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How to Create Programmatic Service Level Indicators and Service Level Objectives

Ishan Mukherjee
New Relic

Programmatically tracked service level indicators (SLIs) are foundational to every site reliability engineering practice. When engineering teams have programmatic SLIs in place, they lessen the need to manually track performance and incident data. They're also able to reduce manual toil because our DevOps teams define the capabilities and metrics that define their SLI data, which they collect automatically — hence "programmatic."

Programmatic SLIs have three key characteristics: they're current (they reflect the state of a system right now), they're automated (they're reported by instrumentation, not by humans), and they're useful (they're selected based on what a system's user cares about). In this post, I'll explain how site reliability engineers (SREs) can help their teams develop and create programmatic SLIs.

SLIs — Identifying Capabilities

An important part of creating programmatic SLIs is identifying the capability of the system or service for which you're creating the SLI. Here are a few definitions:

■ A system is a group of services and infrastructure components that exposes one or more capabilities to external customers (either end users or other internal teams).

■ A service is a runtime process (or a horizontally-scaled tier of processes) that makes up a portion of a system.

■ A capability is a particular aspect of functionality exposed by a service to its users, phrased in plain-language terms.

SLIs and SLOs — Indicators and Objectives

But first, we need some more definitions. An indicator is something you can measure about a system that acts as a proxy for the customer experience. An objective is a goal for a specific indicator that you're committed to achieving.

Configuring indicators and objectives is the easy part. The hard part is thinking through what measurable system behavior serves as a proxy for customer experience. When setting system-level SLIs, think about the key performance indicators (KPIs) for those systems, for example:

■ User-facing system KPIs most often include availability, latency, and throughput.

■ Storage system KPIs often emphasize latency, availability, and durability.

■ Big data systems, such as data processing pipelines, typically use KPIs such as throughput and end-to-end latency.

Your indicators and objectives should provide an accurate snapshot of the impact of your system on your customers.

A more precise description of the indicator and objective relationship is to say that SLIs are expressed in relation to service level objectives (SLOs). When you think about the availability of a system, for example, SLIs are the key measurements of the availability of the system while SLOs are the goals you set for how much availability you expect out of that system. And service level agreements (SLAs) explain the results of breaking the SLO commitments.

Create Programmatic SLIs

You should write your programmatic SLIs in collaboration with your product managers, engineering managers, and individual contributors who work on a system. To define your programmatic SLIs (and SLOs), apply these steps:

1. Identify the system and its services.

2. Identify the customer-facing capabilities of the system or services.

3. Articulate a plain-language definition of what it means for each capability to be available.

4. Define one or more SLIs for that definition.

5. Measure the system to get a baseline.

6. Define an SLO for each capability, and track how you perform against it.

7. Iterate and refine our system, and fine-tune the SLOs over time.

Example capabilities and definitions

Here are two example capabilities and definitions for an imaginary team that manages an imaginary dashboard service:

Capability: Dashboards overview.

Availability Definition: Customers are able to select the dashboard launcher, and see a list of all dashboards available to them.

Capability: Dashboards detail view.

Availability Definition: Customers can view a dashboard, and widgets render accurately and timely manner.

To express these availability definitions as programmatic SLIs (with SLOs to measure them), you'd state these service capabilities as:

■ Requests for the full list of available dashboards returns within 100 milliseconds 99.9% of the time.

■ Requests to open the dashboard launcher complete without error 99.9% of the time.

■ Requests for an individual dashboard return within 100 milliseconds 99.9% of the time.

■ Requests to open an individual dashboard complete without error 99.9% of the time.

After you've settled on your SLIs, they should be reasonably stable, but systems evolve, and you'll need to revisit them regularly. It's a good idea to revisit them quarterly, or whenever you make changes to your services, traffic volume, and upstream and downstream dependencies.

Ishan Mukherjee is SVP of Growth at New Relic

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How to Create Programmatic Service Level Indicators and Service Level Objectives

Ishan Mukherjee
New Relic

Programmatically tracked service level indicators (SLIs) are foundational to every site reliability engineering practice. When engineering teams have programmatic SLIs in place, they lessen the need to manually track performance and incident data. They're also able to reduce manual toil because our DevOps teams define the capabilities and metrics that define their SLI data, which they collect automatically — hence "programmatic."

Programmatic SLIs have three key characteristics: they're current (they reflect the state of a system right now), they're automated (they're reported by instrumentation, not by humans), and they're useful (they're selected based on what a system's user cares about). In this post, I'll explain how site reliability engineers (SREs) can help their teams develop and create programmatic SLIs.

SLIs — Identifying Capabilities

An important part of creating programmatic SLIs is identifying the capability of the system or service for which you're creating the SLI. Here are a few definitions:

■ A system is a group of services and infrastructure components that exposes one or more capabilities to external customers (either end users or other internal teams).

■ A service is a runtime process (or a horizontally-scaled tier of processes) that makes up a portion of a system.

■ A capability is a particular aspect of functionality exposed by a service to its users, phrased in plain-language terms.

SLIs and SLOs — Indicators and Objectives

But first, we need some more definitions. An indicator is something you can measure about a system that acts as a proxy for the customer experience. An objective is a goal for a specific indicator that you're committed to achieving.

Configuring indicators and objectives is the easy part. The hard part is thinking through what measurable system behavior serves as a proxy for customer experience. When setting system-level SLIs, think about the key performance indicators (KPIs) for those systems, for example:

■ User-facing system KPIs most often include availability, latency, and throughput.

■ Storage system KPIs often emphasize latency, availability, and durability.

■ Big data systems, such as data processing pipelines, typically use KPIs such as throughput and end-to-end latency.

Your indicators and objectives should provide an accurate snapshot of the impact of your system on your customers.

A more precise description of the indicator and objective relationship is to say that SLIs are expressed in relation to service level objectives (SLOs). When you think about the availability of a system, for example, SLIs are the key measurements of the availability of the system while SLOs are the goals you set for how much availability you expect out of that system. And service level agreements (SLAs) explain the results of breaking the SLO commitments.

Create Programmatic SLIs

You should write your programmatic SLIs in collaboration with your product managers, engineering managers, and individual contributors who work on a system. To define your programmatic SLIs (and SLOs), apply these steps:

1. Identify the system and its services.

2. Identify the customer-facing capabilities of the system or services.

3. Articulate a plain-language definition of what it means for each capability to be available.

4. Define one or more SLIs for that definition.

5. Measure the system to get a baseline.

6. Define an SLO for each capability, and track how you perform against it.

7. Iterate and refine our system, and fine-tune the SLOs over time.

Example capabilities and definitions

Here are two example capabilities and definitions for an imaginary team that manages an imaginary dashboard service:

Capability: Dashboards overview.

Availability Definition: Customers are able to select the dashboard launcher, and see a list of all dashboards available to them.

Capability: Dashboards detail view.

Availability Definition: Customers can view a dashboard, and widgets render accurately and timely manner.

To express these availability definitions as programmatic SLIs (with SLOs to measure them), you'd state these service capabilities as:

■ Requests for the full list of available dashboards returns within 100 milliseconds 99.9% of the time.

■ Requests to open the dashboard launcher complete without error 99.9% of the time.

■ Requests for an individual dashboard return within 100 milliseconds 99.9% of the time.

■ Requests to open an individual dashboard complete without error 99.9% of the time.

After you've settled on your SLIs, they should be reasonably stable, but systems evolve, and you'll need to revisit them regularly. It's a good idea to revisit them quarterly, or whenever you make changes to your services, traffic volume, and upstream and downstream dependencies.

Ishan Mukherjee is SVP of Growth at New Relic

Hot Topics

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...