Index Intelligence
Beacon’s Index Intelligence module evaluates the effectiveness of database indexes and identifies opportunities for improvement. It detects missing indexes that would benefit common queries, unused indexes that consume resources without value, duplicate indexes that waste space, and inefficient indexes that fail to serve their intended purpose.
This module answers the question: “Are my indexes helping or hurting, and where should I add or remove them?”
Capabilities
Section titled “Capabilities”1. Missing Index Detection
Section titled “1. Missing Index Detection”Beacon identifies queries that would likely benefit from an index that does not currently exist.
| Signal | Description |
|---|---|
| Affected Query Patterns | Normalized queries that scan large tables without index support. |
| Candidate Columns | Columns appearing in filters, joins, or ordering that lack indexing. |
| Estimated Benefit | Projected improvement based on scan frequency and table size. |
| Impact Ranking | Prioritization of missing indexes by potential gain. |
| Supporting Queries | The specific queries that would benefit from the proposed index. |
Operational value: Points directly to the indexes most likely to improve performance, ranked by real workload impact rather than guesswork.
2. Unused Index Detection
Section titled “2. Unused Index Detection”Beacon identifies indexes that are not being used by query execution.
| Signal | Description |
|---|---|
| Zero-Usage Indexes | Indexes with no recorded scans over the observation period. |
| Usage Count | How often each index has been used. |
| Last Used Timestamp | When an index was last observed in use. |
| Storage Cost | Space consumed by the unused index. |
| Write Overhead | Estimated maintenance cost imposed by the index. |
Operational value: Unused indexes consume storage and slow down writes. Identifying them enables safe removal and reclaimed resources.
3. Duplicate Index Detection
Section titled “3. Duplicate Index Detection”Beacon detects indexes that are redundant with one another.
| Signal | Description |
|---|---|
| Identical Definitions | Indexes covering exactly the same columns and expressions. |
| Prefix Overlap | Indexes whose leading columns are fully covered by another index. |
| Redundancy Group | Clusters of indexes serving the same purpose. |
| Consolidation Suggestion | Which index to keep and which to remove. |
Operational value: Eliminates redundant storage and write overhead without losing query coverage.
4. Inefficient Index Detection
Section titled “4. Inefficient Index Detection”Beacon identifies indexes that exist but are not performing effectively.
| Signal | Description |
|---|---|
| Low Selectivity | Indexes on columns with too few distinct values to be useful. |
| Frequent Bypass | Indexes available but not chosen by the query planner. |
| High Maintenance Cost | Indexes whose write overhead outweighs their read benefit. |
| Bloat Indicators | Indexes consuming more space than their data warrants. |
| Fragmentation | Indexes whose structure has degraded over time. |
Operational value: Not all indexes help. Identifying ineffective ones allows teams to refine rather than accumulate index clutter.
5. Index Usage Analytics
Section titled “5. Index Usage Analytics”Beacon tracks how indexes are used across the workload over time.
| Signal | Description |
|---|---|
| Usage Frequency | How often each index is scanned. |
| Usage Trends | Whether usage is increasing, stable, or declining. |
| Query Attribution | Which queries rely on each index. |
| Scan Type | Index scan, index-only scan, or bitmap scan. |
| Rows Retrieved vs. Scanned | Efficiency of each index’s usage. |
Operational value: Provides an evidence base for index decisions, grounded in actual workload behavior.
6. Index Size & Storage Analysis
Section titled “6. Index Size & Storage Analysis”Beacon measures the storage footprint of indexes.
| Signal | Description |
|---|---|
| Index Size | Storage consumed by each index. |
| Size Relative to Table | How index size compares to the underlying table. |
| Total Index Footprint | Aggregate index storage per table or schema. |
| Growth Over Time | How index storage has changed historically. |
Operational value: Informs capacity planning and highlights tables where index overhead is disproportionate.
7. Index Recommendations
Section titled “7. Index Recommendations”Beacon consolidates findings into actionable recommendations.
| Recommendation Type | Trigger |
|---|---|
| Create Index | Missing index detected with high estimated benefit. |
| Drop Index | Unused or duplicate index with no observed value. |
| Consolidate Indexes | Multiple overlapping indexes that could be merged. |
| Reconsider Index | Inefficient index that may not justify its cost. |
| Rebuild Index | Bloat or fragmentation affecting index performance. |
Operational value: Provides a prioritized, evidence-backed action list for index optimization.
Analysis Views
Section titled “Analysis Views”Index Overview
Section titled “Index Overview”A summary of all indexes per instance with key health indicators.
Recommendation Queue
Section titled “Recommendation Queue”A prioritized list of index actions across all monitored databases.
Index Detail View
Section titled “Index Detail View”Focused analysis of a single index, including usage, size, and supporting queries.
Table Index View
Section titled “Table Index View”All indexes on a specific table, with overlap and redundancy highlighted.
Configuration Options
Section titled “Configuration Options”| Option | Purpose |
|---|---|
| Usage Observation Window | How long usage is tracked before an index is considered unused. |
| Recommendation Sensitivity | Threshold for surfacing recommendations. |
| Excluded Indexes | Suppress specific indexes from analysis. |
| Storage Thresholds | Size limits that trigger inefficiency flags. |
| Auto-Refresh Interval | How often index analytics are recalculated. |
Operational Scenarios
Section titled “Operational Scenarios”Scenario 1 — Reducing write overhead A high-write table has accumulated several indexes over time. Beacon identifies two as unused and one as duplicate, recommending removal. After removal, write throughput improves and storage is reclaimed.
Scenario 2 — Fixing a slow query A frequently executed query performs a large sequential scan. Beacon’s missing index detection proposes a candidate index, lists the supporting queries, and ranks it high by estimated benefit.
Scenario 3 — Auditing index bloat A routine review reveals an index consuming more storage than its table. Beacon flags it as bloated and recommends a rebuild, restoring efficiency.
Summary
Section titled “Summary”Beacon’s Index Intelligence module brings rigor to index management. By detecting missing, unused, duplicate, and inefficient indexes — and grounding every recommendation in observed workload behavior — it helps teams maintain lean, effective indexing that supports performance without unnecessary overhead.