Excessive disk writes / SSD wear concern on macOS Codex app and JetBrains ACP

Resolved 💬 4 comments Opened Jun 24, 2026 by Ko7ov-Konstantin Closed Jul 10, 2026

Excessive disk writes / SSD wear concern on macOS Codex app and JetBrains ACP

Environment

  • macOS 26.5.1, arm64
  • MacBook Air M4, Apple SSD AP0256Z
  • Codex CLI: 0.142.0
  • Bundled Codex app CLI: 0.142.0
  • Surfaces used: Codex macOS app + JetBrains/PhpStorm Codex ACP
  • Feedback/session ID: 019ef542-c75a-7a13-aacd-cebe3296df6e

Problem

Codex appears to cause very high SSD write volume on macOS, raising SSD wear concerns.

Observed data

  • IORegistry Bytes (Write) since boot previously measured at 4,772,341,477,376 bytes.
  • Current later measurement: 4,774,095,269,888 bytes.
  • Boot date: June 6, 2026.
  • Measured write deltas while Codex was active:
  • ~1.05 GB written over 2 minutes.
  • Later ~0.65 GB written over 2 minutes.
  • In a mostly idle state, still ~0.413 GB written over 2 minutes, about 207 MB/min.
  • /private/var/folders/.../X/com.openai.codex.code_sign_clone grew rapidly after cleanup and is currently about 12 GB.
  • ~/.codex/logs_2.sqlite is currently about 166 MB, WAL about 31 MB.
  • Earlier during investigation, Codex-related code_sign_clone and log files were much larger before cleanup.
  • Process list shows Codex macOS app processes and JetBrains/PhpStorm Codex ACP processes active, including codex-acp and codex app-server.

Why this matters

This is not only disk space usage. The main concern is sustained physical SSD writes and SSD wear on a MacBook with soldered storage.

Expected behavior

Codex should avoid sustained high disk write amplification during normal app or IDE usage, or provide a setting/diagnostic explaining what is being written and how to reduce it.

Request

Please investigate high write amplification from Codex app-server / macOS app / JetBrains ACP, especially around com.openai.codex.code_sign_clone and logs_2.sqlite.

View original on GitHub ↗

This issue has 4 comments on GitHub. Read the full discussion on GitHub ↗