What is Multi-Cloud?
Multi-cloud is a cloud computing model where an organization distributes assets over at least two clouds from different providers, whether public or private.
Why is multi-cloud so popular?
Nearly all organizations have outgrown a single cloud environment for their IT infrastructure. To keep their businesses running efficiently, most run a combination of public and private clouds from multiple providers. Deploying a multi-cloud virtual infrastructure makes many business goals easier, which has led to its dominance in computing.
In fact, according to a 2020 report, 93 percent of enterprises that have more than 1,000 employees are using a multi-cloud strategy. And in another survey, 98 percent are planning to make the switch by 2021.
What should companies consider when creating a multi-cloud strategy?
As organizations develop their multi-cloud strategies, they must consider each cloud’s API formats and encodings, user access, and where data, applications, and web services reside to create a seamless experience. Taking care of integrating resources, security concerns, and varying privacy regulations is also critical to the design. But with careful planning, the resulting multi-cloud architecture should make it easy to access and manage data from any location with the lowest latency possible.
Multi-Cloud Architecture and Components
A. Understanding the components of a multi-cloud environment:
A multi-cloud environment is an IT architecture that utilizes multiple cloud service providers to meet various business needs. It can include a combination of public, private, and hybrid clouds. Understanding the components of a multi-cloud environment is crucial for effective management and optimization:
- Cloud Resources: Building blocks like VMs, storage, and databases from different providers for cost and performance optimization.
- Networking: Key for secure connectivity, including VPCs and Virtual Networks.
- Management Tools: Essential for resource orchestration, including Kubernetes, Terraform, and cloud management platforms.
- Security Tools: IAM, encryption, and CSPM ensure multi-cloud data security and compliance.
- Monitoring and Analytics: Vital for performance insights, cost optimization, and log analysis.
B. Considerations for data portability and application compatibility:
- Data Formats and Standards: Open formats reduce vendor lock-in, easing data migration.
- Data Migration Tools: Invest in AWS DataSync Azure Data Factory for seamless data movement.
- Application Design: Use cloud-agnostic design with containers (e.g., Docker) and Kubernetes.
- API Compatibility: Ensure APIs work across providers to avoid integration issues.
- Testing and Validation: Rigorous testing identifies and addresses compatibility issues in multi-cloud setups.
- Data Backup and Recovery: Implement robust data resilience and disaster recovery strategies.
Cloud-Native Application Development in Multi-Cloud
A. Designing applications for multi-cloud compatibility:
- Decoupled Services: Embrace microservices architecture for flexibility in choosing different cloud providers for various application components.
- Cloud-Agnostic APIs: Create APIs and interfaces that work seamlessly across multiple cloud providers, ensuring integration and portability.
- Data Independence: Isolate data access layers and use standardized data formats to prevent vendor lock-in. Consider multi-cloud databases for data availability.
- Service Discovery: Implement dynamic service discovery mechanisms, enabling connections to services across different clouds.
- Load Balancing and Failover: Utilize cloud-agnostic load balancers and failover mechanisms for high availability across cloud providers.
B. Implementing cloud-native architectures in multi-cloud environments:
- Containers: Leverage Docker and Kubernetes for consistent application deployment across cloud providers.
- Serverless: Use serverless platforms like AWS Lambda, Azure Functions, and Google Cloud Functions for scalable, event-driven components that abstract infrastructure complexities.
- API Gateways: Manage and secure APIs across multiple clouds with cloud-native API gateways offering features like rate limiting and caching.
- Auto-scaling: Implement auto-scaling policies to adjust resources based on workload demands, harnessing multi-cloud providers' capabilities.
- Observability and Monitoring: Gain insights with cloud-native observability tools like Prometheus, Grafana, and provider-specific services for troubleshooting in a multi-cloud environment.
C. Leveraging containerization and serverless computing for portability:
- Container Orchestration: Use Kubernetes to manage containerized applications consistently across various cloud providers and on-premises infrastructure.
- Serverless Functions: Develop and deploy serverless functions in a provider-agnostic manner using frameworks.
- Infrastructure as Code (IaC): Define and manage cloud resources consistently with IaC tools like Terraform and AWS CloudFormation across different clouds.
- Cross-Cloud CI/CD Pipelines: Automate deployment with CI/CD pipelines using tools like Jenkins, Travis CI, and GitLab CI/CD.
- Monitoring and Tracing: Ensure consistent monitoring and tracing solutions with open-source tools like Jaeger and Zipkin that work across diverse cloud environments.
By following these strategies, organizations can create highly portable and resilient applications capable of running seamlessly across different cloud providers in a multi-cloud environment, maximizing flexibility and adaptability.
Security and Compliance in Multi-Cloud
A. Multi-cloud security considerations and challenges:
- Data Security: Ensure data encryption in transit and at rest across all cloud providers to prevent breaches.
- Identity and Access Management (IAM): Manage access complexity with RBAC and most minor privilege access practices.
- Network Security: Implement firewalls, intrusion detection, and VPNs for secure network configurations.
- Logging and Monitoring: Centralize logs and employ SIEM systems for real-time threat detection.
- Security Automation: Automate security policies with Config tools.
- Incident Response: Develop a multi-cloud incident response plan with clear roles and responsibilities.
B. Identity and access management (IAM) in a multi-cloud setup:
- IAM Federation: Create trust relationships between the identity provider and cloud providers.
- Role-Based Access Control (RBAC): Define consistent roles and permissions across all clouds.
- Cross-Cloud IAM Solutions: Explore third-party IAM solutions for centralized management.
- Multi-Factor Authentication (MFA): Enforce MFA for added security and incredibly privileged accounts.
- Regular Auditing and Review: Audit IAM policies and access controls regularly.
C. Compliance and regulatory implications for multi-cloud deployments:
- Data Residency and Sovereignty: Comply with data residency and sovereignty laws by selecting compliant cloud regions.
- Data Encryption: Encrypt data in transit and at rest and maintain control over encryption keys.
- Audit and Reporting: Implement auditing and reporting mechanisms for industry-specific compliance.
- Data Retention: Enforce data retention policies and proper disposal.
- Compliance as Code: Use IaC and configuration management for consistent compliance.
- Third-Party Audits: Engage third-party auditors to validate compliance.
- Documentation and Training: Maintain comprehensive compliance documentation and provide training for stakeholders.
Thorough security and compliance planning are critical for safe multi-cloud operations, reducing security risks and ensuring regulatory adherence across diverse cloud environments.
Multi-Cloud Cost Optimization
A. Multi-cloud cost management:
- Cost visibility: Use cloud cost management tools and dashboards to track cloud expenditure.
- Resource Tagging: Tag projects, teams, and departments to categorize and assign expenses. This simplifies cost driver identification.
- Cost Allocation: Accurately allocate expenses to company divisions or projects for transparency.
- Budgeting: Set budgets for each cloud provider and track expenditures. Alerts can be set to warn you when expenditure exceeds thresholds.
- Cost Attribution: Identify cost-causing services and resources. Optimize or decommission unused resources.
- Rightsizing: Monitor resource utilization and rightsize instances and services to fit the workload. Many cloud providers provide rightsizing solutions.
B. Cloud provider cost comparison:
- Total Cost of Ownership (TCO) Analysis: Compare workload expenses on different cloud providers over time. Consider computation, storage, data transport, and support expenses.
- Cloud cost calculators: Cloud companies offer online cost calculators to evaluate workload expenses on their systems. Compare startup costs using these calculators.
- Pilot Projects: Use different cloud platforms to collect real-world cost data and evaluate each provider's performance and budget.
- Third-Party Cost Analysis Tools: Third-party cost analysis tools can comprehensively provide cloud provider cost comparisons.
C. Multi-cloud cost optimization:
- Reserved Instances: Invest in reserved instances or savings plans to cut expenses for recurring, predictable workloads. Match instance types and terms to your requirements.
- Spot Instances: For workloads that can withstand disruptions, use spot instances or preemptible VMs. These are much cheaper than on-demand instances.
- Auto-scaling: Implement auto-scaling policies to adjust resources automatically based on workload demand. Save money by scaling down during low usage.
- Idle Resource Identification: Assess idle or underused resources using automation and monitoring techniques. Automate shutdowns or suspensions.
- Data Transfer Optimization: Consider cloud provider-region data transfer expenses. Use CDNs or compressed data formats to optimize data transport.
- Resource Lifecycle Policies: Automate data and resource deletion after a certain period.
- Cost Governance: Implement cost governance rules to hold teams accountable for cloud expenditure and follow cost optimization best practices.
- Use of Serverless: Embrace serverless computing where applicable. Serverless services are cost-effective for event-driven workloads and eliminate the need to manage infrastructure.
- Use cloud-native services which provide pay-as-you-go pricing and automated scalability.
- Regular Review: Analyze and improve your multi-cloud environment continuously. Cloud providers create new services and pricing methods, so remaining updated is crucial.
Cost management and optimization in multi-cloud environments require ongoing attention. By monitoring cost optimization strategies, organizations can maximize the value they derive from their multi-cloud investments while minimizing unnecessary spending.
Data Management in Multi-Cloud
Data Management in Multi-Cloud- Data management in a multi-cloud context is a complex but essential aspect of cloud computing strategy. Managing data effectively across multiple cloud providers requires careful planning, robust strategies, and various tools and technologies. Here are some key considerations and best practices for data management in a multi-cloud environment:
A. Data migration and replication across multi-cloud:
- Ensure data compatibility across cloud providers using open standards.
- Use cloud providers or third-party tools for efficient data transfer.
- Implement data replication for consistency across cloud regions.
- Utilize Content Delivery Networks (CDNs) to reduce data migration needs.
- Explore hybrid cloud options for seamless data movement.
B. Data backup and disaster recovery in multi-cloud environments:
- Backup data to multiple cloud providers for redundancy.
- Create backup copies using snapshots and cross-region replication.
- Consider cloud-to-cloud backup solutions for specialized backup.
- Develop a comprehensive disaster recovery plan and test it regularly.
- Enforce data retention policies in compliance with regulations.
C. Data governance and compliance in a multi-cloud setup:
- Classify data based on sensitivity and apply encryption and access controls.
- Implement encryption for data at rest and in transit.
- Enable auditing and monitoring to track data access and changes.
- Enforce role-based access control (RBAC) and least privilege access.
- Conduct regular compliance assessments and adhere to data governance policies.
- Ensure data sovereignty compliance in different regions.
- Facilitate data portability while maintaining integrity and compliance.
- Define data lifecycle management policies for creation, use, archive, and deletion.
Data management in a multi-cloud environment requires careful planning and adherence to data governance and compliance principles. By addressing the pointers above, organizations can ensure that their data remains accessible, secure, and compliant across multiple cloud providers.
Performance and Scalability in Multi-Cloud
A. Load balancing and auto-scaling:
- Load Balancing: Use load balancers to evenly distribute traffic across cloud regions and providers for responsive workloads.
- Global Load Balancers: Optimize response times with global load balancers that route traffic to the nearest healthy instance.
- Auto-Scaling: Automatically adjust instances based on workload to handle increased traffic with horizontal scaling.
- Cross-Cloud Load Balancing: Distributing traffic across providers ensures redundancy and service availability during cloud outages.
B. High availability and fault tolerance:
- Multi-Region Deployment: Deploy in multiple regions for high availability and reduce downtime risks.
- Failover and Redundancy: Set up failover and redundancy at both app and infrastructure levels, including multi-cloud strategies.
- Active-Active and Active-Passive: Consider active-active for even distribution and active-passive for standby failover.
- Health Checks and Monitoring: Detect and respond to failures promptly with health checks and monitoring, triggering automated failover.
- Disaster Recovery Planning: Develop and test recovery plans covering cloud-specific and multi-cloud scenarios, with data backup in multiple locations.
C. Performance monitoring and optimization:
- Monitoring Tools: Use cloud-native tools to monitor app performance and resource utilization.
- Unified Monitoring: Consider suitable monitoring solutions for a single view of multi-cloud performance.
- Performance Benchmarking: Regularly benchmark performance to find improvement areas.
- Application Profiling: Identify performance bottlenecks with profiling tools and optimize code and configurations.
- Content Delivery Networks (CDNs): Reduce latency with CDNs for global content distribution.
- Content Optimization: Optimize content to reduce load times using optimization tools.
- Database Optimization: Fine-tune databases and implement caching and indexing strategies.
- Cost-Performance Trade-offs: Evaluate cost vs. performance for resource selection, considering associated expenses.
By focusing on all the pointers, organizations can ensure that their multi-cloud deployments are responsive, reliable, and capable of scaling to meet the demands of their users while minimizing downtime and performance bottlenecks.
Cloud Interoperability and Standardization
A. Interoperability challenges:
- Diverse APIs: Managing resources consistently across clouds is difficult due to varying APIs and interfaces.
- Data Portability: Ensuring data compatibility between clouds is complex due to differences in formats, storage, and services.
- Orchestration: Coordinating workflows across clouds is challenging with differing orchestration tools.
- Vendor Lock-In: Avoiding vendor lock-in is challenging, as proprietary services can hinder workload migration.
B. Industry standards and initiatives:
- Cloud Standards: The National Institute of Standards and Technology (NIST) defines cloud computing standards for interoperability and best practices.
- Cloud Native Computing Foundation (CNCF): CNCF promotes cloud-native technologies and tools like Kubernetes for multi-cloud deployment.
- Open Container Initiative (OCI): OCI sets container standards for portability across cloud providers.
- OpenStack: Offers interoperability and portability for building private and hybrid clouds.
C. Intercloud communication and data transfer:
- Direct Interconnects: Cloud providers offer dedicated connections for secure, high-speed communication.
- VPNs: Secure communication channels between on-premises and cloud resources and between cloud providers.
- API Integration: Programmatic interaction and integration of services between different providers.
- Data Transfer Services: Services like AWS DataSync and Azure Data Box facilitate secure data movement between clouds.
Effective standards adoption and intercloud communication strategies simplify multi-cloud usage, enabling organizations to harness its benefits while addressing challenges
Managing Governance and Compliance in Multi-Cloud
A. Establishing governance frameworks:
- Policy Definition: Define clear governance policies covering security, access control, data management, and cost control.
- RBAC: Implement role-based access control aligned with governance policies.
- Resource Tagging: Enforce resource tagging for cost allocation and compliance tracking.
- Compliance Standards: Align governance with relevant compliance standards and regulations.
- Change Management: Establish approval and documentation processes for changes.
- Monitoring and Enforcement: Use automated tools for policy consistency.
B. Compliance management and audit:
- Continuous Monitoring: Implement ongoing compliance checks.
- Audit Trails: Maintain detailed activity logs.
- Regular Audits: Conduct compliance audits.
- Documentation: Keep comprehensive compliance records.
- Incident Response: Develop procedures for compliance breaches.
- Data Protection: Encrypt and protect sensitive data.
C. Integrating multi-cloud governance:
- Alignment: Align with broader IT governance.
- Executive Support: Gain leadership support.
- Collaboration: Foster teamwork among IT, compliance, and business units.
- Training: Provide governance awareness training.
- Feedback: Gather stakeholder feedback for improvements.
- Review and Updates: Adapt policies to evolving requirements.
Effective multi-cloud governance and compliance require structured frameworks, monitoring, integration, and continuous improvement.
Future Trends and Innovations in Multi-Cloud
A. Edge computing and distributed multi-cloud strategies:
- Edge Clouds: Organizations will adopt multi-clouds closer to edge devices for low-latency IoT and edge applications.
- Distributed Clouds: Cloud providers will extend infrastructure to multiple locations for improved performance and resilience.
- 5G Integration: 5G networks will drive multi-cloud solutions for edge computing, benefiting AR, VR, and autonomous vehicles.
B. AI-driven multi-cloud management and optimization:
- Cost Optimization: AI and machine learning will optimize multi-cloud costs through usage analysis and resource consolidation.
- Performance Optimization: AI analytics will continually optimize multi-cloud performance, adjusting resources based on demand.
- Security and Compliance: AI will enhance threat detection, compliance monitoring, and autonomous cloud operations.
C. Advancements in multi-cloud tools and platforms:
- Management Platforms: Multi-cloud management platforms will become more comprehensive for provisioning and optimization.
- Intercloud Solutions: Tools for seamless intercloud communication and data transfer will simplify multi-cloud architectures.
- Integration: Solutions for integrating hybrid and multi-cloud environments will become more prevalent.
- Container and Serverless Orchestration: Advanced orchestration tools will manage complex architectures across cloud providers.
- Edge Management Tools: Specialized tools for edge computing management will emerge.
- Standardization Efforts: Industry standards for multi-cloud management will provide guidelines and best practices.
Multi-cloud computing will evolve with a focus on edge computing, AI-driven management, advanced tools, and continued standardization efforts, enabling efficient and secure management in a complex cloud landscape.
Why do companies use a multi-cloud approach?
Multi-cloud environments provide several advantages, but their real value depends on an organization’s goals. Potential advantages include greater flexibility, risk mitigation, access to expensive technology without the capital expenditure, high availability, and more. Each is covered in detail below:
- Flexibility: A flexible modular infrastructure helps companies develop software faster, adjust quickly to changing demand, and only pay for what they consume. It also allows companies to take advantage of technology advances rapidly, select different vendors to combine services, and create applications that are more custom and provide competitive advantage.
- Resiliency: By using multiple clouds, companies have limited exposure to just one vendor, which reduces the risk of outages/security failures. When one cloud fails, services from other providers can still run, keeping your business in operation. With such redundancies, organizations have an always-on, highly scalable backup for data, workflows, and systems.
- Costs: By using resources as a service, companies can avoid capital expenditures and increased staff count to reduce the cost of data management. And with providers absorbing the cost of maintenance and upgrades, an enterprise can focus more resources to deliver new/more products and services to customers without increasing personnel to manage them.
- Availability/performance: Once a new solution/service is identified, a cloud provider can get it up and running almost instantly, compared to longer on-premises timelines. Also, deploying workloads on clouds closer to where users reside can maximize response times and maintain high availability.
- Innovation: With a multi-cloud environment, enterprises can develop new and enhanced products and services, create innovative business models, and create new revenue streams.
- Data sovereignty: Regulations, laws, and corporate policies can require data to physically reside in a given region or country. Organizations can use a multi-cloud solution to locate data storage within the areas being regulated.
What is the difference between multi-cloud and hybrid cloud?
The main distinction between multi-cloud and hybrid cloud is that hybrid cloud consists of different cloud types—such as public/private and on/off-premises—while multi-cloud includes different service providers. Selecting between the two cloud models depends on the IT needs of an organization.
A hybrid cloud is actually just one object that joins the distinct environments of private and public cloud. The two are integrated together and act as one unit. The private and public cloud share resources and can move workloads from one to the other as demand fluctuates.
Working within a multi-cloud environment is much more complex. Essentially, it’s just like solving a puzzle with many pieces. A business can choose the components that work best for their requirements and either integrate them or not, depending on their goals. While it can be challenging, once the environment is assembled your organization can reap the benefit of better resource utilization, resiliency, and potentially lower costs.
How are multi-cloud environments used?
Organizations achieve varying benefits from using multi-cloud environments, such as scalability and customization, disaster recovery, application development, and managing in-house “shadow IT” services. The following are a few examples:
SNP, Poland’s leading SAP services provider, expanded its customer offerings through advanced storage services from the HPE GreenLake edge-to-cloud platform. GreenLake’s platform delivered a multi-cloud solution that enhanced SNP’s built-in high storage availability while ensuring business continuity and non-disruptive operations for its European customers.
The world’s largest legal team, Garrigues, needed a budget-friendly solution that offered the agility and scalability to handle spikes in demand with the same speed, reliability, and performance that their firm required to serve up any of 70 million documents instantly. HPE GreenLake cloud services was the game-changer for them. The multi-cloud service provided powerful processing capacity at a knowable cost beforehand.
An IT infrastructure-as-a-service provider offers a world-class private cloud for mid- to large-scale businesses to scale their applications globally. Looking to ensure constant availability with high application performance and end-user service quality, blueApache was struggling with forecasting their hardware requirements, which led to excess capacity much of the time. Using HPE GreenLake to manage their cloud infrastructure has allowed them to scale flexibly and economically so their time to value is accelerated while their upfront expenses decrease.
A major life insurance firm, YF Life, wanted to be able to develop new products and services while driving process efficiencies. Another critical component was their need to strictly control regulatory compliance and data sovereignty laws. These needs led them to HPE GreenLake, HPE Pointnext, HPE OneView, and HPE GreenLake Central. With these HPE solutions, YF Life was able to reduce their TCO by about 35%, support new electronic policy solutions, and gain a clearer picture of IT expenses.
HPE and multi-cloud
As a longtime leader in technology innovation, HPE offers a full suite of products and services to manage multi-cloud environments with simplicity and enhanced data protection and availability. With HPE, customers can build their cloud strategy, implement multi-cloud environments, and streamline costs and operations using consumption models.
The HPE GreenLake edge-to-cloud platform provides the operational efficiencies and agility you need along with governance, compliance, and visibility all in one as-a-service pay-per-usage contract. And with our cloud platform, you can quickly scale up infrastructure to retain financial flexibility, preserve cash flow, control spend, and reduce the cost of over-provisioning resources.
HPE GreenLake also delivers multi-cloud and workloads as-a-service to help you gain more business value, control, and adaptability. To maximize resource usage and manage spending, you gain a single view of usage and aggregate costs across multi-cloud with the visibility needed to handle every detail.
In addition, HPE GreenLake offers cloud data services to help customers protect their data and rapidly act on insights, from edge to cloud. Our subscribers are able to recover in minutes from ransomware, cyberattacks, and other unplanned downtime, bringing data back to its original state just seconds before the attack or disruption.
And customers can use HPE GreenLake’s cloud platform for industry-leading intelligent storage services. Powered by HPE InfoSight’s predictive analytics, you can run mission-critical applications in a secure, always-on, and agile data environment.