Service Level Objectives (SLOs) have emerged as a crucial tool for ensuring reliability providing a framework to measure and maintain service quality. In this comprehensive guide, seasoned Senior Site Reliability Engineer, Danny Mican, shares insights on implementing SLOs effectively using the IIDARR process. He stresses the vital need for actionable SLOs, consistently applying a feedback approach, crucial in navigating the Features vs. Technical Debt debate.
Table of Contents:
Implementing SLOs From Scratch With the IIDARR Process
Using SLOs Throughout the Product Life Cycle
The IIDARR Rule-of-Thumb for SLO Implementation
Things to Keep in Mind During Implementation
Approach
Identify (Service Level Indicator)
Instrument
Define (Service Level Objective)
Alert (Actionable Objectives)
Report/Refine (Revist Objective)
The Customer
Myths and Anti-patterns That You Can Avoid
Conclusion
Implementing SLOs From Scratch With the IIDARR Process
Incorporating Service Level Objectives (SLOs) seamlessly into your organization's operations is a critical task that demands collaboration across various business units. Ensuring buy-in from Product, Engineering, and Site Reliability is essential to avoid partial SLO implementation, which can lead to suboptimal returns on investment and, in some cases, outright failure. This article outlines a structured process, following the IIDARR (Identify, Instrument, Define, Alert, Report/Refine) framework, to guide organizations in scaling the adoption of Service Level Objectives.
Utilizing SLOs Throughout the Product Life Cycle
While many resources focus on the technical aspects of selecting Service Level Indicators (SLIs) and formulating and measuring objectives, few delve into the strategies for integrating SLOs into everyday operations and decision-making processes. Establishing an organizational process that spans the entire product lifecycle is crucial for successfully implementing SLOs and incorporating them into regular operations.
The ultimate goal is to create a streamlined process that enables teams to gain accurate insights into their customers' experiences. This, in turn, empowers teams to identify and address issues proactively, ensuring a seamless service for customers. Additionally, organizations can leverage historical performance data to make informed decisions on prioritizing technical debt versus feature velocity.
The IIDARR Rule-of-Thumb for SLO Implementation
The IIDARR process comprises distinct phases essential for successful SLO implementation:
Identify: Determine the operations and flows crucial to supporting customers, resulting in Service Level Indicator definitions.
Instrument (Measure): Capture data from identified operations to generate concrete, queryable metrics.
Define: Quantify and simplify the customer experience by expressing it as a written Service Level Objective.
Alert (Action): Enforce SLOs through automated detection, linking customers, engineering, and product teams. The alerting phase creates a tangible link between customers, engineering, and product teams, fostering a responsive connection. During this stage, an alert is generated within dedicated alerting systems like Prometheus, Datadog, among others, and integrated into an incident management system designed to promptly notify the relevant teams.
Report/Refine: Reporting offers insights into performance trends on a weekly, monthly, and quarterly basis, fostering a comprehensive understanding of historical data. This systematic record-keeping empowers organizations to assess the actual level of service delivered to clients.
Refining institutes a structured routine for conducting reviews, facilitating continuous improvement. This process aids in comprehending clients' utilization of the product, identifying significant transactions, and evaluating the attained level of service.
Succeeding with Service Level Objectives necessitates the ability to reflect on historical data for service performance enhancements. Reporting democratizes SLOs, making them accessible to incident responders, management, and leadership teams.
The initial adoption of Service Level Objectives (SLOs) is enhanced by consolidating the implementation within a single resource or tool:
6. Inventory - Monitoring progress is crucial for obtaining a comprehensive overview of SLOs across teams and projects. It facilitates a clear understanding of the implementation status of all available SLOs. During the initial deployment of SLOs across teams, inventorying proves beneficial in providing a holistic perspective of the rollout. Centralized inventorying is recommended until teams are proficient with the process and each team has fully integrated an SLO into their workflow. Even as teams transition to autonomous management of their SLOs, maintaining a centralized and searchable repository of all SLOs, categorized by team, service, and Service Level Indicator type, remains invaluable.
Refining establishes a formal cadence for performing a review in order to support continuous improvement and understand clients use of the product (i.e. which transactions are important) and the level of service is being achieved.
Succeeding with SLOs requires the ability to both: look back historically and find avenues for service performance improvements. Finally, Reporting democratizes SLOs and makes them available for incident responders, management, and leadership teams.
Things to Keep in Mind During Implementation
All elements of the IIDARR process are interconnected, forming a cohesive framework. Treating them as standalone steps risks partial implementation and potential failure.
Identify: Service Level Indicator (SLI)
The first crucial step is to identify the Service Level Indicators (SLIs) that will serve as the foundation for your objectives. These SLIs, as defined by Google, are key service operations selected based on their importance. This process revolves around understanding which operations require measurement to gauge their significance.
In many instances, teams often rely on intuition to designate essential operations for their services. However, this approach may lack comprehensive information about the service itself. To address this, certain heuristics can be employed to establish the importance of operations, such as:
The operation's revenue-generating potential.
The operation with the highest traffic.
A "coarse" grained Service Level Indicator based on overall service traffic.
For instance, in an authentication company, an operation irregularly fetching a user profile may be less critical than a transaction authenticating a user called hundreds of times per second.
The outcome of this identification process should be a prioritized list of significant operations performed by a service. It's crucial to note that many operations may span multiple individual HTTP endpoints. Google provides in-depth strategies for identifying SLIs in their recent Art of SLOs course.
This stage results in a comprehensive written entry that includes details such as:
What is being measured?
The Type (Availability/Latency)?
Specification?
How it is being measured?
From where it is being measured?
For a practical illustration of these concepts, you can refer to the Art of SLOs Google Course under the "Developing SLOs and SLIs" section, providing a tangible example to guide your understanding of this critical identification process.
Instrument
Following the identification of Service Level Indicators (SLIs), the next crucial step in implementing Service Level Objectives (SLOs) is acquiring the necessary data. This involves determining the logical level of data collection and establishing instrumentation processes for transaction recording. Choosing a system for data storage is pivotal, requiring support for self-service and alerting to ensure scalable SLOs.
The logical strategy for data collection is outlined during the identification phase. Many established organizations have predefined metrics providers. After defining the metric store, the next step is active data collection, achieved through White Box or Black Box Monitoring—technology or provider-specific processes. Even without emitted metrics, request data is accessible at the load balancer or queue level, particularly in cloud provider environments.
By strategically addressing these components, organizations set the groundwork for successful SLO implementation, ensuring acquired data is structured for effective SLO management and scalability.
Define (Service Level Objective)
Google extensively covers target selection, emphasizing the importance of favoring gradual refinement over seeking a "perfect" initial value.
A practical heuristic involves examining historical performance and selecting a target consistently achievable over the interval defined in the Identify stage (typically 7, 14, or 30 days). Consultation with a monitoring system allows for a simple average of the target value, serving as the initial objective.
For instance, if the average latency over the last week or month was 200ms, this becomes the starting point. In cases with no historical data, a reasonable guess aligned with desired customer experience can guide the initial value selection. This value, whether derived from implicit or explicit constraints, can be effortlessly refined after data collection.
This stage enhances the text generated during the Identify step, incorporating the formalized Service Level Objective (SLO) to ensure a strategic and actionable approach to target definition.
Service Level Objective Examples
Consider the scenario where an eCommerce platform sets an SLO for order processing time. The Service Level Objective example entails maintaining this metric under 500 milliseconds, ensuring swift and efficient processing.
Service Level Objective Examples:
Metric: Order Processing Time
Threshold: <500 milliseconds
A cloud storage service may define an SLO for Availability, specifying a robust 99.9% uptime over a 30-day period.
Service Level Objective Examples:
Type: Availability
Specification: 99.9% uptime
Interval: 30 days
In a Content Delivery Network (CDN), the Service Level Objective example might be based on response time measured at the edge servers.
Service Level Objective Example:
Measurement Location: Edge Servers
Applying the SLO concept to a video streaming service, an SLO could target a video buffering rate below 2%, ensuring a seamless user experience.
Service Level Objective Examples:
Metric: Video Buffering Rate
Threshold: <2%
Alert (Actionable Objectives)
Alerting plays a crucial role in keeping objectives "living" by providing real-time notifications to engineers when their budgets are nearing exhaustion.
Adopting a structured and generic alerting approach allows the development of default tooling and policies, transforming alerting into a streamlined and generic formula when accurately expressing a customer's experience in SLO terms.
The recommended strategy, known as Multiple Burn Rate Alerts and detailed in Google's SRE workbook, advocates for each SLO having at least two alerts:
Active Alert: Triggered when 2% of the budget is exhausted in 1 hour.
Passive Log: Triggered when 10% of the budget is exhausted in 1 day.
This straightforward strategy ensures effective alerting, with templated math that is easy to calculate, as outlined in detail in the SRE Workbook. This stage results in the implementation of two dynamic alerts, fortifying the SLO framework with real-time notifications and proactive management capabilities.
Achieving success with Service Level Objectives (SLOs) necessitates:
Historic SLO Data: A repository of historical SLO data is crucial.
Periodic Data Revisits: Regular reviews of this data are essential.
It's imperative to consistently assess SLO performance, with the frequency ideally aligning with organizational iteration intervals (sprints, weeks, etc.). The closer this interval, the more informed the decision-making process becomes, guiding choices between bolstering reliability or focusing on feature development.
This stage empowers SLOs to serve as valuable tools for risk assessment, availability comparison between services, and guiding future work along two strategic poles:
Risk Aversion, Shore up Reliability, Tech Debt:
Prioritize reliability enhancements.
Address technical debt to fortify system robustness.
Feature Velocity, Constant Deploys, New Features:
Focus on rapid feature deployment.
Continuously introduce new features to enhance product offerings.
The decision-making process, balancing feature velocity and technical debt, is a pivotal outcome of SLO implementation. This stage serves as the foundation for informed choices, aligning Service Level Objectives with organizational goals and strategies.
Within the IIDARR system, each element is intricately connected to the customer, fostering a profound understanding of their perspective. The elements are strategically aligned as follows:
Identify:
Selects operations crucial to the customer's experience.
Instrumentation:
Designed to capture the customer experience.
Explicitly identifies gaps in any instrumentation strategy.
Define (SLO):
Directly represents customers making requests.
This process aims to establish a system capable of alerting on incidents directly linked to the customer experience. Serving as a stepping stone, this approach aims to quantify and measure customer experience, rendering the entire process highly actionable. By anchoring each stage to the customer, the IIDARR system ensures a customer-centric focus throughout, aligning operations with real customer needs and enhancing the overall effectiveness of the Service Level Objective framework.
Myths and Anti-patterns That You Can Avoid
In the journey towards successful adoption of Service Level Objectives (SLOs), organizations should be mindful of common myths and anti-patterns that may hinder widespread integration across teams:
Reliance on Hope:
Adopting SLOs necessitates a strategic approach beyond ad-hoc methods.
Following the principle that "Hope is not a strategy" (Ben Treynor).
SRE "Does" SLOs for Teams:
SLOs intimately link customer experience with individual service performance.
It's imperative for individual product teams to independently deploy their SLOs.
Static SLOs:
SLOs are inherently iterative and dynamic.
Continuous improvement is hindered if data is collected without introducing feedback loops.
Lack of Automated Enforcement in Feedback Loops:
Opt-in or best-effort feedback loops can result in teams falling out of sync.
Teams must actively participate in Reporting/Refining and alerting on their SLOs, crucial communication points aligning customer, product, and engineering perspectives.
By navigating these potential pitfalls, organizations can foster a more effective and collaborative SLO adoption process, ensuring alignment with customer expectations and promoting a culture of continuous improvement.
Conclusion
In the pursuit of Service Level Objective (SLO) success, the primary hurdles aren't purely technical. SLOs, while not magical, demand a clear, explicit process with a focus on feedback loops for scalable adoption. Initiating SLOs becomes more manageable when the importance of this endeavor is well-understood.
It's crucial to recognize that SLOs should be actionable, following a continuous feedback approach, playing a pivotal role in the perpetual debate between Features and Technical Debt prioritization. Emphasizing clarity, explicit processes, and the intrinsic value of feedback loops sets the stage for a successful and sustainable SLO journey.
In this blog, Danny Mican, a Senior Site Reliability Engineer, outlines how to implement SLOs from scratch using the IIDARR process. He also states it is extremely crucial for your SLOs to be actionable and is always following a feedback approach as it will play an important role in the debate of Features Vs Technical Debt.
Table of Contents:
Service Level Objectives (SLOs) have emerged as a crucial tool for ensuring reliability providing a framework to measure and maintain service quality. In this comprehensive guide, seasoned Senior Site Reliability Engineer, Danny Mican, shares insights on implementing SLOs effectively using the IIDARR process. He stresses the vital need for actionable SLOs, consistently applying a feedback approach, crucial in navigating the Features vs. Technical Debt debate.
Table of Contents:
Implementing SLOs From Scratch With the IIDARR Process
Using SLOs Throughout the Product Life Cycle
The IIDARR Rule-of-Thumb for SLO Implementation
Things to Keep in Mind During Implementation
Approach
Identify (Service Level Indicator)
Instrument
Define (Service Level Objective)
Alert (Actionable Objectives)
Report/Refine (Revist Objective)
The Customer
Myths and Anti-patterns That You Can Avoid
Conclusion
Implementing SLOs From Scratch With the IIDARR Process
Incorporating Service Level Objectives (SLOs) seamlessly into your organization's operations is a critical task that demands collaboration across various business units. Ensuring buy-in from Product, Engineering, and Site Reliability is essential to avoid partial SLO implementation, which can lead to suboptimal returns on investment and, in some cases, outright failure. This article outlines a structured process, following the IIDARR (Identify, Instrument, Define, Alert, Report/Refine) framework, to guide organizations in scaling the adoption of Service Level Objectives.
Utilizing SLOs Throughout the Product Life Cycle
While many resources focus on the technical aspects of selecting Service Level Indicators (SLIs) and formulating and measuring objectives, few delve into the strategies for integrating SLOs into everyday operations and decision-making processes. Establishing an organizational process that spans the entire product lifecycle is crucial for successfully implementing SLOs and incorporating them into regular operations.
The ultimate goal is to create a streamlined process that enables teams to gain accurate insights into their customers' experiences. This, in turn, empowers teams to identify and address issues proactively, ensuring a seamless service for customers. Additionally, organizations can leverage historical performance data to make informed decisions on prioritizing technical debt versus feature velocity.
The IIDARR Rule-of-Thumb for SLO Implementation
The IIDARR process comprises distinct phases essential for successful SLO implementation:
Identify: Determine the operations and flows crucial to supporting customers, resulting in Service Level Indicator definitions.
Instrument (Measure): Capture data from identified operations to generate concrete, queryable metrics.
Define: Quantify and simplify the customer experience by expressing it as a written Service Level Objective.
Alert (Action): Enforce SLOs through automated detection, linking customers, engineering, and product teams. The alerting phase creates a tangible link between customers, engineering, and product teams, fostering a responsive connection. During this stage, an alert is generated within dedicated alerting systems like Prometheus, Datadog, among others, and integrated into an incident management system designed to promptly notify the relevant teams.
Report/Refine: Reporting offers insights into performance trends on a weekly, monthly, and quarterly basis, fostering a comprehensive understanding of historical data. This systematic record-keeping empowers organizations to assess the actual level of service delivered to clients.
Refining institutes a structured routine for conducting reviews, facilitating continuous improvement. This process aids in comprehending clients' utilization of the product, identifying significant transactions, and evaluating the attained level of service.
Succeeding with Service Level Objectives necessitates the ability to reflect on historical data for service performance enhancements. Reporting democratizes SLOs, making them accessible to incident responders, management, and leadership teams.
The initial adoption of Service Level Objectives (SLOs) is enhanced by consolidating the implementation within a single resource or tool:
6. Inventory - Monitoring progress is crucial for obtaining a comprehensive overview of SLOs across teams and projects. It facilitates a clear understanding of the implementation status of all available SLOs. During the initial deployment of SLOs across teams, inventorying proves beneficial in providing a holistic perspective of the rollout. Centralized inventorying is recommended until teams are proficient with the process and each team has fully integrated an SLO into their workflow. Even as teams transition to autonomous management of their SLOs, maintaining a centralized and searchable repository of all SLOs, categorized by team, service, and Service Level Indicator type, remains invaluable.
Refining establishes a formal cadence for performing a review in order to support continuous improvement and understand clients use of the product (i.e. which transactions are important) and the level of service is being achieved.
Succeeding with SLOs requires the ability to both: look back historically and find avenues for service performance improvements. Finally, Reporting democratizes SLOs and makes them available for incident responders, management, and leadership teams.
Things to Keep in Mind During Implementation
All elements of the IIDARR process are interconnected, forming a cohesive framework. Treating them as standalone steps risks partial implementation and potential failure.
Identify: Service Level Indicator (SLI)
The first crucial step is to identify the Service Level Indicators (SLIs) that will serve as the foundation for your objectives. These SLIs, as defined by Google, are key service operations selected based on their importance. This process revolves around understanding which operations require measurement to gauge their significance.
In many instances, teams often rely on intuition to designate essential operations for their services. However, this approach may lack comprehensive information about the service itself. To address this, certain heuristics can be employed to establish the importance of operations, such as:
The operation's revenue-generating potential.
The operation with the highest traffic.
A "coarse" grained Service Level Indicator based on overall service traffic.
For instance, in an authentication company, an operation irregularly fetching a user profile may be less critical than a transaction authenticating a user called hundreds of times per second.
The outcome of this identification process should be a prioritized list of significant operations performed by a service. It's crucial to note that many operations may span multiple individual HTTP endpoints. Google provides in-depth strategies for identifying SLIs in their recent Art of SLOs course.
This stage results in a comprehensive written entry that includes details such as:
What is being measured?
The Type (Availability/Latency)?
Specification?
How it is being measured?
From where it is being measured?
For a practical illustration of these concepts, you can refer to the Art of SLOs Google Course under the "Developing SLOs and SLIs" section, providing a tangible example to guide your understanding of this critical identification process.
Instrument
Following the identification of Service Level Indicators (SLIs), the next crucial step in implementing Service Level Objectives (SLOs) is acquiring the necessary data. This involves determining the logical level of data collection and establishing instrumentation processes for transaction recording. Choosing a system for data storage is pivotal, requiring support for self-service and alerting to ensure scalable SLOs.
The logical strategy for data collection is outlined during the identification phase. Many established organizations have predefined metrics providers. After defining the metric store, the next step is active data collection, achieved through White Box or Black Box Monitoring—technology or provider-specific processes. Even without emitted metrics, request data is accessible at the load balancer or queue level, particularly in cloud provider environments.
By strategically addressing these components, organizations set the groundwork for successful SLO implementation, ensuring acquired data is structured for effective SLO management and scalability.
Define (Service Level Objective)
Google extensively covers target selection, emphasizing the importance of favoring gradual refinement over seeking a "perfect" initial value.
A practical heuristic involves examining historical performance and selecting a target consistently achievable over the interval defined in the Identify stage (typically 7, 14, or 30 days). Consultation with a monitoring system allows for a simple average of the target value, serving as the initial objective.
For instance, if the average latency over the last week or month was 200ms, this becomes the starting point. In cases with no historical data, a reasonable guess aligned with desired customer experience can guide the initial value selection. This value, whether derived from implicit or explicit constraints, can be effortlessly refined after data collection.
This stage enhances the text generated during the Identify step, incorporating the formalized Service Level Objective (SLO) to ensure a strategic and actionable approach to target definition.
Service Level Objective Examples
Consider the scenario where an eCommerce platform sets an SLO for order processing time. The Service Level Objective example entails maintaining this metric under 500 milliseconds, ensuring swift and efficient processing.
Service Level Objective Examples:
Metric: Order Processing Time
Threshold: <500 milliseconds
A cloud storage service may define an SLO for Availability, specifying a robust 99.9% uptime over a 30-day period.
Service Level Objective Examples:
Type: Availability
Specification: 99.9% uptime
Interval: 30 days
In a Content Delivery Network (CDN), the Service Level Objective example might be based on response time measured at the edge servers.
Service Level Objective Example:
Measurement Location: Edge Servers
Applying the SLO concept to a video streaming service, an SLO could target a video buffering rate below 2%, ensuring a seamless user experience.
Service Level Objective Examples:
Metric: Video Buffering Rate
Threshold: <2%
Alert (Actionable Objectives)
Alerting plays a crucial role in keeping objectives "living" by providing real-time notifications to engineers when their budgets are nearing exhaustion.
Adopting a structured and generic alerting approach allows the development of default tooling and policies, transforming alerting into a streamlined and generic formula when accurately expressing a customer's experience in SLO terms.
The recommended strategy, known as Multiple Burn Rate Alerts and detailed in Google's SRE workbook, advocates for each SLO having at least two alerts:
Active Alert: Triggered when 2% of the budget is exhausted in 1 hour.
Passive Log: Triggered when 10% of the budget is exhausted in 1 day.
This straightforward strategy ensures effective alerting, with templated math that is easy to calculate, as outlined in detail in the SRE Workbook. This stage results in the implementation of two dynamic alerts, fortifying the SLO framework with real-time notifications and proactive management capabilities.
Achieving success with Service Level Objectives (SLOs) necessitates:
Historic SLO Data: A repository of historical SLO data is crucial.
Periodic Data Revisits: Regular reviews of this data are essential.
It's imperative to consistently assess SLO performance, with the frequency ideally aligning with organizational iteration intervals (sprints, weeks, etc.). The closer this interval, the more informed the decision-making process becomes, guiding choices between bolstering reliability or focusing on feature development.
This stage empowers SLOs to serve as valuable tools for risk assessment, availability comparison between services, and guiding future work along two strategic poles:
Risk Aversion, Shore up Reliability, Tech Debt:
Prioritize reliability enhancements.
Address technical debt to fortify system robustness.
Feature Velocity, Constant Deploys, New Features:
Focus on rapid feature deployment.
Continuously introduce new features to enhance product offerings.
The decision-making process, balancing feature velocity and technical debt, is a pivotal outcome of SLO implementation. This stage serves as the foundation for informed choices, aligning Service Level Objectives with organizational goals and strategies.
Within the IIDARR system, each element is intricately connected to the customer, fostering a profound understanding of their perspective. The elements are strategically aligned as follows:
Identify:
Selects operations crucial to the customer's experience.
Instrumentation:
Designed to capture the customer experience.
Explicitly identifies gaps in any instrumentation strategy.
Define (SLO):
Directly represents customers making requests.
This process aims to establish a system capable of alerting on incidents directly linked to the customer experience. Serving as a stepping stone, this approach aims to quantify and measure customer experience, rendering the entire process highly actionable. By anchoring each stage to the customer, the IIDARR system ensures a customer-centric focus throughout, aligning operations with real customer needs and enhancing the overall effectiveness of the Service Level Objective framework.
Myths and Anti-patterns That You Can Avoid
In the journey towards successful adoption of Service Level Objectives (SLOs), organizations should be mindful of common myths and anti-patterns that may hinder widespread integration across teams:
Reliance on Hope:
Adopting SLOs necessitates a strategic approach beyond ad-hoc methods.
Following the principle that "Hope is not a strategy" (Ben Treynor).
SRE "Does" SLOs for Teams:
SLOs intimately link customer experience with individual service performance.
It's imperative for individual product teams to independently deploy their SLOs.
Static SLOs:
SLOs are inherently iterative and dynamic.
Continuous improvement is hindered if data is collected without introducing feedback loops.
Lack of Automated Enforcement in Feedback Loops:
Opt-in or best-effort feedback loops can result in teams falling out of sync.
Teams must actively participate in Reporting/Refining and alerting on their SLOs, crucial communication points aligning customer, product, and engineering perspectives.
By navigating these potential pitfalls, organizations can foster a more effective and collaborative SLO adoption process, ensuring alignment with customer expectations and promoting a culture of continuous improvement.
Conclusion
In the pursuit of Service Level Objective (SLO) success, the primary hurdles aren't purely technical. SLOs, while not magical, demand a clear, explicit process with a focus on feedback loops for scalable adoption. Initiating SLOs becomes more manageable when the importance of this endeavor is well-understood.
It's crucial to recognize that SLOs should be actionable, following a continuous feedback approach, playing a pivotal role in the perpetual debate between Features and Technical Debt prioritization. Emphasizing clarity, explicit processes, and the intrinsic value of feedback loops sets the stage for a successful and sustainable SLO journey.
What you should do now
Schedule a demo with Squadcast to learn about the platform, answer your questions, and evaluate if Squadcast is the right fit for you.
Curious about how Squadcast can assist you in implementing SRE best practices? Discover the platform's capabilities through our Interactive Demo.
.svg){kind=small}
.svg){kind=small}
.svg){kind=small}
