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Digital.ai Release vs Harness comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 5, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Digital.ai Release
Ranking in Build Automation
15th
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
5
Ranking in other categories
Release Automation (10th), DevSecOps (7th)
Harness
Ranking in Build Automation
7th
Average Rating
7.8
Reviews Sentiment
7.8
Number of Reviews
7
Ranking in other categories
Static Application Security Testing (SAST) (16th), Cloud Cost Management (9th), Feature Management (2nd)
 

Mindshare comparison

As of January 2026, in the Build Automation category, the mindshare of Digital.ai Release is 1.8%, up from 0.8% compared to the previous year. The mindshare of Harness is 5.8%, up from 5.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Build Automation Market Share Distribution
ProductMarket Share (%)
Harness5.8%
Digital.ai Release1.8%
Other92.4%
Build Automation
 

Featured Reviews

Jeanne-Mari Chandran - PeerSpot reviewer
Software Configuration Specialist at a insurance company with 10,001+ employees
Experience seamless project management and integration with robust tools
The features I find most valuable in Digital.ai Release are the integration with MS Teams, because we have MS Teams channels that publish or push notifications to that. When we start deployments, it sends a notification to the people that we are doing a deployment to their environment. It notifies them when the deployment is started, completed, or if attention is required. I also appreciate the fact that it has plugins for Bamboo and I use lots of Gradle and JSON scripts, and we do SQL upgrades as well, triggering Flyway scripts via Bamboo, along with the integration with XLD and Jira; it's all Atlassian software. Regarding environment management capabilities, Digital.ai Release is mostly useful for me, as it is more application related and that is managed via my XLD dictionary. We have one artifact that is environment agnostic, which has placeholders that correspond to my XLD keys and values, and at deployment time, it substitutes the placeholders with those environment specific values. We don't need to make a specific deployment artifact for dev, test, or production; it is all the same artifact using environment variables, ensuring what we take to production is what was tested.
reviewer2787357 - PeerSpot reviewer
Site Reliability Engineer at Granicus Inc.
Automated delivery has made production releases safer and has reduced deployment incidents
The first point for improvement is the steep learning curve, where concepts such as services, environment, pipelines, and templates take time to understand. New users often need training before becoming productive, resulting in slower initial onboarding compared to simpler CD tools. An improvement idea is better guided onboarding with more opinionated defaults and examples. The second improvement can be on UI complexity and navigation; the UI can feel cluttered with many options and finding past executions, logs, or specific settings sometimes takes extra clicks, leading to small but noticeable productivity loss. Simplified UI views for common workflows and improved search and filtering could help. I also see cost and licensing as potential areas for improvement, as pricing can feel high for small teams and advanced features are tied to higher tiers, which may limit adoption for startups or smaller organizations. Flexible pricing models and more essential features in lower tiers could address this issue.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The solution can apply one template across multiple applications."
"Overall, I would give Digital.ai Release a rating of nine out of ten; there's always room for improvement, but it's really good."
"The orchestration, building the release, and then just executing it and managing that pipeline — the orchestration capabilities are great for that."
"The most valuable feature of Digital.ai Release is its ability to communicate with various deployment systems, such as XLD and batch deployments, as well as integrate with tools, such as Flyway and Bamboo. We use Bamboo as our build orchestrator, and Digital.ai Release also integrates with Jira, another Atlassian solution. These capabilities make it a powerful tool for managing workflow, test automation, and other processes."
"The time is also reduced because the manual work has tremendously decreased. We just have to click one button, and it will create everything for us."
"Everything in Harness is configured and runs smoothly."
"It's a highly customizable DevOps tool."
"Harness integrates all functions like execution pipelines, environment checks, and log monitoring in one place."
"Harness integrates all functions like execution pipelines, environment checks, and log monitoring in one place, making it convenient."
"Harness starts integrating with organizations, making everything automated without the need for manual interruption."
"By adopting templates and various different pipelines across our own IDP platform, we have saved upwards of 30 to 40% of development time and also reduced risks of failures or error rates by upwards of 70%."
"The features of Harness are valuable, supporting rolling deployments, basic deployments, and blue-green deployments with zero downtime."
"Production deployments are faster and more reliable, especially for Kubernetes and cloud-based services, with significant reduction in deployment-related incidents, faster recovery when issues occur, faster, more confident releases, increased deployment frequency with higher confidence, and better governance and compliance that improved visibility and coordination across Dev, QA, Ops, and SRE teams."
 

Cons

"The backfill could be improved, we could automate that. Right now it's subjective — it's up to the lead developer's memory to remember to backfill."
"Currently, we put artifact details manually. What we could improve, in our case, is the deployment instruction base. Developers input all the information, including which artifact and where it needs to be deployed. What Digital.ai could do is automatically go to the deployment instruction page, take those artifact details, and implement them."
"Digital.ai Release could improve by having a better plugin that works with Guardian that we use for mainframe migrations. If there could be an interface or plugin for Guardian that would be beneficial."
"I would like to improve Digital.ai Release by exploring its cloud capabilities as we are currently in the middle of migrating to the cloud, but I actually have no idea what Digital.ai's cloud capabilities are."
"The solution is a little bit expensive."
"When integrating Harness with more than twenty applications in one place, it becomes less stable, causing improvements to be necessary."
"Even with automation, there's a requirement for manual change requests for approvals."
"The first point for improvement is the steep learning curve, where concepts such as services, environment, pipelines, and templates take time to understand."
"There's also room for improvement in debugging pipeline issues, which can sometimes become complex."
"I prefer the previous less compact UI version of Harness, which showed more details on the screen."
"When deploying multiple components to multiple environments, like production and BCP, failures sometimes occur. Improvements are needed when deploying one component to one environment."
"Harness setup and configurations could be made easier to configure, which would be helpful."
"Infrastructure as code or pipeline as code is something that Harness severely lacks."
 

Pricing and Cost Advice

"Overall, the price is just too high; especially considering we're in the middle of a pandemic."
"The solution's license includes all features."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
29%
Computer Software Company
11%
Insurance Company
11%
Healthcare Company
10%
Financial Services Firm
29%
Computer Software Company
9%
Manufacturing Company
7%
Retailer
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Large Enterprise7
 

Questions from the Community

What do you like most about Digital.ai Release ?
The time is also reduced because the manual work has tremendously decreased. We just have to click one button, and it will create everything for us.
What needs improvement with Digital.ai Release ?
Based on my experience, I would like to improve Digital.ai Release by exploring its cloud capabilities as we are currently in the middle of migrating to the cloud, but I actually have no idea what ...
What is your primary use case for Digital.ai Release ?
My use case for Digital.ai Release is that I work for an insurance company on a very big project that develops multiple different pieces of software. We use Digital.ai Release to move our software ...
What do you like most about Harness?
It's a highly customizable DevOps tool.
What needs improvement with Harness?
The first point for improvement is the steep learning curve, where concepts such as services, environment, pipelines, and templates take time to understand. New users often need training before bec...
What is your primary use case for Harness?
My main use case for Harness is continuous deployment (CD), specifically for safe, automated deployment to production, especially in Kubernetes and cloud environments. For continuous deployment in ...
 

Comparisons

 

Also Known As

XL Release, XebiaLabs XL Release
Armory
 

Overview

 

Sample Customers

3M, GE, John Deere, Deutsche Telekom, Cable & Wireless, Xerox, and Société Générale, Liberty Mutual, EA, Rabobank
Linedata, Openbank, Home Depot, Advanced
Find out what your peers are saying about Digital.ai Release vs. Harness and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.