# What are the best configuration management platforms for DevOps engineers reducing manual effort in large IT environments?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">What actually reduces manual effort for a DevOps engineer managing configuration across a large IT environment, beyond the general promise of "automation" that every tool in the <a class="a a--md" elv="true" href="https://www.g2.com/categories/configuration-management">Configuration Management category</a> makes? What we're hoping to find:</p><ul>
<li>Declarative configuration that lets an engineer define desired state once, not per-server</li>
<li>Idempotent runs that don't require manual verification after every deployment</li>
<li>Rollback capability that actually works under pressure, not just in documentation</li>
<li>A learning curve that doesn't require the whole team to become experts in one vendor's syntax</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/red-hat-ansible-automation-platform/reviews"><strong>Red Hat Ansible Automation Platform</strong></a>: The most reviewed platform here, reviewers cite agentless architecture and a lower learning curve as the reason manual configuration work actually decreased.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/progress-chef/reviews"><strong>Progress Chef</strong></a>: Reviewers cite strong declarative configuration for complex, large-scale environments, though several note the syntax takes real time to learn.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/puppet-enterprise/reviews"><strong>Puppet Enterprise</strong></a>: Reviewers cite reliable idempotent runs at scale, a longer-established tool that some reviewers say feels heavier to set up than Ansible.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For engineers who migrated from manual scripts to one of these, how much of the original manual work actually disappeared, versus just shifting into maintaining the automation itself?</p>

##### Post Metadata
- Posted at: 12 days ago
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;&lt;span style=&quot;background-color: transparent; color: rgb(0, 0, 0);&quot;&gt;Configuration Management reviews on G2 describe the learning curve and the automation payoff as two separate bets, not one package deal. Ansible&#39;s agentless setup and lower learning curve showing up as the most-reviewed option here tracks with a real pattern: teams adopting something they can get running without a big upfront training investment tend to generate more reviews faster than tools with a steeper ramp. Chef&#39;s stronger declarative configuration for complex environments, paired with a real syntax learning curve, and Puppet&#39;s reliable idempotent runs paired with a heavier setup, both suggest the same tradeoff from different angles: more configuration power tends to come with more upfront investment before that power pays off.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span style=&quot;background-color: transparent; color: rgb(0, 0, 0);&quot;&gt;The rollback-under-pressure requirement in the post is the harder thing to verify from reviews generally, since most reviewers describe day-to-day configuration work rather than a specific incident where rollback actually got tested for real. The post&#39;s closing question about work disappearing versus shifting into maintaining the automation itself is probably the clearest way to frame any of these tools, since even a well-loved platform still needs someone tending the playbooks, recipes, or manifests as the environment changes.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;/p&gt;

##### Comment Metadata
- Posted at: 11 days ago
- Author title: Marketing





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