refers to the legal jurisdiction that applies to the data based on its location. Different countries have different laws and regulations regarding data privacy, security, retention, and access. For example, the European Union’s General Data Protection Regulation (GDPR) imposes strict rules on how personal data of EU citizens can be collected, processed, stored, and transferred.
To comply with data sovereignty requirements, businesses need to have policy-based control over their data placement across different clouds. Policy-based control means that businesses can define rules and conditions that determine where their data can be stored and accessed based on factors such as data type, sensitivity level, geographic location, regulatory compliance, etc.
For example, a business can set up a policy that states that personal data of EU customers can only be stored in EU-based cloud regions or on-premises data centers. This way, the business can ensure that its data is compliant with GDPR and avoid potential fines and penalties.
Egress Fees and Caching
One of the challenges of multi-cloud data management is the cost of egress fees. Egress fees are charges from cloud providers for moving or transferring data from the cloud storage where it was uploaded. Egress fees can vary depending on the cloud provider, the destination of the data, and the amount of data transferred.
Egress fees can be a significant expense for businesses that need to access or move their data frequently across different clouds or to on-premises storage. For example, egress fees can occur when:
- Data is replicated or backed up to another cloud or on-premises storage for disaster recovery purposes.
- Data is migrated or moved to another cloud for performance or cost optimization reasons.
- Data is analyzed or processed by applications or services on another cloud or on-premises storage.
- Data is downloaded or streamed by users or customers from the cloud.
One way to reduce egress fees is to use caching – storing copies of frequently accessed portions of the data at cloud locations where they are likely to be consumed. File caching can improve application performance by reducing latency and bandwidth consumption, and at the same time, save on egress fees by minimizing the need to transfer data from the cloud storage where it was uploaded.
There are different types of caching that can be used for reducing egress fees as part of your multi-cloud data management architecture:
- Content delivery network (CDN) caching: A CDN is a network of servers that are distributed across different geographic locations. A CDN can cache static content such as images, videos, and web pages, and deliver them to users or customers from the nearest server. It can reduce egress fees by serving content from the edge servers instead of from the cloud storage where it was uploaded.
- Edge filers: Edge filers are devices that provide file services (such as SMB and NFS) at the edge of the network, closer to the users or customers. Edge filers can cache file data from multiple cloud storage providers and serve it from their local storage. They can reduce egress fees by serving file data from the edge (or from the cloud provider where the application is deployed, for in-cloud workloads) instead of from the cloud storage where it was originally uploaded.
Conclusion
Multi-cloud data management is a key strategy for businesses that want to leverage the benefits of cloud computing, but it requires careful planning and execution: Businesses need to have policy-based control over their data placement to comply with data sovereignty and other regulatory requirements, and often, use caching solutions to reduce or eliminate egress fees and optimize access performance.
