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Service Level Objectives

How to get started, adopt, scale, and improve software reliability using SLOs


80% indicate an increased focus on system reliability

The pandemic for most companies has driven increased cloud adoption, remote workers, and supply chain issues. Have these changing conditions led to an increasing focus on system reliability?


Understanding SLOs

Service level objectives (SLOs) are a critical best practice embraced by engineers and developers. Our resource serves as a centralized hub for learning about SLOs, their significance, and how to embark on your SLO journey.

Within the SLO landscape, you'll discover a vibrant community of developers creating free and open-source tools that empower engineering teams worldwide. We have carefully curated a list of the finest tools available.

In addition to tools, this resource sheds light on books, training courses, blogs, and other educational materials, catering to individuals at every stage of their SLO journey. Whether you're an experienced SLO enthusiast or just starting out, this page equips you with the knowledge and tools to optimize your projects and achieve exceptional SLO implementation.

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What is an SLO?

What are the common definitions of an SLO and how does it differ from an SLA?

Why SLOs?

How can SLOs help? Why are they used? What are the use cases?

Use Cases of SLOs

What should you expect from the SLO products?

What is an SLO?

An SLO is a reliability or performance goal set by the team managing the software and services.

Service level objectives (SLOs) are measurable targets that define the desired level of service reliability. They involve setting thresholds for key performance indicators, known as service level indicators (SLIs), and establishing an associated error budget. A service level agreement is the provider-promised reliability standard, agreed to by your customers.

SLOs provide a clear framework to evaluate and maintain the quality of services, allowing organizations to balance reliability and innovation.


Why SLOs?

SLOs let you manage software reliability by making data-driven decisions about tradeoffs.

By Embracing SLOs, organizations can enhance their service delivery, build customer loyalty, and drive positive outcomes by making data-driven decisions.

  • Cost Savings: Proactively managing performance reduces costly downtime and disruptions, resulting in financial savings.
  • Efficient Resource Allocation: Clear SLOs help optimize resource usage, ensuring efforts are focused on high-value areas.
  • Data-Driven Decision-Making: SLOs enable a data-driven approach, allowing organizations to prioritize actions based on customer impact.
  • Streamlined Operations: Identify inefficiencies and bottlenecks; SLOs lead to streamlined processes and reduced operational costs.


SLO Use Cases

SLO use casesSLOs offer key features and use cases in software engineering and service management. They enable teams to set error budgets, balancing innovation and stability while also providing a framework for managing technical debt effectively. SLOs foster collaboration, accountability, and continuous improvement, driving enhanced system performance and the delivery of high-quality services.

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What is an SLO?

A service level objective is an actual target value (or range of values) for the availability of the service, which is measured by a service level indicator. SLOs allow you to define the reliability of your products and services in terms of customer expectations.

Each SLO can have one or more defined objectives (targets and values), with an indication of the user experience (e.g., Good or Acceptable) when that target is met.

What is an error budget?

An error budget is a concept in SLO (service level objective) management that represents the acceptable amount of system instability or downtime within a specific time period. It allows teams to allocate resources for innovation and development while ensuring a certain level of reliability and service quality.

What’s the difference between an SLI/SLA/SLO?

  • SLI (service level indicator): SLIs are specific metrics or measurements that quantify the performance or behavior of a service. They provide objective data about the service's performance, such as response time, error rate, availability, or throughput.

  • SLA (service level agreement): SLAs are formal agreements or contracts between service providers and customers that define the expected level of service and the consequences if those expectations are not met. SLAs typically include specific targets for SLIs and may outline remedies or penalties for service failures.

  • SLO (service level objective): SLOs are specific, measurable targets or goals set by the service provider to ensure the desired level of service quality. They are based on SLIs and define the acceptable range or threshold for each metric. SLOs help establish performance goals and guide decision-making to meet customer expectations.

In summary, SLIs are the actual measurements of service performance, SLAs are contractual agreements that define service expectations, and SLOs are the measurable targets or objectives set by the service provider based on SLIs to ensure the desired level of service quality.

How does alerting off a SLO work?

Alerting off a SLO involves setting up monitoring and alerting systems to notify teams when the actual performance or reliability of a service deviates from the defined SLO targets. Here's how it typically works:

  1. Define SLOs: First, establish the specific SLOs for the service, such as response time, error rate, or availability, along with the acceptable threshold or range for each metric.

  2. Monitoring: Implement monitoring systems that continuously collect data on the relevant metrics, tracking the actual performance of the service in real-time.

  3. Comparison: Compare the real-time monitoring data against the defined SLOs. This comparison can be done using automated tools or scripts that periodically evaluate the metrics.

  4. Deviation Detection: If the monitored metrics breach the defined SLO thresholds or fall outside the acceptable range, it indicates a deviation from the expected service quality.

  5. Alerting: Configure the monitoring system to generate alerts when a deviation is detected. The alerts are typically sent to relevant teams or individuals responsible for managing the service, allowing them to respond promptly to the issue.

  6. Incident Management: Upon receiving an alert, the appropriate team can investigate the cause of the deviation, diagnose the underlying problem, and take corrective actions to bring the service back within the desired SLO targets.

By alerting off a SLO, teams can proactively monitor service performance, identify issues early on, and take timely actions to ensure service reliability and meet customer expectations.

What is the difference between SLOs, APM, and AIOps?

SLOs are specific performance targets that ensure desired service quality, while APM (Application Performance Monitoring) focuses on monitoring and optimizing the performance of applications. On the other hand, AIOps (Artificial Intelligence for IT Operations) leverages AI-driven automation to enhance IT operations, providing insights and streamlining processes for improved efficiency and incident management. While SLOs set goals, APM measures application performance, and AIOps employs AI technology to optimize IT operations.

How can SLOs help with cloud migration?

By defining performance targets and metrics, SLOs ensure that the migrated applications and services meet the desired level of performance and availability. They assist in identifying critical services and components that require special attention during the migration process, enabling organizations to plan resources, make architectural decisions, and allocate sufficient time for testing and validation. SLOs also provide a framework for continuous performance monitoring and optimization in the cloud environment, helping organizations maintain and improve their application performance post-migration. Overall, SLOs serve as a guiding principle for a successful and well-managed cloud migration journey.

How can SLOs help manage technical debt?

SLOs can be effective in managing technical debt by providing a structured approach. By setting performance targets and monitoring metrics, SLOs offer visibility into the impact of technical debt on service quality. They help prioritize efforts and resources, enabling organizations to address critical areas affected by technical debt. SLOs act as a guide for decision-making, facilitating discussions on resource allocation and trade-offs between resolving technical debt and delivering new features. By aligning technical debt management with SLOs, organizations can proactively address issues, improve service quality, and mitigate the long-term effects of accumulated technical debt.

How can SLOs help reduce costs?

Depending on your use case, and how you apply them, SLOs can help reduce costs through:

  • Optimized Resource Allocation: By aligning performance targets with business objectives, organizations can optimize the allocation of resources, avoiding unnecessary costs associated with excessive capacity or underutilization.
  • Proactive Issue Prevention: SLO monitoring enables organizations to proactively identify and address performance issues, minimizing the costs associated with service disruptions, customer dissatisfaction, and reactive problem resolution.
  • Efficient Troubleshooting: SLOs provide a framework for prioritizing troubleshooting efforts, allowing organizations to focus resources on resolving issues that directly impact service quality, reducing the time and costs involved in extensive troubleshooting.

How do SLOs help with load balancing?

SLOs play a significant role in load balancing by providing a performance-focused approach to workload distribution. By establishing specific performance targets and continuously monitoring system metrics, organizations can gain insights into their system's performance. This knowledge enables capacity planning, helping organizations determine the optimal workload capacity of their systems. Load balancers can then use this information to dynamically distribute incoming traffic across multiple instances or servers, ensuring workloads are evenly balanced and maintaining the desired level of performance. Additionally, SLOs inform scaling decisions, triggering automatic resource scaling when performance thresholds are approached or exceeded. Ultimately, SLOs empower organizations to achieve effective load balancing and ensure optimal performance across their services.

What's the difference between SLOs and traditional monitoring?

The difference between SLOs and traditional monitoring lies in their focus and purpose. Traditional monitoring primarily involves the collection and analysis of various metrics and data points to track the health and performance of systems or services. It provides insights into the current state of the system and helps identify issues or anomalies.

On the other hand, SLOs are performance targets set by organizations to define the desired level of service quality that they aim to provide to their users or customers. SLOs are typically defined based on specific metrics and thresholds that reflect the users' experience or the service's critical parameters. SLOs shift the focus from solely monitoring metrics to monitoring and ensuring that the defined performance targets are consistently met. In other words, SLOs enrich the preexisting monitoring data with a focus on customers and their accepted level of service performance.

While traditional monitoring is more reactive and centered around detecting and diagnosing issues, SLOs provide a proactive approach by establishing clear objectives and continuously measuring performance against those objectives. SLOs help align the monitoring efforts with the overall business goals and customer expectations, allowing organizations to prioritize their efforts based on the impact on user experience and business outcomes.

How could companies using any observability strategy benefit from adding SLOs?

Companies utilizing any observability strategy can derive significant benefits from incorporating service level objectives (SLOs) into their practices. By adding SLOs, companies gain a more comprehensive view of their systems and services, allowing them to bridge the gap between monitoring and user experience. SLOs provide a customer-centric perspective, enabling businesses to set measurable performance targets and align their observability efforts accordingly. This integration enhances incident response, facilitates proactive issue detection, improves service reliability, and empowers organizations to prioritize efforts based on the impact to end-users. Ultimately, the incorporation of SLOs into observability strategies helps companies deliver exceptional user experiences, optimize system performance, and drive overall business success.

How do SLOs impact Key Performance Indicators (KPIs) for businesses?

SLOs (service level objectives) have a significant impact on Key Performance Indicators (KPIs) for businesses. SLOs provide specific performance targets that directly influence the metrics used as KPIs. By aligning KPIs with SLOs, companies can measure their performance against customer-centric goals and track the actual outcomes of their services. This alignment ensures that KPIs reflect the quality of service delivered and the overall user experience, enabling businesses to monitor and optimize their performance based on the defined SLOs. Ultimately, the integration of SLOs into KPIs allows companies to have a more accurate and meaningful assessment of their service performance and make informed decisions to drive continuous improvement.

What's the best SLO platform?

Determining the "best" SLO platform depends on various factors and specific requirements of each organization. There are several reputable SLO platforms available in the market, each with its own strengths and features. Some popular options include Nobl9, Blameless, Honeycomb, and Datadog. The best platform for your organization would depend on your specific needs, such as integration capabilities, ease of use, scalability, pricing, and compatibility with your existing infrastructure. It is recommended to evaluate different platforms based on your unique requirements and consider factors like reliability, flexibility, and cost.

What is a tool that can help me measure reliability?

There are several tools available in the market that can help measure service reliability, each with its own strengths and features. One notable tool is Nobl9, a comprehensive platform focused on SLOs. Nobl9 offers a wide range of capabilities for setting, tracking, and analyzing reliability targets, empowering organizations to monitor their service performance and make data-driven improvements. Additionally, other tools like Blameless and Honeycomb provide valuable features for measuring and managing reliability metrics. It is important to evaluate different tools based on your specific needs and requirements to determine the best fit for your organization's reliability measurement and optimization.

Could SLOs help mitigate the risk of IT change/cloud migration?

Implementing service level objectives can significantly help mitigate the risk associated with IT change and cloud migration. By defining clear performance targets and thresholds in SLOs, organizations can set expectations and establish a baseline for measuring the impact of changes or migrations on service reliability. SLOs enable proactive monitoring and measurement of critical metrics during the transition, allowing teams to identify and address any performance degradation or issues promptly. This helps in identifying potential risks and ensuring that the migrated systems or changes meet the desired performance and reliability standards. SLOs also provide a framework for continuous improvement, enabling organizations to optimize their services and minimize the impact of changes on end-users.

Can SLOs help justify changes to a process or an organization?

SLOs can play a significant role in justifying changes to processes or organizations. By defining specific performance targets and measuring against them, SLOs provide concrete metrics to assess the impact of proposed changes. SLOs enable organizations to evaluate how process modifications or organizational adjustments affect service reliability, user experience, and key business outcomes. By leveraging SLOs as a quantitative measure, stakeholders can make data-driven decisions, demonstrate the value of proposed changes, and ensure that any modifications align with the desired performance standards. This enables a more transparent and objective justification for process or organizational changes based on measurable improvements in service delivery and customer satisfaction. SLO dashboards, presented in products like Nobl9, can also help justify change by showing stakeholders the whole picture of reliability across products and services.

Training Courses

SRE Service Level Objectives and Error Budgets
This course will broaden your knowledge of service level objectives (SLOs) and error budgets. An SLO is a goal for how well a product or service should operate. By the end of this course, you will have a clear understanding of both an SLO and an error budget and how the two of them are used together to balance service reliability With the pace of innovation.
Go to Cloud Academy
The Art of SLOs
The Art of SLOs is a workshop developed by Google's Customer Reliability Engineering team. The goal of the workshop is to introduce participants to the way Google measures service reliability—in terms of Service Level Indicators (SLIs) and Service Level Objectives (SLOs)—and give them some hands-on experience with creating these measures in practice.
Go to YouTube
A Year of SLO Bootcamps
You'll learn a proven strategy for helping teams get over the hump of a first SLO and how to drive a scalable organizational and cultural change to the SLO-based way of thinking. With COVID, I had to adapt my SLO Bootcamp to being online only, and this forced me to focus on just the essentials, increase interactivity, and ensure the course was of value to all the participants. I'll go over resources you can use to run your own SLO Bootcamp too!
Go to YouTube


SLO Articles & Videos

SLO Books

Check out the best books on SLOs that we could find. All these books are community-oriented, educational passages relaying the most important concepts of SLOs.

SLO Adoption and Usage in Site Reliability Engineering
Julie McCoy, Nicole Forsgren
This practical report details why and how to make SLOs, service-level indicators (SLIs), and error budgets critical components of your SRE practice.
Go to O'Reilly
Implementing Service Level Objectives
Alex Hidalgo
In this book, recognized SLO expert Alex Hidalgo explains how to build an SLO culture from the ground up.
Go to O'Reilly
97 Things Every Cloud Engineer Should Know
Emily Freeman, Nathen Harvey
With this book, professionals from around the world provide valuable insight into today's cloud engineering role.
Go to Amazon
97 Things Every SRE Should Know
Emil Stolarsky, Jaime Woo
With this practical book, newcomers and old hats alike will explore a broad range of conversations happening in SRE.
Go to Amazon
Site Reliability Engineering
Betsy Beyer, Chris Jones, Jennifer Petoff and Niall Richard Murphy
Members of the SRE team explain how their engagement with the entire software lifecycle has enabled Google to build, deploy, monitor, and maintain some of the largest software systems in the world.
Go to Amazon
Site Reliability Engineering Workbook
Betsy Beyer, Niall Richard Murphy, David K. Rensin, Kent Kawahara and Stephen Thorne
The Site Reliability Workbook is the hands-on companion to the Site Reliability Engineering book and uses concrete examples to show how to put SRE principles and practices to work.
Go to Amazon
Building Secure & Reliable Systems
Heather Adkins, Betsy Beyer, Paul Blankinship, Ana Oprea, Piotr Lewandowski, Adam Stubblefield
In this book, experts from Google share best practices to help your organization design scalable and reliable systems that are fundamentally secure.
Go to Amazon
Cloud Observability in Action
Michael Hausenblas
This book teaches you how to set up an observability system that learns from a cloud application’s signals, logging, and monitoring using free and open source tools.
Go to Manning