Cost optimization: 2 real scaling case studies
2 of the 73 engineering write-ups in our database are tagged with the technique "cost optimization". They come from 2 companies (Atlassian and Netflix) and were published between 2025 and 2026. 2 of the 2 state concrete scale numbers, for example "15+ PB compressed data in cold storage" (Netflix). Each card below links to our short summary and the original post.
TimeSeries Tiered Storage Journey: Kafka/Flink Streams to Native Cassandra Cold Reads
Netflix moved older data in its multi-petabyte TimeSeries Abstraction out of hot Cassandra storage in two steps. First, Kafka and Flink streamed events to S3 as Parquet files, which a daily job compacted into small, time-sorted row groups with Bloom filters cached in EVCache (p50 ~150 ms, p99 ~500 ms). The second design skips that streaming pipeline: a ReadOnlyCompactionStrategy aligns immutable SSTables to token ranges, and a custom pluggable Memtable (Cassandra 4.1) reads directly from existing Cassandra backups in S3. It now holds over 15 PB of compressed cold data, cut disk usage on affected clusters from 80% to 7%, and improved p90 latency by ~30%.
Migrating the Jira Database Platform to AWS Aurora
Atlassian migrated about four million Jira databases from RDS Postgres to Aurora, balancing reliability, downtime and cost.