A hyperscaler is a company that provides cloud services on a massive scale — offering IT infrastructure such as computing power, storage, and networking that is flexible, highly available, and globally scalable. Common examples of hyperscalers include:

• Amazon Web Services (AWS)

• Microsoft Azure

• Google Cloud Platform (GCP)

• Alibaba Cloud

• IBM Cloud (on a somewhat smaller scale)

Key characteristics of hyperscalers:

1. Massive scalability
   They can scale their services virtually without limits, depending on the customer's needs.

2. Global infrastructure
   Their data centers are distributed worldwide, enabling high availability, low latency, and redundancy.

3. Automation & standardization
   Many operations are automated (e.g., provisioning, monitoring, billing), making services more efficient and cost-effective.

4. Self-service & pay-as-you-go
   Customers usually access services via web portals or APIs and pay only for what they actually use.

5. Innovation platform
   Hyperscalers offer not only infrastructure (IaaS), but also platform services (PaaS), as well as tools for AI, big data, or IoT.

What are hyperscalers used for?

• Hosting websites or web applications

• Data storage (e.g., backups, archives)

• Big data analytics

• Machine learning / AI

• Streaming services

• Corporate IT infrastructure

Redundancy in software development refers to the intentional duplication of components, data, or functions within a system to enhance reliability, availability, and fault tolerance. Redundancy can be implemented in various ways and often serves to compensate for the failure of part of a system, ensuring the overall functionality remains intact.

Types of Redundancy in Software Development:

1. Code Redundancy:

   • Repeated Functionality: The same functionality is implemented in multiple parts of the code, which can make maintenance harder but might be used to mitigate specific risks.
   • Error Correction: Duplicated code or additional checks to detect and correct errors.

2. Data Redundancy:

   • Databases: The same data is stored in multiple tables or even across different databases to ensure availability and consistency.
   • Backups: Regular backups of data to allow recovery in case of data loss or corruption.

3. System Redundancy:

   • Server Clusters: Multiple servers providing the same services to increase fault tolerance. If one server fails, others take over.
   • Load Balancing: Distributing traffic across multiple servers to avoid overloading and increase reliability.
   • Failover Systems: A redundant system that automatically activates if the primary system fails.

4. Network Redundancy:

   • Multiple Network Paths: Using multiple network connections to ensure that if one path fails, traffic can be rerouted through another.

Advantages of Redundancy:

• Increased Reliability: The presence of multiple components performing the same function allows the system to remain operational even if one component fails.
• Improved Availability: Redundant systems ensure continuous operation, even during component failures.
• Fault Tolerance: Systems can detect and correct errors by using redundant information or processes.

Disadvantages of Redundancy:

• Increased Resource Consumption: Redundancy can lead to higher memory and processing overhead because more components need to be operated or maintained.
• Complexity: Redundancy can increase system complexity, making it harder to maintain and understand.
• Cost: Implementing and maintaining redundant systems is often more expensive.

Example of Redundancy:

In a cloud service, a company might operate multiple server clusters at different geographic locations. This redundancy ensures that the service remains available even if an entire cluster goes offline due to a power outage or network failure.

Redundancy is a key component in software development and architecture, particularly in mission-critical or highly available systems. It’s about finding the right balance between reliability and efficiency by implementing the appropriate redundancy measures to minimize the risk of failures.