Cache

The Cache resource provides visibility into every cache interaction tracked by Laritor. Each entry shows whether the application attempted to read or write a cache key—and if that attempt resulted in a hit or a miss. This helps you understand caching behavior, detect patterns of repeated cache misses, and optimize key usage.

Navigation: Access Cache via the sidebar under the “Cache” section.

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1. Cache Index Table

The Cache index displays a paginated list of cache events, ordered by Occurred At in descending order (most recent first). By default, 25 entries are shown per page, with a Load More button at the bottom to fetch additional records.

1.1 Columns

1. Cache Key

   • The identifier used for the cache operation (e.g., user_42_profile, settings_global).

2. Occurrence

   • The context in which the cache event occurred, such as:
     • Request (e.g., Request #1023)
     • Command (e.g., Command cache:clear)
     • Scheduled Task (e.g., Task backup:run)
     • Queued Job (e.g., Job SendEmailJob)
   • Clicking the occurrence link navigates to the corresponding details page (e.g., Request Details) so you can inspect the surrounding events.

3. Occurred At

   • Timestamp when Laritor recorded the cache interaction (e.g., 2025-05-30 14:45:12).

4. Hit / Miss

   • Indicates whether the cache operation resulted in a HIT (found in cache) or MISS (not found in cache).

Tip: Frequent cache misses for the same key can indicate that your application is not populating the cache correctly or keys are being invalidated too aggressively.

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2. Filters

Above the Cache table, you’ll find controls to refine the displayed entries:

1. Search (Cache Key)

   • A free-text search field matching against the cache key name. Partial matches and substrings are supported (e.g., searching “user_” will match user_42_profile, user_5_settings, etc.).

2. Date & Time Range

   • Select Start Date & Time and End Date & Time to show only cache events that occurred within that window.

3. Status Filter

   • Clickable badges for HIT and MISS. Clicking a badge filters to events with that outcome, so you can focus solely on misses or verify hit patterns.

Tip: Combine Search and Status filters to find all misses for a specific key (e.g., session_user) over the last 24 hours.

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3. Grouping

Next to or above the filter controls, you will see a Group By selector. Choose Key to aggregate cache events by cache key name. When grouped by key, the table transforms into an aggregated view displaying, for each key:

• Total Hits
  Number of times that key resulted in a cache hit.

• Total Misses
  Number of times that key resulted in a cache miss.

• Hit Rate
  The percentage of hits out of total attempts for that key, calculated as
  `(Total Hits / (Total Hits + Total Misses)) × 100%`.

Grouping by key helps you quickly identify:

• Keys with low hit rates that may need re-evaluation.
• Keys with very high usage (frequent hits) that are good candidates for long-lived caching.
• Keys with consistently poor hit rates, indicating potential logic errors or stale key naming.

Tip: Sort by Hit Rate in ascending order to locate the cache keys most likely causing performance issues (those with high miss ratios).

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4. Load More

• By default, the Cache table shows 25 entries (or aggregate rows, if grouped by key).
• Click Load More at the bottom to fetch the next batch of 25 results, ordered by Occurred At (or by aggregate metrics when grouped).
• This incremental loading ensures quick initial page loads while still providing access to your entire cache event history.

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5. Best Practices

• Spot High-Miss Keys

  • Filter by MISS status or group by key to find keys with frequent misses. Investigate why those keys aren’t being populated or whether the TTL is too short.

• Validate Key Usage

  • Use the Search filter to focus on specific key prefixes (e.g., user_ or product_) and confirm that expected hit rates align with your caching strategy.

• Monitor Hit Ratios Over Time

  • Combine Date & Time Range filters with the Group By view to see how hit rates for critical keys change before and after a deployment.

• Identify Cold Keys

  • Keys with high miss counts and few total accesses (low total occurrences) may be unused or misnamed. Consider removing or renaming them to reduce cache pollution.

• Focus on High-Volume Keys

  • When grouped by key, sort by Total Hits + Total Misses to see which cache keys are most heavily accessed. Optimize those first to maximize performance gains.

• Correlate with Parent Context

  • Click the Occurrence link to see the full timeline of the request, command, task, or job where the cache event occurred. This context helps you understand why a key was missed (e.g., during a database write) or repeatedly accessed.

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By leveraging the Cache index, filters, grouping, and per-occurrence drill-down, Laritor empowers you to track caching behavior, identify inefficiencies, and optimize your cache key strategy—resulting in faster data retrieval and improved application performance.