# Observability
All Observability notes →7 — Metrics Storage (TSDB)
Chunk/block encoding, the write-ahead log, compaction and the write amplification it trades for query speed, and why a cardinality spike is a storage-engine problem, not just a cost line item.
8 — Log Aggregation
Schema-on-write vs. schema-on-read as competing bets about when to pay indexing cost, and the two different deduplication problems a log pipeline actually has to solve.
7 — Distributed Tracing Backend
How spans that arrive out of order, from different services, get assembled into one trace — and the two competing storage models (indexed search vs. object storage plus a trace-ID lookup) that trade query flexibility for cost.
# Data Engineering
All Data Engineering notes →1 — Files and Storage Formats
The file formats data engineers choose between — CSV, JSON, Avro, Parquet, ORC — plus the compression, encoding, partitioning, and bucketing decisions that determine how efficiently they can be queried.
2 — Storage Engines
How storage engines are actually built — row vs. column stores, LSM trees vs. B+ trees, and the object storage, HDFS, and lake storage layers data platforms sit on.
3 — Data Lake, Warehouse & Lakehouse
Data lakes, warehouses, marts, and the lakehouse architectures (Delta Lake, Apache Iceberg, Apache Hudi) that merge them, organized through the medallion (bronze/silver/gold) pattern.
# Dbms
All Dbms notes →1 — Physical Storage
Covers how data is physically laid out on disk — pages, blocks, records, slotted pages, heap files, and clustered storage.
2 — Indexing
Covers why indexes exist and the major index types — clustered, non-clustered, composite, covering, partial, and bitmap.
3 — B-Trees
Covers B-tree and B+-tree structure, insert/delete operations, and why B+-trees are favored for range queries.
4 — Hash Indexes
Covers static and dynamic hashing schemes, including extendible and linear hashing, for equality-lookup indexes.
# Infrastructure Platform Engineering
All Infrastructure Platform Engineering notes →1 — Storage Services
Covers the platform's storage service catalog — object, block, and file storage offerings.
2 — Managed Databases
Covers managed database offerings on the platform — relational, NoSQL, in-memory, and data warehouse services.
3 — Backup & Recovery
Covers backup and recovery design for platform-provisioned storage — backup policy, replication, and recovery strategy.
4 — Data Governance
Covers data governance for platform storage — classification, encryption, retention, and lifecycle policy enforcement.
# Kubernetes
All Kubernetes notes →1 — Volumes
A Kubernetes volume is scoped to the pod, not the container, so it survives container crashes and restarts but is deleted the moment the pod itself is removed.
2 — Persistent Volumes
PersistentVolumes decouple storage provisioning from pod scheduling by making storage a cluster-scoped resource with its own lifecycle, independent of any pod or namespace.
3 — Persistent Volume Claims
A PVC lets an application manifest request storage abstractly, by size and access mode, so developers never need to know or care which physical backend actually satisfies it.
4 — Storage Classes
StorageClasses turn PV provisioning into a self-service API, letting a PVC request storage by named profile instead of an admin having to hand-create a matching PV first.
5 — CSI Drivers
The Container Storage Interface moved vendor-specific storage code out of Kubernetes core entirely, so new backends can ship as independently versioned plugins instead of waiting on a Kubernetes release.
6 — Stateful Storage Design
Pairing StatefulSet ordinal identity with per-replica PVCs is what lets a rescheduled database pod reattach to its own disk instead of a peer's, which is the whole trick behind running stateful workloads on Kubernetes.