Defining Service Level Objectives (SLOs) seems straightforward: pick a target, monitor it, and report on it. But getting this wrong, in the context of building an entire SLO program, has serious consequences. Teams struggle with unreliable customer experiences, bloated infrastructure spending, and a pile of meaningless dashboards. Many people know this, which is why picking the right targets can feel like a major barrier to rolling out SLOs across services.
If you’re leading or growing an SLO program, here are five common traps to avoid.
Why it’s a problem: 100% availability sounds great, but unless you manage air traffic control or nuclear plant systems, it’s a fantasy and an expensive one. Striving for perfection forces over-engineering and takes teams away from improvements that would make a bigger impact on reliability.
What to do instead: Use error budgets to define an acceptable threshold for failure. For example, if 99.9% uptime is enough to avoid customer support calls and churn, targeting higher just wastes resources that could be used better elsewhere. It’s worth mentioning that even 99.9% is often unattainable, and if users and customers won’t notice or complain, it’s completely acceptable to set the SLO way lower than that.
Why it’s a problem: Your authentication API and your payments service are not equally critical. Applying a blanket target to every service leads to misaligned priorities and frustrated teams. Some services are far more critical to the user and/or overall business objectives (cost/revenue), that it’s strongly encouraged to think of each service individually, and aligned to the broader context of the business.
What to do instead: Define SLOs in the context of the user journey and business importance. Use structured review cycles to ensure teams aren’t simply duplicating targets without thinking about the end goal of improving the service from a business (cost) or user experience perspective.
Why it’s a problem: Setting targets without looking at historical performance is just guessing. This creates SLOs that are constantly violated (and therefore ignored) or never threatened (and therefore useless).
What to do instead: Replay historical data to test and validate SLO thresholds before they go live. Nobl9’s SLO Replay and SLI Analyzer help teams model what targets are realistically achievable based on past performance.
Why it’s a problem: SLOs without clear owners inevitably degrade. They become stale, misconfigured, or get ignored during incidents. Crucially, no one is accountable when targets are missed.
What to do instead: Implement a clear ownership model at the service level. Nobl9 includes tooling to make sure that accountability for each SLO is assigned and tracked.
Why it’s a problem: An SLO that was relevant a year ago might be irrelevant today because of architectural changes, product growth, or changes in user behavior. Without regular, structured reviews, stale SLOs will mislead teams and destroy trust in the entire program.
What to do instead: Establish mandatory review cycles. Use automation, like Nobl9’s Oversight suite, to flag outdated or broken SLOs and prompt teams to revisit their definitions.
Nobl9 provides a set of tools to operationalize and oversee an SLO program across its lifecycle, directly addressing the pitfalls mentioned above: