We were discussing Object Storage and file systems.
Object storage fits the cloud-first strategy. Therefore it comes with the benefits of cloud migration of workloads. However, not all workloads are suited for this cloud first strategy. We determine the suitability based on performance and cost-perspective. Ideally this is determined in the production environment. There are tools that can perform workload IO capture and playback. With this IO pattern replayed on a new storage system, the suitability of the cloud first strategy becomes clear.
However, IT may not always have the options to measure the production workload. Instead a lab environment is created where the production like workload may be synthetically generated. This kind of workload generator or benchmarking tool is also helpful in determining the suitability of the cloud first initiative, The IO profile of a workload helps with the planning of the storage resources.
The performance expectations and the cost planning will help with the evaluation of the storage alternative.
One thing to note here is that workload patterns can change over time. There may be certain seasons where the peak load may occur annually. Planning for the day to day load as well as the peak load therefore becomes important. Workload profiling can be repeated year round so that the average and the maximum are known for effective planning and estimation.
Storage is almost always available in tiers. It is important to recognize which tier the workload is most suited for. Public cloud providers publish guidelines for their tiers. With the help of the workload profiling and the testing against the cloud configurations, the suitability of the storage system candidate can be evaluated.
Storage systems planners know their workload profiles. While deployers view applications, services and access control, storage planners see workload profiles and make their recommendations based exclusively on the IO, costs and performance. In the object storage world, we have the luxury of comparision with file-systems. In a file-system, we have several layers each contributing to the overall I/O of data. A file system can be local or remote and may not be distributing load. A file-system helps with connecting Inter-operable systems such as linux with a windows fileshare and vice versa with protocols such as CIFS. NFS helps with linux-linux file share mount:
sudo mount -t nfs -o vers=3,sec=sys,proto=tcp ip.ip.ip.ip:/namespace/my_bucket/ /home/my/share
A file-system may also be exported as an object-storage.
On the other hand, a bucket is independent of the filesystem. As long as it is filesystem enabled, users can get the convenience of a file system as well as the object storage. Moreover, the user account accessing the bucket can also be setup. Only the IT can help determine the correct strategy for the workload because they can profile the workload.
Object storage fits the cloud-first strategy. Therefore it comes with the benefits of cloud migration of workloads. However, not all workloads are suited for this cloud first strategy. We determine the suitability based on performance and cost-perspective. Ideally this is determined in the production environment. There are tools that can perform workload IO capture and playback. With this IO pattern replayed on a new storage system, the suitability of the cloud first strategy becomes clear.
However, IT may not always have the options to measure the production workload. Instead a lab environment is created where the production like workload may be synthetically generated. This kind of workload generator or benchmarking tool is also helpful in determining the suitability of the cloud first initiative, The IO profile of a workload helps with the planning of the storage resources.
The performance expectations and the cost planning will help with the evaluation of the storage alternative.
One thing to note here is that workload patterns can change over time. There may be certain seasons where the peak load may occur annually. Planning for the day to day load as well as the peak load therefore becomes important. Workload profiling can be repeated year round so that the average and the maximum are known for effective planning and estimation.
Storage is almost always available in tiers. It is important to recognize which tier the workload is most suited for. Public cloud providers publish guidelines for their tiers. With the help of the workload profiling and the testing against the cloud configurations, the suitability of the storage system candidate can be evaluated.
Storage systems planners know their workload profiles. While deployers view applications, services and access control, storage planners see workload profiles and make their recommendations based exclusively on the IO, costs and performance. In the object storage world, we have the luxury of comparision with file-systems. In a file-system, we have several layers each contributing to the overall I/O of data. A file system can be local or remote and may not be distributing load. A file-system helps with connecting Inter-operable systems such as linux with a windows fileshare and vice versa with protocols such as CIFS. NFS helps with linux-linux file share mount:
sudo mount -t nfs -o vers=3,sec=sys,proto=tcp ip.ip.ip.ip:/namespace/my_bucket/ /home/my/share
A file-system may also be exported as an object-storage.
On the other hand, a bucket is independent of the filesystem. As long as it is filesystem enabled, users can get the convenience of a file system as well as the object storage. Moreover, the user account accessing the bucket can also be setup. Only the IT can help determine the correct strategy for the workload because they can profile the workload.
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