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Microsoft DP-800 Practice Test 60

Question 590

A database engineer at Pinecrest Operations is investigating this case: Mobile clients need to know which catalog keys changed. The relevant finding is: Full row-history logging is unnecessary. What operational condition would provide the earliest useful regression warning?

  1. Track trigger lag and duplicate processing
  2. Monitor retention expiry and version gaps
  3. Monitor missing correlation and sampling errors
  4. Monitor capture job lag and retention windows

Explanation

Correct Answer

B:

Full row-history logging is unnecessary. Monitor retention expiry and version gaps.

Incorrect Answers

A:

“Track trigger lag and duplicate processing” addresses the azure functions sql trigger binding situation—polling entire table every minute is wasteful. The observed failure is: Full row-history logging is unnecessary. Monitor retention expiry and version gaps.

C:

“Monitor missing correlation and sampling errors” concerns HTTP response latency is available but SQL dependency duration is missing; the reported problem instead is Full row-history logging is unnecessary. Monitor retention expiry and version gaps.

D:

“Monitor capture job lag and retention windows” concerns Nightly full refresh misses interim state; the reported problem instead is Full row-history logging is unnecessary. Monitor retention expiry and version gaps.

Question 591

Marigold Banking is responsible for an Azure SQL or Microsoft SQL workload. An Azure Function must react to updated SQL records. Operational evidence: Polling entire table every minute is wasteful. What initial check best narrows the technical cause without altering business data?

  1. Inspect Application Insights dependency instrumentation
  2. Inspect supported SQL trigger binding and underlying change tracking
  3. Inspect stored procedure contract and supported DAB action mapping
  4. Inspect entity fields and DAB role action permissions

Explanation

Correct Answer

B:

Polling entire table every minute is wasteful. Inspect supported SQL trigger binding and underlying change tracking.

Incorrect Answers

A:

“Inspect Application Insights dependency instrumentation” concerns HTTP response latency is available but SQL dependency duration is missing; the reported problem instead is Polling entire table every minute is wasteful. Inspect supported SQL trigger binding and underlying change tracking.

C:

“Inspect stored procedure contract and supported DAB action mapping” concerns Direct table insert bypasses business constraints; the reported problem instead is Polling entire table every minute is wasteful. Inspect supported SQL trigger binding and underlying change tracking.

D:

“Inspect entity fields and DAB role action permissions” concerns Role mapping permits clients to select every column; the reported problem instead is Polling entire table every minute is wasteful. Inspect supported SQL trigger binding and underlying change tracking.

Question 592

At Riverbend Retail, an Azure Function must react to updated SQL records. The observed constraint is: Polling entire table every minute is wasteful. Which proposed change is the most suitable response to the observed constraint?

  1. Configure supported Azure Functions SQL trigger binding with least privilege
  2. Configure supported JWT authentication and scoped API roles
  3. Configure supported one-to-many GraphQL relationship between entities
  4. Trace supported SQL dependencies and correlation identifiers

Explanation

Correct Answer

A:

Polling entire table every minute is wasteful. Configure supported Azure Functions SQL trigger binding with least privilege.

Incorrect Answers

B:

“Configure supported JWT authentication and scoped API roles” concerns Anonymous API access bypasses identity checks; the reported problem instead is Polling entire table every minute is wasteful. Configure supported Azure Functions SQL trigger binding with least privilege.

C:

“Configure supported one-to-many GraphQL relationship between entities” concerns GraphQL schema lacks relationship mapping despite SQL foreign key; the reported problem instead is Polling entire table every minute is wasteful. Configure supported Azure Functions SQL trigger binding with least privilege.

D:

“Trace supported SQL dependencies and correlation identifiers” addresses the application insights database dependency situation—hTTP response latency is available but SQL dependency duration is missing. The observed failure is: Polling entire table every minute is wasteful. Configure supported Azure Functions SQL trigger binding with least privilege.

Question 593

A database engineer at Prairie Logistics is investigating this case: An Azure Function must react to updated SQL records. The relevant finding is: Polling entire table every minute is wasteful. What isolated pilot would provide the strongest evidence before rollout?

  1. Update a synthetic tracked row and observe function invocation
  2. Insert/update/delete synthetic rows and read captured changes
  3. Request successive pages from a synthetic large dataset
  4. Update sample status and follow test approval workflow

Explanation

Correct Answer

A:

Polling entire table every minute is wasteful. Update a synthetic tracked row and observe function invocation.

Incorrect Answers

B:

“Insert/update/delete synthetic rows and read captured changes” concerns Nightly full refresh misses interim state; the reported problem instead is Polling entire table every minute is wasteful. Update a synthetic tracked row and observe function invocation.

C:

“Request successive pages from a synthetic large dataset” concerns Unbounded pages risk resource exhaustion; the reported problem instead is Polling entire table every minute is wasteful. Update a synthetic tracked row and observe function invocation.

D:

“Update sample status and follow test approval workflow” concerns One-off SQL triggers cannot safely call external systems; the reported problem instead is Polling entire table every minute is wasteful. Update a synthetic tracked row and observe function invocation.

Question 594

Silverpine Labs is responsible for an Azure SQL or Microsoft SQL workload. An Azure Function must react to updated SQL records. Operational evidence: Polling entire table every minute is wasteful. Which acceptance result most directly demonstrates the requirement has been satisfied?

  1. Trace spans connect HTTP call with SQL dependency duration
  2. Downstream receives committed changes in intended order
  3. Client receives changed keys and refreshes correct rows
  4. One intended event is processed with idempotency controls

Explanation

Correct Answer

D:

Polling entire table every minute is wasteful. One intended event is processed with idempotency controls.

Incorrect Answers

A:

“Trace spans connect HTTP call with SQL dependency duration” concerns HTTP response latency is available but SQL dependency duration is missing; the reported problem instead is Polling entire table every minute is wasteful. One intended event is processed with idempotency controls.

B:

“Downstream receives committed changes in intended order” concerns Nightly full refresh misses interim state; the reported problem instead is Polling entire table every minute is wasteful. One intended event is processed with idempotency controls.

C:

“Client receives changed keys and refreshes correct rows” concerns Full row-history logging is unnecessary; the reported problem instead is Polling entire table every minute is wasteful. One intended event is processed with idempotency controls.

Question 595

At Briarfield Foods, an Azure Function must react to updated SQL records. The observed constraint is: Polling entire table every minute is wasteful. What operational condition would provide the earliest useful regression warning?

  1. Track retention expiry and version gaps
  2. Monitor missing correlation and sampling errors
  3. Monitor trigger lag and duplicate processing
  4. Monitor capture job lag and retention windows

Explanation

Correct Answer

C:

Polling entire table every minute is wasteful. Monitor trigger lag and duplicate processing.

Incorrect Answers

A:

“Track retention expiry and version gaps” addresses the change tracking lightweight sync situation—full row-history logging is unnecessary. The observed failure is: Polling entire table every minute is wasteful. Monitor trigger lag and duplicate processing.

B:

“Monitor missing correlation and sampling errors” concerns HTTP response latency is available but SQL dependency duration is missing; the reported problem instead is Polling entire table every minute is wasteful. Monitor trigger lag and duplicate processing.

D:

“Monitor capture job lag and retention windows” concerns Nightly full refresh misses interim state; the reported problem instead is Polling entire table every minute is wasteful. Monitor trigger lag and duplicate processing.

Question 596

A database engineer at Northstar Analytics is investigating this case: A business process sends approvals after customer status changes. The relevant finding is: One-off SQL triggers cannot safely call external systems. What initial check best narrows the technical cause without altering business data?

  1. Review event delivery and Logic Apps connector capability
  2. Inspect DAB relationships and entity naming
  3. Inspect Application Insights dependency instrumentation
  4. Inspect Azure Monitor metrics and diagnostic settings

Explanation

Correct Answer

A:

One-off SQL triggers cannot safely call external systems. Review event delivery and Logic Apps connector capability.

Incorrect Answers

B:

“Inspect DAB relationships and entity naming” concerns GraphQL schema lacks relationship mapping despite SQL foreign key; the reported problem instead is One-off SQL triggers cannot safely call external systems. Review event delivery and Logic Apps connector capability.

C:

“Inspect Application Insights dependency instrumentation” concerns HTTP response latency is available but SQL dependency duration is missing; the reported problem instead is One-off SQL triggers cannot safely call external systems. Review event delivery and Logic Apps connector capability.

D:

“Inspect Azure Monitor metrics and diagnostic settings” concerns Application logs alone cannot distinguish database waits from network errors; the reported problem instead is One-off SQL triggers cannot safely call external systems. Review event delivery and Logic Apps connector capability.

Question 597

Maple Harbor Research is responsible for an Azure SQL or Microsoft SQL workload. A business process sends approvals after customer status changes. Operational evidence: One-off SQL triggers cannot safely call external systems. Which proposed change is the most suitable response to the observed constraint?

  1. Create Data API builder config with approved SQL source/entity mapping
  2. Route relevant SQL metrics/logs into approved Log Analytics workspace
  3. Use an approved SQL change feed connected to Logic Apps
  4. Use SQL Change Tracking with version tokens and consistent sync snapshots

Explanation

Correct Answer

C:

One-off SQL triggers cannot safely call external systems. Use an approved SQL change feed connected to Logic Apps.

Incorrect Answers

A:

“Create Data API builder config with approved SQL source/entity mapping” concerns No configuration maps entities to SQL objects or runtime connections; the reported problem instead is One-off SQL triggers cannot safely call external systems. Use an approved SQL change feed connected to Logic Apps.

B:

“Route relevant SQL metrics/logs into approved Log Analytics workspace” concerns Application logs alone cannot distinguish database waits from network errors; the reported problem instead is One-off SQL triggers cannot safely call external systems. Use an approved SQL change feed connected to Logic Apps.

D:

“Use SQL Change Tracking with version tokens and consistent sync snapshots” concerns Full row-history logging is unnecessary; the reported problem instead is One-off SQL triggers cannot safely call external systems. Use an approved SQL change feed connected to Logic Apps.

Question 598

At Juniper Commerce, a business process sends approvals after customer status changes. The observed constraint is: One-off SQL triggers cannot safely call external systems. What isolated pilot would provide the strongest evidence before rollout?

  1. Update sample status and follow test approval workflow
  2. Update a synthetic tracked row and observe function invocation
  3. Insert/update/delete synthetic rows and read captured changes
  4. Start DAB in a test container against sample SQL

Explanation

Correct Answer

A:

One-off SQL triggers cannot safely call external systems. Update sample status and follow test approval workflow.

Incorrect Answers

B:

“Update a synthetic tracked row and observe function invocation” concerns Polling entire table every minute is wasteful; the reported problem instead is One-off SQL triggers cannot safely call external systems. Update sample status and follow test approval workflow.

C:

“Insert/update/delete synthetic rows and read captured changes” concerns Nightly full refresh misses interim state; the reported problem instead is One-off SQL triggers cannot safely call external systems. Update sample status and follow test approval workflow.

D:

“Start DAB in a test container against sample SQL” concerns No configuration maps entities to SQL objects or runtime connections; the reported problem instead is One-off SQL triggers cannot safely call external systems. Update sample status and follow test approval workflow.

Question 599

A database engineer at Summit Logistics is investigating this case: A business process sends approvals after customer status changes. The relevant finding is: One-off SQL triggers cannot safely call external systems. Which acceptance result most directly demonstrates the requirement has been satisfied?

  1. Trace spans connect HTTP call with SQL dependency duration
  2. Workflow receives correct state without blocking OLTP transaction
  3. Client receives changed keys and refreshes correct rows
  4. Downstream receives committed changes in intended order

Explanation

Correct Answer

B:

One-off SQL triggers cannot safely call external systems. Workflow receives correct state without blocking OLTP transaction.

Incorrect Answers

A:

“Trace spans connect HTTP call with SQL dependency duration” concerns HTTP response latency is available but SQL dependency duration is missing; the reported problem instead is One-off SQL triggers cannot safely call external systems. Workflow receives correct state without blocking OLTP transaction.

C:

“Client receives changed keys and refreshes correct rows” concerns Full row-history logging is unnecessary; the reported problem instead is One-off SQL triggers cannot safely call external systems. Workflow receives correct state without blocking OLTP transaction.

D:

“Downstream receives committed changes in intended order” concerns Nightly full refresh misses interim state; the reported problem instead is One-off SQL triggers cannot safely call external systems. Workflow receives correct state without blocking OLTP transaction.

Question 600

BrightPath Studios is responsible for an Azure SQL or Microsoft SQL workload. A business process sends approvals after customer status changes. Operational evidence: One-off SQL triggers cannot safely call external systems. What operational condition would provide the earliest useful regression warning?

  1. Monitor retries, dead-letter states and authorization
  2. Monitor config validation and service startup errors
  3. Monitor GraphQL query cost and relationship failures
  4. Monitor missing correlation and sampling errors

Explanation

Correct Answer

A:

One-off SQL triggers cannot safely call external systems. Monitor retries, dead-letter states and authorization.

Incorrect Answers

B:

“Monitor config validation and service startup errors” concerns No configuration maps entities to SQL objects or runtime connections; the reported problem instead is One-off SQL triggers cannot safely call external systems. Monitor retries, dead-letter states and authorization.

C:

“Monitor GraphQL query cost and relationship failures” concerns GraphQL schema lacks relationship mapping despite SQL foreign key; the reported problem instead is One-off SQL triggers cannot safely call external systems. Monitor retries, dead-letter states and authorization.

D:

“Monitor missing correlation and sampling errors” concerns HTTP response latency is available but SQL dependency duration is missing; the reported problem instead is One-off SQL triggers cannot safely call external systems. Monitor retries, dead-letter states and authorization.

Developing AI-Enabled Database Solutions (DP-800) Practice Tests