Glossary of terms
Auto Scaling is a cloud computing feature that automatically adjusts the number of computational resources in a server farm or pool based on the load or demand for those resources. It ensures that the right amount of computing power is available to handle varying workloads efficiently and cost-effectively.
1. Dynamic resource allocation: Automatically adds or removes resources based on predefined conditions or metrics.
2. Load balancing integration: Works in conjunction with load balancers to distribute traffic across available resources.
3. Scheduled scaling: Allows for planned scaling actions based on anticipated demand patterns.
4. Health checks: Monitors the health of instances and replaces unhealthy ones.
5. Custom metrics support: Enables scaling based on application-specific metrics in addition to standard system metrics.
6. Cooldown periods: Implements waiting periods between scaling actions to prevent rapid fluctuations.
7. Multiple scaling policies: Supports various scaling strategies, such as target tracking, step scaling, and simple scaling.
8. Instance protection: Allows specific instances to be protected from scale-in events.
9. Notifications: Sends alerts about scaling events through various channels.
10. Multi-AZ support: Can distribute resources across multiple availability zones for increased reliability.
1. Infrastructure management: Applies to various cloud resources, including virtual machines, containers, and serverless functions.
2. Application types: Suitable for web applications, mobile backends, batch processing jobs, and microservices architectures.
3. Cloud environments: Available in public, private, and hybrid cloud setups.
4. Scalability range: Can handle scaling from a few instances to thousands, depending on the cloud provider’s limits.
5. Cost optimization: Helps in reducing operational costs by matching resource allocation to actual demand.
6. Performance management: Ensures application performance by maintaining appropriate resource levels during traffic spikes.
7. Fault tolerance: Improves system reliability by automatically replacing failed instances.
8. Global reach: Can be applied across multiple geographic regions for globally distributed applications.
9. Integration capabilities: Often integrates with monitoring, logging, and alerting systems for comprehensive management.
10. Compliance and security: Adheres to various compliance standards and security best practices in resource provisioning and management.
Auto Scaling’s scope encompasses a wide range of scenarios, from small-scale applications to large, complex distributed systems, making it a fundamental feature in modern cloud computing environments.
Artificial intelligence (AI) has become an integral part of modern life, from the algorithms that curate our social media feeds to the systems that make
In today’s fast-paced digital world, cloud automation has rapidly evolved from a cutting-edge innovation to an essential component of modern business operations. As companies increasingly
Businesses need reliable and efficient management of information flows to operate. Data collection, storage, and management require a well-developed infrastructure with workstations, database servers, storage nodes and networks, engineering networks, and data transmission networks. Building such an infrastructure requires serious start-up investments and ongoing maintenance costs. Using cloud network technology eliminates most of these problems. So what is cloud technology?