<aside> 💡 Generated by BigBrain. Repeated material was merged while distinct trade-offs, caveats, examples, and operational details were retained.
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Availability refers to the ability of a system to remain operational and accessible over time, even in the face of failures. Resilience extends this concept by emphasizing the system's ability to recover from disruptions and continue functioning. These principles are critical for modern distributed systems, where downtime can lead to significant financial and reputational losses.
Key metrics for availability include:
Load balancers distribute incoming requests across multiple servers to prevent any single server from becoming overwhelmed. They analyze factors like CPU utilization, memory usage, and response times to route traffic efficiently. This ensures smooth operations even during peak loads.
Data redundancy involves storing multiple copies of data across different locations, such as data centers or cloud regions. This ensures that if one location fails, data remains accessible from another. Isolation further reduces the impact radius of failures by separating redundant components across servers, racks, availability zones, or regions.
Failover refers to the automatic switching of operations from a primary system to a backup system when the primary fails. For example:
Auto-scaling dynamically adjusts computing resources based on demand. For instance, virtual machines or containers can be added during traffic spikes and removed during low usage. This ensures consistent performance while optimizing resource utilization.