A bit more context there since you might wonder why customers can cause Sev1’s.

Well, I work for a Database Technology company and we provide a managed service offering. This managed service offering has SLA’s that essentially enforce a 5 minute response time for any “urgent” issue.

Well, a common urgent issue is that the customer suddenly wants to load in a bunch of new data without informing us which causes the cluster to stop accepting write loads.

It’s to the point where most if not all urgent pages result in some form of scaling of the cluster.

Since this is a customer driven behavior, there is no real ability to plan for it - and since these particular customers have special requirements (and thus, less ability to automate scaling operations), I’m unsure if there is any recourse here.

It’s to the point that it doesn’t even feel like an SRE team anymore - we should just instead be called “On-demand scaling agents”. Since we’re constantly trying to scale ahead of our customers.

All in all, I’m starting to feel like this is a management/sales level issue that I cannot possibly address. If we’re selling this managed service offering as essentially “magic” that can be scaled whenever they need then it seems like we’re being setup for failure at the organizational level. Not to mention, not being smart about costs behind scaling and factoring that into these contracts.

So, fellow SRE’s have you had to have this conversation with a larger org? What works for something like this? What doesn’t? Should I just seek greener pastures at this point?

P.S. - Posted c/Programming due to lack of a c/SRE

  • BanditMcDougal@lemmy.world
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    1 year ago

    My answer won’t be as popular, but it’ll definitely get the attention of the right people on the customer’s side: charge HANDSOMELY for issues caused due to customers using the systems outside of agreemed to or published best practices.

    • Oliver Lowe@lemmy.sdf.org
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      1 year ago

      I am consistently surprised by what companies are willing to pay to not worry about capacity. Incredible DataDog bills, for example, because they didn’t want to think about how many application metrics to store; “just keep it all!”. And boy do they happily pay for it!