Service Level Objective Examples

Service level objectives (SLOs) are a core component of site reliability engineering (SRE). They help SRE teams define and maintain reliability based on service-level indicators (SLIs). Creating meaningful SLOs is essential for their success and requires a structured approach that aligns with user expectations and business goals. Implementing well-designed SLOs delivers tangible business benefits, including reduced downtime costs, improved customer satisfaction, and more efficient resource allocation.

The SLO development lifecycle (SLODLC) provides a framework for creating metrics that matter to service-centric organizations. Practitioners in the DevOps community created the SLODLC framework to provide practical, actionable templates and examples to help organizations in their journey to adopt SLOs.

The SLODLC framework has six phases: initiate, discover, review, design, implement, and operate. This article discusses each phase and provides real-world examples of how it helps deliver a service and manage the tradeoffs involved in running a digital application.

Summary of key concepts as context for the service level objective examples

Phase 0: Initiate

Before setting any SLOs, teams must understand why reliability matters to the relevant stakeholders and how SLOs will impact decision-making. Buy-in from leadership, engineering teams, and other stakeholders is essential for success, and Phase 0 helps achieve this.

The Business Case Worksheet is pivotal to Phase 0. It aims to summarize why you are considering this journey, which helps confirm buy-in from all involved. It establishes the business objectives the SLOs will support, the critical services that require reliability tracking, and how the SLOs will influence engineering trade-offs, among other goals.

Here is an example excerpt from the Business Case Worksheet that could apply to a commerce business, showing Section 1.2, which details achievable goals that are anticipated from the adoption of SLODLC:

Keep each item concise, similar to the example above. Along with the rest of the worksheet, this should ensure that the reasoning for implementing SLOs and SLIs is clear to all stakeholders and that everyone is invested in their success.

Phase 0 should be less about specific SLI targets and more about the high-level SLOs being considered. This can include both highly technical objectives (“Maintaining a high-performance and reliable online presence”) and less technical ones (“Reducing stock replacement times”). The importance of this phase is that the objectives can be measured and can improve business performance, not necessarily how they are measured or at what levels the measures are expected to be.

Phase 1: Discover—Identifying user expectations and SLIs 

With buy-in confirmed during Phase 0, Phase 1 aims to establish a more specific purpose and impact of SLOs with the help of the Discovery Worksheet. By concentrating on the services the SLOs relate to, their context within the business, and the expectations of various stakeholders, more formal, measurable targets are created to form the basis of the SLOs.

Example 1

An example of Section 1.4 of the Discovery Worksheet, “Service Expectations,” that could apply to a commerce business is shown below:

As with Phase 0, this could include both technical and non-technical items. This helps establish the difference between users' and engineers' expectations, ensuring correct prioritization. While engineers may be inclined to perceive response time or availability to be the highest priority, users may be more concerned that the data be accurate and durable. A delayed response may be accepted if the reaction is always accurate. Phase 1 establishes these differences in expectation and formally prioritizes them.

Section 2 of the Discovery Worksheet, “Prioritize User Journeys and Expectations,” captures user expectations more deeply. Here is an example of Section 2.1 capturing a variety of users with their specific expectations for functionality and performance.

Understanding the variety of system users, what they use the system for, and their expectations for successful operation helps identify which SLIs are most important to real-world reliability. Although every business’s prioritization will differ, the example excerpt above could be used to argue that retail customers' expectations should take priority over store managers’ as being unable to check stock availability before visiting a store or not being notified when an item is restocked could lead to loss of custom. In contrast, a store manager receiving low stock alerts daily, rather than in real time, could be nothing more than a minor inconvenience if stock is dispatched less than daily.

Note that some users’ expectations may overlap. Thoroughly including each user groups’ expectations ensures that these overlaps are uncovered and helps with prioritization.

Example 2

With the service level and user expectations agreed on, Section 4, “Observe System Behavior,” establishes how the expectations can be observed and monitored. For example:

The examples above cover just part of the Discovery Worksheet, but when worked to completion, a picture of the user experience, expectations, appropriate SLIs, and where to find the data to measure them begins to develop.

Phase 2: Design—Defining achievable vs. aspirational SLOs

Once the SLIs to be measured are identified, Phase 2 aims to design realistic targets and aspirational goals for them, balancing user expectations against system constraints and differentiating between short-term and long-term goals.

This is achieved using the SLI/SLO Specification Template.

Some example SLI/SLO specifications that could come from the previous discovery phase include the following:

Each example references the item from previous phases, which justifies measuring the SLO, a measurable, achievable, and aspirational target to confirm with certainty whether the SLO has been met, and the measurement used to verify the metric. 

Tips:

• The SLI, SLO, targets, and measurement should clearly define what is considered an acceptable level of service or an aspiration for improvement.
• Targets should be set to reasonable levels and may already be regularly achieved. Setting unattainable or overly ambitious targets from the outset does little to assist in genuinely measuring performance.
• Aspirational targets should be set to a higher standard that is rarely met, if ever, to ensure that improvements are always worked toward.

Phase 3: Implement—Instrumenting and collecting SLIs

The next step is monitoring the defined SLOs in production and ensuring that teams have real-time visibility into performance. With that in mind, the SLODLC Implement Worksheet used in Phase 3 specifies what tools should track SLIs, how to alert teams when SLOs are at risk, and how to collect meaningful metrics without adding unnecessary overhead.

Here is an example excerpt from Section 2 of an “Implement Worksheet” related to the page load time SLO. It defines several ways that statistics relevant to the SLO could be collected.

Recording, storing, and analyzing metrics is only useful if stakeholders have visibility of the analysis. Visualisations and dashboards, such as those available as part of Nobl9 Reliability Center (shown below), provide clear and concise views of when an SLO is at risk or has been breached, prompting quick reactions to potential issues.

Service Health Dashboard: Error budget

Phase 4: Operate—Using SLOs for incident response and scaling

SLOs should not be treated as just metrics. They should guide operational decisions and help teams prioritize reliability efforts relative to new feature work. They may even influence on-call alerting and decisions about whether the deployment of new features should be reduced to preserve reliability.

Given the example from Phase 3 above, on-call alerting is activated if the aggregated data suggests that fewer than 99% of pages load in under 500 ms over some time interval, indicating that performance has dropped below the previously agreed acceptable level. The Nobl9 platform offers rich features and integrations with various alert systems.

Depending on the outcome of the on-call investigation, a decision could be made to reverse a recent deployment deemed to have introduced the drop in performance and restrict any further planned deployments until a full investigation into the cause has been completed.

Alternatively, suppose performance is known to drop during the deployment process for any reason. In that case, on-call alerting may be paused during a planned deployment, and the temporary drop in performance may be accepted if data suggests that far more than 99% of page loads have recently been completed in under 500 ms. In this case, the risk of breaching the SLO’s target is significantly reduced.

Furthermore, suppose the data suggests that 100% of page loads are completed within 500 ms, and 98% are completed in close to 200 ms. This is a prompt to adjust expectations and achieve the aspirational target of 99% of loads in under 200 ms.

Periodic Review—Adapting SLOs based on performance trends

SLOs aren’t static. As the example above suggests, they should be reviewed regularly to account for infrastructure changes, user growth, and changes in expectations. You should review whether SLOs are too aggressive or lenient, whether traffic pattern changes require adjustments, whether you are meeting SLOs or exceeding them without risk periodically, and when changes are made in the knowledge that they could have an impact. The Periodic Review Checklist and Nobl9 consolidated SLO reports can help with this. 

An example excerpt from a Periodic Review Checklist after reviewing SLOs related to page load times is shown below:

Conclusion

Implementing effective SLOs involves more than just picking numbers. Following a structured framework that ties business needs, user expectations, and technical realities together, such as the SLODLC methodology and the wide variety of templates and worksheets it offers, helps create actionable, measurable, and adaptable SLOs. This, in turn, helps teams define, measure, and maintain reliability.