Good Software with useful metrics insight
October 12, 2022

Good Software with useful metrics insight

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Allstacks

Our Organisation uses Allstacks to deploy software without much hassle as it allows creation of pipeline along with providing realtime metrics for easier detection of any issue in case it arises. It provides a clear look into the the problems which are causing inefficiencies. Allstacks provides insightful data based on a number of parameters which is not there in any other platform. To resolve any issue, we don't have to rely on gut feeling rather we can rely on metrics.
  • Creates a Software Development Pipeline with all the essential stages.
  • Provides insightful metrics to remove errors and ease the process of rebuild.
  • Provides transparency for easier debugging
  • Features like which user of the software will upgrade or churn before they do so can be added
  • Teams and individual dashboards can be made better
  • Allstacks has slightly improved the deployment time and thus resulting in reduced overall software development cost.
  • It has positively impacted the Return on Investment
  • It has significantly improved the debugging time thus leading to enhanced productivity and thus positive ROI
The detailed metrics which are shown when a software is deployed using pipeline is one of the greatest feature which overpowers GitLab.It has a very simple UI which allows easier creation of pipeline with all the required stages.

Do you think Allstacks delivers good value for the price?

Yes

Are you happy with Allstacks's feature set?

Yes

Did Allstacks live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Allstacks go as expected?

Yes

Would you buy Allstacks again?

Yes

One of the greatest feature of Allstacks is that it provides predictive analysis for the deployed software in case it will fail. It helps Software Developers a lot of time debugging the error and thus improves efficiency.
Another great feature is that it uses historical work data and uses Machine Learning and AI to build predictive model.