There are specific details that can be improved in Deepwatch. After implementing it, we tracked both response time and threat detection accuracy using the SIEM dashboard. We measured response time using MTTD and MTTR. There are areas that can be improved, such as every alert having a timestamp for detection time and acknowledgment. We observed the MTTR dropping from a few hours to under one hour after using Deepwatch, so baseline metrics can be enhanced. Deepwatch can reduce alert fatigue since sometimes it generates a high volume of alerts that overwhelm our team. This can create too many alerts in a short amount of time, making it hard for our team to understand what to do. Additionally, the dashboard can be improved for better user-friendliness for end-users, requiring better visualization of MTTR, threat trends, and risk scoring. Improvements can also be made in more automated playbooks for automated response to common threats, and there is room for deeper integration capabilities, as integration with some internal tools may require additional effort.
IT Infrastructure & Cloud Manager at Softcell Technologies Limited
Real User
Top 5
Mar 26, 2026
Deepwatch could improve with more granular customization of detection rules and alert tuning to better fit specific cloud workloads and use cases. Additionally, it can be improved by enhancing the dashboarding. It should also support deeper cloud-native integrations such as AWS, Azure, and GCP, which would further improve operational efficiency and control. Regarding the support, I would say that the support team should be more responsive because ideally, the response time of the support is quite long, which is sometimes frustrating. However, I do agree that for easy issues, they respond within the expected time, but for complex issues, they do take time to respond.
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There are specific details that can be improved in Deepwatch. After implementing it, we tracked both response time and threat detection accuracy using the SIEM dashboard. We measured response time using MTTD and MTTR. There are areas that can be improved, such as every alert having a timestamp for detection time and acknowledgment. We observed the MTTR dropping from a few hours to under one hour after using Deepwatch, so baseline metrics can be enhanced. Deepwatch can reduce alert fatigue since sometimes it generates a high volume of alerts that overwhelm our team. This can create too many alerts in a short amount of time, making it hard for our team to understand what to do. Additionally, the dashboard can be improved for better user-friendliness for end-users, requiring better visualization of MTTR, threat trends, and risk scoring. Improvements can also be made in more automated playbooks for automated response to common threats, and there is room for deeper integration capabilities, as integration with some internal tools may require additional effort.
Deepwatch could improve with more granular customization of detection rules and alert tuning to better fit specific cloud workloads and use cases. Additionally, it can be improved by enhancing the dashboarding. It should also support deeper cloud-native integrations such as AWS, Azure, and GCP, which would further improve operational efficiency and control. Regarding the support, I would say that the support team should be more responsive because ideally, the response time of the support is quite long, which is sometimes frustrating. However, I do agree that for easy issues, they respond within the expected time, but for complex issues, they do take time to respond.