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Use case / AI diagnostics

AI Log Diagnostics With MCP and Fluxtail

AI log diagnostics are most useful when they work from scoped log streams, receiver context, and raw rows. Fluxtail combines MCP diagnostics and AI chat with streams, live tail, filters, facets, histograms, and alerts so summaries stay tied to real logs.

AI log diagnostics MCP diagnostics Error summaries Receiver health
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Ask against real streams

Scope questions by stream, receiver, service, host, namespace, or time range.

Summarize repeated errors

Group noisy exceptions and repeated messages after filtering the relevant window.

Check missing logs

Use no-log and receiver health diagnostics when the issue is silence, not noise.

Keep raw rows visible

Treat summaries as a guide, then confirm against the underlying log records.

Source

When this source should be centralized

Use this path when the source already emits logs and central reading, filtering, or alerting is the next need.

01

A stream has many similar errors

Use AI log diagnostics after filters narrow the stream enough for repeated failures to be grouped without hiding the raw rows.

02

A receiver stopped getting logs

No-log diagnostics and receiver health checks help when the source is quiet and the ingest path may be the issue.

03

An alert needs a short explanation

A scoped summary can explain a filtered time window while the original rows stay available for verification.

Prompts

Example diagnostic prompt and result shape

Good AI log diagnostics start with a scoped stream, receiver, service, or time range, then point back to the raw rows.

Scoped diagnostic prompts
text
1find exceptions in checkout-live from the last 30 minutes
2summarize_errors for service checkout-api since 14:00
3why are no logs arriving for receiver edge-syslog?
4check receiver health for the OTLP production receiver
Raw rows behind a summary
output
2026-04-25T14:21:09Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4921
2026-04-25T14:21:15Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4922
2026-04-25T14:21:22Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4923
Useful summary shape
text
1Repeated PaymentGatewayTimeout errors appeared in checkout-api between 14:21:09 and 14:21:22.
2The affected rows share service=checkout-api, level=ERROR, and error class PaymentGatewayTimeout.
3Check the payment gateway dependency and retry budget for that window.
Questions

Good Questions to Ask

Start with a stream, receiver, service, host, namespace, or time window. Narrow questions produce answers that can be checked.

01

Error and exception questions

Ask what exception classes repeated, which service emitted most ERROR rows, or which error codes dominated the window.

Examples
text
1What exception classes repeated in checkout-live during the last 30 minutes?
2Summarize errors for service checkout-api after the deploy.
3Which host produced the most ERROR rows in this window?
02

Missing-log questions

Ask why a receiver or stream is quiet only after naming the source and expected window.

Examples
text
1Why are no logs arriving for receiver edge-syslog?
2Check receiver health for the OTLP production receiver.
Scope

Bad Questions to Avoid

Broad prompts make weak diagnostic output because the system has too much context and no clear evidence window.

01

Too broad

Avoid prompts like “What is wrong with production?” or “Summarize everything.” Start with a stream, service, receiver, or time range.

02

No evidence window

Avoid asking for a cause without a stream or time window. First isolate the rows, then ask for a summary.

Diagnostics

Diagnostics Fluxtail Can Support

Use MCP diagnostics for find_exceptions, summarize_errors, why_no_logs, check_receiver_health, and ingestion guidance. Use AI chat for summaries and explanations after the relevant log slice is available.

01

Known diagnostic tasks

find_exceptions and summarize_errors help with noisy failures. why_no_logs and check_receiver_health help when a source goes quiet.

02

Raw rows remain the anchor

Every useful answer should be checked against the stream, time window, filters, and log rows used to produce it.

Setup

How logs move into Fluxtail

Keep the sender configuration explicit, then confirm the resulting stream keeps the fields needed for reading and filtering.

01

Start from a stream, receiver, or filtered result

Pick the stream, service, receiver, host, namespace, or time window before asking for a summary.

02

Run a focused diagnostic

Use MCP tools or built-in AI chat for find_exceptions, summarize_errors, why_no_logs, check_receiver_health, or ingestion guidance.

03

Open the raw evidence

Review the underlying log rows before deciding the summary is correct.

04

Turn repeated findings into alerts

Once a repeated pattern is understood, promote it into a saved filter or alert path.

Prompts

Example diagnostic prompt and result shape

Good AI log diagnostics start with a scoped stream, receiver, service, or time range, then point back to the raw rows.

Scoped diagnostic prompts
text
1find exceptions in checkout-live from the last 30 minutes
2summarize_errors for service checkout-api since 14:00
3why are no logs arriving for receiver edge-syslog?
4check receiver health for the OTLP production receiver
Raw rows behind a summary
output
2026-04-25T14:21:09Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4921
2026-04-25T14:21:15Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4922
2026-04-25T14:21:22Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4923
Useful summary shape
text
1Repeated PaymentGatewayTimeout errors appeared in checkout-api between 14:21:09 and 14:21:22.
2The affected rows share service=checkout-api, level=ERROR, and error class PaymentGatewayTimeout.
3Check the payment gateway dependency and retry budget for that window.
Verification

What to check before relying on it

Collection is useful only when the resulting rows still carry enough context to search, filter, and alert on.

01

The prompt is scoped

Confirm the prompt includes a stream, receiver, service, host, namespace, time window, or filtered result.

02

The answer can be checked

Confirm the answer points back to raw rows, repeated messages, fields, or receiver status used to produce it.

03

The pattern matches filters and histograms

Use filters, facets, and histograms to confirm the same pattern before turning a finding into an alert.

Prompts

Example diagnostic prompt and result shape

Good AI log diagnostics start with a scoped stream, receiver, service, or time range, then point back to the raw rows.

Scoped diagnostic prompts
text
1find exceptions in checkout-live from the last 30 minutes
2summarize_errors for service checkout-api since 14:00
3why are no logs arriving for receiver edge-syslog?
4check receiver health for the OTLP production receiver
Raw rows behind a summary
output
2026-04-25T14:21:09Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4921
2026-04-25T14:21:15Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4922
2026-04-25T14:21:22Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4923
Useful summary shape
text
1Repeated PaymentGatewayTimeout errors appeared in checkout-api between 14:21:09 and 14:21:22.
2The affected rows share service=checkout-api, level=ERROR, and error class PaymentGatewayTimeout.
3Check the payment gateway dependency and retry budget for that window.
Prompts

Example diagnostic prompt and result shape

Good AI log diagnostics start with a scoped stream, receiver, service, or time range, then point back to the raw rows.

Scoped diagnostic prompts
text
1find exceptions in checkout-live from the last 30 minutes
2summarize_errors for service checkout-api since 14:00
3why are no logs arriving for receiver edge-syslog?
4check receiver health for the OTLP production receiver
Raw rows behind a summary
output
2026-04-25T14:21:09Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4921
2026-04-25T14:21:15Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4922
2026-04-25T14:21:22Z ERROR checkout-api PaymentGatewayTimeout order_id=ord_4923
Useful summary shape
text
1Repeated PaymentGatewayTimeout errors appeared in checkout-api between 14:21:09 and 14:21:22.
2The affected rows share service=checkout-api, level=ERROR, and error class PaymentGatewayTimeout.
3Check the payment gateway dependency and retry budget for that window.
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Next step

Send one real source and read the logs

The fastest check is to point one real source at Fluxtail and see whether the resulting stream is easier to read.

Point one real source at Fluxtail.

Create a receiver, send one source, and inspect the first stream.

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