Fault Tolerant Microservices

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Fault Tolerant Microservices by Mind Map: Fault Tolerant Microservices

1. Architectures

1.1. Service Discovery

1.1.1. client-side

1.1.2. server-side

1.1.3. Decision Guidance Models for Microservices – Service Discovery and Fault Tolerance

1.1.4. Circuit Breakers, Discovery, and API Gateways in Microservices

1.2. Load Balancing

1.2.1. client-side

1.2.2. server-side

2. Terminology

2.1. Types of Faults

3. Técnicas

3.1. Prevention

3.1.1. Fault Injection

3.1.1.1. Chaos Engineering

3.1.1.1.1. A Platform for Automating Chaos Experiments (ChAP)

3.1.1.1.2. Gremlin

3.1.1.1.3. Failure as a Service (FaaS): A Cloud Service for LargeScale, Online Failure Drills

3.1.1.1.4. Lineage-driven fault injection

3.1.1.2. System

3.1.1.2.1. Fate and Destini

3.1.1.3. Application

3.1.2. Communication

3.1.2.1. Synchronous

3.1.2.1.1. Circuit Breakers

3.1.2.1.2. Bulkheads

3.1.2.1.3. Timeouts

3.1.2.1.4. Throttling

3.1.2.1.5. Circuit Breakers, Discovery, and API Gateways in Microservices

3.1.2.1.6. Decision Guidance Models for Microservices – Service Discovery and Fault Tolerance

3.1.2.1.7. Release it!

3.1.2.1.8. Cloud Design Patterns PRESCRIPTIVE ARCHITECTURE GUIDANCE FOR CLOUD APPLICATIONS

3.1.2.2. Asynchronous

3.1.3. Fault Density Analysis

3.1.4. Fault-tree Analysis

3.1.5. Cloud Provider

3.1.5.1. Reliability evaluation of cloud computing systems using hybrid methods

3.1.5.2. Failure Management for Reliable Cloud Computing: A Taxonomy, Model and Future Directions

3.1.5.3. Building Fault-Tolerant Applications on AWS

3.1.6. Formal Methods

3.1.6.1. TLA+

3.1.6.1.1. how amazon uses formal methods

3.2. Detection

3.2.1. Monitoring

3.2.1.1. An architecture for self-managing microservices

3.2.2. Chaos Engineering

3.3. Handling

3.3.1. Retry with exponential backoff

3.3.2. Fallback

3.3.3. Replication

3.3.3.1. Service Orchestration

3.3.3.1.1. An architecture for self-managing microservices

3.3.3.2. Load Balancing

3.3.3.2.1. An architecture for self-managing microservices

3.3.3.2.2. Decision Guidance Models for Microservices – Service Discovery and Fault Tolerance

3.3.3.3. Auto-scaling

3.3.3.3.1. AGILE: elastic distributed resource scaling for Infrastructure-as-a-Service

3.3.4. Restart

3.3.5. Saga

3.4. Diagnosis

3.4.1. Automatic diagnosis

3.4.1.1. Automatic Failure Diagnosis Support in Distributed Large-Scale Software Systems based on Timing Behavior Anomaly Correlation

3.5. The verification of a distributed system

4. Modeling

5. Microservices: yesterday, today, and tomorrow