System Design AI

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42. Design a Metrics Monitoring Platform
Collect 5 million samples a second from 500,000 hosts, store them as time series, chart them and page people.
ClassicMedium
Databases Streaming Observability
+7
Distributed systems Alerting AWS Cardinality Kafka Prometheus Time series
Worked design
Practice
84. Design a Time-Series Database
The database under a metrics platform: a WAL and head block, compressed chunks, a label index, rollups, compaction and blocks in S3.
ClassicMedium
Databases Observability AWS
+4
Compression Prometheus Storage engine Time series
Worked design
Practice
97. Design a Distributed Logging and Error Tracking System
Ten terabytes of logs an hour from host agents through Kafka into tiered OpenSearch and S3, with regex search, live tail and exceptions grouped into issues.
ClassicMedium
Streaming Search Observability
+7
Distributed systems AWS Error tracking Flink Kafka Logging OpenSearch
Worked design
Practice
112. Design ML Model Monitoring and Drift Detection
Know within hours when hundreds of production models see broken inputs, drift or falling quality, before the labels arrive.
ClassicMedium
Observability AI infrastructure AWS
+3
Drift MLOps Monitoring
Worked design
Practice
117. Design a Self-Healing GPU Fleet
Detect, classify and repair failing GPU nodes (Xid errors, ECC, NVLink and EFA faults, stragglers, silent corruption) without draining the fleet.
ClassicMedium
Observability AI infrastructure AWS
+2
GPUs Reliability
Worked design
Practice

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