Pulumi Review: Real Production Experience After 2 Years

After two years of running Pulumi in production with a team that was initially skeptical as hell, I can tell you what actually happens when you bet your infrastructure on this thing. This isn't another tutorial or feature comparison - it's a real-world evaluation of what works, what doesn't, and what you'll actually experience when you bet your infrastructure on Pulumi.

The core engine consists of the language host (runs your code), deployment engine (calculates changes), and resource providers (manage actual cloud resources). This separation is what makes Pulumi powerful - you get real programming languages with declarative infrastructure management.

OK Fine, Some Things Actually Work

Developer Experience is Legitimately Superior: The IDE integration isn't marketing fluff. Having real autocomplete, type checking, and refactoring tools for infrastructure code changes everything. When a developer can Ctrl+Click to jump to a resource definition or get IntelliSense for AWS resource properties, it eliminates the constant context switching between documentation and code.

Testing Infrastructure Code Actually Works: Unlike YAML-based tools where "testing" means hoping your syntax is correct, Pulumi enables real unit tests. This changes everything - you can catch configuration errors, dependency issues, and resource conflicts before they hit production. The ability to mock cloud services and validate infrastructure logic has prevented several outages.

Complex Logic Becomes Manageable: When you need to create 20 similar resources with slight variations, or implement conditional resource creation based on environment variables, real programming languages shine. A simple for loop in TypeScript beats wrestling with Terraform's count and for_each.

What Nobody Warns You About (The Shit Parts)

Pricing Will Hurt Your Budget: The pricing model starts innocent enough at $40/month for teams, but then it scales based on resources managed. We're paying around $580/month for our setup. Terraform Cloud would cost us maybe $120-140/month for the same thing. Yeah, it's expensive.

Ecosystem Gaps Are Real: While Pulumi supports 290+ providers, newer cloud services often appear in Terraform first. We've had to wait 3-6 months for critical AWS features to become available in Pulumi. The auto-generated providers help, but they're not always reliable.

Learning Curve for Operations Teams: Despite marketing claims about "familiar languages," operations engineers who've spent years with declarative tools struggle with imperative infrastructure code. The mental model shift from "describe what you want" to "program how to get it" creates friction in teams with mixed backgrounds.

Does This Thing Actually Work When It Matters?

State Management is Solid: Pulumi Cloud's state backend has been reliable. No data loss, no corruption issues in our experience. The automatic backups and versioning work as advertised. However, we've experienced 3 service outages in 2 years that prevented deployments entirely.

Deployment Speed: Infrastructure deployments average 15% faster than our previous Terraform setup, primarily due to better dependency resolution. However, the initial program execution adds 10-30 seconds of overhead that pure declarative tools don't have.

Error Handling is Fucking Terrible: When shit breaks, the error messages are useless. "Resource creation failed" - oh great, thanks Pulumi, really narrowed it down there. You'll spend way too much time digging through AWS CloudTrail to figure out what actually went wrong. Enable verbose logging from day one: pulumi up --logtostderr -v=9 - you'll be typing that command a lot.

How Your Team Will Actually React

Developers Love It: Front-end and back-end developers adopted Pulumi quickly. The familiar syntax and tooling reduced onboarding time from weeks to days. Code reviews for infrastructure became as natural as application code reviews.

DevOps Teams Are Mixed: Senior engineers appreciate the power and flexibility. Junior engineers and those from traditional operations backgrounds prefer the explicit nature of declarative tools. Plan for a 3-6 month transition period and additional training costs.

Security Teams Need Convincing: The policy as code features help, but security teams initially worried about developers having too much flexibility in infrastructure code. We addressed this with CrossGuard policies and mandatory code reviews.

The Times It Completely Screwed Us Over

So this one time, AWS provider... I think it was 5.42.0? Maybe 5.41-something? Either way, it completely fucked our EKS setup overnight. Just stopped working. Error message was something like "InvalidParameterException: Cluster version 1.27 is not supported" which made absolutely no sense because we'd been running 1.27 for months.

Took us like 4 hours to figure out they changed the default Kubernetes version in the provider update. Four fucking hours. On a Tuesday morning. With production down. Now we pin every provider version because trust is apparently a luxury we can't afford.

Then there was this other clusterfuck where someone (who shall remain nameless but knows who they are) manually tweaked an RDS instance in the AWS console. Don't ask me why. Pulumi completely lost its shit and started throwing "resource differs from expected state" errors everywhere. Real helpful, right?

Spent most of a Saturday comparing Pulumi state files to actual AWS resources line by line until we figured out what got changed. Good times. Really what I wanted to do with my weekend.

Oh, and let's not forget the time when our deployment just... hung. For like 2 hours. Some kind of dependency loop that the engine couldn't figure out, timeout error was useless as always, and we couldn't even cancel the damn thing properly. Had to pulumi cancel and then clean up the half-deployed mess manually. That was fun to explain to management.

The Bottom Line

Pulumi isn't a revolutionary replacement for existing tools - it's an evolutionary improvement with clear trade-offs. The developer experience improvements are real and significant. The ability to test infrastructure code and use familiar programming constructs adds genuine value. However, the higher costs, smaller ecosystem, and team transition challenges mean it's not automatically the right choice for every organization.

For teams with strong development backgrounds building cloud-native applications, Pulumi's benefits outweigh the costs. For traditional infrastructure teams managing stable, well-understood environments, the advantages are less compelling.

The tool itself is production-ready, but success depends more on team composition and organizational priorities than technical capabilities.

The pricing conversation around Pulumi is often misleading because most analyses focus on the base subscription costs without considering the total economic impact. After managing Pulumi deployments across multiple environments, here's the complete financial picture that matters for decision-makers.

Direct Costs: More Than the Subscription

We're managing something like 1,100-1,300 resources across AWS - EKS clusters, RDS instances, Lambda functions, and all the supporting crap that comes with it. The Pulumi Enterprise plan hits us for around $580/month, give or take. That's about $7,000/year, which honestly makes me wince every time I see the invoice.

The comparison to Terraform Cloud is where it gets painful. They switched to resource-based pricing in 2023, and for our setup we'd probably pay around $1,200-1,400/year. So yeah, we're paying roughly $5,500-6,000 more annually for Pulumi. That's real money that comes out of our infrastructure budget.

Every month I see that $580 invoice and die a little inside. Sure, there are some cost analysis blogs out there if you want to read more marketing bullshit, but the numbers don't lie - we're paying 4-5x what Terraform Cloud would cost us.

Hidden Costs: Training and Transition

Training Investment: We dropped around $12,000-15,000 on external training and probably burned 150+ hours of internal knowledge transfer. That training bill hurt, especially when half the team was still bitching about missing Terraform two months later. "Why can't I just write some fucking HCL?" was basically our team motto for the first quarter.

Productivity Impact: The first few months were rough - our deployment velocity dropped by maybe 35-40% while everyone figured out the new patterns. For our team's hourly rates, that probably cost us $10,000-12,000 in lost productivity. Hard to calculate exactly, but it felt expensive.

Tool Migration: Migrating our existing Terraform stuff took about 3 weeks of senior engineer time, maybe more if you count all the cleanup. The conversion tools spit out code that technically works but looks like shit. You'll rewrite most of it anyway. Check out real migration war stories on Reddit - they're not sugar-coating it.

Where Pulumi Actually Saves Us Money

Faster Development: Once everyone stopped complaining and learned the damn thing, our infrastructure work got noticeably faster. Complex changes that used to take 1-2 days now take maybe half a day, sometimes less. Hard to put an exact number on it, but we're probably saving 6-10 hours per week across the team. That's real money.

Fewer Fuckups: The type checking and IDE support has definitely cut down on stupid mistakes. We used to have infrastructure incidents maybe once every 3-4 weeks - usually because someone typo'd a resource name or forgot a dependency. Now it's more like once every 6-8 weeks, and they're usually smaller. Each incident used to cost us 3-5 engineer-hours to debug and fix. So we're probably preventing 8-12 incidents per year, which adds up. The compiler catches the dumb shit before it hits prod, which is honestly worth the price sometimes.

Code Reuse: The shared library approach actually works. We built internal patterns for common stuff and now spinning up a new service takes maybe 2-3 hours instead of 4-6. With 20-something new services last year, that saved us a bunch of time. The SANS case study talks about similar improvements, though their numbers are probably more optimistic than ours.

Resource Scaling Reality

The resource-based pricing model creates interesting dynamics:

• Development environments: Our staging and development stacks cost $45/month and $67/month respectively. These would be free with Terraform Cloud's per-user model.
• Temporary environments: Feature branches and testing infrastructure become expensive quickly. A typical integration test environment with 50 resources costs $9.13/month if left running.
• Multi-region deployments: Our disaster recovery setup in a second AWS region doubles our resource count and costs.

Does It Actually Pay For Itself?

Look, I'm not going to pretend I have some perfect spreadsheet that calculates ROI to the dollar. But after two years, we're probably saving money overall. Here's the rough math:

• We pay about $5,500-6,000 more per year for Pulumi vs Terraform Cloud
• Training and migration probably cost us $25,000-30,000 upfront (including lost productivity)
• But we're definitely more productive now - maybe 20-30% faster on infrastructure work
• And we have way fewer "oh shit" moments that cost us hours of debugging

Year 1: Definitely cost us money overall, probably $15,000-20,000 net negative
Year 2+: We're probably breaking even or slightly ahead, but the spreadsheet is complicated enough that I'm not 100% sure

When the Economics Make Sense

From our experience, Pulumi's economics work best for:

High-Velocity Development Teams: Organizations deploying infrastructure changes multiple times per week benefit most from the productivity improvements.

Complex Infrastructure Requirements: Simple, static infrastructure doesn't justify the premium. Complex deployments with conditionals, loops, and integrations show clear ROI.

Developer-Heavy Organizations: Teams with strong programming backgrounds minimize training costs and maximize productivity gains. See Lemonade's case study for how development teams standardized infrastructure components and 4IR's experience cutting deployment time from days to hours.

Multi-Cloud Deployments: The consistent programming model across clouds provides value that's hard to quantify but real in practice. The Firefly comparison analysis discusses multi-cloud advantages in detail.

When It Doesn't Make Sense

Small Teams with Simple Infrastructure: The subscription cost premium is hard to justify for basic setups.

Traditional Operations Teams: If your team primarily consists of systems administrators without programming backgrounds, the training costs and productivity impact may never pay off.

Budget-Constrained Environments: The higher direct costs require careful justification and may not fit all budget profiles.

Legacy-Heavy Environments: If most of your infrastructure uses providers that lag in Pulumi's ecosystem, stick with more mature tooling.

The Bottom Line on Costs

Pulumi costs a shit-ton more than alternatives, let's be honest about that. We're paying 4-5x what we'd pay for Terraform Cloud, and that stings every month when I see the invoice.

But here's the thing - for our team, it's probably worth it. We're a bunch of developers who hate YAML and love having real programming tools for infrastructure. The productivity gains are real, even if they're hard to quantify precisely.

If you're mostly ops people managing stable infrastructure that changes once a month, save your money. If you're shipping code daily and your infrastructure is constantly evolving, the premium might make sense. Just don't expect it to pay for itself in the first year - plan for 18-24 months before you see real ROI.

After 24 months in production, thousands of deployments, and managing infrastructure for applications serving 2.3 million users monthly, here's the unvarnished assessment every technical leader needs.

The Case for Pulumi:

When It Genuinely Excels

For Developer-Heavy Organizations: If your infrastructure team consists primarily of software engineers rather than traditional system administrators, Pulumi is transformative.

The ability to apply software engineering best practices

• version control, code reviews, unit testing, continuous integration
• to infrastructure code eliminates entire classes of problems.

We've probably deployed 800-something infrastructure changes in the past year. Most work fine, some don't. Our success rate is definitely better than with Terraform

• maybe 95% vs the previous 90%
• but it's not like we suddenly became infrastructure gods. The type checking catches stupid mistakes, which helps.

For Complex, Dynamic Infrastructure: Static infrastructure doesn't benefit much from Pulumi's programming model.

However, if you're building platforms that create infrastructure dynamically based on application requirements, Pulumi shines. Our platform automatically provisions complete environments (databases, load balancers, monitoring, CI/CD) when developers deploy new services. This level of automation would be prohibitively complex with declarative tools.

For Multi-Team Coordination: The ability to create reusable components and libraries transforms how teams collaborate.

Our platform team maintains shared infrastructure components that application teams consume as libraries. Changes propagate automatically without copying configuration files. This shared code model scales better than any alternative we've used.

The Case Against Pulumi: When to Choose Something Else

For Traditional Operations Teams:

If your team consists of greybeard sysadmins who've been managing infrastructure with YAML and shell scripts for 15 years, Pulumi will make them absolutely miserable. We dropped $15,000+ on training and 18 months later, half our ops team still grumbles about missing Terraform.

One guy literally said "Why are we programming our fucking firewalls now?" in a team meeting. Loudly. Multiple times. That pretty much sums up the resistance you'll face.

And honestly? I get it. These people have been declaratively describing what they want for decades. "Here's my desired state, make it happen." Now we're asking them to imperatively program how to get there. It's like asking a painter to suddenly become a sculptor

• same medium, completely different mental model.

For Simple, Stable Infrastructure: Managing a few dozen static resources doesn't justify Pulumi's complexity or cost.

If your infrastructure changes quarterly rather than weekly, and consists primarily of standard cloud resources, traditional tools are simpler and more cost-effective.

For Budget-Conscious Environments: The subscription costs are real and significant.

At scale, Pulumi costs 3-5x more than alternatives. For a startup or budget-constrained team, this premium may be unjustifiable regardless of productivity benefits.

Performance in Production: The Real Numbers

Reliability: 99.7% uptime for the Pulumi Cloud service in our experience.

The 3 outages were frustrating but brief (under 4 hours each). Compare this to managing your own Terraform remote state infrastructure, and the reliability is actually better.

Speed: Infrastructure deployments average 12 minutes for our complex environments, compared to 14 minutes with Terraform.

The improvement isn't dramatic, but it's consistent. The real speed gain comes from development velocity

• writing and testing infrastructure code is significantly faster.

Resource Efficiency: Pulumi's state management is more efficient than we expected.

State files are smaller, operations are faster, and the automatic cleanup of unused resources has prevented state bloat.

Team Adoption: What Actually Happens

Month 1-3:

Expect productivity to drop 30-40% as teams adapt. Developers adapt quickly, operations teams struggle. Plan for this and don't schedule critical infrastructure projects during the transition.

Month 4-6: Teams reach baseline productivity with Terraform-equivalent capabilities.

The programming model starts showing benefits for complex tasks.

Month 7-12: Productivity gains become evident.

Teams build internal libraries, implement testing, and create automation that wasn't practical before.

Year 2+: Teams report 25-30% higher productivity for infrastructure work.

The compound benefits of shared libraries, testing, and familiar tooling accumulate.

Integration with Existing Tools

CI/CD Integration: Works well with all major platforms. GitHub Actions, GitLab CI, and Jenkins integration are straightforward.

The Automation API enables custom workflows that weren't possible with declarative tools.

For enterprise deployment patterns, see Pulumi Deployments and production-ready container deployment strategies.

Monitoring and Observability:

Resource tagging and metadata management is superior to other Ia

C tools. Integration with monitoring platforms (DataDog, New Relic, CloudWatch) is seamless because you can programmatically ensure consistent configuration.

Security Tooling: CrossGuard policies integrate well with existing security scanning tools.

The ability to test security policies in isolation before deployment has prevented several compliance issues.

The Economics: Final Analysis

For our organization, Pulumi costs $7,000/year more than Terraform Cloud but saves approximately $50,000/year in engineering productivity and reduced incidents.

The ROI calculation is positive after 18 months.

However, this calculation assumes:

• Complex infrastructure requirements
• Frequent infrastructure changes
• Developer-heavy team composition
• High incident costs (common in high-traffic environments)

If any of these assumptions don't match your situation, the economics may not work.

Migration Strategy:

Lessons Learned

Start Small: Don't migrate everything at once.

Choose a single, non-critical service for the initial migration. Learn the tooling and patterns before committing to larger changes. For migration strategies, see Learning Machine's experience eliminating hundreds of thousands of lines of configuration code.

Invest in Training:

The $15,000 we spent on external training was worthwhile. The documentation is good, but hands-on training accelerates adoption significantly. The Platform Engineering Tools guide discusses ROI analysis for training investments.

Plan for Dual Operations:

You'll run both Terraform and Pulumi for 6-12 months during migration. Budget for the operational overhead of managing two toolchains. The CloudBolt comparison provides additional migration considerations.

Would I Do It Again?

After two years and thousands of deployments and way too much money spent on subscriptions? Yeah, probably. But only because our team is mostly developers who hate YAML with a burning passion and get genuinely excited about having proper IDE support for infrastructure.

Speaking of which

• can we talk about how fucking amazing it is to have Intelli

Sense for AWS resources? Like, actual autocomplete that knows what properties exist? After years of constantly alt-tabbing between Terraform docs and my editor, this feels like cheating.

But look, I wouldn't recommend this to everyone. Not even close.

Use Pulumi if:

• Your team consists mostly of software engineers who think in code, not traditional ops people who think in config files
• You're constantly changing infrastructure (like, daily) not just maintaining a stable set of servers that change monthly
• You can afford to pay 4-5x more for tooling and deal with waiting 6 months for new AWS services to be supported
• Your team won't revolt when you tell them they're now programming their firewall rules in TypeScript

Stick with Terraform if:

• Your team actually likes declarative tools and explicit configuration (weird, but some people do)
• You need every bleeding-edge cloud service supported the day it launches
• Budget matters and you can't justify paying premium prices for developer happiness
• Your infrastructure is mostly static and changes monthly, not daily

The honest truth? It's not really about the technology

• it's about your team. Pulumi makes developer-heavy teams significantly more productive. It makes traditional ops teams want to quit and join a company that still uses Ansible playbooks.

Choose accordingly, and don't say I didn't warn you.