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Difficulty: MediumAligning Technical Service Level Objectives (SLAs/SLOs/SLIs) with Business Objectives

An online media streaming enterprise hosts two key workloads on Google Cloud: a real-time Live Video Playback API supporting live high-profile sports broadcasts, and an asynchronous Recommendation Generation Pipeline that processes user viewing history overnight to update playlist recommendations. The Site Reliability Engineering (SRE) team needs to define service indicators and objectives that reflect business priorities without creating unnecessary operational overhead. Which TWO strategies should the team implement to align technical SLOs and error budgets with business impact? (Select TWO.)

  1. Define a strict availability and latency SLO based on successful HTTP responses for the Live Video Playback API, using its error budget to regulate release velocity during critical live events.Answer
  2. B
    Enforce a uniform 99.99% availability SLO across both the Live Video Playback API and the Recommendation Generation Pipeline to maintain consistent operational standards.
  3. Define the SLI for the Recommendation Generation Pipeline as the percentage of batch jobs completed within a 12-hour completion window, allowing a more permissive SLO and larger error budget.Answer
  4. D
    Configure immediate pager alerts for operations whenever the instantaneous SLI metric for the Live Video Playback API dips by 0.01% over any 1-minute sampling interval.

Answer

The SRE team should define a strict availability and latency SLO for the real-time Live Video Playback API tied to release management error budgets, and measure the Recommendation Generation Pipeline using a batch job completion window SLI that allows a larger error budget.
Correctly aligning technical service objectives with business goals requires differentiating between user-facing, real-time services and background asynchronous processes. The Live Video Playback API directly impacts revenue during live events, justifying a strict SLO and using its error budget to govern release policy. Conversely, the Recommendation Generation Pipeline is a batch workload where user experience is preserved as long as jobs finish within a 12-hour window, warranting a flexible SLI definition and higher error tolerance.

Step-by-Step Solution

1
Analyze business criticality of each workload
Live Video Playback API has immediate revenue impact requiring high availability; Recommendation Generation is asynchronous and tolerates moderate processing delays.
SLOs must reflect the business consequences of downtime or performance degradation.
2
Formulate appropriate SLI measurement windows and metrics
The real-time service uses immediate HTTP success rates, whereas the batch pipeline uses a multi-hour job completion threshold.
SLIs must measure user satisfaction metrics appropriate to the workload type (synchronous API vs asynchronous batch).
3
Establish error budgets aligned with business risk tolerance
Live streaming receives a tighter error budget used to gate deployments, while batch processing receives a looser budget to avoid operational overhead.
Error budgets act as a control mechanism between feature velocity and service reliability.

Key Concept

Aligning Service Level Objectives (SLOs) and Error Budgets with Business Impact
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Aligning Technical Service Level Objectives (SLAs/SLOs/SLIs) with Business Objectives