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What is SRE?
Site reliability engineering (SRE) applies engineering methods to operating and improving services. Rather than treating reliability as an abstract goal, a team defines what acceptable service looks like for users, measures it, and uses that evidence to guide operational work and changes.
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Google’s SRE Workbook presents service-level objectives (SLOs), monitoring, alerting, toil reduction, and simplicity as foundational practices. These are practices teams can adopt; they do not imply that every organization needs a dedicated SRE team or a particular organizational structure.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesHow do SLOs make reliability concrete?
A service-level indicator (SLI) is a measurement of an aspect of service behavior that matters to users. A service-level objective (SLO) sets a target for that indicator over a defined period. The useful SLI and target depend on the service and its users; there is no universal uptime percentage that fits every team.
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For example, a team might measure whether requests succeed or how quickly users receive responses. The SLO makes the intended service level explicit, so the team can assess reliability and make tradeoffs with clearer context. Google’s SRE resource library includes dedicated chapters on implementing SLOs and alerting on SLOs.
What should a monitoring system help you do?
Monitoring should support decisions and investigation, not just populate dashboards. The Google SRE Workbook describes monitoring as a way to see system health and diagnose problems. Useful monitoring helps a team:
- Notice conditions that require attention.
- Investigate and diagnose service problems.
- Visualize system behavior and spot longer-term trends.
- Compare behavior before and after a change or experiment.
Metrics and structured logs are useful for fundamental monitoring needs. Text logs, event logs, distributed tracing, and event introspection can also provide valuable context. The right mix depends on what the team needs to see and how quickly it needs to see it.
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A single system may cover a team’s needs, or the team may combine tools. The Workbook emphasizes considerations such as data freshness and retrieval speed. The following additional questions are a practical decision framework, not a formal Google scoring rubric:
- Freshness and speed: Does data arrive quickly enough to alert responders and assess whether a mitigation worked?
- Coverage: Does monitoring reflect user-facing health as well as relevant system components?
- Diagnostic value: Can responders move from a symptom toward likely causes using available metrics, logs, traces, and context?
- Operational fit: Can the team maintain the system and fit it into its services and workflows?
- Cost and complexity: Is the added detail worth the resources and maintenance it requires?
How should SRE teams design alerts?
Alert on conditions that need attention, and connect those alerts to service impact where possible. An alert should give a responder a useful starting point for understanding what is wrong and investigating it. More alerts do not automatically mean better reliability: alerts that do not prompt meaningful action can add noise without helping users.
Using an SLO to inform alerting helps connect signals to the service level the team is trying to provide. Google’s SRE resource library includes a dedicated chapter on alerting on SLOs, alongside its material on implementing SLOs.
What is toil, and how can a team reduce it?
Toil is repetitive, predictable operational work that consumes time without creating a durable improvement to the service. Examples vary by team; the important step is to identify recurring work and measure its cost instead of relying only on intuition.
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Best Value
Prioritize toil reduction by value
Compare the effort and cost of fixing a toil source with the operational time the fix is expected to save. SLOs can also help teams decide which work matters most to reliability. Google’s stated policy in the 2018 SRE Workbook is to limit SRE team time spent on operational work—including both toil and non-toil operational work—to 50%. This describes Google’s practice in that publication context, not a universal target for other teams.
Automate complex workflows in stages
Some operational requests are too variable to automate safely at once. For complex workflows, begin with structured requests and human review. That creates a clearer record of what people need and how requests are handled. Once patterns are stable and the domain is better understood, automate the repeatable parts and make common requests self-service where appropriate.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can a team get started with SRE?
Use a small, service-focused sequence. The steps below synthesize the Workbook’s guidance; they are not a verbatim Google checklist.
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Quick Recap
- Choose one service. Agree on a reliability objective that reflects what users need from it.
- Identify the signals. Decide what measurements show whether the objective is being met and what additional data will help diagnose failures.
- Review alerts and data freshness. Check whether alerts lead to useful action and whether data arrives quickly enough for response.
- Record recurring operational work. Track what tasks recur and how much time they consume.
- Pick a high-value toil source. Compare the expected time saved with the cost of remediation, and remove the underlying cause where possible.
- Automate stable patterns carefully. For complex workflows, start with structured requests and human review; automate repeatable steps as the process becomes clear.
- Revisit the objective and workload. Reassess them after meaningful service or product changes.
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