When setting up robust production systems, minimizing downtime and service interruptions is often a high priority. Regardless of how reliable your systems and software are, problems can occur that can bring down your applications or your servers.
Implementing high availability for your infrastructure is a useful strategy to reduce the impact of these types of events.
New strategies for modern service assurance
It can then restart the problem application that tripped up the crashed server. Typically, availability as a whole is expressed as a percentage of uptime defined by service level agreements (SLAs). High Availability (HA) describes systems that are dependable enough to operate continuously without failing. Now you’ve got some additional terminology added to your cloud vocabulary.
Passive redundancy is used to achieve high availability by including enough excess capacity in the design to accommodate a performance decline. The simplest example is a boat with two separate engines driving two separate propellers. The boat continues toward its destination despite failure of a single engine or propeller. A more complex example is multiple redundant power generation facilities within a large system involving electric power transmission. Malfunction of single components is not considered to be a failure unless the resulting performance decline exceeds the specification limits for the entire system.
Translations of availability
Read on to learn what availability is, how to measure it, and what best practices your team should adopt to prevent costly service disruptions. Find out the questions to ask about cloud applications to determine the level of availability they need and whether all that availability is necessary. HA systems are used in situations and industries where it is critical the system remains operational.
For this reason, organizations evaluate the IT service levels necessary to run business operations smoothly, to ensure minimal disruptions in event of IT service outages. Multiple systems operate in tandem to achieve fault tolerance, identically mirroring applications and executing instructions together. When the main system fails, another system should take over with no loss in uptime.
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%). This means that in most verticals, especially software-driven services, a high availability architecture makes a lot of sense. It is highly cost-effective compared to a fault tolerant solution, which cannot handle software issues in the same way. These high availability servers both possess failover capabilities and monitor each other. If the primary server has issues, only one of the backup servers needs to detect them.
To remove this single point of failure, as mentioned before, we need to implement a cluster of load balancers behind a Reserved IP. Corosync and Pacemaker are popular choices for creating such a setup, on both Ubuntu and CentOS servers. With the described scenario, which is not uncommon in real life, the load balancing layer itself remains a single point of failure. With an increased demand for reliable and performant infrastructures designed to serve critical systems, the terms scalability and high availability couldn’t be more popular. While handling increased system load is a common concern, decreasing downtime and eliminating single points of failure are just as important. High availability is a quality of infrastructure design at scale that addresses these latter considerations.
- A high availability cluster is a set of hosts that operate as a single system to provide continuous uptime.
- With an increased demand for reliable and performant infrastructures designed to serve critical systems, the terms scalability and high availability couldn’t be more popular.
- The services were available only as long as the lights were on and the doors open.
- A poorly performing but still online service is not a highly available system.
Ideally, you’ll apply these tips at the start of your app design, but you’ll also be able to use the best practices below on an existing system. It is impossible for systems to be available 100% of the time, so true high-availability systems generally strive for five nines as the standard of operational performance. Furthermore, these methods are capable to identify the most critical items and failure modes or events that impact availability. 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. Multiple redundant nodes must be connected together as a cluster where each node should be equally capable of failure detection and recovery.
One of the goals of high availability is to eliminate single points of failure in your infrastructure. A single point of failure is a component of your technology stack that would cause a service interruption if it became unavailable. As such, any component that is a requisite for the proper functionality of your application that does not have redundancy is considered to be a single point of failure.
To eliminate single points of failure, each layer of your stack must be prepared for redundancy. For instance, imagine you have an infrastructure consisting of two identical, redundant web servers behind a load balancer. The traffic coming from clients will be equally distributed between the web servers, but if one of the servers goes down, the load balancer will redirect all traffic to the remaining online server.
Network availability is measured as a percentage and is monitored to ensure the network runs consistently for end users. To obtain redundancy, IT organizations should follow an N+1, N+2, 2N or 2N+1 strategy. N represents the definition of availability number of, say, servers needed to keep the system running. An N+1 model requires all the servers needed to run the system plus an additional one. A 2N model would require twice as many servers as the system normally needs.
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