Wednesday, June 18, 2025

Amazon S3 Intelligent Tiering Storage Class | Overview.

Amazon S3 Intelligent Tiering Storage Class - Overview.

Scope:

  • Intro,
  • How Amazon S3 Intelligent-Tiering storage class Works,
  • Storage Tiers in S3 Intelligent-Tiering,
  • Key Features,
  • Use Cases.

Intro:

  • The Amazon S3 Intelligent-Tiering storage class is designed to optimize storage costs automatically when data access patterns are unpredictable. 
  • Amazon S3 Intelligent-Tiering storage class moves data between different access tiers based on usage, without performance impact or operational overhead.

 How Amazon S3 Intelligent-Tiering storage class Works

S3 Intelligent-Tiering automatically moves data between tiers:

  • Frequent Access Tier,
  • Infrequent Access Tier,
  • Archive Instant Access Tier,
  • Archive Access Tier,
  • Deep Archive Access Tier,

NB:

  • AWS monitors access patterns and automatically transitions objects after 30 days of inactivity, without retrieval fees or latency penalties (except for Archive tiers).

 Storage Tiers in S3 Intelligent-Tiering

Tier

Access Frequency

Latency

Description

Frequent Access

Often accessed

Milliseconds

Default for newly uploaded or accessed data

Infrequent Access

Not accessed in 30days

Milliseconds

Lower cost for less active data

Archive Instant Access

Not accessed in 90days

Milliseconds

Cheaper than IA, good for rarely used data

Archive Access

Not accessed in 180days

Hours (3–5 hrs)

Similar to Glacier

Deep Archive Access

Not accessed in 180days+

Hours (12–48 hrs)

Similar to Glacier Deep Archive

NB:

  • Only Archive tiers are optional and must be enabled.

 Key Features

  • Automatic tiering – No human need to manage transitions manually.
  • Millisecond access – For non-archive tiers.
  • No retrieval fees – For Frequent, Infrequent, and Archive Instant.
  • Low latency retrieval – With optional archive tiers.
  • Minimal monitoring charge – $0.0025 per 1,000 objects/month.

twtech Use Cases

  • Data lakes with unpredictable access.
  • Analytics workloads with changing data patterns.
  • SaaS platforms storing user-generated content.
  • Long-term backup where some data is occasionally needed.

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