Although this can be highly confusing, the following terminology is used throughout this appendix to identify the different entities:. Starting with a simple example a single hard drive inside a computer a component-by-component analysis will be given. Breaking this down into the major storage subsystem components, the system consists of:. All data is written to the disk as a block, but different applications using different block sizes.
On a component-by-component basis:. The hard drive — The average 10,RPM hard drive has a 7-millisecond ms seek time and a 3 ms access time. Access time is the average amount of time it takes to read or write the data to disk, once the head is in the correct location.
Thus, the average time for reading a unique block of data in a 10,RPM HD constitutes a seek and an access, for a total of approximately 10 ms or.
This example does not reflect the disk cache, where the data of one cylinder is typically kept. So far, the transfer rate of the hard drive has been irrelevant. See the following tables for comparison. The figures in the following table represent an example. Most attached storage devices currently use PCI Express, which provides much higher throughput.
PCI bus — This is an often overlooked component. In this example, this will not be the bottleneck; however as systems scale up, it can become a bottleneck. Following is the equation:.
Additionally, any other device such as the network adapter, second SCSI controller, and so on will reduce the bandwidth available as the bandwidth is shared and the devices will contend for the limited resources. Now, having analyzed a simple configuration, the following table demonstrates where the bottleneck will occur as components in the storage subsystem are changed or added.
Introducing RAID The nature of a storage subsystem does not change dramatically when an array controller is introduced; it just replaces the SCSI adapter in the calculations.
This means that during a read or a write operation, a portion of the data is pulled from or pushed to each disk, increasing the amount of data that can transit the system during the same time period.
In RAID 1, the data is mirrored duplicated across a pair of spindles for redundancy. The caveat is that write operations gain no performance advantage in a RAID 1.
This is because the same data needs to be written to both drives for the sake of redundancy. As one of the major advantages in using a SAN is an additional amount of redundancy over internally or externally attached storage, capacity planning now needs to take into account fault tolerance needs.
Also, more components are introduced that need to be evaluated. Breaking a SAN down into the component parts:. When designing any system for redundancy, additional components are included to accommodate the potential of failure.
It is very important, when capacity planning, to exclude the redundant component from available resources. When analyzing the behavior of the SCSI or Fibre Channel hard drive, the method of analyzing the behavior as outlined previously does not change.
Although there are certain advantages and disadvantages to each protocol, the limiting factor on a per disk basis is the mechanical limitation of the hard drive. Where this deviates from the simple previous example is in the aggregation of multiple channels. Again, fault tolerance is a major player in this calculation, in the event of the loss of an entire channel, the system is only left with 5 functioning channels. Next, obtaining the manufacturer's specifications for the controller modules is required in order to gain an understanding of the throughput each module can support.
The total throughput of the system may be 15, IOPS if redundancy is not desired. In calculating maximum throughput in the case of failure, the limitation is the throughput of one controller, or 7, IOPS. This threshold is well below the 12, IOPS assuming 4 KB block size maximum that can be supported by all of the storage channels, and thus, is currently the bottleneck in the analysis.
En route to the server, the data will most likely transit a SAN switch. Again, fault tolerance being a concern, if one switch fails, the total throughput of the system will be 10, IOPS.
Caches are one of the components that can significantly impact the overall performance at any point in the storage system. Detailed analysis about caching algorithms is beyond the scope of this article; however, some basic statements about caching on disk subsystems are worth illuminating:.
It only allows for the writes to be buffered until the spindles are available to commit the data. Larger caches only allow for more data to be buffered. This means longer periods of saturation can be accommodated. In a normally operating storage subsystem, the operating system will experience improved write performance as the data only needs to be written to cache. Any enhancement is non-existent if the operating system or application-based cache size is greater than the hardware-based cache size.
SSDs are a completely different animal than spindle-based hard disks. One way to think about storage is picturing household plumbing. Imagine the IOPS of the media that the data is stored on is the household main drain.
When this is clogged such as roots in the pipe or limited it is collapsed or too small , all the sinks in the household back up when too much water is being used too many guests. Different approaches can be taken to resolve the different scenarios:. In any plumbing design, multiple drains feed into the main drain. If anything stops up one of those drains or a junction point, only the things behind that junction point back up.
It is helpful to understand why these recommendations exist so that the changes in storage technology can be accommodated. These recommendations exist for two reasons. The challenge presented by today's storage options is that the fundamental assumptions behind these recommendations are no longer true. In fact these scenarios add an additional layer of complexity in that other hosts accessing the shared media can degrade responsiveness to the domain controller.
The cold cache state occurs in scenarios such as when the domain controller is initially rebooted or the Active Directory service is restarted and there is no Active Directory data in RAM. Warm cache state is where the domain controller is in a steady state and the database is cached. These are important to note as they will drive very different performance profiles, and having enough RAM to cache the entire database does not help performance when the cache is cold.
For both the cold cache and warm cache scenario, the question becomes how fast the storage can move the data from disk into memory. Warming the cache is a scenario where, over time, performance improves as more queries reuse data, the cache hit rate increases, and the frequency of needing to go to disk decreases. As a result the adverse performance impact of going to disk decreases.
Any degradation in performance is only transient while waiting for the cache to warm and grow to the maximum, system-dependent allowed size. The conversation can be simplified to how quickly the data can be gotten off of disk, and is a simple measure of the IOPS available to Active Directory, which is subjective to IOPS available from the underlying storage.
For normal operating conditions, the storage planning goal is minimize the wait times for a request from AD DS to be returned from disk. There are a variety of ways to measure this. The desired operating threshold must be much lower, preferably as close to the speed of the storage as possible, in the 2 to 6 millisecond. It is normal for short periods to observe the latencies climb when components aggressively read or write to disk, such as when the system is being backed up or when AD DS is running garbage collection.
Additional head room on top of the calculations should be provided to accommodate these periodic events. The goal being to provide enough throughput to accommodate these scenarios without impacting normal function. As can be seen, there is a physical limit based on the storage design to how quickly the cache can possibly warm.
What will warm the cache are incoming client requests up to the rate that the underlying storage can provide. That can adversely affect delivering data that clients need first because, by design, it will generate competition for scarce disk resources as artificial attempts to warm the cache will load data that is not relevant to the clients contacting the DC.
Skip to main content. This browser is no longer supported. Download Microsoft Edge More info. Contents Exit focus mode. Please rate your experience Yes No. Any additional feedback? Note Adding Active Directory-aware applications might have a noticeable impact on the DC load, whether the load is coming from the application servers or clients. Note A corollary while sizing memory is sizing of the page file. Note Generally, the majority of network traffic on a DC is outbound as the DC responds to client queries.
Note All performance data is historical. Note A similar approach can be used to estimate the additional capacity necessary when consolidating data centers, or retiring a domain controller in a satellite location. Note The articles are based on data size estimates made at the time of the release of Active Directory in Windows Note For new environments, notice that the estimates in Growth Estimates for Active Directory Users and Organizational Units indicate that , users in the same domain consume about MB of space.
Please note that the attributes populated can have a huge impact on the total amount. Attributes will be populated on many objects by both third-party and Microsoft products, including Microsoft Exchange Server and Lync. An evaluation based on the portfolio of the products in the environment is preferred, but the exercise of detailing out the math and testing for precise estimates for all but the largest environments may not actually be worth significant time and effort.
Note This storage needed is in addition to the storage needed for SYSVOL, operating system, page file, temporary files, local cached data such as installer files , and applications. Note On a well-managed system, said spikes are might be backup software running, full system antivirus scans, hardware or software inventory, software or patch deployment, and so on. Note Intraforest and interforest scenarios may cause the authentication to traverse multiple trusts and each stage would need to be tuned.
For all the Metasploit fans, there is no need to get depressed. Metasploit can work just fine in extracting hashes from the NTDS. We have 2 exploits that can work side by side to target NTDS.
The first one locates the ntds file. We need a session on the Target System to move forward. Upon running the exploit, we see that we have the location of the NTDS. Moving on, we use another exploit that can extract the NTDS. The catch is, it transfers these files in. The exploit works and transfers the cab file to a location that can be seen in the image.
Now to extract the NTDS. This will extract all 3 files. Suppose a scenario where we were able to procure the login credentials of the server by any method but it is not possible to access the server directly, we can use this exploit in the Metasploit framework to extract the hashes from the NTDS. We will use this auxiliary to grab the hashes. The auxiliary will grab the hashes and display it on our screen in a few seconds. CrackMapExec is a really sleek tool that can be installed with a simple apt install and it runs very swiftly.
This tool acts as a database for Active Directory and stores all its data including all the credentials and so we will manipulate this file to dump the hashes as discussed previously. It requires a bunch of things. Password: [email protected]. To ensure that all the hashes that we extracted can be cracked, we decided to take one and extract it using John the Ripper.
The size of ntds cannot impact the active directory replication when the domain controllers are already promoted. Please don't forget to mark this reply as answer if it help you to fix your issue. If the size of ntds is not the same on all domain controllers , I recommend you to demote and repromote the domain controller to reduce the ntds size.
Something here may help. Active Directory automatically performs online defragmentation of the database at certain intervals as part of the Garbage Collection process. By default, this occurs every 12 hours. As any other database, Active Directory database must be periodically maintain to reduce data fragmentation, speed up search and increase LDAP query performance. The Active Directory database is stored in ntds. In this case, its size is about MB.
Before you begin offline defragmentation, it is recommended to perform a full backup of ntds. You can do that using a standard Windows Server Backup system state backup or third-party utilities.
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