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

A online gaming enterprise hosts two main workloads on Google Cloud: a synchronous Matchmaking Engine that pairs active players for live multiplayer games, and a Weekly Leaderboard Aggregation Pipeline that asynchronously processes player rankings once every seven days. The business requires high player retention during active gameplay sessions, while leaderboard updates can tolerate execution delays of several hours without affecting customer revenue. Which engineering strategy correctly aligns technical Service Level Objectives (SLOs) and Service Level Indicators (SLIs) with the business impact of these two services?

  1. Define a high-availability SLO (e.g., 99.95%99.95\%) measured via successful request ratio SLI for the Matchmaking Engine, while defining a lower availability and freshness SLO measured via batch completion window SLI for the Leaderboard Pipeline.Answer
  2. B
    Set the target SLO percentage directly as the SLI metric for both services, configuring alerting rules to fire whenever the measured SLI matches the defined SLO target.
  3. C
    Enforce a uniform 99.99%99.99\% availability SLO for both workloads, relying on static CPU utilization alerts to manage system capacity during high-traffic events.
  4. D
    Assign a strict contractual SLA of 99.99%99.99\% availability to the Weekly Leaderboard Pipeline while operating the Matchmaking Engine on a best-effort basis without error budget tracking.

Answer

Establish a high-availability SLO measured via successful request ratio SLI for the Matchmaking Engine, while defining a lower availability and freshness SLO measured via batch completion window SLI for the Leaderboard Pipeline.
Differentiating service level targets based on business impact ensures that critical real-time services (Matchmaking Engine) receive high reliability goals and appropriate success-rate SLIs, while background processing (Leaderboard Pipeline) receives relaxed goals evaluated on completion windows. This optimizes operational effort and cloud spend while protecting user experience.

Step-by-Step Solution

1
Analyze business impact for each service
The Matchmaking Engine directly drives user retention during live gameplay (high business impact), whereas the Leaderboard Pipeline processes data asynchronously with minimal revenue impact during transient delays (low business impact).
SLOs and error budgets must reflect business revenue and user experience impact.
2
Select appropriate Service Level Indicators (SLIs) for each service pattern
The Matchmaking Engine requires a latency/success ratio metric (e.g., successful requests divided by total requests), whereas the Leaderboard Pipeline requires a data freshness or job completion window metric.
Different architectural patterns (synchronous API vs asynchronous batch) require different SLI measurement types.
3
Align Service Level Objectives (SLOs) and error budgets
Assign a strict availability goal (such as 99.95%99.95\%) to the Matchmaking Engine and a more relaxed target to the Leaderboard Pipeline to avoid operational over-engineering.
Over-engineering low-impact services wastes operational budget and engineering effort.

Key Concept

SLO/SLI Alignment with Business Impact
Estimated Time:1m 30s
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Topics

Aligning Technical Service Level Objectives (SLAs/SLOs/SLIs) with Business Objectives