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Observability-first development for teams shipping AI-generated code. SLOs in Dash0 turn "is it reliable enough?" into one number the whole company agrees on: a target, a rolling window, and an error budget you spend on purpose. Predictive burn-rate alerts catch a slow leak before users do and page only when it is a fire. Align engineering to business goals, release with confidence, and see exactly what every deploy cost you. Now generally available. 25 SLOs per organization, included.
We built this because "is the service reliable enough?" kept getting three different answers from three engineers. With AI writing more of the code, releases are faster and the blast radius is less predictable, so you need a contract that is not a vibe. An SLO is that contract: a target, a rolling 28-day window, and the error budget that falls out of it. When the budget is healthy you ship. When it is burning you slow down. That is observability-first development, and it is how engineering and the business end up looking at the same number.
The proactive part is burn rate. Instead of paging on one bad minute, Dash0 derives fast and slow burn pressure from every SLO with multi-window alerts. Fast burn is a fire and pages you. Slow burn is a leak that would quietly break the promise by the end of the window, so it opens a ticket before users notice.
For the technically curious: pick a service, describe good and total events with two plain PromQL label selectors, set a target. Dash0 builds and manages the recording rules behind it, so there is no plumbing. Every SLO gets a burndown, remaining error budget, and pre-filled burn-rate check rules. Create them in the UI, with Agent0, or as OpenSLO YAML, API and Terraform. 25 SLOs per organization, included.
Would love to hear how you define reliability today, and what you would want an SLO product to do next.
Really happy to see this out in the wild! I’ve been working on the engineering side of SLOs at Dash0, and it’s been a pretty interesting journey getting all the pieces together.
One of the things we cared about was making SLOs feel like a natural part of the observability workflow rather than yet another isolated system.
Very curious to hear how people are using it in practice, especially at scale. Feedback, weird use cases and edge cases are all very welcome :)
About Service Level Objectives · Dash0 on Product Hunt
“Reliability is a budget. Spend it on purpose.”
Service Level Objectives · Dash0 was submitted on Product Hunt and earned 5 upvotes and 2 comments, placing #128 on the daily leaderboard. Observability-first development for teams shipping AI-generated code. SLOs in Dash0 turn "is it reliable enough?" into one number the whole company agrees on: a target, a rolling window, and an error budget you spend on purpose. Predictive burn-rate alerts catch a slow leak before users do and page only when it is a fire. Align engineering to business goals, release with confidence, and see exactly what every deploy cost you. Now generally available. 25 SLOs per organization, included.
Service Level Objectives · Dash0 was featured in Analytics (173.8k followers), SaaS (44.3k followers) and Developer Tools (519.8k followers) on Product Hunt. Together, these topics include over 158.2k products, making this a competitive space to launch in.
Who hunted Service Level Objectives · Dash0?
Service Level Objectives · Dash0 was hunted by Liat Hoffman. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Reviews
Service Level Objectives · Dash0 has received 5 reviews on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.
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Liat Hoffman
Hi Product Hunt, Liat here, PM for SLOs at Dash0.
We built this because "is the service reliable enough?" kept getting three different answers from three engineers. With AI writing more of the code, releases are faster and the blast radius is less predictable, so you need a contract that is not a vibe. An SLO is that contract: a target, a rolling 28-day window, and the error budget that falls out of it. When the budget is healthy you ship. When it is burning you slow down. That is observability-first development, and it is how engineering and the business end up looking at the same number.
The proactive part is burn rate. Instead of paging on one bad minute, Dash0 derives fast and slow burn pressure from every SLO with multi-window alerts. Fast burn is a fire and pages you. Slow burn is a leak that would quietly break the promise by the end of the window, so it opens a ticket before users notice.
For the technically curious: pick a service, describe good and total events with two plain PromQL label selectors, set a target. Dash0 builds and manages the recording rules behind it, so there is no plumbing. Every SLO gets a burndown, remaining error budget, and pre-filled burn-rate check rules. Create them in the UI, with Agent0, or as OpenSLO YAML, API and Terraform. 25 SLOs per organization, included.
Would love to hear how you define reliability today, and what you would want an SLO product to do next.