Operations 5 min read

How We Cut BIM Drawing Failures from 0.01% to 0.0005% with Automated Monitoring

The BIM construction‑drawing team built an automated monitoring and validation tool using Spring Boot, REST‑Assured and JIRA APIs, turning a tedious manual bug‑fix workflow into a streamlined process that reduced online drawing‑failure rates from 0.01% to virtually zero.

Qunhe Technology Quality Tech
Qunhe Technology Quality Tech
Qunhe Technology Quality Tech
How We Cut BIM Drawing Failures from 0.01% to 0.0005% with Automated Monitoring

Auto bug reporting? Auto validation? Is this everyone’s ideal?

We are the BIM construction‑drawing testing team. Online drawing failures are a major concern, especially when the drawing service fails to generate output. To lower failure rates and improve user satisfaction we needed a way to detect and fix failures automatically.

Previously this work was done manually, which was cumbersome. The manual steps were:

Query Tetris monitoring for anomalies and de‑duplicate the information.

Retrieve failed drawing plan details and construct the POST request body.

Validate drawing in the beta environment (some issues may already be fixed).

Re‑query Tetris monitoring to confirm whether the anomaly persists.

If the anomaly remains, submit a bug in JIRA.

After the bug is fixed, repeat the validation and monitoring steps.

Key pain points: many plans, redundant exception types, cumbersome verification and repair, repetitive mechanical workflow.

We split the whole process into discrete steps (see diagram) and automated the entire pipeline, freeing up labor and boosting efficiency.

The tool’s UI only requires entering a JIRA ID; then the front‑end sends a POST request to trigger drawing, followed by GET polling to check results.

The response contains three parts:

Overview: counts of pass, fail, error, and pass rate.

Exception information: de‑duplicated exception messages.

Detailed exception information: de‑duplicated details with timestamps, call stacks, etc.

Implementing the tool required:

Spring Boot framework with scheduled triggers.

Tetris API integration.

Regular‑expression matching for de‑duplication.

Rest‑Assured for sending HTTP requests.

JIRA API integration.

Business logic to orchestrate the workflow.

Results

Online drawing‑failure rate dropped from 0.01% to 0.0005%, while drawing volume quadrupled compared to the start of the year.

Feedback from the fault‑monitoring team decreased dramatically: in the first half of 2019 there were four drawing‑failure incidents; in the second half, the number fell to zero.

Future Work

We aim to achieve full‑process automation and are actively working toward that goal.

monitoringAutomationOperationsSpring BootBIMJira
Qunhe Technology Quality Tech
Written by

Qunhe Technology Quality Tech

Kujiale Technology Quality

0 followers
Reader feedback

How this landed with the community

login Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.