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Fault Tolerance & High Availability
What is Fault Tolerance?
→ Ability of a system to continue functioning even when some components fail
→ Ensures minimal downtime and uninterrupted services
→ Achieved through redundancy, replication, and failover mechanisms
Fault Tolerance Techniques
→ Redundancy → Multiple instances of critical components
→ Replication → Copying data across multiple nodes or servers
→ Failover → Automatic switching to a standby system during failure
→ Error Detection → Identifying failures through monitoring and health checks
→ Graceful Degradation → Reducing functionality instead of full system crash
What is High Availability (HA)?
→ High Availability ensures systems are always accessible with minimal downtime
→ Measured in “nines” (e.g., 99.9% uptime ≈ 8.76 hours downtime/year)
→ Achieved by designing systems to eliminate single points of failure
High Availability Strategies
→ Load Balancing → Distribute traffic across multiple servers
→ Clustering → Group servers to act as a single system for reliability
→ Data Replication → Keep multiple data copies for recovery
→ Geographic Distribution → Deploy servers across regions to handle outages
→ Monitoring & Alerts → Detect failures early and respond quickly
Fault Tolerance vs High Availability
→ Fault Tolerance → Focuses on preventing failures from affecting the system
→ High Availability → Focuses on minimizing downtime during failures
→ Both are often combined for mission-critical applications
Real-World Examples
→ Banking → Redundant servers to ensure no downtime for transactions
→ Cloud Platforms → Replication across data centers for global uptime
→ E-commerce → Load balancers and failover systems during sales surges
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Belajar Python itu gampang kalau tau triknya!
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#python#pythonprogramming#PyCoding
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