Distributed cloud infrastructure is gaining traction due to its ability to boost performance and reduce latency, enhance security and compliance, optimize Cost Management, and more. Discover more with Control Plane.

Think of the traditional cloud as a centralized powerhouse -- a massive network of data centers offering vast computing and storage resources. But what if you could extend that power outwards, placing it closer to where your users and devices need it most? That's the essence of distributed cloud infrastructure.

Distributed cloud offers the flexibility and agility your business needs to scale at different geographical locations, respond to changing demands, and unlock growth potential. The distributed cloud market was already a big hitter back in 2022, valued at $4.4 billion, and it is set to rise to $11.2 billion by 2027. 

What is a distributed cloud infrastructure?

A distributed cloud infrastructure is an architecture that leverages multiple clouds to satisfy compliance requirements, performance needs, or support edge computing, all while being centrally managed by a single public cloud provider. A distributed cloud service is a public cloud that distributes its services across various locations, including:

• The public cloud provider's infrastructure
• On-premises at customer data centers or edge locations
• Another cloud provider's data center
• Third-party or colocation center hardware

This strategic placement across regions and availability zones (AZs) within a cloud provider like AWS ensures flexibility and high availability. Despite being scattered across multiple locations and potentially even geographies, all these cloud services are managed as one unified entity through a single control plane. 

This control plane handles the inherent discrepancies and inconsistencies in such a hybrid, multi-cloud environment. Distribution of services empowers your organization to address precise requirements such as:

• Response time and performance thresholds
• Regulatory or governance compliance mandates
• Specific needs that necessitate cloud infrastructure to be deployed outside the cloud provider's standard availability zones

Use cases for a distributed cloud infrastructure

Ops Engineer Use Cases

• Content Delivery Network (CDN): Ops teams leverage globally distributed points of presence (PoPs) to store content closer to end users, drastically improving loading times and overall user experience.
• Monitoring and Visibility: Distributed cloud demands real-time visibility into the infrastructure's health. Ops teams configure robust monitoring and alerting, covering geographically dispersed components, to quickly troubleshoot and maintain system health.
• Infrastructure Optimization: Detailed metrics and analysis of resource utilization patterns across multiple regions enable informed decisions about scaling and capacity planning, leading to cost savings.

DevOps Use Cases

• Hybrid Cloud Deployments: DevOps teams seamlessly bridge the gap between on-premises data centers and cloud environments. This offers flexibility in workload placement and management strategies, including SaaS vs. self-hosted solutions.
• Disaster Recovery and Business Continuity: Automating failover procedures and regularly testing disaster recovery scenarios become priorities. They utilize infrastructure as code (IaC) principles for swift and consistent resource provisioning upon failures.
• Microservices Architecture: The distributed cloud model supports granular microservices deployment and scaling across locations. This promotes flexibility, rapid iteration, and streamlined management, often aided by Kubernetes orchestration tools and SaaS platforms.

Innovation Use Cases

• IoT Device Management and Edge Computing: Distributed architectures bring compute and storage closer to IoT devices for low-latency processing, supporting real-time analytics and decision-making capabilities.
• Global Gaming Infrastructure: Distributed cloud ensures optimal performance for online gaming platforms. It reduces lag by placing gaming servers near players and supports massive scaling for peak traffic.
• AI/ML at the Edge: Distributed cloud allows for the training and deployment of machine learning models closer to the data source, enabling faster insights and minimizing the need for backhauling large datasets.

Governance Use Cases

• Regulatory Compliance in Healthcare: Strict data residency requirements are met by storing and processing sensitive patient information within specific geographical boundaries, aligning with HIPAA or similar regulations.
• Securing Sensitive Data: The distributed model allows for fine-grained control over data placement and access, enhancing security posture. Sensitive data can be isolated on-premises or in specific cloud regions with heightened security measures.
• Data Sovereignty and Localization: Enterprises control where data resides for privacy and regulatory purposes. A distributed cloud model meets strict data localization laws and aligns with broader cloud risk management frameworks for compliance.

5 Challenges of a Distributed Cloud Infrastructure

Distributed cloud architectures have enticing benefits -- improved performance, resilience, and the ability to conquer compliance hurdles. However, without using an Internal Developer Platform like Control Plane to support developers, the increased complexity of managing a sprawling network presents a unique set of challenges to overcome.

Challenge 1: Complexity

Managing a network of geographically dispersed cloud resources, potentially spanning multiple cloud providers and on-premises locations, introduces significant new layers of complexity. Increased complexity in infrastructure can hinder:

• Troubleshooting and resolving performance issues
• Maintaining consistent configuration and governance policies
• Ensuring seamless communication between distributed components

Challenge 2: Security

Protecting data and applications becomes more difficult in a distributed environment. This complexity extends to managing secrets within containerized environments like those orchestrated by Kubernetes. There are more potential points of vulnerability, and it's harder to enforce uniform security standards across multiple locations, leading to:

• Loss of sensitive data or disruption of critical systems
• Compliance violations and potential regulatory penalties
• Damaged reputation and loss of customer trust

Challenge 3: Visibility & Monitoring

Real-time visibility into distributed systems' health, performance, and utilization is essential yet complicated. Without visibility, it becomes hard to:

• Quickly detect and mitigate outages or failures
• Optimize resource usage and proactively plan for scaling
• Gain insights into potential bottlenecks for optimization

Challenge 4: Heterogeneity

Distributed cloud environments often involve a mix of different hardware, software, operating systems, and cloud providers, resulting in an inherently diverse environment.

Heterogeneity complicates development, deployment, and management tasks. Ensuring compatibility and maintaining performance standards across the various components becomes even more challenging.

Challenge 5: Latency and Network Performance

While distributed clouds help reduce latency in some instances, they can also introduce new network performance bottlenecks if poorly configured or monitored.

Network challenges can:

• Negatively impact the user experience for applications that require real-time or near-real-time performance, leading to service disruptions or outages
• Challenge compliance efforts where strict data locality mandates exist

7 reasons to adopt a distributed cloud infrastructure

Reason 1: Enhanced Performance and Reduced Latency

Traditional data centers face the physical limitations of distance when it comes to performance. A distributed cloud architecture combats this by strategically placing computing, storage, and networking resources geographically closer to end-users. The physical proximity reduces the time data takes to travel, significantly boosting application responsiveness.

You can maximize performance by analyzing network traffic patterns, identifying applications with the absolute strictest latency requirements (e.g., real-time collaboration tools, online games), and considering deploying them in 'mini-clouds' at edge locations.

An IDP such as Control Plane shines in this scenario. When using Control Plane, engineers can create an unlimited number of Global Virtual Clouds™ (GVC™). When backend code is deployed to a GVC™, the workload gets instantly served as TLS endpoints from the GVC™'s locations, featuring built-in geo-routing. If a location or region experiences an outage, end-users remain unaffected as they are instantly routed to the nearest healthy location within the GVC™ delivering the lowest latency. Engineers have the flexibility to select any combination of locations that your organization requires to attain 99.999% availability, ultra-low latency, and security and compliance requirements.

Workloads deployed to these locations run on Control Plane's pre-existing clusters, eliminating the hassle of setting up your own clusters or creating your own cloud accounts. Control Plane offers all locations from AWS, GCP, and Azure.

Reason 2: Improved Resilience and Availability

By distributing resources across multiple regions or even cloud providers, distributed cloud architectures prevent single points of failure. If one site experiences an outage, traffic can be seamlessly routed to other locations, maintaining service continuity. 

Implement asynchronous or synchronous data replication strategies for maximum resilience based on your recovery point objective (RPO) and recovery time objective (RTO) targets. Additionally, utilize load balancing and auto-scaling techniques to distribute traffic effectively across multiple locations in your network.

Reason 3: Scalability on Demand

Distributed clouds excel at elasticity, offering the ability to allocate or release resources across multiple sites quickly. Unlike traditional on-premises infrastructure, you're not limited by physical hardware constraints.

To leverage scalability, embrace cloud-native development practices like containers and microservices for greater agility. Paired with orchestration tools like Kubernetes, you achieve seamless automated management of containerized workloads across geographically dispersed nodes.

Reason 4: Regulatory Compliance

Data sovereignty regulations (think GDPR) often mandate strict controls on where data resides. Distributed clouds empower you to designate the data storage and processing location, ensuring compliance. Consult legal experts and cloud providers specializing in compliance to map regulatory requirements carefully into your architectural choices. 

Data partitioning allows sensitive data to be processed in its correct location while other components leverage broader distributed cloud resources. Design your applications with data partitioning in mind.

Reason 5: Innovation and the Edge

Distributed cloud architectures play a pivotal role in enabling the future of technology -- from IoT deployments to AI/ML applications at the edge. They provide the low-latency computing power and networking infrastructure necessary to handle the real-time demands of such innovations. This extends to secure, controlled collaboration platforms for third-party partners (such as in research or cross-company initiatives), where fine-grained permissions management protects innovation secrets while enabling effective teamwork.

Explore event-driven architectures and streaming data platforms to manage the velocity and volume of data generated at the edge. Integrating distributed cloud with edge devices using specialized hardware or software allows for sophisticated local computation and data pre-processing.

Reason 6: Optimized Content Delivery (CDN)

CDNs built upon a distributed cloud model rely on points of presence (PoPs) scattered across the globe, caching content closer to users. This results in faster download speeds and a seamless user experience. 

Carefully evaluating cache invalidation and content update strategies will ensure your users consistently access the freshest resources available.

Reason 7: Hybrid Cloud Flexibility

Frequently, distributed clouds seamlessly integrate with your existing on-premises infrastructure -- effectively extending your data center's reach. This setup allows for workload bursting to the cloud, data migration, or integrating cloud-based services, all while keeping core components on-premises.

To maximize flexibility, focus on developing a robust network overlay for secure connectivity and maintain cohesive security policies and identity management.

Use an IDP toRise Above The Clouds

Distributed cloud offers improved performance, resilience across geographies, and the keys to complex compliance requirements. However, managing this infrastructure can take time and effort. 

Control Plane is an Internal Developer Platform (IDP) that delivers *instant *cloud-native maturity without extensive time and financial investment. Control Plane simplifies the picture by providing a unified platform to orchestrate cloud services from multiple providers, optimizing them for latency and availability.  

With the Control Plane IDP platform, you can achieve a 60-80% reduction in cloud compute costs and enjoy the flexibility to select any combination of locations you require to attain 99.999% availability, ultra-low latency, and security and compliance requirements. Embrace the power of distributed cloud without the complexity -- try Control Plane today.