Observability Storage Architecture Overview: From Gorilla to Parquet

Sun, 14 Jun 2026 00:00:00 +0000

Introduction

Observability has become a core infrastructure pillar of the cloud-native era. The five signals—Metrics, Logs, Traces, RUM, and Profiling—each generate massive volumes of data, and their storage efficiency directly determines platform cost boundaries and query performance. On the collection side, eBPF technology is reshaping how data is acquired. Behind all of this, storage architecture evolution is the foundation that enables observability to scale in production.

 mermaid
 

 flowchart TD
 A[Five Signals of<br/>Observability] --> B[Metrics]
 A --> C[Logs]
 A --> D[Traces]
 A --> E[RUM + Profiling]

 style A fill:#9C27B0,color:#fff
 style B fill:#2196F3,color:#fff
 style C fill:#2196F3,color:#fff
 style D fill:#2196F3,color:#fff
 style E fill:#2196F3,color:#fff
 

 mermaid
 

 flowchart TD
 G[Storage Evolution<br/>Convergent Paths] --> H[Proprietary Format<br/>→ Columnar Standard]
 G --> I[Index Bloat<br/>→ Weak Index + Object Store]

 style G fill:#FF9800,color:#fff
 style H fill:#4CAF50,color:#fff
 style I fill:#4CAF50,color:#fff
 

Figure: The five observability signals each produce data with different characteristics, yet their storage evolution converges on two core themes across all signals: the shift from proprietary storage formats to Parquet/Arrow columnar standards, and the move from full-field inverted indexes to weak-index strategies with object storage.

Gorilla on Mi&Bee Blog

Observability Storage Architecture Overview: From Gorilla to Parquet

Introduction