A service level agreement (“SLA”) formalizes an organization’s availability objectives and requirements. The idea is to make your products, services, and tools available to your customers and employees at any time from anywhere using any device with an internet connection. Cloud computing scalability refers to how well your system can react and adapt to changing demands. As your company grows, you want to be able to seamlessly add resources without losing quality of service or interruptions. As demand on your resources decreases, you want to be able to quickly and efficiently downscale your system so you don’t continue to pay for resources you don’t need. Availability is the assurance that an enterprise’s IT infrastructure has suitable recoverability and protection from system failures, natural disasters or malicious attacks.

While vendors work to promise and deliver upon SLA commitments, certain real-world circumstances may prevent them from doing so. In that case, vendors typically don’t compensate for the business losses, but only reimburses credits for the extra downtime incurred to the customer. Additionally, vendors only promise “commercially reasonable” efforts to meet certain SLA objectives.

Service-Oriented Architecture vs Microservices Architecture: Comparing SOA to MSA

High availability minimizes or (ideally) eliminates service downtime regardless of what incident the company runs into (a power outage, hardware failure, unresponsive apps, lost connection with the cloud provider, etc.). The term reliability refers to the ability of computer hardware and software to consistently perform according to certain specifications. More specifically, it measures the likelihood that a specific system or application will meet its expected performance levels within a given time period. In computing, the term availability is used to describe the period of time when a service is available, as well as the time required by a system to respond to a request made by a user.

On the other hand, implementing high availability strategies nearly always involves software. This website is using a security service to protect itself from online attacks. There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data.

No system is entirely failsafe—even a five-nines setup requires a few seconds to a minute to perform failover and switch to a backup component. Some systems are self-monitoring and use diagnostics to automatically identify and correct software and hardware faults before more serious trouble occurs. For example, OSes such as Microsoft Windows 365 include built-in features that automatically detect and fix computer issues, and antivirus software and spyware autoprotect features include detection and removal programs. Ideally, maintenance and repair operations cause as little downtime or disruption as possible.

Failure is only significant if this occurs during a mission critical period. Online shopping stores are expected to sell products regardless of time zone, business hours, and holidays—the last is even the source of the largest revenue streams globally. Social media outlets keep users engaged because their friends and https://www.globalcloudteam.com/ connections are online and available for communication any time of the day. Each layer of a highly available system will have different needs in terms of software and configuration. However, at the application level, load balancers represent an essential piece of software for creating any high availability setup.

Cloud computing 101: The interrelationship of scalability, reliability, and availability

High availability (HA) is a characteristic of a system that aims to ensure an agreed level of operational performance, usually uptime, for a higher than normal period. HAProxy (High Availability Proxy) is a common choice for load balancing, as it can handle load balancing at multiple layers, and for different kinds of servers, including database servers. Availability is often expressed as a percentage indicating how much uptime is expected from a particular system or component in a given period of time, where a value of 100% would indicate that the system never fails. For instance, a system that guarantees 99% of availability in a period of one year can have up to 3.65 days of downtime (1%).

Lie, Hwang, and Tillman [1977] developed a complete survey along with a systematic classification of availability. Proper planning and cloud visualization can help you address faults quickly so that they don’t become huge problems that keep people from accessing your cloud offerings. The cloud makes it easy to build fault-tolerance into your infrastructure.

Reliability

Typically, scheduled downtime is a result of maintenance that is disruptive to system operation and usually cannot be avoided with a currently installed system design. Scheduled downtime events might include patches to system software that require a reboot or system configuration changes that only take effect upon a reboot. In general, scheduled downtime is usually the result of some logical, management-initiated event. Unscheduled downtime events typically arise from some physical event, such as a hardware or software failure or environmental anomaly.

• If one component goes down (e.g., one of the on-site servers or a cloud-based app that connects the system with an edge server), the entire HA system must remain operational.
• To achieve high availability, first identify and eliminate single points of failure in the operating system’s infrastructure.
• An HA system must almost instantly redirect requests to a backup setup in case of failure.
• For example, you can add processing power or more memory to a server by linking it with other servers.

Availability must be measured to be determined, ideally with comprehensive monitoring tools (“instrumentation”) that are themselves highly available. If users can be warned away from scheduled downtimes, then the distinction is useful. But if the requirement is for true high availability, then downtime is downtime whether or not it is scheduled. There are three principles of systems design in reliability engineering which can help achieve high availability. For critical infrastructure, such as hospital emergency rooms or power supply to nuclear power cooling plants, even the six-nines could potentially risk human lives.

The second primary classification for availability is contingent on the various mechanisms for downtime such as the inherent availability, achieved availability, and operational availability. Mi [1998] gives some comparison results of availability considering inherent availability. An important consideration in evaluating SLAs is to understand how well it aligns with business goals. The resulting strategy is often a tradeoff between cost and service levels in context of the business value, impact, and requirements for maintaining a reliable and available service. This means that in most verticals, especially software-driven services, a high availability architecture makes a lot of sense.

For such specific use cases, several redundant layers of IT system and utility power infrastructure are deployed to reach High Availability figures close to 100%, such as nine-nines or perhaps, even better. Availability percentage is calculated over a significant duration where typically at least one downtime incident has occurred. This can be a few hours, days, or even months, especially since IT incidents can occur for a variety of distinct causes. It then gives the duration of downtime that can be expected with a particular percentage of Availability.

There may be singular components in your infrastructure that are not single points of failure. One important question is whether you have mechanisms in place to detect any data loss or other system failures and adapt quickly. Another is whether you have redundant system components in place that can cover the same tasks. In this process, users set up servers to switch responsibilities to a remote server as needed. They should also evaluate each piece of hardware for durability using vendor metrics such as mean time between failures (MTBF). Typically, availability as a whole is expressed as a percentage of uptime defined by service level agreements (SLAs).

This kind of system retains the memory and data of its programs, which is a major benefit. However, it may take longer to adapt to failures for networks and systems that are more complex. In addition, software problems that cause systems to crash can sometimes cause redundant systems operating in tandem to fail similarly, causing a system-wide crash. Highly available hardware includes servers and components such as network interfaces and hard disks that resist and recover well from hardware failures and power outages.

It is highly cost-effective compared to a fault tolerant solution, which cannot handle software issues in the same way. High availability and fault tolerance both refer to techniques for delivering high levels of uptime. However, fault tolerant vs high availability strategies achieve that goal differently. These include recovery time, and both scheduled and unscheduled maintenance periods. Use PhoenixNAP’s backup and restore solutions to create cloud-based backups of valuable data and ensure resistance against cyberattacks, natural disasters, and employee error.