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Combining multiple cloud providers creates more agile and robust architectures yet introduces management and governance complexities. This quick introduction to multi-cloud computing’s benefits and challenges will explain why most enterprises move their infrastructure to the cloud and how Starburst unifies distributed data storage to streamline data access.
A multi-cloud infrastructure uses cloud services from one or more vendors. These services may be public clouds, private clouds, or a combination of both. Companies integrate services from multiple cloud providers to make their distributed infrastructure more flexible and resilient while balancing performance and cost.
Multi-cloud refers to an architecture that exists purely in the cloud. Integrating an enterprise’s Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS) providers into a cohesive whole allows apps, storage, and workflows to function across providers.
Hybrid-cloud architectures add on-premises elements to the mix. These could be private clouds or legacy data centers that the company must maintain for compliance or due to technical debt.
Strictly applying these definitions would mean that only cloud-native businesses founded in the past two decades can genuinely claim to have multi-cloud architectures. Once on-premises resources enter the mix, as they do with most enterprises, it’s technically a hybrid cloud.
Compared to standardizing on a single cloud service provider, such as Amazon Web Services (AWS), developing multi-cloud architectures introduces challenges that companies must overcome.
Unifying the services from multiple providers into a cohesive environment requires a clear multi-cloud strategy, skilled staffing, and financial resources.
Each additional service multiplies the complexities, so companies must carefully plan the evolution of their cloud infrastructure.
Multi-cloud adds to IT staffing challenges since a company’s developers must understand the nuances of each service to ensure the two work together seamlessly. For example, two storage service providers will have different APIs, taxonomies, and features.
Investing in multi-cloud management platforms can help abstract these differences to streamline orchestration.
Public cloud providers set their pricing to encourage customers to stay in their ecosystems. For example, services like Microsoft Azure or Google Cloud Platform charge more for transferring data to other cloud providers than for internal data moves.
Companies with multi-cloud strategies must design their integration workflows to avoid excessive costs.
Security with a single cloud provider may seem more straightforward since security teams only need to learn one shared responsibility model, one set of controls, and one logging system.
However, a monolithic architecture constrains compliance. For example, a single vendor may not have the data center locations a company needs to comply with data sovereignty regulations.
Shadow IT is a particular cloud management and security challenge. Signing up with a SaaS is easy and usually free for individuals and small teams. Employees who bypass “cumbersome” governance policies may have the best intentions, but they create opportunities for data leakage that put the company at risk.
Network access controls, scanning, and strict policy enforcement can limit unauthorized cloud usage, but it won’t be enough. Multi-cloud strategies should understand why people want additional SaaS applications and create processes for experimentation that balance workplace innovation with management discipline.
Despite these challenges, the compelling benefits of multi-cloud computing make it the end goal of many company strategies.
Multi-cloud architectures improve the user experience and let companies balance workloads across providers.
Multi-cloud approaches push data and applications closer to users at the network edge to get the low-latency connection today’s distributed workforce demands.
Using multiple cloud vendors also makes cloud infrastructure more performant. When one vendor’s networks slow, IT teams can shift workloads to another provider and maintain the performance of their distributed network.
For similar reasons, multi-cloud architectures are more resilient since one service provider’s scheduled downtime or unplanned service outages won’t disrupt operations.
Kubernetes and other containerization systems enable platform-agnostic microservice architectures that reinforce business continuity by failing over gracefully from one cloud service to another.
Likewise, multi-cloud storage redundancy ensures company data is always accessible and speeds disaster recovery.
With the rise of data privacy and sovereignty regulation, multi-cloud strategies have allowed companies to strengthen their compliance efforts and minimize risk.
For example, American companies often find localized storage improves General Data Protection Regulation (GDPR) compliance. Rather than moving data to its primary service provider in the US, the company will add a service provider with data centers in the European Union to store data about EU residents.
Building an architecture on a single vendor’s platform prioritizes simplicity over quality. No cloud service provider can provide the best features for every use case. As a result, monolithic architectures accept inefficiencies.
A multi-cloud approach lets companies choose the best vendors for each use case. For example, they may pick a vendor to manage real-time data while going with another to store historical data.
Having different cloud vendors also gives enterprises more negotiating power to get better prices and support. Companies can move their applications or data elsewhere to avoid the costs of vendor lock-in.
Ensuring efficient access to data is a critical step to realizing the benefits of distributing applications and storage across multiple cloud providers. Starburst’s modern data lake analytics platform is a hybrid-cloud and multi-cloud solution that enables access to all enterprise data no matter where it lives.
Starburst Galaxy abstracts public cloud, private cloud, and on-premises data sources within a virtual data access layer based on the open-source Trino query engine. Data users can explore, discover, query, and analyze any dataset using the SQL tools they already use. Pipeline development is no longer necessary for every project, freeing data teams to support more complex big data initiatives.
Starburst integrates your different cloud providers within a unified data access interface that masks vendor-to-vendor variation from the user experience. Data users can focus on discovering and analyzing data rather than understanding the nuances of each platform’s API.
Starburst makes your data more portable to prevent vendor lock-in. With over 50 connectors to enterprise-class data sources, you can choose cloud storage providers that meet your performance, cost, and business needs. Switching vendors is much simpler since Starburst makes your cloud migrations transparent to data users.
Starburst also integrates your on-premises data storage within its single point of access to improve productivity and the return on data center investments. Analysts generate more complete insights when they can query on-premises systems as easily as the cloud. Making legacy systems more accessible also helps extend their usefulness, reducing the pressure for capital-intensive replacements.
While a virtual access layer democratizes data access, Starburst lets data governance teams develop role-based and attribute-based access controls. These granular policies can limit each user’s access to data at the schema, table, row, and column levels. This level of control is crucial in multi-cloud environments where data may reside in different regulatory jurisdictions.
Unlike traditional data warehouses and data lakes, Starburst is not a central data repository. All data lives at the source. As a result, Starburst decouples storage and compute to enable more cost-effective architectures. IT departments can combine storage vendors to reduce overall cloud costs.
Decoupling storage from compute avoids the tradeoffs imposed by a single cloud provider. You can build a performant cloud compute infrastructure that efficiently optimizes workloads.
Starburst builds upon the massively parallel processing SQL query engine with performance-enhancing features such as cached views, pushdown queries, and dynamic filtering. Starburst optimizers create query plans that balance performance and cost across most connectors.
Starburst’s single point of access improves multi-cloud use cases and enables data users to produce deeper insights that can support business growth.
Starburst lets data scientists and analysts access data sources directly, creating queries without needing custom data pipelines. Exploration and discovery become more agile as scientists can iterate towards more complete requirements for their big data projects.
Starburst frees data engineers from having to support every user request. Instead, data teams can focus on higher-priority projects. Direct access to data also simplifies data management by letting engineers quickly query metadata as they build complex pipelines.
Federating access control policies in Starburst lets governance teams apply policies uniformly across every cloud service provider. Stewards and admins can define a policy without creating implementations for each vendor. Moreover, Starburst’s granular access controls let governance teams design rules that comply with regional regulations while preserving appropriate user access.
IT infrastructure teams can use Starburst’s management tools to optimize their workloads. Starburst activity logs let IT departments analyze data usage to optimize network and infrastructure performance.
Up to $500 in usage credits included
Up to $500 in usage credits included