How to Analyse Server Room Temperature Data Logger Records Malaysia

A server-room data logger can collect hundreds or thousands of temperature and humidity readings, but the recorded values are only useful when they are interpreted correctly.

Simply checking the highest and lowest readings may miss repeated cooling cycles, short temperature spikes and differences between network-rack locations.

A structured approach to server room data logger analysis helps Malaysian maintenance teams determine when an environmental problem occurred, where it developed and what may have caused it.

What Should Be Checked First?

Before analysing the graph, confirm:

Logger model
Sensor type
Logger identification
Exact monitoring location
Start and stop time
Recording interval
Temperature unit
Whether humidity was recorded
Equipment operating condition
Cooling-system status
Any alarm limits used
Whether the logger clock was correct

A graph without reliable location and time information may be difficult to interpret.

1. Confirm the Logger Location

Record whether the logger was placed at:

General room area
Front of a network rack
Rear of a network rack
Top, middle or bottom of a rack
Hot aisle
Cold aisle
Cooling-unit intake
Cooling-unit outlet
UPS area
Battery room
Door or external-wall area

A rack exhaust logger should not be evaluated in the same way as a cold-aisle logger.

2. Review the Monitoring Period

Check whether the data covers:

Normal working hours
Overnight operation
Weekend conditions
Peak server load
Cooling-system cycling
Maintenance activity
Power interruption
Equipment installation
Alarm event

The monitoring period must include the condition being investigated.

3. Check Maximum Temperature

The maximum reading shows the highest recorded temperature, but ask:

How long did it remain high?
Did it occur once or repeatedly?
Was the logger moved?
Did the cooling system stop?
Was a door opened?
Did server load increase?
Was maintenance performed nearby?

A brief single spike may have a different cause and risk level from several hours of high temperature.

4. Check Minimum Temperature

An unusually low reading may indicate:

Logger placed directly in cooling air
Excessive local cooling
Cooling-system cycling
Logger moved from another environment
Sensor exposure to a cold surface
Incorrect placement

Very low readings should not automatically be treated as good cooling performance.

5. Calculate or Review the Average

Average temperature provides a general indication but can hide short abnormal periods.

For example, a room may have an acceptable daily average while experiencing repeated high-temperature peaks.

Always review the graph together with the average.

6. Identify Temperature Spikes

A spike is a rapid increase followed by a return toward normal conditions.

Possible causes include:

Cooling-unit interruption
Door opening
High equipment load
Temporary airflow blockage
Maintenance work
Power transfer
Logger handling
Sudden environmental change

Check whether the spike appears on one logger or several loggers at the same time.

7. Look for Gradual Temperature Rise

A slow increase may indicate:

Cooling performance gradually decreasing
Filter becoming restricted
Server load increasing
Hot-air recirculation
Room heat accumulation
Cooling unit unable to match the load
Progressive equipment problem

A gradual trend can be more important than one isolated high reading.

8. Identify Repeating Cooling Cycles

A regular rising and falling pattern may reflect normal cooling control.

However, investigate when:

Temperature swings become larger
Cycles become more frequent
Peak temperature increases
Cooling periods become longer
Different areas respond very differently

Compare with previous records when available.

9. Compare Day and Night Conditions

Server rooms may operate differently outside normal hours.

Check whether:

Cooling settings change
Fewer cooling units operate
Building air-conditioning is reduced
Room temperature rises overnight
Weekend conditions differ
Equipment load remains high while cooling decreases

A technician visiting only during office hours may never observe the problem directly.

10. Compare Weekday and Weekend Data

Weekend trends can reveal:

Reduced cooling operation
Different access patterns
Maintenance activities
Higher or lower IT load
Long-duration temperature rise
Environmental-control scheduling problems

Monitoring should include a weekend when recurring weekend alarms are reported.

11. Compare Multiple Logger Locations

Front Versus Rear of Rack

The rear normally records warmer exhaust air.

A growing temperature difference may indicate higher equipment load or reduced airflow.

Top Versus Bottom of Rack

A warmer top section may indicate:

Heat rising within the rack
Hot-air recirculation
Insufficient upper-level airflow
High-load equipment near the top

Hot Aisle Versus Cold Aisle

This comparison helps assess air separation and cooling distribution.

Problem Rack Versus Reference Rack

If only one rack shows abnormal temperature, investigate its equipment load, airflow and cable management.

UPS Area Versus General Room

Higher UPS-area temperature may indicate local heat generation or poor ventilation.

12. Analyse Relative Humidity

When using a temperature-and-humidity logger, check:

Maximum humidity
Minimum humidity
Average humidity
Rapid humidity changes
Relationship between temperature and humidity
Differences between locations
Changes when doors open
Changes during cooling cycles

Humidity readings must be interpreted together with temperature.

13. Compare Data With Cooling-System Events

Match the graph with:

Cooling-unit start and stop times
Filter replacement
HVAC servicing
Fan failure
Alarm events
Control-setting changes
Cooling-unit rotation
Power interruption

A shared time reference is essential.

14. Compare Data With IT Load

A temperature rise may coincide with:

New server installation
Increased processing load
Backup activity
Data migration
High network traffic
Additional rack equipment
Equipment testing

If possible, compare environmental records with system-load information.

15. Identify Sensor or Logger Errors

Possible signs include:

Impossible sudden jump
Flat line for a long period
Missing data
Repeated identical reading
Reading inconsistent with every other logger
Incorrect date or time
Temperature unit confusion
Logger stopping early
Humidity value outside expected behaviour

Inspect the logger, battery, settings and download process before concluding that the server room experienced an environmental failure.

Using Elitech RC-5 Records

The Elitech RC-5 Temperature Data Logger can support analysis of:

General room temperature
Rack inlet temperature
UPS-room temperature
Overnight cooling
Temperature alarms
Before-and-after maintenance conditions

Because it records temperature, humidity analysis requires a different or additional logger.

Using Elitech GSP-6 Pro Records

The Elitech GSP-6 Pro can be considered when analysis requires both:

Temperature trend
Relative-humidity trend

This is useful for more complete server-room environmental assessment.

Confirm the selected sensor configuration and current software functions before use.

Example: Temperature Rises Every Night

Possible investigation sequence:

Confirm the logger clock.
Identify the exact time of each rise.
Compare with cooling schedules.
Check whether building HVAC is reduced.
Compare multiple logger locations.
Review equipment load.
Measure airflow during the affected period.
Inspect cooling equipment.
Correct the cause.
Repeat overnight monitoring.

Example: Only the Top of One Rack Is Hot

Possible causes include:

Hot-air recirculation
Missing blanking panels
High-load equipment at the top
Blocked upper airflow
Failed equipment fan
Cable congestion
Poor aisle containment

Use:

Temperature readings at different heights
Thermal camera
Airflow meter
Equipment status records

The Noyafa NF-522 Thermal Camera can help locate the exact hotspot within the rack.

Example: Short Temperature Spikes During Maintenance

Check whether:

Rack doors were open
Cooling airflow was obstructed
Equipment was moved
A cooling unit was temporarily stopped
The logger was handled
The room door remained open

Documented maintenance events prevent normal work activity from being misinterpreted as equipment failure.

Example: Humidity Changes When the Door Opens

Compare:

Door-opening time
External-area humidity
Server-room humidity
Duration of the change
Recovery time
Frequency of access

The result may justify reviewing door seals, access practices or pressure relationships.

Data Logger Versus Thermal Camera During Analysis

A logger identifies when the temperature changed.

A thermal camera identifies where abnormal heat is located.

Example:

Logger shows temperature rising between 2:00 AM and 4:00 AM.
Maintenance team inspects during the affected period.
Thermal camera identifies a hot upper rack.
Airflow measurement confirms insufficient cooling.
Cable management and blanking panels are corrected.
Logger confirms improved overnight conditions.

What Should Be Included in the Analysis Report?

Include:

Monitoring objective
Logger model and identification
Sensor type
Logger location
Photograph of placement
Recording interval
Monitoring start and finish time
Maximum reading
Minimum reading
Average reading
Temperature graph
Humidity graph, where applicable
Time of abnormal events
Comparison between locations
Cooling and equipment events
Possible cause
Corrective action
Follow-up monitoring result

Common Data Analysis Mistakes

Avoid:

Reviewing only maximum and minimum values
Ignoring logger location
Comparing rack exhaust with cold-aisle readings
Using loggers with unsynchronised clocks
Ignoring equipment load
Treating every short spike as a major failure
Assuming repeated cycling is automatically normal
Ignoring missing or flat data
Failing to compare with cooling-system events
Making conclusions from only one logger
Not repeating monitoring after corrective work

A Practical Analysis Sequence

Confirm the logger and sensor.
Verify the exact placement.
Check the recording interval and time.
Review maximum, minimum and average readings.
Identify spikes and gradual trends.
Look for repeating cycles.
Compare day, night and weekend conditions.
Compare multiple locations.
Review humidity where available.
Match events with cooling and IT load.
Investigate possible logger errors.
Take corrective action.
Repeat monitoring.
Document the final result.

Turn Logger Records Into Maintenance Decisions

A data logger report should do more than show a temperature graph.

When location, timing, cooling operation and equipment load are analysed together, the records can reveal whether a server-room problem is caused by the whole cooling system, one network rack or a temporary operating event.

This allows maintenance teams to make corrective decisions based on measured evidence rather than assumptions.

Contact MTM Precision

MTM Precision Sdn. Bhd.

Showroom & Service Centre

No. 29-1 & 29-2, Jalan Bandar 18,
Pusat Bandar Puchong,
47160 Puchong, Selangor, Malaysia

🌐 Website: www.mtmpre.com.my
📧 Email: mtmpre@yahoo.com
📱 WhatsApp: +6016-660 7346