Apr 9, 22:51 UTC
Completed - The scheduled maintenance has been completed.

Apr 9, 18:00 UTC
In progress - Scheduled maintenance is currently in progress. We will provide updates as necessary.

Apr 7, 18:23 UTC
Update - We will be undergoing scheduled maintenance during this time.

Apr 7, 18:18 UTC
Scheduled - Start: 2026-04-09 18:00 UTC
End: 2026-04-10 24:00 UTC

During the above window, our Engineering team will perform maintenance on core MongoDB services in the BLR1, NYC3, SFO2, SGP1, SYD1 & TOR1regions to enhance security and improve auditing and compliance. Please note that existing databases and workloads will continue to function normally and will not be impacted.

Expected Impact:

We do not anticipate any service disruptions during this window. Your existing databases and workloads will continue to run normally without interruption.

In the event that an unexpected issue occurs, administrative actions, such as creating, deleting, or scaling Managed MongoDB databases in the BLR1, NYC3, SFO2, SGP1, SYD1 & TOR1 regions, may experience delays.

If an unexpected issue arises, we will work to keep any impact to a minimum and may revert the changes if required.

If you have any questions related to this event, please open a ticket from your cloud support page: https://cloudsupport.digitalocean.com/s/createticket

Apr 7, 17:49 UTC
Resolved - Our Engineering team has resolved the control plane disruption that occurred from 17:06 to 17:18 UTC. During this time, users may have experienced intermittent issues with managing their resources through the Cloud Control Panel or DigitalOcean API. The root cause of the disruption was identified and addressed, and all services are now operating normally.

If you continue to experience any problems, please open a ticket with our Support team. We apologize for any inconvenience this may have caused.

Apr 7, 15:50 UTC
Resolved - Service has been fully restored, and the model is now operating normally. We have implemented improvements to enhance stability and reduce the likelihood of similar issues in the future.

Apr 7, 12:55 UTC
Identified - We are currently investigating reports of elevated latency affecting requests to this model when using Serverless Inference and Agents.

Earlier observations indicated increased error rates for the open-source Qwen 3 32B model. The Ray dashboard also showed multiple workers in a pending state, suggesting capacity constraints.

Our analysis determined that the model was experiencing higher-than-expected request volume without sufficient resources to scale accordingly. To address this, the node pool size has been increased to improve available capacity. However, there are still insufficient nodes to fully support the desired number of model replicas.

Following the node pool expansion, a new pod-related error has been identified. Our Engineering team is actively working to resolve this issue and restore full service performance.

Apr 7, 12:49 UTC
Investigating - Serverless inference for alibaba-qwen3-32b (Qwen 3 32B) in tor1 is experiencing high error rates starting at 10:46 UTC.