Sign In
Sign In

Service Level Agreement (SLA): Meaning, Metrics, Examples

Service Level Agreement (SLA): Meaning, Metrics, Examples
Hostman Team
Technical writer
Infrastructure

An SLA is an agreement that defines the level of service a company provides to its customers. This term is usually used in IT and telecommunications. 

Unlike standard service contracts, a Service Level Agreement provides a very detailed description of service quality, operating modes, response times to incidents, and other parameters.

Main Characteristics of an SLA

A Service Level Agreement usually has the following characteristics:

  • Maximum possible transparency of all processes and interactions between the service provider and the client. When drafting the contract, vague wording that could be interpreted ambiguously in one direction or another is avoided.

  • Clearly defined rights and obligations understood by all participants in the agreement. For example, a provider commits to ensuring 99.9% service availability and to pay compensation if a lower figure is recorded, while the client has the right to request that compensation.

  • Expectation management. For instance, a client might expect 24/7, ultra-fast support even for minor issues, while the provider cannot offer such a service. In this case, the client should either lower their expectations or sign a contract with another provider. A third option is also possible: the provider may raise the service level if it benefits their business processes.

The agreement specifies the timeframes for fixing issues and solving other problems. It also describes possible compensations that the client may receive if the company fails to meet the declared metrics.

An SLA does not always need to be a large document. The main thing is that it clearly describes the core parameters of the service in understandable terms. For example, the AWS S3 SLA is only one page long. It lists monthly uptime percentages and the amount of compensation the client receives if the service fails to meet those thresholds.

What is Usually Included in an SLA

The example above from Amazon Web Services is not a standard; it is just one possible format tailored to a specific service.

An IT SLA often includes the following sections:

  • The procedure for using the service.

  • Responsibilities of both parties, including tools for mutual monitoring of performance.

  • Specific steps for troubleshooting and restoring functionality.

The agreement may also specify its term. In some cases, the parties describe in detail the procedure for adding new requirements for functionality or service availability.

When describing service quality, its parameters are also disclosed. These typically include:

  • Service availability.

  • Response time to a problem.

  • Time to fix incidents.

The SLA may also specify a metric for operating hours.

When describing payment procedures, it may indicate the billing model (e.g., pay-as-you-go, fixed rate, etc.). If penalties are provided, the SLA will specify the situations in which the provider must pay them. If the client is entitled to compensation, the SLA also describes the relevant situations and payment procedures.

Key SLA Parameters

SLA parameters are metrics that can be measured. The agreement should not contain vague phrases like “issues will be resolved quickly, before you even notice.” Such wording is unclear and prevents all participants from organizing proper workflows.

For example, the support schedule metric should clearly define when and for which groups of users technical support is available.

Suppose a company divides its clients into several groups:

  • Group 1: 24/7 phone and chat support.

  • Group 2: phone and chat support only on weekdays.

  • Group 3: chat-only support on weekdays.

Metrics are necessary so that all participants understand which services they receive, when, and in what scope.

From this, several key characteristics follow:

  • Metrics must always be publicly available.

  • Their descriptions must be unambiguous for all parties.

  • Clients must be notified in advance about metric changes.

When defining metrics, it’s important not to set overly strict requirements, as this significantly increases costs.

For instance, suppose a typical specialist can resolve a problem in 4 hours, while a higher-level expert can do it in 2 hours. Writing “2 hours” as the SLA metric is not ideal, as it would immediately make the expert’s work more expensive. If you specify “1 hour,” costs rise further due to the increased risk of penalties for non-compliance.

Other important metrics can include response time to a client request. The values may differ depending on the client’s status and problem criticality.

For example, a company providing IT outsourcing services might have:

  • Premium clients: response within 15 minutes.

  • Basic clients: response within 24 hours.

All of this must be clearly reflected in the SLA.

In addition to response time, there’s also incident resolution time. The logic for this parameter is similar: even if a client is important, requests are prioritized based on criticality.

For example:

  • If a client’s local office network stops working and all processes halt, that issue must be prioritized. The SLA may state that local network troubleshooting should take no more than 5 hours.

  • If the same client needs to add a few new devices to an already working network, the resolution time may be several hours or even days.

The combination of response time and resolution time forms downtime.

These and other parameters must be described in the SLA and accepted by all parties before cooperation begins. This approach reduces conflicts; everyone understands what to expect from each other.

Service Availability

For providers, one of the most important SLA parameters is service availability. It is usually measured in days, hours, or minutes over an agreed period. For example, a provider guarantees that a cloud computing service will be available 99.99% of the time during a year.

At first glance, the difference between SLA 99 and SLA 100 may seem small. But in absolute terms, it’s significant.

  • At 99%, you agree that servers may be down up to 4 days per year.

  • At 100%, downtime should be zero—something no company can guarantee.

That’s why SLAs are usually written with “nines”: e.g., 99.9%, 99.99%, etc.

For example, Hostman.com guarantees 99.98% uptime, meaning total annual downtime will not exceed 1 hour 45 minutes.

Some providers promise “five nines”: 99.999% uptime, or less than 15 minutes of downtime per year. But this is not always the best option. Two points to consider:

  1. The higher the SLA percentage, the higher the cost.

  2. Not every client needs such a high level. In most cases, 99.982% uptime (or slightly higher) is sufficient.

It’s important to check not only the number of nines but also the time unit used for measurement. By default, SLA indicators are calculated annually. For example, 99.95% availability equals no more than 4.5 hours of downtime per year.

If the contract doesn’t explicitly say that the time unit is “per year,” be sure to clarify, as some providers disguise monthly values as annual.

Another key concept is aggregate availability, which equals the lowest of all measured values.

Benefits of an SLA

Signing and adhering to an SLA benefits both parties.

For the company, it defines obligations and protects against unreasonable client demands, such as urgently fixing a minor issue in the middle of the night.

Other benefits include:

  • The provider can use the SLA to organize both external and internal processes, such as introducing different support levels depending on service criticality and client importance.

  • Clients gain clarity about what services they can expect, in what timeframes, and in what order, helping them plan their core operations.

SLA vs. SLO: What’s the Difference

An SLA can also be viewed as an indicator of user satisfaction, ranging from 0% to 100%.

Absolute satisfaction (100%) is impossible, just as it’s impossible to guarantee 100% uptime. Therefore, when choosing metrics, one should be realistic and select achievable values.

For example, if your team doesn’t provide 24/7 support, you shouldn’t promise it. When the team expands, you can update the SLA and delight clients by offering round-the-clock assistance.

To monitor service levels internally, another system is used: SLO (Service Level Objective). These are the target values the provider aims to achieve.

Example: Current capabilities are handling 50 tickets per business day, working 9:00 to 18:00, five days a week. These metrics are fixed in the SLA and shown to clients.

Meanwhile, the SLO document sets internal goals, for example, increasing the number of handled tickets to 75 per day or switching to 24/7 support. This directly affects the company’s future service level.

How to Create a Proper SLA

Start with a descriptive section, which usually includes:

  • A glossary
  • System description
  • Participant roles (users, support specialists)
  • Boundaries of operation: geography, time, functionality

The next section describes the services provided, giving the client a full understanding of what they can expect when signing with the provider.

Then comes the main section, describing the service level. It should include metrics that reflect quality and are easily measurable, as well as metric values that are specific numbers guiding all participants.

You can end the SLA with references to other documents that regulate service processes.

At all stages of preparing an SLA, remember: it is a regulatory document. Its main goal is control. The more control over the process, the better the SLA. If there is no control, such an agreement is meaningless.

Checklist: What to Consider When Preparing an SLA

If you are not signing but drafting an SLA to offer clients, pay attention to the following points:

  • Users. In large systems, divide users into groups and manage them separately. This helps allocate resources efficiently and avoid overload from different client types.

  • Services. Consider the criticality of each service for each client group. Example: You provide a CRM to trading companies. If they can’t use it, they lose money and complain, meaning it’s a high-criticality service. Printer replacement or user account creation can wait until tomorrow.

  • Service quality parameters. They must align with business goals and client needs. A typical example is incident resolution times, e.g., 24/7 support versus 9 a.m. to 5 p.m. on weekdays only.

An SLA is a document that must be announced to all users whenever it is introduced or updated, regardless of privilege level or service criticality.

SLA is a management tool that constantly evolves. You may find that current quality parameters harm business processes or no longer meet client expectations. In that case, management should decide to optimize processes or improve services.

The main goal of SLA indicators is not to attract users but to ensure open dialogue with them. Every participant accepts the agreement and commits to following it.

Violation of an SLA is grounds to claim compensation and terminate cooperation.

Infrastructure

Similar

Infrastructure

VMware Cloud Director: What It Is and How to Use It

VMware Cloud Director (formerly vCloud Director, or “vCD”) is a modern solution for cloud providers, mainly designed for building virtual data centers on top of physical infrastructure. The platform allows combining all of a data center’s physical resources into virtual pools, which are then offered to end users on a rental basis. It integrates tightly with VMware’s own technologies: vCenter and vSphere. vCenter is a set of tools for managing virtual infrastructure, and vSphere is the virtualization platform for cloud computing. Key Capabilities of VMware Cloud Director Creation of virtual data centers (vDCs) with full isolation of virtual services and resources. Migration of virtual machines (VMs) between clouds, and self-deployment of OVF templates. Snapshots and rollback of VM changes. Creation of isolated and routable networks with external access. Integrated, tiered storage with load balancing between virtual machines. Network security: perimeter protection and firewalling. Encryption of access to cloud resources to secure the virtual infrastructure. Unified authentication across all VMware services (single sign-on) so users don’t need to re-authenticate. Deployment of multi‑tier applications as ready-made virtual appliances, with VMs and OS images. Allocation of isolated resources for different departments within a single virtual structure. How VMware Cloud Director Works VMware Cloud Director uses a multi-tenant model. Rather than building a dedicated environment for every customer, it creates a shared virtual environment. This reduces infrastructure maintenance costs massively: for large cloud providers, savings can reach hundreds of thousands or even millions of dollars per year, which in turn lowers the rental cost for end users. Resource consumption model: Using vCenter and vSphere, the provider aggregates physical resources into a shared pool called a “virtual data center” (vDC). From that pool, resources are allocated into Org vDCs (Organizational Virtual Data Centers), which are the fundamental compute units consumed by customers. VMware Cloud Director syncs with the vSphere database to request and allocate the required amount of resources. Org vDCs are containers of VMs and can be configured independently. Customers can order different numbers of Org vDCs for different purposes, e.g., one Org vDC for marketing, another for finance, a third for HR. At the same time, interconnectivity can be established between these Org vDCs, forming a large, virtual private data center. It’s also possible to combine Org vDCs into multiple networks. Additionally, within those networks, one can create vApps (virtual applications) made up of VMs, each with their own gateways to connect to Org vDCs. This setup allows building virtual networks of any architecture, isolated or routable, to match various business needs. When such a network is created, the provider assigns a user from the customer organization to the role of network administrator. A unique URL is also assigned to each organization. The administrator is responsible for adding or removing users, assigning roles and resources, creating network services, and more. They also manage connections to services provided by the cloud provider. For instance, VM templates or OVF/OVA modules, which simplify backup and VM migration. Resource Allocation Models in VMware Cloud Director VMware Cloud Director supports several models for allocating resources, depending on how you want to manage usage: Allocation Pool: You set resource limits and also define a guaranteed percentage of the shared pool for a user. This  model is good when you want predictable costs but don’t need full reservation. Pay-As-You-Go: No guaranteed resources, only consumption-based; ideal if usage is variable. The model is flexible and fits users who want to grow gradually. Reservation Pool: You reserve all available resources; user requests are limited only by what the provider’s data center can supply. Reservation Pool is suited for organizations that need fixed performance and large infrastructure. Useful Features of VMware Cloud Director Here are several powerful features that optimize resource usage, routing, and tenant isolation: Delegation of Privileges You can assign network administrators from the users of each organization. These admins get broad rights: they can create and manage VMs, deploy OVF/OVA templates, manage VM migration, set up isolated/routable networks, balance VM workloads, and more. Monitoring and Analytics Cloud Director includes a unified system for monitoring and analyzing VM infrastructure: VMs, storage, networks, memory. All data is logged and visualized in a dedicated dashboard, making it easier to detect and resolve problems proactively. Networking Features Networking in vCloud Director supports dynamic routing, distributed firewalls, hybrid cloud integration, and flexible traffic distribution. Many of these features are now standard in the newer versions of Cloud Director. If you don’t already have some of them, you may need to upgrade your NSX Edge and convert it to an Advanced Gateway in the UI. Dynamic routing improves reliability by eliminating manual route configuration. You can also define custom routing rules based on IP/MAC addresses or groups of servers. With NSX Edge load balancing, incoming traffic can be distributed evenly across pools of VMs selected by IP, improving scalability and performance. Access Control and More You can create custom user roles in the Cloud Director UI to control access tailored to organizational needs. VMs can be pinned to specific ESXi host groups (affinity rules), which helps with licensing or performance. If Distributed Resource Scheduler (DRS) is supported, Cloud Director can automatically balance VMs across hosts based on load. Additional useful features include automatic VM discovery and import, batch updating of server cluster cells, and network migration tools.
25 November 2025 · 5 min to read
Infrastructure

Why Developers Use the Cloud: Capabilities and Advantages

Today, up to 100% of startups begin operating based on providers offering services ranging from simple virtual hosting to dedicated servers. In this article, we will examine the advantages of cloud computing that have led to its dominance over the “classic” approach of having a dedicated server in a separate room. Cloud Use Cases Typical scenarios for using cloud technologies include: Full migration of a business application to a remote server. For example, enterprise resource planning or accounting software. These applications support operation via remote desktop interfaces, thin clients, or web browsers. Migration of specific business functions. Increasingly, archival copies are stored in the cloud while software continues running locally. Alternatively, a backup SQL server node can be hosted remotely and connected in case the local server fails. Implementation of new services. Businesses are increasingly adopting automated systems for data collection and analytics. For example, Business Intelligence (BI) technologies have become popular, helping generate current and comparative reports. Interaction between local and cloud environments. Hybrid services are well established in large networks. For example, a retail store may operate a local network with an on-site server, receive orders from an online store, and send requests back to transport companies, and so on.This setup allows offline operation even if the internet is fully disconnected: processing sales, receiving shipments, conducting inventories, with automatic synchronization once connectivity is restored. These examples represent foundational scenarios, giving developers plenty of room to innovate. This is one reason more and more coders are attracted to the cloud. Advantages Now let’s examine the advantages and disadvantages of cloud computing. Yes, the technology has some drawbacks, including dependency on internet bandwidth and somewhat higher requirements for IT specialists. Experienced professionals may need retraining, whereas younger personnel who learn cloud technologies from the start do not face such challenges. Speed Software development often requires significant time and effort for application testing. Applications must be verified across multiple platforms, resolutions, and device types. Maintaining local machines dedicated to testing is inefficient. Cloud computing solves this by enabling rapid deployment of virtually any environment, isolated from other projects, ensuring it does not interfere with team development. High deployment speed and access to cloud services also encourage IT startups to launch almost “from scratch,” with minimal resource investment. The advantages of cloud services are especially critical when development volumes periodically expand. Purchasing hardware consumes a developer’s most valuable resource: time. In the cloud, selecting a plan takes just a few minutes, and the setup of a remote host for specific tasks can begin immediately. Hardware resources on the remote server, such as CPU cores, memory, and storage, can also be easily adjusted. Security Building a private server is expensive. Besides the powerful machines, you will need backup power and internet lines, a separate room with air conditioning and fire protection, and security personnel to prevent unauthorized access. Cloud providers automatically provide all these features at any service level. Other security advantages include: Easier identity and access management (IAM). Higher reliability for continuous business operations. Protection against theft or seizure of storage devices containing sensitive data. On a cloud server, users cannot simply plug in a USB drive to download files. Data does not reside on local machines, and access is controlled according to company policy. Users only see what their role allows. This approach reduces the risk of viruses and accidental or intentional file deletion. Antivirus software runs on cloud platforms, and backups are automatically maintained. Cost Efficiency Purchasing server hardware is a major budget burden, even for large corporations. Before the cloud boom, this limited IT development. Modern developers often need test environments with unique infrastructure, which may only be required temporarily. Buying hardware for a one-time test is inefficient. Short-term rental of cloud infrastructure allows developers to complete tasks without worrying about hardware maintenance. Equipment costs directly impact project pricing and developer competitiveness, so cloud adoption is advantageous. Today, most software is developed for cloud infrastructure, at least with support for it. Maintenance, storage, and disposal costs for IT equipment also add up. Hardware becomes obsolete even if unused. This makes maintaining developer workstations for “simple” desktop software costly. Offloading this to a cloud provider allows developers to always work with the latest infrastructure. Convenience Another cloud advantage is ease of use. Cloud platforms simplify team collaboration and enable remote work. The platform is accessible from any device: desktop, laptop, tablet, or smartphone, allowing work from home, the office, or even a beach in Bali. Clouds have become a foundation for remote work, including project management. Other conveniences include: Easy client demonstrations: Developers can grant access and remotely show functionality, or run it on the client’s office computer without installing additional components. Quick deployment of standard solutions: Setting up an additional workstation takes only a few minutes, from registering a new user to their trial login. New developers can quickly join ongoing tasks. Easy role changes: In dynamic teams, personnel often switch between projects. Access to project folders can be revoked with a few clicks once a task is completed. This also applies to routine work: adding new employees, blocking access for former staff, or reassigning personnel. A single administrative console provides an overview of activity and simplifies version tracking, archiving, and rapid deployment during failures. Stability Another factor affecting developer success is the speed of task completion. Beyond rapid deployment, system stability is critical. On local machines, specialists depend on hardware reliability. A failure could delay project timelines due to hardware replacement and configuration. Moving software testing to the cloud enhances the stability of local IT resources, particularly in hybrid systems. Cloud data centers provide Tier 3 minimum reliability (99.982% uptime) without additional client investment. Resources are pre-provisioned and ready for use according to the chosen plan. Development, testing, and operation are typically conducted within a single provider’s platform, in an environment isolated from client services. Conclusion Cloud technologies offer numerous advantages with relatively few drawbacks. Businesses and individual users value these benefits, and developers are encouraged to follow trends and create new, in-demand products. Virtually all commerce has migrated to the cloud, and industrial sectors, especially those with extensive branch networks and remote facilities, are also adopting cloud solutions.
25 November 2025 · 6 min to read
Infrastructure

PostgreSQL vs MySQL: Which Database Is Right for Your Business?

PostgreSQL and MySQL are among the most popular relational databases. In this article, we will examine the functional differences between them and compare their performance so that you can choose the database that is suitable for your business. PostgreSQL vs MySQL Despite the increasing similarity in features between PostgreSQL and MySQL, important differences remain. For example, PostgreSQL is better suited for managing large and complex databases, while MySQL is optimal for website and online-application databases because it is oriented toward speed. This follows from the internal structure of these relational database systems, which we will examine. Data Storage in PostgreSQL and MySQL Like any other relational databases, these systems store data in tables. However, MySQL uses several storage engines for this, while PostgreSQL uses only a single storage engine. On one hand, this makes PostgreSQL more convenient, because MySQL’s engines read and write data to disk differently. On the other hand, MySQL offers greater flexibility in choosing a data engine. However, PostgreSQL has an advantage: its storage engine implements table inheritance, where tables are represented as objects. As a result, operations are performed using object-oriented functions. Support The SQL standard is over 35 years old, and only the developers of PostgreSQL aim to bring their product into full compliance with the standard. The developers of MySQL use a different approach: if a certain feature simplifies working with the system, it will be implemented even if it does not fully conform to the standard. This makes MySQL more user-friendly compared to PostgreSQL. In terms of community support, the number of MySQL developers still exceeds those working with PostgreSQL, but you can receive qualified help in both communities. In addition, many free guides and even books have been written about PostgreSQL, containing answers to most questions. It is also worth noting that both platforms are free, but MySQL has several commercial editions, which can sometimes lead to additional expenses. Programming Languages Both systems support a wide range of programming languages. Among the popular ones are C++, Java, Python, lua, and PHP. Therefore, a company’s development team will not face difficulties implementing features in either system. Operating Systems MySQL is a more universal system that runs on Windows, Linux, macOS, and several other operating systems. PostgreSQL was originally designed for Linux, but with the REST API interface, it becomes an equally universal solution that operates on any OS. Data Processing PostgreSQL provides more capabilities for data processing. For example, a cursor is used for moving through table data, and responses are written to the memory of the database server rather than the client, as in MySQL. PostgreSQL also allows building indexes simultaneously for several columns. It supports different index types, allowing work with multiple data types. This database also supports regular expressions in queries. However, new fields in PostgreSQL can only be added at the end of a table. Parallel data processing is better organized in PostgreSQL because the platform has a built-in implementation of MVCC (multiversion concurrency control). MVCC can also be supported in MySQL, but only if InnoDB is used. Concerning replication, PostgreSQL supports logical, streaming, and bidirectional replication, while MySQL supports circular replication as well as master-master and master-standby. Replication refers to copying data between databases located on different servers. PostgreSQL and MySQL: Performance Comparison Testing is fair only when comparing two clean, “out-of-the-box” systems. Indexed testing provides the following results: Insertion: PostgreSQL is more than 2.7× faster, processing a 400,000-record database in 5.5 seconds versus 15 seconds for MySQL. Inner join: PostgreSQL processes 400,000 records in 1.1 seconds, MySQL in 2.8 seconds: a gain of more than 2.5×. Indexed sorting: PostgreSQL processes the same number of records in 0.9 seconds, MySQL in 1.5 seconds. Grouping: For the same 400,000-record database, PostgreSQL achieves 0.35 seconds, MySQL 0.52 seconds. Indexed selection: PostgreSQL is 2× faster: 0.6 seconds vs. 1.2 seconds. When it comes to updating data, PostgreSQL’s update time increases gradually as the number of records grows, while MySQL processes them in roughly the same time, starting from 100,000 records. This is due to different data-storage implementations. Nevertheless, PostgreSQL holds a significant advantage over MySQL even with large data volumes: 3.5 seconds versus 9.5 seconds for 400,000 records—more than 2.7× faster. Without indexes, PostgreSQL also shows surprisingly high performance, processing a 400,000-record database in 1.3, 0.7, and 2.2 seconds for inner join, selection, and update operations, respectively. Thus, PostgreSQL delivers an average performance advantage of about 2× (2.06). Although MySQL was originally positioned as a high-performance platform, constant optimization by the PostgreSQL development team has resulted in greater efficiency. Advantages for Developers Here we consider only the unique features characteristic of each platform. Therefore, we will not discuss support for MVCC or ACID, as these features are present in both systems. From a developer’s perspective, MySQL is advantageous because it: Provides increased flexibility and is easily scalable, with more than ten storage engines based on different data-storage algorithms. Handles small read-oriented databases more efficiently (i.e., without frequent writes). Is easier to manage and maintain, because it requires less configuration and fewer preparatory steps before starting work. From a developer’s perspective, PostgreSQL is advantageous because it: Offers an object-oriented approach to data, enabling inheritance and allowing the creation of more complex table structures that do not fit the traditional relational model. Handles write-oriented databases better, including validation of written data. Supports object-oriented programming features, enabling work with NoSQL-style data, including XML and JSON formats. Can support databases without limitations on data volume. Some companies use PostgreSQL to run databases as large as several petabytes. PostgreSQL and MySQL Comparison For clarity, the main features of both systems can be presented in a table:   PostgreSQL MySQL Supported OS Solaris, Windows, Linux, OS X, Unix, HP-UX Solaris, Windows, Linux, OS X, FreeBSD Use cases Large databases with complex queries (e.g., Big Data) Lighter databases (e.g., websites and applications) Data types Supports advanced data types, including arrays and hstore Supports standard SQL data types Table inheritance Yes No Triggers Supports triggers for a wide range of commands Limited trigger support Storage engines Single (Storage Engine) Multiple As we can see, several features are implemented only in PostgreSQL. Both systems support ODBC, JDBC, CTE (common table expressions), declarative partitioning, GIS, SRS, window functions, and many other features. Conclusion Each system has its strengths. MySQL handles horizontal scaling well and is easier to configure and manage. However, if you expect database expansion or plan to work with different data types, it is better to consider implementing PostgreSQL in advance. Moreover, PostgreSQL is a fully free solution, so companies with limited budgets can use it without fear of unnecessary costs.
24 November 2025 · 6 min to read

Do you have questions,
comments, or concerns?

Our professionals are available to assist you at any moment,
whether you need help or are just unsure of where to start.
Email us
Hostman's Support