3 Steps to Avoid Service Level Disagreements

John Lucania
Learn more about SmartBear

You ask a friend to "check" on your dog while you're away. Obliging, your friend goes to your house, rings the doorbell to listen for a bark and then returns to their car. However, when you made the request you really wanted your friend to go into the house for a bit, make sure there were no issues and immediately notify you if something was wrong. A perfect case of a poorly negotiated SLA!

What Are SLAs and Why Do We Have Them?

A Service Level Agreement is a contractual agreement between a service provider and a customer regarding the level of service that will be provided. SLAs are beneficial for both parties – they define what is being purchased and also the roles and responsibilities to remediate any issues. A well-constructed SLA strengthens the customer relationship by bridging the gap between the vendor services and customer expectations. With software services, websites and applications becoming increasingly complex, negotiating and adhering to SLAs is more important than ever.

What Do SLAs Typically Cover?

It is very important to keep the SLA simple, measurable and realistic. SLAs typically cover:

■ Description of overall services

■ Service performance metrics

■ Financial aspects of service delivery

■ Responsibilities of service provider and customer

■ Disaster recovery process

■ Review process and frequency of review

■ Termination of agreement process

The specific performance metrics that manage the compliance of service delivery are called Service Level Objectives (SLOs). In the context of web services, SLOs would cover availability, uptime and response time for the service; probably accessibility by geography and problem resolution metrics such as mean time to answer and/or mean time to repair.

Is a service really available if the customer cannot use it? A well-constructed SLA should include a unit of measurement that defines availability to align with the customer's critical business process, and not just the availability of the servers URL/URI or log in process.

Using our doorbell analogy in web services context, a poorly negotiated SLA will ring the doorbell equivalent of looking for the 200 OK from the server. The 200 code, like the dog's bark, will just tell you that someone is home and not the actual condition i.e. health of the service. Checking a website or authenticating without validating the business process you rely on, exposes you to downtime without financial leverage.

Step One: Measure What You Have

What can you, the service provider, do to get most out of SLAs? Let's say you are providing a marketing automation system to an enterprise that will run its global web activities over your system. You have promised them 95% availability and suitable performance from the USA east and west coasts, UK, Germany and India.

Before you commit to an exact performance target, hopefully you have measured what you have now. You need to baseline the performance of your service in order to understand what you can offer. No sense promising 95% availability in India if your system typically only is available 80% of the time in India. However, when it comes to SLAs, under committing can lead to lost business opportunities and lost revenue. You can use your SLA as a competitive advantage, only if you know what you can and cannot deliver. Baselining performance will help you commit not too much, not too little but just right!

Using a synthetic performance monitoring tool, you can baseline your services. Ex. Let's say you want to measure performance of a user log in activity from UK during business hours. You can record this multi-step user transaction and use that script to create a monitor. Next, you can create an SLA for that monitor by setting desired response time and availability objective. A quality synthetic tool will not only see if the service is up and running but also measures the response times and functional correctness from its global monitoring nodes; assuring SLA compliance by comparing the actual performance with SLA objectives.

By observing your monitors in real time , as well as from the SLA summary, you get the realistic and complete picture of your performance.

Step Two: Include What Applies to Your Customer, Exclude the Rest

If your agreement states that you will provide a certain level of service for east coast, west coast, UK, Germany and India, don't provide the data regarding the Netherlands and Africa. You also need to account for operational time for you, clearly mention the descriptions of your maintenance windows and/or upgrades. When building the service-level-agreement, keep in mind the operating periods as well as both ongoing and one-time events.

Customers are getting used to the multi tenancy nature of service providers. So be open to SLA negotiations, however calculate the cost associated with customization and make sure it aligns with your aggregate business interest in that customer. Many times the customer can also be found in over/under demanding situations. Baselining customer's performance requirements will lead to more realistic SLAs and a win-win situation for both parties.

Step Three: Monitor Aggressively

In order to make realistic availability and performance goals and keep them, you have to take enough measurements so that a single failure doesn't skew the overall results.

I want to talk a little bit about the law of large numbers: which is a principle of probability and statistics. The law of large numbers states that as a sample size grows, its mean will get closer and closer to the average of the whole population.

This is an important context for monitoring and setting SLAs. If you run an availability test from 5 locations once an hour, one time, and one of those tests fails. Your availability is down to 80 percent. If you run tests from 10 locations every 5 minutes for an hour that is 50 tests – and if 1 fails then your availability is now 98%! Less aggressive monitoring leaves you vulnerable to an SLA violation for a brief outage.

In conclusion, service level agreements are valuable for you and your customers. These three steps will help you look at SLAs as an opportunity than a restriction.

■ Make the right agreement based on baseline performance

■ Measure the correct things with the correct frequency

■ Take enough measurements to smooth out variability

John Lucania is Senior Sales Engineer at SmartBear Software.

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3 Steps to Avoid Service Level Disagreements

John Lucania
Learn more about SmartBear

You ask a friend to "check" on your dog while you're away. Obliging, your friend goes to your house, rings the doorbell to listen for a bark and then returns to their car. However, when you made the request you really wanted your friend to go into the house for a bit, make sure there were no issues and immediately notify you if something was wrong. A perfect case of a poorly negotiated SLA!

What Are SLAs and Why Do We Have Them?

A Service Level Agreement is a contractual agreement between a service provider and a customer regarding the level of service that will be provided. SLAs are beneficial for both parties – they define what is being purchased and also the roles and responsibilities to remediate any issues. A well-constructed SLA strengthens the customer relationship by bridging the gap between the vendor services and customer expectations. With software services, websites and applications becoming increasingly complex, negotiating and adhering to SLAs is more important than ever.

What Do SLAs Typically Cover?

It is very important to keep the SLA simple, measurable and realistic. SLAs typically cover:

■ Description of overall services

■ Service performance metrics

■ Financial aspects of service delivery

■ Responsibilities of service provider and customer

■ Disaster recovery process

■ Review process and frequency of review

■ Termination of agreement process

The specific performance metrics that manage the compliance of service delivery are called Service Level Objectives (SLOs). In the context of web services, SLOs would cover availability, uptime and response time for the service; probably accessibility by geography and problem resolution metrics such as mean time to answer and/or mean time to repair.

Is a service really available if the customer cannot use it? A well-constructed SLA should include a unit of measurement that defines availability to align with the customer's critical business process, and not just the availability of the servers URL/URI or log in process.

Using our doorbell analogy in web services context, a poorly negotiated SLA will ring the doorbell equivalent of looking for the 200 OK from the server. The 200 code, like the dog's bark, will just tell you that someone is home and not the actual condition i.e. health of the service. Checking a website or authenticating without validating the business process you rely on, exposes you to downtime without financial leverage.

Step One: Measure What You Have

What can you, the service provider, do to get most out of SLAs? Let's say you are providing a marketing automation system to an enterprise that will run its global web activities over your system. You have promised them 95% availability and suitable performance from the USA east and west coasts, UK, Germany and India.

Before you commit to an exact performance target, hopefully you have measured what you have now. You need to baseline the performance of your service in order to understand what you can offer. No sense promising 95% availability in India if your system typically only is available 80% of the time in India. However, when it comes to SLAs, under committing can lead to lost business opportunities and lost revenue. You can use your SLA as a competitive advantage, only if you know what you can and cannot deliver. Baselining performance will help you commit not too much, not too little but just right!

Using a synthetic performance monitoring tool, you can baseline your services. Ex. Let's say you want to measure performance of a user log in activity from UK during business hours. You can record this multi-step user transaction and use that script to create a monitor. Next, you can create an SLA for that monitor by setting desired response time and availability objective. A quality synthetic tool will not only see if the service is up and running but also measures the response times and functional correctness from its global monitoring nodes; assuring SLA compliance by comparing the actual performance with SLA objectives.

By observing your monitors in real time , as well as from the SLA summary, you get the realistic and complete picture of your performance.

Step Two: Include What Applies to Your Customer, Exclude the Rest

If your agreement states that you will provide a certain level of service for east coast, west coast, UK, Germany and India, don't provide the data regarding the Netherlands and Africa. You also need to account for operational time for you, clearly mention the descriptions of your maintenance windows and/or upgrades. When building the service-level-agreement, keep in mind the operating periods as well as both ongoing and one-time events.

Customers are getting used to the multi tenancy nature of service providers. So be open to SLA negotiations, however calculate the cost associated with customization and make sure it aligns with your aggregate business interest in that customer. Many times the customer can also be found in over/under demanding situations. Baselining customer's performance requirements will lead to more realistic SLAs and a win-win situation for both parties.

Step Three: Monitor Aggressively

In order to make realistic availability and performance goals and keep them, you have to take enough measurements so that a single failure doesn't skew the overall results.

I want to talk a little bit about the law of large numbers: which is a principle of probability and statistics. The law of large numbers states that as a sample size grows, its mean will get closer and closer to the average of the whole population.

This is an important context for monitoring and setting SLAs. If you run an availability test from 5 locations once an hour, one time, and one of those tests fails. Your availability is down to 80 percent. If you run tests from 10 locations every 5 minutes for an hour that is 50 tests – and if 1 fails then your availability is now 98%! Less aggressive monitoring leaves you vulnerable to an SLA violation for a brief outage.

In conclusion, service level agreements are valuable for you and your customers. These three steps will help you look at SLAs as an opportunity than a restriction.

■ Make the right agreement based on baseline performance

■ Measure the correct things with the correct frequency

■ Take enough measurements to smooth out variability

John Lucania is Senior Sales Engineer at SmartBear Software.

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Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

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Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

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AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

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Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

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If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

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