.net qr code library Clustering in .NET framework

Creation QR Code in .NET framework Clustering

Clustering
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One of the more expensive options with physical servers is the notion of clusters. In order to build a cluster, you first build your primary server (or node), which has a defined set of shared disks (called a resource group). Sharing disks between multiple nodes does not require a SAN, but having a SAN can make your life a little easier. You then add nodes to the cluster, with each node being defined to that same resource group. The entire cluster appears on your network as a single server instance, but it is really made up of multiple server instances. You will hear talk of primary nodes, secondary nodes, or failover nodes; all that talk amounts to fancy words for a server instance.
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Figure 3 8 provides an example of a four-node cluster. The arrangement may at first glance appear similar to that in Figure 3 7. The difference is that all four nodes in the cluster share access to the same set of database disks. Furthermore, the outside world sees the cluster as a single database instance.
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Figure 3 8. A four-node cluster built around shared disks
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The reason clusters can be so expensive is because they typically require a lot of additional hardware like a SAN, and each node in the cluster needs to have very similar hardware. However, with virtualization you can look to use clusters with virtual servers and reduce your costs. You can even find some third-party software applications that help you to failover your virtual instances during times of peak usage, which will (in theory) help to increase your availability (often called uptime). If this all sounds too good to be true, that s because it is too good to be true. There simply must be a downside to clustering, even on virtual servers, right Absolutely. Many times I have had the opportunity to load software onto a cluster. And despite the vendor assuring me that I only need to load their software onto the primary node, I will often find their software not working should the cluster fail over to a different node. Historically you will find horror stories relating to the application of SQL hotfixes and service packs to the primary node, and their failure to work on the other nodes. And while each version of SQL and server OS helps to reduce those headaches, you should be aware that they can still happen. The other downside to the use of clusters is the increase in the number of servers that your shop needs to administer. While having three nodes sounds like a great way to achieve HA, it may not sound so great to the people that need to administer those
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CHAPTER 3: Some Basics
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instances and apply things like service packs. Believe me, administrators enjoy having a weekend off every now and then, same as everyone else. Need more downsides to clusters How about the amount of time it takes for the failover to happen Depending on your configuration it can take less than a minute to several minutes. And what about those transactions and connections in flight during the failover Will they see an interruption in service Probably, so your application had better be able to handle such an event; otherwise, your phone will ring off the hook the minute people perceive there is an issue. Need more downside Well, how about that clusters do not protect you from a disk failure If you are going about setting up clusters and think that they are a good DR strategy, then you are looking Mr. Murphy right in the face and laughing at his laws.
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Log shipping is a traditional method of HA, allowing for you to maintain your data in two (or more) places at the same time. The idea is quite simple: 1. 2. 3. Do a backup of your transaction log on your production server. Copy that backup file to another server. Restore that backup file to another server.
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And there you go you now have a database (see Figure 3 9) that should look just like the database that went offline for whatever reason. Well, close enough to the database that went offline. I mean, how often are you doing those transaction log backups Every minute Five minutes Ten Fifteen
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