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Best High Performance VPS Server 2020

Servers with the most modern hardware provide for full speed of your virtual server. Without exception the fastest technology, BestPATH routing and SSD drives ensure a high degree of speed.

Fast Response Times

High performance VPS are known for their fast response times. Modern servers are directly connected to the core systems without detours and without long distances. This ensures low latencies and maximum speed.

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Different Fire Compartments

Different fire compartments are no problem for High Performance VPS. Sometimes you just need a little bit more security. A cluster is not operated correctly if the backup servers are located in the same fire compartment as the main system. Good providers ensure that the backup systems are always located in a separate fire compartment.

High Availability

Air conditioning systems, power engineering and IP connections must be 99.9% accessible. And if nothing should fail for a long time, it should be possible to book corresponding SLAs.

Premium Managed Service

With a Managed cloud VPS server you don’t have to take care of anything and can concentrate on the maintenance of your websites or projects. With Managed Services, providers ensure that the servers are always up and running.

The Cause For Slow Workloads In Older Systems

Virtualization has arrived in the data centers. After the servers, storage and networks are now also largely virtualized. Software-defined storage (SDS) is derived from virtualization. The principle is the same: Hardware resources are abstracted. This leads to cost savings and more efficient systems.

If you, like me, prefer fact-based analysis of your IT problems, then this is a discussion about storage in virtual environments that doesn’t link, mix, or otherwise draw the wrong conclusions from different data.

Almost as quickly as server virtualization came into fashion as more than just a testing tool, there were rumors emerging about the bad impact that traditional storage has on that environment. It was repeatedly reported that storage slows down workloads after they were virtualized and realized in hypervisor environments.

There have been emerging rumors about the poor impact that traditional storage has on this environment.

This demonization of traditional storage systems has mostly focused on the known shortcomings of these products and topologies. For years, storage vendors have equipped their disk boxes with proprietary controllers and proprietary software features to both lock in customers and prevent competitive integration.

Combining this with the industry’s reluctance to operate with each other and find a common approach to management, you have all the ingredients for a fragile and expensive infrastructure together.

The above points can hardly be denied. The situation worsened so much in the early 2000s that analysts often advised their customers to buy storage from only one vendor in the hope that this homogeneity would ensure coherent management. This is the linchpin of a cost-sensitive strategy.

In summary, unmanaged storage was the root cause of many IT problems. It often meant an over-allocation and under-utilization of resources, which drove up the demand for capacity and thus CAPEX.

Of course, the companies also needed more IT staff with specific experience in storage architectures and administration to manage their systems and connectivity, which in turn drove up OPEX.

Is Storage Really To Blame For Bottlenecks?

While it is fair to say that these characteristics made storage unattractive and required revision, they do not explain the problem of poor virtual server performance.

And yet VMware and other hypervisor vendors insist on drawing false relationships and causal relationships between problematic VPS performance and proprietary storage. This resulted in VMware’s vStorage APIs for Array Integration in 2006 and the recently introduced Virtual SAN. Both still address the performance problem by attacking the “bad” storage.

There are instances where storage latencies can slow down the performance of the application. These include the speed of the storage system and the network or fabric that connects the storage to the servers. This is known and is typically mitigated by a combination of caching and parallel processes.

When the processors are running hot, this often indicates a problem in the application or in the hypervisor software.

The caching collects the writes on a fast storage layer, making the slower memory invisible to the application. Parallel processes accelerate the number of tasks to complete, such as I/O processes, so that more workloads can be processed in less time.

Different strategies can be tried when you realize that the application I/O experiences a “logjam” on its way to storage. This path is a combination of software (APIs, command languages and protocols) and hardware (HBAs, cables, switch ports and device connections) that links the application to the stored data. A simple indicator of a problem on this path is a growing I/O queue, meaning that many write operations are waiting to be written to the storage.

I’ve experienced in user environments and our labs that the waiting list of writes for VM performance issues is quite short. In other words, the problem of slow VMs cannot logically be attributed to storage latencies.

In most of these situations, there is also an extremely high rate of processor load on the servers that host these VMs. When the processors are running hot, this often indicates a problem in the application or in the hypervisor software. This means that the logjam is above the storage I/O layer.

The Hypervisor Can Be The Bottleneck

So the evil, traditional, proprietary storage might not be the cause of the slow VMs. It is more likely that the virtualized application or hypervisor is the problem.

This raises the question of why the existing storage should be removed – in most cases an infrastructure where a lot of energy and money has been put into, for example, installing a SAN or integrating NAS file servers into the network. And this is now to be replaced by DAS JBODs that operate with the hypervisor manufacturer’s current software controller kit.

The so-called “I/O blender effect” (mixing effect) is real. If you connect some VMs and simply let them run, many random I/Os mix to an incoherent mix of write processes that consume flash resources in a short time and occupy disk space, which in turn leads to slow VMs.

This is not a storage problem per se, but one of the hypervisor strategy. Suppose you want to continue using your hypervisor, you should find a more efficient way to organize and write data. For example, you can use the log-structuring approach of companies like StarWind Software, or an efficient software controller from PernixData, or a comprehensive controller from DataCore – in all these cases you don’t need to change your underlying storage hardware infrastructure.

Whether you replace your existing storage with a server-side approach is up to you. However, you should know exactly why you are doing this.

My research shows that replacing traditional storage with DAS does not address the problem of slow VMs. Rather, you should first perform simple measurements to check processor activity and queue before deciding on a new strategy.