By Alex Bramley, Customer Reliability Engineer
Previous episodes of CRE life lessons have talked in detail about the importance of quantifying a service’s availability and using SLOs to manage the competing priorities of features-focused development teams (“devs”) versus a reliability-focused SRE team. Good SLOs can help reduce organizational friction and maintain development velocity without sacrificing reliability. But what should happen when SLOs are violated?
In this blogpost, we discuss why you should create a policy on how SREs and devs respond to SLO violations, and provide some ideas for the structure and components of that policy. Future posts will go over an example taken from an SRE team here at Google, and work through some scenarios that put that policy into action.
In the ideal world (assuming spherical SREs in a vacuum), an SLO represents the dividing line between two binary states: developing new features when there’s error budget to spare, and improving service reliability when there isn’t. Most real engineering organizations will instead vary their effort on a spectrum between these two extremes as business priorities dictate. Even when a service is operating well within its SLOs, choosing to do some proactive reliability work may reduce the risk of future outages, improve efficiency and provide cost savings; conversely it’s rare to find an organization that completely drops all in-flight feature development as soon as an SLO is violated.
Describing key inflection points from that spectrum in a policy document is an important part of the relationship between an SRE team and the dev teams with whom they partner. This ensures that all parts of the organization have roughly the same understanding around what is expected of them when responding to (soon to be) violated SLOs, and – most importantly – that the consequences of not responding are clearly communicated to all parties. The exact choice of inflection points and consequences will be specific to the organization and its business priorities.
Having a strong culture of blameless postmortems and fixing root causes should eventually mean that most SLO violations are unique – informally, “we are in the business of novel outages.” It follows that the response to each violation will also be unique; making judgement calls around these is a part of an SREs job when responding to the violation. But a large variance in the range of possible responses results in inconsistency of outcomes, people trying to game the system and uncertainty for the engineering organization.
For the purposes of an escalation policy, we recommend that SLO violations be grouped into a few buckets of increasing severity based on the cumulative impact of the violation over time (i.e., how much error budget has been burned over what time horizon), with clearly defined boundaries for moving from one bucket to another. It’s useful to have some business justification for why violations are grouped as they are, but this should be in an appendix to the main policy to keep the policy itself clear.
It’s a good idea to tie at least some of the bucket boundaries to any SLO-based alerting you have. For example, you may choose to page SREs to investigate when 10% of the weekly error budget has been burned in the past hour; this is an example of an inflection point tied to a consequence. It forms the boundary between buckets we might informally title “not enough error budget burned to notify anyone immediately” and “someone needs to investigate this right now before the service is out of its long-term SLO.” We’ll examine more concrete examples in our next post, where we look at a policy from an SRE team within Google.
The consequences of a violation are the meat of the policy. They describe actions that will be taken to bring the service back into SLO, whether this is by root causing and fixing the relevant class of issue, automating any stop-gap mitigation tasks or by reducing the near-term risk of further deterioration. Again, the choice of consequence for a given threshold is going to be specific to the organization defining the policy, but there are several broad areas into which these fall. This list is not exhaustive!
Notify someone of potential or actual SLO violation
The most common consequence of any potential or actual SLO violation is that your monitoring systems tells a human that they need to investigate and take remedial action. For a mature, SRE-supported service, this will normally be in the form of a page to the oncall when a large quantity of error budget has been burned over a short window, or a ticket when there’s an elevated burn rate over a longer time horizon. It’s not a bad idea for that page to also create a ticket in which you can record debugging details, use as a centralized communication point and reference when escalating a serious violation.
The relevant dev team should also be notified. It’s OK for this to be a manual process; the SRE team can add value by filtering and aggregating violations and providing meaningful context. But ideally a small group of senior people in the dev team should be made aware of actual violations in an automated fashion (e.g., by CCing them on any tickets), so that they’re not surprised by escalations and can chime in if they have pertinent information.
Escalate the violation to the relevant dev team
The key difference between notification and escalation is the expectation of action on the part of the dev team. Many serious SLO violations require close cooperation between SREs and developers to find the root cause and prevent recurrence. Escalation is not an admission of defeat. SREs should escalate as soon as they’re reasonably sure that input from the dev team will meaningfully reduce the time to resolution. The policy should set an upper bound on the length of time an SLO violation (or near miss) can persist without escalation.
Escalation does not signify the end of SRE’s involvement with an SLO violation. The policy should describe the responsibilities of each team and a lower bound on the amount of engineering time they should divert towards investigating the violation and fixing the root cause. It will probably be useful to describe multiple levels of escalation, up to and including getting executive-level support to commandeer the engineering time of the entire dev team until the service is reliable.
Mitigate risk of service changes causing further impact to SLOs
Since a service in violation of its SLO is by definition making users unhappy, day-to-day operations that may increase the rate at which error budget is burned should be slowed or stopped completely. Usually, this means restricting the rate of binary releases and experiments, or stopping them completely until the service is again within SLO. This is where the policy needs to ensure all parties (SRE, development, QA/testing, product and execs) are on the same page. For some engineering organizations, the idea that SLO violations will impact their development and release velocity may be difficult to accept. Reaching a documented agreement on how and when releases will be blocked – and what fraction of engineers will be dedicated to reliability work when this occurs – is a key goal.
Revoke support for the service
If a service is shown to be incapable of meeting its agreed-upon SLOs over an extended time period, and the dev team responsible for that service is unwilling to commit to engineering improvements to its reliability, then SRE teams at Google have the option of handing back the responsibility for running that service in production. This is unlikely to be the consequence of a single SLO violation, rather the combination of multiple serious outages over an extended period of time, where postmortem AIs have been assigned to the dev team but not prioritized or completed.
This has worked well at Google, because it changes the incentives behind any conversation around engineering for reliability. Any dev team that neglects the reliability of a service knows that they will bear the consequences of that neglect. By definition, revoking SRE support for a service is a last resort, but stating the conditions that must be met for it to happen makes it a matter of policy, not an idle threat. Why should SRE care about service reliability if the dev team doesn’t?
Hopefully this post has helped you think about the trade-off between engineering for reliability and features, and how responding to SLO violations moves the needle towards reliability. In our next post, we’ll present an escalation policy from one of Google’s SRE teams, to show the choices they made to help the dev teams they partner with maintain a high development velocity.