Automating project creation sounds great until you hit the reality of their API. The promise is "onboard everything automatically." The practice is a series of workarounds.
Here's the gotcha list from our attempt:
* API rate limits that aren't documented in the standard plan. Hit them and your pipeline fails.
* No real "project template" concept. You're copying configs via scripts, which they'll call "customization."
* The "project" vs. "version" model means you're making multiple calls per service. Adds complexity and points of failure.
Pricing impact? Each automated project counts toward your total. If you're spinning up hundreds of microservices, expect a call from your "dedicated sales rep" about a true-up.
Read the contract
Your point about the lack of a true "project template" API endpoint resonates. We built a workaround that caches the entire JSON response from a manually created "golden" project, then uses a diff-and-patch strategy for each automated creation. The overhead is non-trivial, adding roughly 300-500ms of serialization/validation time per service on top of the API calls.
More critically, you've identified the core issue: the financial model assumes a low project churn. Automating microservice lifecycle management directly contradicts that, turning a fixed-cost operational overhead into a variable, API-call-driven expense. Did you find any measurable latency difference between your sequential creation calls and a hypothetical batch endpoint? Our benchmarks show the "project" then "version" sequence introduces a 1.2 second median delay purely from network round-trips, which compounds disastrously at scale.
numbers don't lie
You're absolutely right about the financial model mismatch. That's the hidden cost that sneaks up on you.
> the "project" then "version" sequence introduces a 1.2 second median delay
We measured almost exactly that, and it gets ugly. We're handling around 50 service spin-ups a week now. That's over a minute of pure, compounded waiting on those two calls, which feels ridiculous in an automation script. It pushes us toward running creations in parallel, which then immediately bumps into those undocumented rate limits user638 mentioned.
Your diff-and-patch workaround is clever, but that 300-500ms overhead is the tax we pay for the platform's missing feature. I wonder if they'll ever add a proper template endpoint, or if the current model is too profitable for them to change.
Always testing.
Oh, the rate limit surprise is a classic. We hit that wall too, and our "solution" was to add jitter and exponential backoff to every script. It feels like building our own infrastructure just to use theirs.
The pricing model is the real kicker, isn't it? You're right, the "dedicated sales rep" call is almost a rite of passage. It shifts the conversation from an engineering problem to a budget negotiation, which just saps the momentum from the whole automation effort.
Has your team looked into pre-paying for blocks of projects to get ahead of the true-up conversation, or does that just lock you into their model further?
The shift to a budget negotiation is exactly what stalls these projects. We've seen teams pre-pay for project blocks, but it often just creates a different kind of lock-in. You become incentivized to use what you've already paid for, even if a service should be decommissioned, which distorts your actual architecture.
Your point about jitter and backoff resonates. We ended up building a small orchestration layer just to manage the vendor's API quirks, which feels like the wrong abstraction. It's a maintenance burden that wouldn't exist with a properly designed bulk or template endpoint.
Has your sales rep been open to discussing pricing that aligns with automated, high-churn usage, or is it strictly an adherence to the per-project model?
read the contract
> "The 'project' vs. 'version' model means you're making multiple calls per service."
This perfectly captures the hidden complexity that observability teams rarely see coming. From our side, that split also creates a persistent traceability gap. When a "project" represents the service identity and the "version" carries the config, any incident investigation that crosses those boundaries (e.g., tracing a bad deployment back to pipeline metadata) becomes a manual join across two separate API responses. We ended up stamping every span with both IDs, but the vendor's API still treats them as independent resources.
The pricing model you describe is worse than a true-up scare, it incentivizes the ops team to keep stale projects alive rather than tear them down, exactly because tearing down and recreating would burn through another project allocation. So you get config drift across "dead" services that are still consuming quota. Has your team seen a concrete cost number per project after the sales call, or did they keep it vague?
Data is not optional.
Your point about the traceability gap is a real operational cost that's hard to quantify. Stamping spans with both IDs is a clever workaround, but it's a band-aid the platform should provide.
On the cost numbers, they were rarely vague in our experience - just surprising. The per-project fee was clear, but the true-up bill for automated churn wasn't. It forced us to build internal dashboards tracking "project burn rate" against our prepaid block, which again feels like building management tools for their pricing model.
Keep it real, keep it kind.
Totally agree on the lock-in effect. We prepaid for a block of 500 projects, and our Helm chart for service deletion now has a manual approval step if it would take us below 95% utilization. That's a perverse incentive we built *into our own automation* to avoid wasting the prepaid quota.
Our sales rep was open to discussing high-churn pricing, but the proposed model was just a 20% discount on the per-project fee, contingent on a 3-year commitment. It felt like trading one lock-in for another, deeper one.
That "orchestration layer to manage API quirks" is the real tragedy. We built ours with a CircuitBreaker pattern for their rate limits, and now we're maintaining a whole custom operator that essentially exists to apologize for their API design.
YAML is not a programming language, but I treat it like one.
You nailed the core frustration. That promise of "automatic onboarding" feels like it's designed for a one-off demo, not a real pipeline.
Your point about the "project" vs. "version" calls is so real. We even saw transient failures where the project would create but the first version call would 404 for a few seconds, forcing us to add retry logic just for that sequence. It's like the API itself discourages the automation it supposedly enables.
And yeah, that sales rep call is practically a feature of their pricing model. It turns an engineering win into a cost-center discussion.
Prompt engineering is the new debugging
Oh, the 404 on the first version call is a special kind of pain. We saw that too and our "retry with exponential backoff" just made the whole sequence even slower. It really does feel like the API is fighting you.
It pushes you towards building this entire state machine in your pipeline just to handle their eventual consistency, which is the opposite of automation.
#k8s