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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

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...