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Service Level Agreement

Metrics of SLA Agreement With Examples

Find out how you can scale your business & benefit from understanding the principles behind SLA agreements.

Every industry has its own set of jargon. However, owing to its broad definition, the term “SLA” is extremely difficult to define. SLA agreement is used by internet service providers to establish uptime goals. They are also used by merchant suppliers to evaluate production costs. Customer service teams, of course, utilize them to set standards for service quality, response speed, and satisfaction.

Most of the service providers are aware of the importance of SLA agreements with their partners and clients. However, creating one can be intimidating if you don’t know where to begin or what to include. In this post, we will tell you everything about SLA agreements and the metrics you may use to track their success. This will help you improve your providers and team accountability. You’ll also see several SLA metric examples to give you a better understanding of what you can track.

What is an SLA Agreement?

A service level agreement (SLA) is a legally enforceable contract between a service provider and one or more clients that specify the precise terms and agreements that represent the duration of the service engagement – that is when the client pays for services and the provider is contractually obliged to deliver them.

An SLA agreement typically outlines the nature of the services to be delivered, as well as the goals of both parties (the provider and the client firm), any conditions, and the points of contact. It also lays out what will happen if the SLA objectives aren’t accomplished. In the case of IT services, the SLA establishes the service provider’s performance standards. SLA metrics, which are commonly used interchangeably with the word SLA, encapsulate these criteria.

In reality, an SLA is a detailed document that outlines all of the service provider’s performance expectations, as well as other specifics.

What Are SLA Metrics?

SLA metrics are a set of measurable and trackable key performance indicators (KPIs). You can track any number of SLA metrics, but many of them can be divided into five categories.

5 Key Service Level Agreement (SLA) Metrics

An SLA agreement is built around metrics. They establish a measurable standard that the service provider must reach or beat. They also make spotting SLA breaches easier. While SLA metrics differ greatly by industry and company, here are the five most important ones to remember.


The proportion or duration of time for which a cloud resource is available to its users is known as its availability. You want availability to be as near to 100 percent as possible. Here are a few availability metrics and examples.


The amount of time that an instance is up, running, and ready for usage is known as uptime. One example is the percentage of time your AWS EC2 instance operates without being rebooted due to an AWS outage. This type of instance has a 100 percent uptime.

Service Availability

The proportion of time that service requests are met with the expected response is known as service availability. For example, your company’s Azure web app service is consistently able to respond when clients need to log in. SLA performance degrades if your monitoring shows this service is suddenly underperforming.

Response Time

Any cloud resource’s reaction time, also known as latency, is the time it takes for a response to arrive after a request. Because response time has such a direct impact on the user experience, you want it to be as short as possible. Here are several examples:


The mean time to repair (MTTR) is the time it takes to solve a particular issue. Depending on the system, the R can stand for repair or resolution, but the objective is the same: you’re concerned about how quickly the supplier or your team resolves a problem. A measure of the time between when you first notice a regional cloud network outage in your monitoring tool and when the alarm goes away is an example.

Transaction Response Time

The transaction response time metric measures how long it takes a transaction request to receive a response, usually in milliseconds. Assume that one of your organization’s users writes an email using Amazon SES. The transaction response time is measured by the time it takes to receive confirmation of a sent email after hitting the “send” button.


The throughput measure refers to the volume of data sent and received by your cloud resources over a given period of time. The system’s throughput should be as high as possible for better results. Here are a few examples:

Disk Write Bytes

The rate at which a system writes bytes of data to a disc during a period of time, usually measured in seconds, is known as disc write bytes. An Amazon S3 storage system, for example, can be used to save large data files uploaded by your users. You don’t want them to have to go grab a cup of coffee after uploading files to your system and waiting for it to finish. In this circumstance, a poor throughput is detrimental to your SLA performance.

Link Throughput

The amount of packet data that may be transferred across a network link in a given amount of time is known as link throughput. Bytes or bits per second are used to represent this measure. A network link between New York City and London, for example, may transport 150Mbps. You can be notified if link throughput falls below a defined alert threshold before users are affected.


The volume or percentage of failed requests to a certain resource is defined by the errors metric. Here are a few examples:

HTTP Errors

The percentage of requests a user sends that return an unexpected HTTP status code is known as HTTP errors. A user receiving the dreaded HTTP 500 “server unavailable” error when using your web application to request an API is one example. Any such error should be checked because it could be the result of a network outage, which could have an impact on your SLA.

Disk Read Errors

The percentage of reading requests to disc that fails is the disc read errors statistic. A PostgreSQL request, for example, could fetch data from the database’s disc. A read error can be caused by a storage problem, which could compromise your SLA.


The utilization metric measures how much of your cloud system’s resources are being used. Listed below are a few examples:

Disk Utilization

The quantity of disc space consumed on a server instance is referred to as disc utilization. As an example, consider an Azure instance that has exhausted its available disc space. You can use the instance disc utilization to see how much space you have left and whether you need to upgrade. An uptime SLA violation will very certainly occur if a server instance runs out of disc space.

Memory Utilization

The quantity of RAM used by a system is referred to as memory usage. An AWS instance with insufficient memory is an example. The instance memory consumption indicator will show you how much memory is being consumed at any particular time. This might help you determine whether you need more RAM or whether a brief reboot is necessary to free up more memory.

Final Words

There’s one more thing to consider when it comes to what should be included in your SLA agreement. Review these metrics on a regular basis to track your progress, and ensure the reports for both sides of the SLA agreement are accessible to the right people.

This phase promotes accountability and openness by allowing both teams to address difficulties and congratulate one another on successful outcomes.

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