Leveraging RUM and Synthetic Monitoring for Robust SLOs
This article explores how combining Real User Monitoring (RUM) and synthetic monitoring is crucial for building comprehensive Service Level Objectives (SLOs). It discusses the strengths and weaknesses of each approach, emphasizing how their combined usage provides a more accurate and actionable view of system performance and user experience in a distributed system context. Understanding these monitoring types is key to defining effective SLIs that reflect both internal system health and external user perception.
Read original on Datadog BlogThe Importance of SLIs and SLOs in System Design
Service Level Indicators (SLIs) and Service Level Objectives (SLOs) are fundamental to modern system design and reliability engineering. SLIs quantify aspects of service reliability (e.g., latency, availability, error rate), while SLOs define the target reliability level for these indicators over a specified period. Without well-defined SLIs and SLOs, it's challenging to gauge system health, prioritize engineering efforts, and communicate service reliability to stakeholders. This article focuses on two primary sources for constructing SLIs: Real User Monitoring (RUM) and synthetic monitoring.
Real User Monitoring (RUM) for User-Centric SLIs
RUM provides insights into the actual experience of end-users by collecting data directly from their browsers or mobile devices. This includes metrics like page load times, front-end errors, and interaction latency. RUM-based SLIs are invaluable because they reflect the true user perception of your service, accounting for factors like network conditions, device types, and browser versions that synthetic tests might miss. For example, an SLI for 'successful page loads' derived from RUM would truly capture what users are experiencing globally.
System Design Implication
When designing a system, especially a user-facing application, ensure that your front-end architecture is instrumented to collect comprehensive RUM data. This data is critical for understanding the 'last mile' performance and user satisfaction, which is often a blind spot for back-end focused metrics. Consider how RUM data will be ingested, stored, and processed by your monitoring system.
Synthetic Monitoring for Proactive and Consistent SLIs
Synthetic monitoring involves scripting automated tests that simulate user interactions from various geographic locations. These tests run periodically against your application's endpoints (web pages, APIs, critical user flows) and provide consistent, controlled measurements of availability and performance. Unlike RUM, synthetic monitoring allows you to detect issues proactively, even before real users are impacted, and to test new features in pre-production environments. It's excellent for establishing a baseline performance against a known set of conditions.
- Consistency: Provides repeatable measurements from known locations.
- Proactiveness: Identifies issues before they affect real users.
- Coverage: Can test critical paths regardless of current user traffic.
- Baseline: Establishes performance benchmarks under controlled conditions.
Combining RUM and Synthetic for Holistic SLOs
The article stresses that neither RUM nor synthetic monitoring alone provides a complete picture. RUM captures the 'what' and 'how' of real user experience, while synthetic monitoring captures the 'if' and 'when' of service availability and performance under ideal conditions. A robust SLO strategy integrates both: synthetic tests validate that the core service functions as expected from various points of presence, while RUM confirms that actual users are indeed having a good experience, identifying regional or device-specific issues. Architecturally, this means designing a monitoring system that can ingest, correlate, and visualize data from both sources to provide a unified view of service health.
Example SLO using both
An SLO could state: "99.9% of user-initiated login requests (RUM) must complete within 2 seconds, AND 100% of synthetic login checks (Synthetic) from primary regions must succeed within 1 second, both measured over a 7-day rolling window." This combines the real user experience with proactive system health checks.