Telemetry

Why Telemetry Matters

ASIC miners are designed for continuous operation.

When a miner fails or begins underperforming, delayed detection can mean lost hashing time.

Telemetry helps operators:

• detect problems quickly

• monitor miner health

• compare hardware performance

• identify abnormal miners

• track energy efficiency

• analyze failures

• automate alerts

• optimize fleet performance

• plan maintenance

Telemetry becomes especially important as mining operations grow.

ASIC Telemetry Data

Telemetry can contain several categories of information.

Performance Telemetry

Examples include:

• hash rate

• accepted shares

• rejected shares

• stale shares

• pool status

Thermal Telemetry

Examples include:

• ASIC temperature

• board temperature

• fan RPM

• cooling-system measurements

Electrical Telemetry

Where supported, this may include:

• miner power

• voltage-related readings

• current

• PSU status

Hardware Telemetry

Examples include:

• hashboard detection

• ASIC chip count

• HW errors

• fan status

• sensor status

System Telemetry

Examples include:

• uptime

• firmware version

• controller status

• network connectivity

Available telemetry varies significantly between ASIC models, firmware, sensors, and management platforms.

Telemetry and Hash Rate

Hash rate is one of the most important telemetry metrics.

Operators may monitor:

• instantaneous hash rate

• short-term average hash rate

• long-term average hash rate

• expected hash rate

• pool-side effective hash rate

A sudden decline can indicate:

• missing hashboard

• ASIC instability

• thermal throttling

• power reduction

• tuning problems

• mining software problems

Hash rate should usually be evaluated over an appropriate time interval because short-term measurements naturally fluctuate.

Telemetry and Power Consumption

Power telemetry allows operators to understand how much electrical power miners consume.

When combined with hash rate, it can be used to estimate energy efficiency.

For example:

Power = 3,500 W

Hash Rate = 140 TH/s

Then:

3,500 ÷ 140 = 25 J/TH

This allows operators to compare miners using useful hashing work rather than electricity consumption alone.

Telemetry and Temperature

Temperature telemetry helps operators identify thermal problems.

Depending on the miner, measurements may include:

• chip-level thermal readings

• board-level temperature

• intake-related measurements

• cooling-system temperatures

A pattern such as:

Temperature Rising → HW Errors Rising → Hash Rate Falling

can indicate a thermal problem that requires investigation.

Temperature values must be interpreted according to the specific miner and sensor location.

Telemetry and Fan Speed

Air-cooled ASIC miners commonly report fan speed in RPM.

Telemetry can reveal:

• failed fan

• unusually slow fan

• unusually high fan speed

• differences between fans

For example:

Fan RPM Drops → Airflow Decreases → Temperature Rises

A monitoring system can detect this pattern before the miner reaches a more serious thermal condition.

RPM alone does not directly measure airflow, but it is a useful operational indicator.

Telemetry and Hardware Errors

ASIC firmware may report HW errors.

Tracking the normalized error behavior over time can help identify:

• aggressive frequency settings

• insufficient voltage

• overheating

• unstable chips

• developing hardware faults

A raw cumulative error count should be interpreted carefully because it generally increases with operating time.

Error rate and its trend are usually more useful than the total count alone.

Telemetry and Hashboards

Telemetry can show whether each expected hashboard is operating.

For example:

Board 1 → Online

Board 2 → Online

Board 3 → Missing

This immediately narrows the diagnostic problem.

However:

Missing Hashboard ≠ Automatically Failed Hashboard

Possible causes include power, communication, firmware, connectors, control-board problems, or the hashboard itself.

Telemetry and ASIC Chips

Some firmware provides information about individual ASIC chips or groups of chips.

This can include:

• detected chip count

• chip status

• error behavior

• tuning information

• thermal information where available

Detailed chip telemetry can be particularly useful for autotuning and board-level diagnostics.

The available level of granularity depends on the miner and firmware.

Telemetry and Mining Pools

Mining telemetry can also include pool-related information.

Examples include:

• active pool

• connection status

• accepted shares

• rejected shares

• stale shares

• connection failures

This helps distinguish between:

Hardware Producing Work

and:

Pool Receiving Useful Work

A miner can report a high local hash rate while pool-side performance is poor because of networking, configuration, or share-submission problems.

Local vs Pool-Side Telemetry

Local and pool-side measurements should not be treated as identical.

Local Telemetry

Generated by the ASIC miner or its controller.

Examples:

• local hash rate

• temperatures

• fan RPM

• HW errors

Pool-Side Telemetry

Generated from work observed by the mining pool.

Examples:

• effective hash rate

• accepted shares

• rejected shares

• stale shares

Comparing both views can reveal problems that would be difficult to identify from either source alone.

Telemetry and ASIC Diagnostics

Telemetry is one of the main sources of information used for ASIC diagnostics.

Consider:

Hash Rate Falling + Temperature Rising + Fan RPM Falling

This combination suggests a different problem from:

Hash Rate Falling + Hashboard Missing + Normal Temperature

Individual metrics provide clues.

Multiple correlated metrics provide much stronger diagnostic information.

Telemetry and Predictive Maintenance

Historical telemetry can reveal gradual changes before complete failure occurs.

For example:

Week 1 → Normal

Week 2 → Slight Increase in Errors

Week 3 → Higher Temperature

Week 4 → Increasing Instability

This trend may indicate a developing problem.

Analyzing historical patterns can help mining operators move from:

Failure → Repair

toward:

Degradation Detected → Inspect → Prevent Failure

This approach is often called predictive or condition-based maintenance.

Telemetry and ASIC Tuning

ASIC tuning depends heavily on telemetry.

When frequency or voltage is changed, operators need to know what happened to:

• hash rate

• power

• temperature

• HW errors

• pool-side performance

A tuning cycle may look like:

Change Setting → Collect Telemetry → Evaluate → Adjust Again

Without reliable telemetry, tuning becomes much less precise.

Telemetry and Autotuning

Autotuning systems can use telemetry as feedback.

For example:

Set Frequency/Voltage → Measure Hash Rate → Measure Power → Check Errors → Adjust

The system repeatedly evaluates the results until it finds a suitable operating configuration.

Telemetry therefore forms the feedback loop that allows automated optimization.

Telemetry and Efficiency Optimization

Efficiency optimization requires at least two critical measurements:

Hash Rate + Power

From these values, the system can estimate J/TH.

Historical telemetry can then show whether efficiency changes because of:

• tuning

• temperature

• hardware aging

• firmware changes

• power profiles

This makes efficiency a measurable operational metric rather than a one-time specification.

Telemetry and Mining OS

A Mining OS can aggregate telemetry from many ASIC miners.

Instead of viewing individual miner interfaces, an operator may see a centralized dashboard containing:

• fleet hash rate

• total power

• average efficiency

• offline miners

• temperature alerts

• hardware errors

The architecture can be:

ASICs → Telemetry → Mining OS → Dashboard

This is particularly useful for large fleets.

Telemetry and APIs

ASIC firmware and management systems may expose telemetry through APIs.

An API allows external software to request or receive structured miner information.

For example:

Monitoring Platform → API → ASIC Controller → Telemetry Data

This allows mining operations to integrate ASIC data with:

• dashboards

• databases

• alerting systems

• automation

• maintenance platforms

API capabilities and data formats vary by manufacturer and firmware.

Telemetry and Alerts

Telemetry becomes more useful when abnormal values generate actionable alerts.

Examples might include:

Hash Rate Below Threshold → Alert

Hashboard Missing → Alert

Fan Failure → Alert

Temperature Above Configured Limit → Alert

The appropriate thresholds depend on miner model, configuration, and operating environment.

Poorly configured thresholds can create excessive false alarms.

Telemetry and Automation

Telemetry can also trigger automated actions.

For example:

Hash Rate = 0 → Restart Mining Process

or:

Temperature Rising → Reduce Power

or:

Miner Fails to Recover → Add to Maintenance Queue

This creates a feedback system:

Telemetry → Decision → Action → New Telemetry

The new measurements then show whether the action solved the problem.

Telemetry and Remote Reboot

Telemetry often determines whether a remote reboot is necessary.

For example:

Miner Online + 0 TH/s + No Shares → Remote Recovery Attempt

After rebooting, telemetry can verify:

• hashboards detected

• hash rate restored

• temperatures normal

• shares accepted

Without this verification, the operator would not know whether the reboot actually solved the problem.

Telemetry Sampling Interval

Telemetry does not necessarily need to be collected every instant.

A system may collect measurements at defined intervals.

Short intervals provide more detailed visibility but create:

• more network traffic

• more storage requirements

• more processing load

Long intervals reduce data volume but may delay problem detection.

The appropriate sampling interval depends on the metric and operational requirements.

Real-Time vs Historical Telemetry

Both types of telemetry are useful.

Real-Time Telemetry

Answers:

“What is happening now?”

Useful for:

• active incidents

• current temperatures

• offline miners

• immediate troubleshooting

Historical Telemetry

Answers:

“What has been happening over time?”

Useful for:

• trend analysis

• tuning comparison

• failure investigation

• maintenance planning

• efficiency analysis

A strong monitoring system typically uses both.

Telemetry Storage

Large mining farms can generate substantial amounts of telemetry data.

If thousands of miners report multiple metrics continuously, the monitoring platform may need to store millions of measurements.

Data can be organized by:

• timestamp

• miner

• site

• rack

• hashboard

• metric

Historical storage allows operators to compare current behavior with previous operating conditions.

Telemetry at Mining-Farm Scale

At industrial scale, telemetry provides visibility across the entire mining operation.

A simplified architecture might be:

ASIC Sensors → Controller Firmware → Network → Telemetry Platform → Analytics/Automation

Operators can then monitor:

• individual chips

• individual miners

• racks

• containers

• facilities

• entire mining fleets

This turns thousands of independent machines into a measurable and manageable infrastructure system.

Telemetry and Security

Telemetry systems can expose valuable operational information about a mining facility.

Depending on the platform, this may include:

• miner addresses

• hardware models

• pool configuration

• performance

• power usage

• facility structure

Telemetry systems should therefore use appropriate:

• authentication

• access controls

• network segmentation

• secure communication

• API permissions

Monitoring interfaces should generally not be directly exposed to untrusted networks.

Telemetry vs Monitoring

The terms are closely related but describe different functions.

Telemetry

The collection and transmission of operational data.

Monitoring

The process of observing and evaluating that data.

In simple terms:

Telemetry Provides the Data

Monitoring Uses the Data

Telemetry vs Diagnostics

Telemetry shows what the miner is reporting.

Diagnostics uses that information, together with other evidence, to determine why a problem exists.

For example:

Telemetry: Hashboard 2 is missing.

Diagnostics: Determine whether the cause is the hashboard, power, communication, firmware, or another component.

Telemetry is therefore an important input to diagnostics rather than a replacement for it.

Benefits of Telemetry

ASIC telemetry can provide:

• real-time visibility

• faster failure detection

• historical performance data

• better diagnostics

• automated alerts

• tuning feedback

• efficiency tracking

• predictive maintenance

• scalable fleet management

The larger the mining operation, the more valuable centralized telemetry becomes.

Limitations of Telemetry

Telemetry is only as useful as the data being measured.

Potential limitations include:

• inaccurate sensors

• missing metrics

• firmware reporting errors

• inconsistent measurement methods

• network interruptions

• delayed data

• excessive sampling intervals

A reported metric should not automatically be treated as perfect ground truth.

Critical problems may require confirmation through additional diagnostics or direct measurement.