{
  "id": 5084926,
  "title": "Preventing Cache Penetration in Spring Boot Using Redis and Bloom Filters",
  "url": "https://urgent.news/2026/09/02/preventing-cache-penetration-in-spring-boot-using-redis-and-bloom",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-09-02T12:35:43.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/shubham_bhati/preventing-cache-penetration-in-spring-boot-using-redis-and-bloom-filters-2ccj"
  },
  "original_language": "en",
  "account": "Cache penetration is a problem where frequent requests for non-existent keys bypass the Redis cache and directly hit the relational database. To prevent this, a Bloom Filter guard layer can be implemented in front of Redis and PostgreSQL. The Bloom Filter is a compact probabilistic data structure that can efficiently check if an element is definitely not in a set or might be in a set.\n\nIn the code, a `CachePenetrationGuard` class is defined with a `BloomFilter` instance. The filter is configured to handle 500,000 expected insertions with a 1% false positive rate. The `registerKey` method adds an account ID to the filter, while `mightContain` checks if an account ID is likely to be present.\n\nIn the `AccountService`, before querying Redis or PostgreSQL, the Bloom Filter is consulted. If the account ID is not likely to be in the filter, the request is immediately rejected, saving the database from unnecessary lookups. If the filter indicates the account ID might be present, Redis is checked. If the data is found in Redis, it is returned. If not, the data is fetched from the database, cached in Redis, and then returned.\n\nCombining Bloom Filters with Redis' TTL jitter can effectively shield backend databases from cache penetration and traffic spikes in production.",
  "summary": "Preventing Cache Penetration in Spring Boot Using Redis and Bloom Filters Cache penetration occurs when high-frequency requests query non-existent keys, bypassing the Redis cache completely and hitting the relational database directly. Here is how we set up a Bloom Filter guard layer in front of Redis and PostgreSQL. 1. The Bloom Filter Guard Concept A Bloom Filter is a space-efficient…",
  "key_points": [
    "Cache penetration occurs when non-existent keys bypass Redis and hit the database.",
    "Bloom Filter guard layer implemented in front of Redis and PostgreSQL."
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}