View source for Diagnosing Database Bottlenecks Using Sensor RRD Charts

= Diagnosing Database Bottlenecks Using Sensor RRD Charts =
[[Category:Administration]]
[[Category:Troubleshooting]]

If your VoIPmonitor GUI becomes unresponsive or PHP processes are being terminated by the OOM (Out of Memory) killer, the root cause may be a '''database performance bottleneck''', not a PHP configuration issue.

This guide explains how to use the sensor's RRD (Round-Robin Database) charts to identify whether the database server is the limiting factor.

== Symptoms of Database Bottlenecks affecting the GUI ==

* GUI becomes extremely slow or unresponsive during peak hours
* PHP processes are killed by the OOM killer on the GUI server
* Dashboard and CDR views take a long time to load
* Alerts and reports fail during high traffic periods
* System appears fine during off-peak hours but degrades during peak usage

{{Note|These symptoms often occur when the GUI server is waiting for database queries to complete, causing PHP processes to pile up and consume excessive memory.}}

== Understanding Sensor RRD Charts ==

The VoIPmonitor sensor generates performance charts (RRD files) that track system metrics over time. These charts are accessible through the GUI and provide visual indicators of where bottlenecks are occurring.

To access sensor RRD charts:
# Navigate to '''Settings > Sensors''' in the GUI
# Click the graph icon next to the sensor
# Select the time range covering the problematic peak hours

== Diagnostic Flowchart ==

<kroki lang="mermaid">
%%{init: {'flowchart': {'nodeSpacing': 15, 'rankSpacing': 40, 'curve': 'basis'}}}%%
flowchart TD
    A[GUI Unresponsive / OOM Errors] --> B{Check RRD Charts}
    B --> C{SQL Cache Growing?}
    C -->|No| D[Not DB bottleneck]
    C -->|Yes| E[DB Bottleneck Confirmed]
    E --> F{Identify Type}
    F --> G{mysqld CPU ~100%?}
    G -->|Yes| H[CPU Bottleneck]
    H --> I[Add CPU cores]
    G -->|No| J{Buffer pool full?}
    J -->|Yes| K[Memory Bottleneck]
    K --> L[Add RAM, tune buffer]
    J -->|No| M{High iowait?}
    M -->|Yes| N[Storage I/O Bottleneck]
    N --> O[Upgrade to SSD/NVMe]

    style A fill:#f9f,stroke:#333
    style E fill:#ff9,stroke:#333
    style H fill:#f96,stroke:#333
    style K fill:#f96,stroke:#333
    style N fill:#f96,stroke:#333
</kroki>

== Diagnostic Step 1: Look for Growing SQL Cache ==

The most critical indicator of a database bottleneck is '''growing SQL cache''' or '''SQL cache files''' during peak hours.

{| class="wikitable"
|-
! Metric !! What to Look For !! Indicates
|-
| '''SQL Cache''' || Consistently increasing during peak hours, never decreasing || Database cannot keep up with insert rate
|-
| '''SQL Cache Files''' || Growing over time during peak usage || Database buffer pool too small or storage too slow
|-
| '''CPU Load (mysqld)''' || Near 100% during peak hours || CPU bottleneck on database server
|-
| '''Disk I/O (mysql)''' || High or saturated during peak hours || Storage bottleneck (magnetic disks instead of SSDs)
|}

If you see SQL cache or SQL cache files growing consistently during peak traffic periods, the database server is the bottleneck.

== Diagnostic Step 2: Determine the Bottleneck Type ==

After identifying that the database is the issue, determine which resource is the limiting factor:

=== CPU Bottleneck ===
* Check database CPU usage during peak hours
* If mysqld is at or near 100% CPU, you need more CPU cores or faster CPUs

=== Memory Bottleneck ===
* Check if SQL cache grows because buffer pool is too small
* Database runs out of RAM for caching, forcing disk reads
* The SQL cache chart shows a pattern of filling up and staying full

=== Storage I/O Bottleneck (Most Common) ===
* High disk I/O wait times for mysqld process
* Disk latency (iowait) increases during peak hours
* Database storage on magnetic disks (e.g., 10K SAS) instead of SSD/NVMe
* SQL cache grows because data cannot be written/read fast enough

== Solutions for Database Performance Bottlenecks ==

=== Solution 1: Add More RAM to the Database Server ===

This is often the most effective fix for memory-related bottlenecks.

{| class="wikitable"
|-
! Current RAM !! Recommended Upgrade !! Expected Impact
|-
| 32GB || 64GB or 128GB || Significantly reduces cache growth
|-
| 64GB || 128GB or 256GB || Handles much higher peak loads
|-
| 128GB || 256GB || Suitable for large deployments
|}

After adding RAM, tune <code>innodb_buffer_pool_size</code> in your MySQL configuration:

<syntaxhighlight lang="ini">
# /etc/mysql/my.cnf
# Set to 50-70% of total RAM on dedicated database server
innodb_buffer_pool_size = 128G
</syntaxhighlight>

For more tuning guidance, see [[Scaling#Optimizing_Database_Performance_.28MySQL.2FMariaDB.29|Scaling - Database Performance]].

{{Warning|1=Do NOT reduce <code>innodb_buffer_pool_size</code> on the GUI server when the database is the bottleneck. This will make the problem worse.}}

=== Solution 2: Upgrade Database Storage to SSD/NVMe ===

If your database storage is on magnetic disks (e.g., 10K SATA or SAS), upgrading to SSDs is often the single most effective improvement.

{| class="wikitable"
|-
! Current Storage !! Recommended Upgrade !! Expected Speedup
|-
| 10K RPM SATA HDD || NVMe SSD array || 10-50x faster I/O
|-
| 10K RPM SAS HDD || Enterprise SSD (SAS/SATA) || 5-20x faster I/O
|-
| Older SSD || Modern NVMe (PCIe 4.0+) || 2-5x faster I/O
|}

For high-traffic deployments, '''NVMe storage is recommended for the database host'''.

See [[Hardware#Database_Storage|Hardware - Storage Selection]] for detailed recommendations.

=== Solution 3: Temporary Mitigation - Schedule Alerts/Reports Outside Peak Hours ===

If you cannot immediately upgrade the database server hardware, temporarily reduce the load by scheduling intensive tasks during off-peak hours.

'''1. Disable or reduce alert frequency''' during peak hours:
* Navigate to '''GUI > Alerts'''
* Temporarily disable high-frequency alerts
* Set alerts to run during off-peak periods (e.g., 2am-4am)

'''2. Schedule reports outside peak usage:'''
* Navigate to '''GUI > Reports'''
* Configure scheduled reports for off-peak hours
* Avoid generating reports during the busiest part of the day

'''3. Reduce dashboard complexity''' during peak hours:
* Simplify dashboards that query large ranges of data
* Avoid "All time" statistics during peak loads
* Use cached dashboards or static displays when possible

=== Solution 4: Consider Component Separation ===

If the database server is a bottleneck and upgrading is not feasible, consider moving to a dedicated database architecture.

In a component separation deployment (see [[Scaling#Scaling_Through_Component_Separation|Scaling - Component Separation]]):
* '''Host 1:''' Dedicated database server with maximum RAM and SSD/NVMe storage
* '''Host 2:''' GUI web server
* '''Host 3:''' Sensor(s)

This allows you to independently scale the database with more powerful hardware without affecting the GUI.

== Common Pitfalls to Avoid ==

{| class="wikitable" style="background:#fff3cd; border:1px solid #ffc107;"
|-
! colspan="2" style="background:#ffc107;" | Incorrect Solutions When Database is the Bottleneck
|-
| style="vertical-align: top;" | '''Reducing PHP memory_limit'''
| This does NOT fix the root cause. PHP waits for the database; less memory means processes crash sooner.
|-
| style="vertical-align: top;" | '''Tuning PHP-FPM worker counts'''
| More workers will pile up waiting for slow database queries, consuming even more memory.
|-
| style="vertical-align: top;" | '''Reducing innodb_buffer_pool_size'''
| This makes the database slower, not faster. It causes more disk I/O and longer query times.
|-
| style="vertical-align: top;" | '''Adding RAM to the GUI server'''
| If the bottleneck is the database, adding RAM to the GUI won't help. The database is the limiting factor.
|}

== Verification Checklist ==

After implementing a database upgrade to fix the bottleneck:

# Monitor SQL cache charts during the next peak traffic period
# Check that SQL cache does not grow uncontrollably
# Verify GUI responsiveness during peak hours
# Confirm no OOM killer events
# Check database query latency (slow queries should be minimal)

== Related Documentation ==

* [[Scaling]] - General performance tuning and scaling guide
* [[Scaling#Optimizing_Database_Performance_.28MySQL.2FMariaDB.29|Optimizing Database Performance]] - MySQL tuning parameters
* [[Hardware]] - Hardware sizing recommendations for different deployment sizes
* [[Scaling#Scaling_Through_Component_Separation|Component Separation]] - Dedicated database architecture

== AI Summary for RAG ==

'''Summary:''' Guide for diagnosing database bottlenecks affecting VoIPmonitor GUI using sensor RRD charts. Symptoms: GUI unresponsive during peak hours, OOM killer terminating PHP processes, slow dashboard/CDR views. KEY DIAGNOSTIC: Check sensor RRD charts (Settings > Sensors > graph icon) for growing SQL cache during peak hours - primary indicator of database bottleneck. Bottleneck types: CPU (mysqld at 100%), Memory (buffer pool too small), Storage I/O (most common - high iowait, magnetic disks). Solutions: (1) Add RAM to database server and tune innodb_buffer_pool_size to 50-70% of RAM; (2) Upgrade storage from HDD to SSD/NVMe (10-50x speedup); (3) Schedule alerts/reports outside peak hours; (4) Component separation with dedicated database server. INCORRECT solutions: Do NOT reduce PHP memory_limit, do NOT tune PHP-FPM workers, do NOT reduce innodb_buffer_pool_size, do NOT add RAM to GUI server instead of database.

'''Keywords:''' database bottleneck, RRD charts, sensor performance, SQL cache, SQL cache files, peak hours, OOM killer, GUI unresponsive, dashboard slow, RAM upgrade, SSD upgrade, NVMe, iowait, innodb_buffer_pool_size, component separation, dedicated database

'''Key Questions:'''
* How do I diagnose database bottlenecks in VoIPmonitor?
* What do growing SQL cache files in RRD charts indicate?
* Why is my VoIPmonitor GUI slow during peak hours?
* How to fix OOM killer terminating PHP processes?
* Should I upgrade RAM on GUI server or database server?
* What storage is recommended for VoIPmonitor database?
* How to access sensor RRD charts in VoIPmonitor GUI?
* What are incorrect solutions for database bottlenecks?
* How much RAM should innodb_buffer_pool_size be set to?
* When should I consider component separation for VoIPmonitor?