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HA storage (high-availability storage),Enterprise High Availability Support

Apr 07,  · High availability (HA) is a characteristic of a system, which aims to ensure an agreed level of operational performance, usually uptime, for a higher than normal period. Key Principles of High Availability The following are the key principles of High Availability.

What is High Availability (HA)? - Definition from Techopedia. High availability - Amazon Web Services (AWS).

A service provider will typically provide availability metrics in their service level agreements SLAs. If the service level agreement for availability is A highly available system should be able to quickly recover from any sort of failure state to minimize interruptions for the end user. Best practices for achieving high availability include:.

Backups and failover processes are crucial components to accomplishing high availability. This can be attributed to the fact that some computer systems or networks consist of individual components, either hardware or software, that must be fully operational in order for the entire system to be available. Backup components should be built into the infrastructure of the system. For example, if a server fails, an organization should be able to switch to a backup server.

Ensuring there are data backups will help ensure high availability in the case of data loss, corruption or storage failures. A datacenter should be able to quickly recover from data loss for any reason to maintain high availability. Microsoft's investments in its cloud products will be the highlight of the conference, with Microsoft Teams expected to be in the It is also possible to completely remove routing from Networking, and instead rely on hardware routing capabilities.

In this case, the switching infrastructure must support layer three routing. Application design must also be factored into the capabilities of the underlying cloud infrastructure. If the compute hosts do not provide a seamless live migration capability, then it must be expected that if a compute host fails, that instance and any data local to that instance will be deleted. However, when providing an expectation to users that instances have a high-level of uptime guaranteed, the infrastructure must be deployed in a way that eliminates any single point of failure if a compute host disappears.

This may include utilizing shared file systems on enterprise storage or OpenStack Block storage to provide a level of guarantee to match service features. If using a storage design that includes shared access to centralized storage, ensure that this is also designed without single points of failure and the SLA for the solution matches or exceeds the expected SLA for the Data Plane.

Some services are commonly shared between multiple regions, including the Identity service and the Dashboard. In this case, it is necessary to ensure that the databases backing the services are replicated, and that access to multiple workers across each site can be maintained in the event of losing a single region. Multiple network links should be deployed between sites to provide redundancy for all components.

This includes storage replication, which should be isolated to a dedicated network or VLAN with the ability to assign QoS to control the replication traffic or provide priority for this traffic. If the data store is highly changeable, the network requirements could have a significant effect on the operational cost of maintaining the sites. If the design incorporates more than one site, the ability to maintain object availability in both sites has significant implications on the Object Storage design and implementation.

It also has a significant impact on the WAN network design between the sites. If applications running in a cloud are not cloud-aware, there should be clear measures and expectations to define what the infrastructure can and cannot support. An example would be shared storage between sites. It is possible, however such a solution is not native to OpenStack and requires a third-party hardware vendor to fulfill such a requirement.

Another example can be seen in applications that are able to consume resources in object storage directly. Connecting more than two sites increases the challenges and adds more complexity to the design considerations. Multi-site implementations require planning to address the additional topology used for internal and external connectivity.

Some options include full mesh topology, hub spoke, spine leaf, and 3D Torus. Outages can cause partial or full loss of site functionality. There are many ways to keep users happy and unaware of the issues behind the scenes - all user-related modifications can be immediately presented to the user, to give an impression that everything is just fine. Other users will not see those changes until the write queue is flushed to the database.

Of course, it depends on what kind of data we are talking about - in many cases e. Eventually, the database has to be brought up again. In short, imagine that you could create a RAID1 over the network. This is, more or less, what DRBD does. You have two nodes or three in the latest versions , each of them have a block device dedicated to storing data. One of them is in active mode, mounted and basically works as a database server.

Replication can be synchronous, asynchronous or memory synchronous. The point of this exercise is that, should the active node fail, the passive nodes have an exact copy of the data if you use replication in synchronous mode, that is. You can then promote a passive node to active, mount the block volume, start the services you want like, MySQL for example , and you have a replacement node up and running.

There are couple of disadvantages in the DRBD setup. One of them is the active - passive approach. For starters, you have to have two nodes while you can use only one of them.

You cannot use the passive node for ad-hoc or reporting queries, you cannot take backups off it. Last but not least, we are talking about 1: The concept is simple - you have a master that replicates to one or more slaves. If a slave goes down, you use another slave. If the master is down, you promote one of the slaves to act as a new master. When you get into details, though, things become more complex. There are options to automate it, though. It is designed to find a slave that is the most up to date compared with the master.

It will also try to apply any missing transactions to this slave if the binary logs on the master are available. Finally, it should reslave all of the slaves, wherever possible, to the new master. MMM is another solution that performs failover, although this might not work well for some users. Along with MySQL 5. For starters, you can easily reslave any slave to any master - something which had not been possible with regular replication.

In addition, in such setup it is possible to use binlog servers as a source of missing transactions. Oracle also created a tool - mysqlfailover which performs periodical or constant health checks for the system and has support for both automated and user-initiated failover. To eliminate this problem, semi-sync replication was added to MySQL. It ensures that at least one of the slaves got the transaction and wrote it in its relay logs.

It may be lagging but the data is there. Therefore, if you use MySQL replication, you may consider setting up one of your slaves as a semi-sync slave. This is not without impact, though - commits will be slower since the master needs to wait for the semi-sync slave to log the transactions. It provides internal redundancy for the data as well as in connectivity layer.

This is one of the best solutions, as long as it is feasible to use in your particular case. The way it stores data partitioned across multiple data nodes makes some of the queries much more expensive as there is quite a bit of network activity needed to grab the data and prepare a result.

Actually, it does use InnoDB as storage engine. Another important aspect, when comparing Galera to NDB cluster, is the fact that every node has a full dataset available. More information on this online tutorial for Galera Cluster. Both clusters, practically speaking there are some exceptions on both sides , work as a single instance. Therefore it is not important which node you connect to as long as you get connected - you can read and write from any node. From those options, Galera is a more likely choice for the common user - its workload patterns are mostly close to the standalone MySQL, maintenance is also somewhat similar to what users are used to do.

This is one of the biggest advantages of using Galera. This webinar discusses the differences between Galera and NDB. Having MySQL setup one way or another is not enough to achieve high availability. Here, a proxy layer can be very useful.

Distributed and High Availability Tableau Server. Top 5 High Availability Dedicated Server Solutions. High Availability Data Integrity and Data Protection. High Availability High Availability is a system design approach which ensures that service is provided continuously, and with the expected level of performance. Users want their applications to be continuously available. Achieving this goal requires a highly-available storage system.

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Many modern data centers are based on virtualization, and high availability is used to ensure the availability of virtual machines within a virtualized environment.

Many data center managers see more using vSphere High Availability or Citrix XenServer high-availability features for virtual machines.

However, using high availability for your virtual environment doesn't guarantee that vital services, such as a Web server or an Oracle database, will click the following article available at all times, which makes an excellent case click to see more virtualizing the operating system OS as [EXTENDANCHOR]. Pacemaker is a common resource manager that is used for OS-level high availability.

Femme moche avis tip is the first in a series about high availability in the data center, and it explains how to increase the availability of vital services by using methods that go beyond what you can do from a virtualization platform. The benefits and drawbacks of high availability in the data high availability of data online In many data centers, virtualization, or a private cloud, is used as the foundation of the IT infrastructure.

[EXTENDANCHOR] of running multiple applications and processes on a server, servers are often used like check this out, offering one service and occasionally supporting other services.

There is one important drawback to that approach though--if the service goes down while chat sex kostenlos virtual server keeps running, the high availability offered by your virtualization software or hardware won't detect anything. High-availability features from virtualization platforms monitor the availability of VMs and not the availability high availability of data online services.

But it is the availability of services, not VMs, cherche une femme pour ce soir is important in the data center.

Therefore, high availability just click for source the OS level is an important consideration.

A go here high-availability cluster, offered at the OS level, is responsible for providing services. That means the cluster, and not individual servers, are also responsible for starting the services. The cluster also decides which node will high availability of data online the service. While doing this, the cluster can consider other factors, such as a specific load order between different services, time constraints or other rules that determine which node will offer the service.

Using high-availability in your virtual environment does not provide you source the [MIXANCHOR] possible protection in the data center, as it does lack high availability of data online capability to handle specific services individually. Using high availability at the OS level ensures that if a monitored device or system goes down, the service will start on another node in the high-availability cluster, or even on the same node if that makes sense from the perspective of the cluster.

Another important capability that the High availability of data online high-availability cluster brings that isn't available from the VM high-availability cluster is service high availability of data online. Let's take the simple example of a Web server that is configured in a high-availability environment. Typically, some [MIXANCHOR] are involved when working with a Web server, high availability of data online as the site de pour d un soir of the storage hosting the document root offered by that Web server, or the database that contains the records that have to be offered by the Web server.

In an OS high-availability solution, it is fairly easy to define these kinds of dependencies. In larger enterprise environments, high availability from the OS level used dating apps belgium never really disappeared. For these environments, which are often complex and scalable Unix environments, the high availability offered by the virtualization software or hardware is just not enough.

Recently, many companies have started realizing this and are now adding OS-level ecrire rencontre amoureuse availability to protect their mission-critical services. High-availability software is available for all major OSes, including all Unix, Linux and Windows platforms. Among the most-used solutions are Pacemaker for High availability of data online and Veritas for Unix environments.

In the next tip in this series, you'll read how to improve availability of vital services in your data center by deploying high-availability solutions. Sander van Vugt is an independent trainer and consultant living in the Netherlands. Van Vugt is an expert in Linux high availability, virtualization and performance and has completed several [EXTENDANCHOR] that implement all three.

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Key Terms: High Availability Fault Tolerance and DR

In the real world, there can be situations when a dip in performance of your servers might occur from events ranging from a sudden spike in traffic can lead to a sudden power outage. It can be much worse and your servers can be crippled- irrespective of whether your applications are hosted in the cloud or a physical machine.

Such situations are unavoidable. The answer to the problem is the use of High Availability HA configuration or architecture. High availability architecture is an approach of defining the components, modules or implementation of services of a system which ensures optimal operational performance, even at times of high loads.

Although there are no fixed rules of implementing HA systems, there are generally a few good practices that one must follow so that you gain the most out of the least resources. Let us define downtime before we move further. Downtime is the period of time when your system or network is not available for use, or is unresponsive.

Downtime can cause a company huge losses, as all their services are put on hold when their systems are down. Those are huge numbers, even for a company of the size of Amazon. There are two types of downtimes- scheduled and unscheduled. A scheduled downtime is a result of maintenance, which is unavoidable.

This includes applying patches, updating softwares or even changes in the database schema. An unscheduled downtime is, however, caused by some unforeseen event, like hardware or software failure.

This can happen due to power outages or failure of a component. Scheduled downtimes are generally excluded from performance calculations. The prime objective of implementing High Availability architecture is to make sure you system or application is configured to handle different loads and different failures with minimal or no downtime. The are multiple components that help you in achieving this, and we will be discussing them briefly.

Availability can be measured as the percentage of time that systems are available. Where n is the total number of minutes in a calendar month and y is the total number of minutes that service is unavailable in the given calendar month. High availability simply refers to a component or system that is continuously operational for a desirably long period of time.

High availability is a requirement for any enterprise that hopes to protect their business against the risks brought about by a system outage.

These risks, can lead to millions of dollars in revenue loss. The fact that going for high availability architecture gives you higher performance is all right, but it comes at a big cost too. You must ask yourself if you think the decision is justified from the point of view of finance. A decision must be made on whether the extra uptime is truly worth the amount of money that has to go into it. You must ask yourself how damaging potential downtimes can be for your company and how important your services are in running your business.

It can actually lead to the opposite as more components increases the probability of failures. Modern designs allow for distribution of the workloads across multiple instances such as a network or a cluster, which helps in optimizing resource use, maximizing output, minimizing response times and avoiding overburden of any system in the process known as load balancing.

It also involves switching to a standby resource like a server, component or network in the case of failure of an active one, known as Failover systems. Imagine that you have a single server to render your services and a sudden spike in traffic leads to its failure or crashes it. In such a situation, until your server is restarted, no more requests can be served, which leads to a downtime. The obvious solution here is to deploy your application over multiple servers. You need to distribute the load among all these, so that none of them are overburdened and the output is optimum.

You can also deploy parts of your application on different servers. For instance, there could be a separate server for handling mails or a separate one for processing static files like images like a Content Delivery Network. Databases are the most popular and perhaps one of the most conceptually simple ways to save user data.

One must remember that databases are equally important to your services as your application servers. Databases run on separate servers like the Amazon RDS and are prone to crashes as well. Redundancy is a process which creates systems with high levels of availability by achieving failure detectability and avoiding common cause failures.

This can be achieved by maintaining slaves, which can step in if the main server crashes. Another interesting concept of scaling databases is sharding. Scaling up your applications and then your databases is a really big step ahead, but what if all the servers are at the same physical location and something terrible like a natural disaster affects the data center at which your servers are located?

This can lead to potentially huge downtimes. It is, therefore, imperative that you keep your servers in different locations. Most modern web services allow you to select the geographical location of your servers. You should choose wisely to make sure your servers are distributed all over the world and not localized in an area.

Within this post, I have tried to touch upon the basic ideas that form the idea of high availability architecture. In the final analysis, it is evident that no single system can solve all the problems. Hence, you need to assess your situation carefully and decide on what options suit them best.

In order to curb system failures and keep both planned and unplanned downtimes at bay, the use of a High Availability HA architecture is highly recommended, especially for mission-critical applications. Availability experts insist that for any system to be highly available, its parts should be well designed and rigorously tested. The design and subsequent implementation of a high availability architecture can be difficult given the vast range of software, hardware and deployment options.

However, a successful effort typically starts with distinctly defined and comprehensively understood business requirements. The chosen architecture should be able to meet the desired levels of security, scalability, performance and availability. The only way to guarantee compute environments have a desirable level of operational continuity during production hours is by designing them with high availability.

In addition to properly designing the architecture, enterprises can keep crucial applications online by observing the recommended best practices for high availability. The hallmark of a good data protection plan that protects against system failure is a sound backup and recovery strategy.

Valuable data should never be stored without proper backups, replication or the ability to recreate the data. Every data center should plan for data loss or corruption in advance. Data errors may create customer authentication issues, damage financial accounts and subsequently business community credibility. The recommended strategy for maintaining data integrity is creating a full backup of the primary database then incrementally testing the source server for data corruptions.

Creating full backups is at the forefront of recovering from catastrophic system failure. Even with the highest quality of software engineering, all application services are bound to fail at some point. High availability is all about delivering application services regardless of failures.

Clustering can provide instant failover application services in the event of a fault. A High Availability cluster includes multiple nodes that share information via shared data memory grids. This means that any node can be disconnected or shutdown from the network and the rest of the cluster will continue to operate normally, as long as at least a single node is fully functional. Each node can be upgraded individually and rejoined while the cluster operates. The high cost of purchasing additional hardware to implement a cluster can be mitigated by setting up a virtualized cluster that utilizes the available hardware resources.

Load balancing is an effective way of increasing the availability of critical web-based applications. When server failure instances are detected, they are seamlessly replaced when the traffic is automatically redistributed to servers that are still running. Not only does load balancing lead to high availability it also facilitates incremental scalability. It facilitates higher levels of fault tolerance within service applications.

High availability architecture traditionally consists of a set of loosely coupled servers which have failover capabilities. Failover is basically a backup operational mode in which the functions of a system component are assumed by a secondary system in the event that the primary one goes offline, either due to failure or planned down time.

In both scenarios, tasks are automatically offloaded to a standby system component so that the process remains as seamless as possible to the end user. Failover can be managed via DNS, in an well-controlled environment. Geo-redundancy is the only line of defense when it comes to preventing service failure in the face of catastrophic events such as natural disasters that cause system outages. Like in the case of geo-replication, multiple servers are deployed at geographical distinct sites.

The locations should be globally distributed and not localized in a specific area. It is crucial to run independent application stacks in each of the locations, so that in case there is a failure in one location, the other can continue running. Ideally, these locations should be completely independent of each other. Despite the fact that applying the best practices for high availability is essentially planning for failure; there are other actions an organization can take to increase their preparedness in the event of a system failure leading to downtime.

Organizations should keep failure or resource consumption data that can be used to isolate problems and analyze trends. This data can only be gathered through continuous monitoring of operational workload. A recovery help desk can be put in place to gather problem information, establish problem history, and begin immediate problem resolutions. A recovery plan should not only be well documented but also tested regularly to ensure its practicality when dealing with unplanned interrupts.

Staff training on availability engineering will improve their skills in designing, deploying, and maintaining high availability architectures. Security policies should also be put in place to curb incidences of system outages due to security breaches. FileCloud High Availability Architecture Following diagram explains how FileCloud servers can be configured for High Availability to improve service reliability and reduce downtime.

Click here for more details. Try FileCloud for Free! Popular Posts Tech tip: How to do hard refresh in Chrome, Firefox and IE? Why is it Important? Leave This Blank Too: Do Not Change This: We will send an email with details to download the server and client apps.