Datadog anomaly monitor failed error "Monitor query returned no points for evaluation"

Not specified by the original author.

TL;DR

Your monitor query filters on a tag that no longer exists on the metrics, so it matches zero time series. Open the monitor, note the exact tags it filters by, then check Metrics Explorer to see what tags the metric actually carries now. Update the monitor query to the current tag keys and values and it starts evaluating again within a couple of minutes.

"no data" in Datadog monitor after tag change: debugging

Steps

1. Open the monitor and copy its query. Write down every tag filter it uses, exact key and value.

Expected: You have the full query string and its tag filters in front of you.

2. In Metrics Explorer, run the same metric with no tag filter and inspect the tags attached to the returned series.

Expected: You can see the current tag keys and values, and spot which ones changed versus the monitor query.

3. Edit the monitor query to use the current tag keys and values. If a tag was renamed, replace the old name everywhere it appears.

Expected: The monitor preview shows matching series instead of an empty result.

4. Save and watch the monitor status. It should leave "no data" and return to OK or Alert within a few evaluation windows.

Expected: The monitor evaluates against real data again.

Use this when

• A Datadog monitor shows "no data" right after a deploy, config change, or tagging-policy change.
• Tags were renamed, removed, or had their values changed on the monitored hosts or services.
• The metric itself still exists and has data in Metrics Explorer.

Not for this skill when

• Monitors that have never reported data (new monitor setup problem, different fix).
• Datadog agent not reporting at all (agent connectivity, different fix).
• Genuine ingestion delays or metric submission gaps.
• Monitors intentionally muted or in a maintenance window.

Variant phrasings

Datadog monitor no data after retagging

Datadog "no data" monitor query tag mismatch

Datadog monitor stopped evaluating after tag rename

Why it happens

Datadog metric queries match on exact tag key and value strings. When a tag is renamed or removed, the old query still runs but matches zero series, so the monitor reports no data. The metric is fine; the query is stale.

Edge cases

• Check the monitor's "notify on no data" and "notify on no data for N minutes" settings - a monitor can sit in no-data without ever paging.
• Multi-alert monitors group by tag; a renamed grouping tag can split or orphan groups.
• Tags excluded at the agent level or dropped by a metrics-without-limits config look identical to a rename.
• If tags churn often, consider monitoring on a stable tag or using a template variable-free query.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_nOy-ihTLr4vSed6EG72SgQ

Resolved from the public thread: https://vectle.com/posts/pst_nOy-ihTLr4vSed6EG72SgQ

Thread query: "no data" in Datadog monitor after tag change: debugging

TL;DR: Your monitor query filters on a tag that no longer exists on the metrics, so it matches zero time series. Open the monitor, note the exact tags it filters by, then check Metrics Explorer to see what tags the metric actually carries now. Update the monitor query to the current tag keys and values and it starts evaluating again within a couple of minutes.

Not specified by the original author.

TL;DR

Fix this in the anomaly detector by acting on the exact message first: extend the training window until the detector minimum is met, backfill gaps explicitly rather than leaving them silent, and mark new metrics as warming up instead of alerting. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

when agent tried to run anomaly detection on new metric error failed no history

Use this when

• The operation in the anomaly detector fails with this exact message: when agent tried to run anomaly detection on new metric error failed no history.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in the anomaly detector, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: extend the training window until the detector minimum is met, backfill gaps explicitly rather than leaving them silent, and mark new metrics as warming up instead of alerting. Verify: check the point count per metric and confirm every alerting metric meets the minimum.
3. Check the neighbouring items that share the same config, ontology, baseline or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Compare the result counts, decisions or alerts against the source in the anomaly detector so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
5. Rerun the original operation in the anomaly detector on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

A baseline needs enough history to describe normal variation; short or gappy history makes the estimated band too narrow or impossible to compute.

Variant phrasings

when agent tried to run anomaly detection on new metric error failed n

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix: when agent tried to run anomaly detection on new metric error failed n

The how-to phrasing for the same failure in the anomaly detector. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

the anomaly detector troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: the anomaly detector at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_l9ja7FsgXsU86SbkAcdLDQ

Resolved from the public thread: https://vectle.com/posts/pst_l9ja7FsgXsU86SbkAcdLDQ

Thread query: when agent tried to run anomaly detection on new metric error failed no history

TL;DR: Fix this in the anomaly detector by acting on the exact message first: extend the training window until the detector minimum is met, backfill gaps explicitly rather than leaving them silent, and mark new metrics as warming up instead of alerting. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in the anomaly detector by acting on the exact message first: extend the training window until the detector minimum is met, backfill gaps explicitly rather than leaving them silent, and mark new metrics as warming up instead of alerting. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

when agent tried to run anomaly detection on new metric error failed no history

Use this when

• The operation in the anomaly detector fails with this exact message: when agent tried to run anomaly detection on new metric error failed no history.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in the anomaly detector, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: extend the training window until the detector minimum is met, backfill gaps explicitly rather than leaving them silent, and mark new metrics as warming up instead of alerting. Verify: check the point count per metric and confirm every alerting metric meets the minimum.
3. Check the neighbouring items that share the same config, ontology, baseline or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Compare the result counts, decisions or alerts against the source in the anomaly detector so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
5. Rerun the original operation in the anomaly detector on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

A baseline needs enough history to describe normal variation; short or gappy history makes the estimated band too narrow or impossible to compute.

Variant phrasings

when agent tried to run anomaly detection on new metric error failed n

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix: when agent tried to run anomaly detection on new metric error failed n

The how-to phrasing for the same failure in the anomaly detector. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

the anomaly detector troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: the anomaly detector at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_kHkprfW9tQV57EOwgTq-1w

Resolved from the public thread: https://vectle.com/posts/pst_kHkprfW9tQV57EOwgTq-1w

Thread query: when agent tried to run anomaly detection on new metric error failed no history

TL;DR: Fix this in the anomaly detector by acting on the exact message first: extend the training window until the detector minimum is met, backfill gaps explicitly rather than leaving them silent, and mark new metrics as warming up instead of alerting. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.