Service Level Indicators (SLIs)

Definition: What Is a Service Level Indicator?

Service Level Indicators (SLIs) are quantifiable defined metrics that measure the performance and availability of a service or distributed system. A few of these metrics will be latency, error rate, throughput, availability, uptime, and response time. It is important to note that SLI metrics are aggregated and expressed as rate, average, percentage, or percentile. For example, an SLI for availability can be defined as an availability of 99.99%.

Simply put, SLIs answer the question, “What are we measuring to show how well our IT service is performing?”

Why Are SLIs Important?

Using SLIs, organizations can measure the performance and availability of their services against the business objectives quantitatively and objectively. However, as good as that sounds, SLIs offer organizations much more.

Here are a few reasons SLIs are important:

• SLI provides a specific way to set defined goals and expectations for your service. Limiting the SLI to the metrics that reflect your service can ensure you deliver on your service-level agreement (SLA), meet your end user’s expectations, and avoid penalties.
• By monitoring SLIs, DevOps and Site Reliability Engineers (SRE) can identify issues swiftly because one can quickly and more accurately pinpoint what is wrong. It also helps in the quick and proactive resolution of said issue.
• With the discovery and remediation of issues comes better service quality. Identifying issues helps the team track your user journey success, measure customer satisfaction, improve user experience, and ensure business success.
• You can also use SLI to track the performance and availability of your services over time. With this information, one can set more proactive progress toward business objectives.

SLIs vs. SLOs vs. SLAs

Service-level indicator (SLI), service-level objective (SLO), and service-level agreement (SLA) are three terms you frequently hear while discussing service-level management. However, while these three terms might sound similar, they’re pretty different.

SLIs, as mentioned earlier, are measurable metrics used to track performance and availability of service. Thus, they act as the foundational elements and will be used to determine if the organization’s services objectives are met.

SLOs are the goal defined by the organization to quantitatively determine the service quality the service provider aims to achieve for a specific SLI. Think of them as thresholds you compare your SLIs to decide whether you’re doing great.

SLAs are mutual contract agreements between the service provider and its client to define the terms of service. It outlines what’s acceptable, the service to be provided, and the penalty for not meeting the agreed-upon service level. It is important to know that the SLOs in SLAs are not set in stone and should be continually reviewed.

Let’s take an example.

Assuming you choose to use authentication failures as metrics to assess the security of your API. Authentication failure here is the SLI. For context, authentication failures are simply the number of times authentication failed; thus, a great indicator of potential unauthorized access.

To ensure the API is secure and trustworthy, you aim for a target of 1%. It will be our SLO.

To guarantee that you can deliver to your client, you enter an agreement and promise this B2B client that your API has an authentication failure of 1.2%. The document that outlines the specifics of this arrangement between the client and you is the SLA.

To summarise, SLIs are the measurable metrics, SLOs are your benchmark or target for each SLI, and SLAs are the legally agreed term of engagement.

Types of Service Level Indicators

Fundamentally, there are two types of SLI: request-based and window-based.

Request-based SLIs

Request-based SLIs measure the number of complete requests or transactions made in or to service compared to the total number of requests or transactions. This metric helps the service provider to spot performance issues or bottlenecks to completing customer requests.

Thus, the formula for request-based SLI will be:

Request-based SLI = good requests / total requests

Let’s say a service has about 20,000 total requests. Out of these, only 17,000 requests were successful or completed. Thus, the service has a success rate of 85%.

It is crucial to know that one must measure request-based SLIs within a specific time range to be measured and reviewed over time.

Window-based SLIs

Window-based SLIs measure the performance and availability of a service within a specific time window. The number of successful requests is calculated over a window period. This SLI helps one monitor, elevate, and identify trends in the service within a specific time range or critical hours.

The formula for window-based SLI will be:

Window-based SLI = good periods / total Periods

Thus, a service with 540,0000 successful requests out of the 600,000 requests during peak hours (2:00 pm to 6:00 pm) has a 90% success rate during peak hours.

What SLI Metrics to Measure?

By tracking SLI metrics, you gain valuable insights into your service. But with so many possible SLI metrics to choose from, how do you know which ones to focus on?

Let’s have a rundown of some important SLI metrics you should measure.

Uptime

Uptime refers to the time the system was operational and running within a certain period without downtime. It is important because it affects end users and measures reliability and availability.

It is, however, important to note that uptime and downtime are based on what you define them as. For example, does downtime mean when the service has been unavailable for more than three or five minutes? That’s up to you to decide.

Response time

Response time measures the time it takes for a service to respond to a request. This metric affects user experience; a faster response time can be tied to higher conversion rates and a more positive user experience.

Just like uptime, it is important to define what an acceptable response time is to you regarding the various types of requests available. By various types of requests, we mean web page load time, API requests, database queries, or application requests. For example, a response time of 15 seconds might be acceptable for database queries, but is that acceptable for your web pages?

Error rate

Error rate captures the frequencies of errors that occurred within a service. Error rates here could be server errors, authentication errors, validation errors, or connectivity errors. A high error rate can be tied to a more negative user experience.

This metric depends highly on the nature of the service. For example, a Fintech application would want a much lower error rate, let’s say 0.9%, unlike a streaming service platform.

Throughput

Throughput measures the rate at which a service process requests such as requests per second. This metric gives you information on your service’s capacity and scalability and helps in the optimization of the service.

It is important to know that throughput can be influenced by factors like network bandwidth, code efficiency, and the processing speed of a system.

Availability

Availability is the percentage of time that a service is available to users. This metric is often confused with uptime. However, they’re not the same.

While uptime measures how long a service has been running without interruption, availability measures how often users can access this service. It means a service can have low uptime but high availability if users can still access it regardless of short and infrequent downtime.

It is calculated as Availability = (uptime / total time) * 100%

Latency

Latency tells us how long it takes for a service to receive and process a user’s request. This is quite important for services requiring quick and responsive user interactions, such as online gaming platforms.

Factors such as the system load, software design, and network infrastructure architecture influence it. Different industries will require different latency expectations. For example, gaming platform users will expect a lower latency level compared to a content delivery network.

Durability

Durability refers to the ability of a service to retain data over time reliably. This is very important for services like file systems and data storage that require data to be stored and accessed over a long period. This metric is affected by storage system design and the replication and backup strategies implemented.

Similar to how different industries have metrics they prioritize, various applications do as well. For example, unlike Big Data systems that prioritize throughput and latency, user-facing applications prioritize metrics like latency and error rate. Regardless of your choice, your metrics must be measurable, actionable, relevant, understandable, and sensitive enough to detect performance changes.

How to Choose the Right SLI Metrics

There is a dilemma that comes with tracking; you don’t want to track too many metrics as that can get redundant and overwhelming. You also don’t want to track too little, as there is the risk that some important parts of the system will be left unmonitored. Hence it is important to choose metrics based on factors that align with the business objectives and end user satisfaction.

A few of these factors are:

• The service being provided by the service provider: Different services will have different priorities and objectives. For example, a cloud storage service provider would prioritize availability and data transfer speed over response time and uptime, like an e-commerce website.
• SLO’s goal: Your metric should align with the business goals. For example, to increase your e-commerce website conversion rate, choosing to measure metrics like response time or click-through rate (CTR) would be great. This is because these metrics will tell you how effective your marketing campaigns are.
• SLA’s expectation: Besides aligning with your business goals, metrics must meet your end users’ expectations. Cloud Storage enables organizations to store, access, and maintain data. These organizations would like to be assured that you can guarantee them access to their data and your service 98% of the time. To ensure that you can provide this, choosing and measuring a metric like availability would be best.
• Technical capabilities: You should be able to monitor the metric you’re picking. Pick feasible, measurable metrics, and don’t over-promise and under-deliver.
• Regulatory requirement: Your industry might be subject to some regulation as a service provider. Thus, there will be some specific requirements. For example, security-related metrics like Time to Mitigation and Time to Alert might be necessary for clients to have confidence in your payment integration API service.

How to Create and Implement SLIs

Your SLI significantly influences your user experience and business objectives. Thus, It is important to create SLI that clearly and concisely identifies the relevant performance metrics that can effectively define the thresholds for each metric in your SLO. And likewise, SLI implementation must be done effectively.

Here are the steps to creating SLIs:

• The first step in implementing SLIs is identifying your service’s users and needs. It requires a deep understanding of the users and figuring out how to improve their experience by tracking relevant and meaningful SLIs.
• By understanding your client’s needs, you can identify and define feasible metrics necessary for your SLIs that measure service performance that matters to your business and, most importantly, end users. The more specific your SLIs, the more accurate and impactful they will be.
• You need to pick the right way to implement data collection and processing. Best done with a tool that lets you collect high volumes of data in real time across your tech stack and process them to create out-of-the-box dashboards.
• Calculate your SLIs and establish thresholds for each. This threshold should be realistic, achievable, and accurately reflect your service. You must also decide on the frequency of measuring these SLIs and reviewing the threshold if you’re not meeting your objectives.
• Frequently monitor metrics to find trends and review SLIs for service optimization.
• Lastly, communicate SLIs and performance to users and stakeholders clearly and concisely. It ensures that SLI remains relevant and service performance continuously improves.

How to Monitor SLIs

Monitoring service level indicators is crucial to meet service level agreements. Here are some tips on how to monitor SLIs effectively:

• Measure behavior on the user’s side as well. This provides you with a better understanding of your users, identifying and solving issues before they affect them and, thus, improving their experience.
• Aggregate your metrics’ raw value. It will give you better insights into your SLIs. However, using percentile instead of average when aggregating is better because it shows a clear distribution of SLI metrics. For example, if you’re monitoring the response time, some requests may take only a few milliseconds to complete, while others may take several seconds. If you were to calculate the average, the result would be a value that doesn’t represent the majority accurately.
• Aggregate over a specific period. It is not enough to just aggregate; you should do it over a specific period, as it will help you identify trends, patterns, and changes in SLI metrics over time. This period, however, should be short, specific, and thought out, as this will help you find patterns that may not be apparent if you only measure metrics at random intervals. One example is measuring a metric for a week, every minute. If there is a change at any specific time within the week, it will be identified quickly.
• Track frequency. This helps identify any changes or inconsistencies in your SLI metrics over time. For example, if you start measuring SLI metrics every 30 seconds and notice a sudden increase in latency, this can be quickly addressed before it affects the reliability and availability of a service. You will also be able to identify inconsistencies and gaps since you get a more accurate view of your services.

Challenges of SLIs

Measuring performance and availability of service can be challenging due to several reasons. Here are some:

• SLI must be feasible to measure, contribute to the user’s experience journey, and align with business objectives. One must understand the service’s components and resonate with users to achieve this.
• The process of collecting and processing SLI data can be complex and resource-intensive. It is primarily because the process requires a reliable data collection and processing infrastructure to guarantee data quality and consistency. Luckily, there are tools out there that can help with this.
• Interpreting SLI data gets challenging when there are multiple SLIs or when SLIs are correlated. To understand your metrics, you must integrate and connect data from different sources and identify trends and issues from the findings.
• Defining your SLO requires establishing thresholds that accurately reflect the service while balancing the user’s needs and expectations for each SLI. This can have some impact on the business objectives and additional costs.

SLI Monitoring with Sematext

Sematext Cloud offers a powerful solution for monitoring Service Level Indicators (SLIs) through its comprehensive suite of tools, including Sematext Synthetics and Sematext Monitoring., while Sematext Infrastructure Monitoring enables you to monitor the underlying infrastructure components that impact SLI metrics.

Sematext Synthetics allows you to create dedicated monitors for your applications and websites to regularly check SLI metrics such as response time, availability, and functionality. This helps you detect any deviations or issues that might affect your systems and address them quickly to maintain optimal SLI values.

In conjunction with Synthetics, Sematext Infrastructure Monitoring provides deep visibility into the underlying infrastructure components that impact SLI metrics, including servers, networks, and databases. With Sematext’s real-time monitoring features, you can identify any bottlenecks or potential issues related to your infrastructure and proactively address them to ensure the reliability and stability of your systems.

Setting up alerting for SLI monitoring in Sematext is simple and flexible. You can configure alerts based on specific SLI metrics, define threshold values, and select the preferred notification channels. Sematext will notify you promptly of any SLI deviations or anomalies so that you can take immediate action.

Sematext’s 14-day free trial to explore all of its SLI monitoring capabilities without any commitment. Sign up now and unlock the potential of Sematext Synthetics and Infrastructure Monitoring to monitor, measure, and optimize your SLIs with confidence.