Site Reliability Engineering Training - SRE Certification Visualpath
                     SLIs,,  SLOs,,  and  SLAs  in  Modern  Cloud-Native  Systems  (2025)
Understanding the Role of Service Metrics in Cloud Operations
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Introduction to SLIs, SLOs, and SLAs
 Definition:
o SLI (Service Level Indicator): Quantitative measure of system performance 
(e.g., response time, error rate).
o SLO (Service Level Objective): A target value or range for an SLI (e.g., 
99.9% uptime).
o SLA (Service Level Agreement): A formal contract specifying the SLOs 
between a service provider and customer.
• Purpose: These are critical for monitoring and ensuring reliable service delivery.
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SLIs in Cloud-Native Systems
 SLIs in Cloud Context:
o Track specific metrics like latency, error rates, 
availability, throughput, and resource utilization.
o Examples:
 Request latency in an API.
 5xx errors in microservices.
 Database query response times.
• Tools Used: Prometheus, Datadog, Grafana, 
OpenTelemetry.
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SLOs in Cloud-Native Systems
 SLOs Defined:
o Service level objectives represent desired performance thresholds for SLIs.
o Example: "Service should have an uptime of 99.95% over a month."
 Importance of SLOs in Cloud:
o Align engineering teams with reliability goals.
o Helps prioritize reliability investments (e.g., scaling, failover strategies).
o Should be based on user expectations and experience.
 Example SLOs:
o "API latency < 200ms 99% of the time."
• "95% of transactions are processed successfully."
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SLAs in Cloud-Native Systems
 SLAs Explained:
o Legal agreements between customers and service 
providers.
oDefine penalties or remediation when SLOs are not met.
 In 2025 Cloud Context:
o Frequently associated with cloud providers (e.g., AWS, 
GCP, Azure).
o Incorporates cloud-native architectures like containers, 
microservices, and serverless.
• Importance: Ensures trust and reliability in service contracts.
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Relationship Between SLIs, SLOs, and SLAs
 Diagram: A flowchart or Venn diagram linking SLI, SLO, and SLA:
o SLI is the data you measure.
o SLO is the goal or target for that data.
o SLA is the formalized agreement outlining SLOs and penalties.
 How They Interact in Cloud-Native Systems:
o SLIs provide the data to evaluate if SLOs are being met.
• SLAs formalize expectations with customers, backed by SLOs.
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SLIs, SLOs, and SLAs in Microservices and 
Serverless Environments
 Microservices Impact:
o Each service has its own SLIs and SLOs.
o Communication between services can impact SLIs (e.g., 
inter-service latency).
 Serverless Context:
o SLOs for serverless applications are often related to 
invocation success rates, execution duration, and cold start 
times.
• SLIs must adapt to the stateless, dynamic nature of serverless 
workloads.
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Challenges in Setting SLIs, SLOs, and SLAs
 Challenges:
oDefining Useful SLIs: Ensuring SLIs are aligned with actual user experience and business 
objectives.
o Balancing SLOs: Too aggressive may lead to over-provisioning; too lenient may hurt customer 
satisfaction.
oMonitoring & Observability: Continuous real-time monitoring with tools like Prometheus and 
Grafana to track SLIs.
 Cloud-Specific Considerations:
oDynamically scaling environments can cause fluctuations in SLO compliance.
• Global distributed architectures add complexity to measuring SLIs accurately.
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Best Practices for Implementing SLIs, SLOs, and SLAs in 2025
 Best Practices:
o Define Clear User-Centric SLIs: Focus on metrics that matter to end users 
(e.g., load times, error rates).
o Continuous Measurement & Alerting: Use automated tools for real-time 
monitoring (e.g., Prometheus, New Relic).
o Iterate on SLOs: Review and adjust SLOs based on changing user 
expectations and system performance.
o Maintain Transparency: Communicate failures and improvements with 
stakeholders through well-defined SLAs.
• Cloud-Native Tools: Leverage cloud-native solutions (e.g., Kubernetes, service 
meshes) to automatically track and scale SLIs/SLOs.
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For More Information About 
Site Reliability Engineering
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