20 Service Level Agreement Examples to Track Your Service Management Metrics

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To be honest, most teams have “had SLAs” for a long time.
But when it comes to actually measuring them – that’s when the surprises begin:

… some SLAs only calculate correctly in “ideal conditions,”
… others stop or start at the wrong moment,
… some metrics simply can’t be built in native JSM,
… and certain processes look clean on a diagram but not in real tickets.

As a result, many SLAs exist more as intentions than as functional metrics.

That’s why we’ve collected 20 of the most practical SLA examples – the ones teams genuinely use to control service quality every day, from incident response to preventive operations and customer satisfaction.

In this article, you’ll find:

• clear metric names
• concrete, realistic goals
• explanations of why each metric matters
• hints on when native JSM capabilities are enough
• and how to cover complex scenarios using SLA Time and Report when JSM falls short

These examples will help you not just “set up SLAs,” but make them actually work in Jira and improve your team’s effectiveness.

Category 1: Incident Management & Response

The primary focus here is the speed of response and the restoration of critical services.

No.	SLA Focus	Metric Goals (Example)	Why It Matters
1	First Response Time	90% of high-priority incidents (P1/P2) – within 15 minutes.	This minimizes user anxiety and guarantees that the incident has been acknowledged and is in progress.
2	Resolution Time	Critical (Priority 1) incidents – resolved within 4 hours.	Directly impacts business continuity and minimizes downtime.
3	Major Incident Restore	Time to Restore Service (TSR) – 99.5% within 1 hour.	A key indicator for ensuring the uninterrupted operation of the most critical assets.
4	Initial Triage Time	Priority and group assignment – 100% within 5 minutes.	Ensures every ticket is quickly routed correctly and assigned the appropriate priority.
5	Status Update Interval	Status updates for P1/P2 incidents – every 30 minutes.	Maintains transparency for the business and prevents unnecessary calls/status requests.

Category 2: Request Fulfillment

This category measures the efficiency and speed of delivering standard services.

No.	SLA Focus	Metric Goals (Example)	Why It Matters
6	New Hardware Provision	Delivery and setup of a standard workstation – 3 business days.	Critical for rapid onboarding of new employees.
7	Password/Access Reset	100% of password reset requests – completed within 5 minutes.	Eliminates minimal but frequent roadblocks for users.
8	Standard Change Fulfillment	Implementation of approved standard changes (e.g., software updates) – 1 business day.	Ensures controlled and rapid change management.
9	System Access Grant	New system access – 4 hours after approval.	Adherence to security policy and prompt granting of working rights.
10	Customer Acceptance Time	Customer confirmation of service received – 2 business days.	Ensures the service was successfully delivered and accepted, avoiding disputes.

Category 3: External and Internal Support

Metrics measuring the quality and coherence of different support levels.

No.	SLA Focus	Metric Goals (Example)	Why It Matters
11	L2 Escalation Time	Transfer of an incident from L1 to L2 – within 2 hours.	Guarantees that time is not wasted at L1 if higher-level expertise is required.
12	Reopened Request Rate	Number of reopened requests – less than 5% of the total volume.	An indicator of the quality and completeness of the initial problem resolution.
13	KB Article Creation Time	Documentation of recurring incidents (more than 3 times per month) – 5 business days.	Reduces future workload through self-service enablement.
14	Customer Satisfaction (CSAT/NPS Follow-up)	Response to negative feedback (CSAT < 3) – within 1 business hour.	Rapid recovery of relationships with dissatisfied customers and collection of critical feedback.
15	Non-Technical Resolution	Resolution of HR or financial support requests – 24 hours.	Adherence to internal business processes, particularly for the back office.

Category 4: Proactive Management and Data Quality

These metrics focus on problem prevention and ensuring reliable analysis.

No.	SLA Focus	Metric Goals (Example)	Why It Matters
16	Proactive Check Cycle	Weekly availability checks of critical services – 100% completed.	The best way to prevent incidents before they impact users.
17	Mandatory Field Completion	98% of critical fields (CI, Resolution Reason) – completed upon ticket closure.	Ensures data quality for accurate analysis and subsequent Problem Management.
18	Change Approval Time	Approval of standard/medium changes – within 4 business hours.	Minimizes delays in change deployment and supports business speed.
19	Preventive Maintenance	Completion of planned updates/patches – by the end of the month.	Maintains system security and performance at the required level.
20	Awaiting Customer Confirmation	Time awaiting customer confirmation before closure – 5 business days.	Allows the team to control the period before a ticket can be forcefully closed if the customer is unresponsive.

🔍 Why some SLAs are difficult or impossible to build in JSM. The Role of "SLA Time and Report"

Native Jira Service Management SLA is powerful, but limited. Teams often hit problems such as:

❌ No multi-condition Start/Stop logic

For example:
“Start when customer comments OR when priority changes.”

❌ No SLA reset

If a ticket is escalated, SLA doesn’t restart.

❌ No way to track time spent only in specific statuses

Especially if statuses repeat (In Progress → Blocked → In Progress).

❌ No interval-based SLA

E.g., “Update status every 30 minutes.”

❌ Reports show outcomes, not causes

You can see breaches, but not why they happened.

This is where SLA become “documentation only,” not a measurable control.

⭐ How SLA Time and Report Solves These Issues

The app was built specifically to measure complex SLA logic that JSM cannot handle natively – ensuring accuracy, flexibility, and full visibility.

🧩 1. Flexible Start, Stop, Pause, and Reset Conditions

Real workflows rarely follow a simple “start here, stop there” pattern. Many processes depend on multiple events, exceptions, or team-specific rules.
SLA Time and Report allows teams to define precise conditions for when an SLA should start, stop, pause, or reset – even if this logic depends on several factors at once.

This includes:

• combined status-based or comment-based conditions
• field-driven triggers
• logic using AND/OR combinations
• automatic SLA reset when the context changes (e.g., escalation, reassignment)
• custom calendars, which let you calculate time differently for various teams, regions, or service hours

For example, Initial Triage Time (SLA #4) can start at issue creation, pause during customer waiting, stop only when both the priority and assignee are set, and reset when the ticket moves to another queue.

Such configurations reflect real processes, not simplified workflows constrained by native JSM.

⚡ 2. Automations Based on SLA Events

When an SLA approaches a breach or finishes outside the target, teams need immediate actions – not periodic checks.
With SLA Time and Report, every SLA event can trigger a workflow action.

This can include status transitions, reassignment, reminders in comments, Slack notifications, etc.

For example, if a ticket hasn’t been updated within the required interval, the system can automatically add a reminder comment – ensuring timely follow-ups without manual monitoring.

📊 3. Detailed Reporting and Time-in-Status Insight

Understanding why SLA was met or breached often requires more than just the final timer.
SLA Time and Report provides detailed analytics that break down time spent in each status, highlight delays, and show patterns across teams, priorities, service, or other custom fields.

This helps pinpoint bottlenecks, recurring issues, or process steps that require optimization – insights that native JSM SLA reports are not designed to provide.

📈 4. SLA Dashboards in Jira

SLA performance becomes far more actionable when visualized directly inside Jira.
SLA Time and Report supports dashboard charts that teams can review daily, not only during monthly analysis.

Available visualizations include Met vs Exceeded  (by priority, team, service, etc.) and SLA per Criteria, helping teams quickly identify risks, workload spikes, or process trends that need attention.

🛡 5. Consistent and Reliable SLA Tracking

Ticket workflows often involve repeated statuses, quick transitions, and exceptions that native JSM may miscalculate.
SLA Time and Report ensures accuracy by capturing every relevant event reliably, handling repeated statuses correctly, and applying SLA rules consistently rather than relying on fragile JQL logic.

This results in stable, predictable SLA measurements – even in complex, high-variability workflows.

Bottom line ✅ 

These 20 SLAs represent the real processes modern service teams rely on:
incident response, request fulfillment, escalations, customer satisfaction, data quality, and proactive maintenance.

But the key takeaway is simple:

SLAs only work if they are measured accurately.

Jira Service Management covers basic cases well, but many essential SLA depend on multi-condition logic, resets, status-specific timers, or detailed reporting that JSM cannot provide on its own.

That’s where tools like SLA Time and Report for Jira become essential.

[Elena_Communardo Products]

Hi @Alina Kurinna _SaaSJet_ Great breakdown. It’s a good reminder that SLAs only add value when they’re measurable in real workflows—not just documented. The practical examples here make a huge difference.

[Alina Kurinna _SaaSJet_]

Thank you so much @Elena_Communardo Products ! 🙌
Really glad you found the breakdown helpful! My goal was to show how SLA metrics can become practical, everyday tools for teams, not just formal definitions, so I’m happy to hear the examples resonated.