|
|
製品 | Traveller | Overview
Traveller CPR Overview
In the world of humans, history and events, time travel remains speculative fiction. But in the world of data, it is now possible to travel the data timeline to any prior point in time, get what you need, and return intact. There has been much anticipation about technologies like Continuous Data Protection (CDP) that allude to (but in current form have never fully realized) the possibility of returning data, quickly and easily, to a coherent state that existed at any prior point in time. DataCore Software has made the possibility a reality with Traveller� Continuous Protection and Recovery (CPR) and MakeTime Productivity software.
In any enterprise, changes to data (creating, deleting, moving, modifying) occur constantly. Because these changes occur constantly, the data that exists at any instant is different than the data that exists at every other instant. The continuous succession of these states is so rapid that data in an enterprise can be understood as a continuum, a constant 吐low� of data that can be arbitrarily divided by reference to time (e.g. The state at 09:01. The state at 09:02, etc.).
It should be understood that the 都tate� refers to more than the data itself at any instant. It is the data, plus the coherency of that data across all data sets, at that instant. Without that coherency, systems and applications cannot work with the data.
Therefore, to be able to reach back and grab the data that existed at any point in the continuum so that it can be used with systems and applications, (1) the entire continuum must be captured so that all of it is available and (2) the data selected must be brought forth coherently. If only certain points within the continuum are preserved, the states within the gaps between those points are lost. If data is not retrieved as a coherent data set, it will not be useful until the correct state is rebuilt and coherency restored. By accomplishing this breakthrough, DataCore has achieved in Traveller what no other solution can provide. It has revolutionized CDP, Snapshots, Backups, Disaster Recovery and Business Continuity, and has introduced Timeshifting as a new, required functionality for data protection and parallel workflow optimization.
Capturing the Continuum � Solving the Gap Problem
Most other solutions, even some that claim to be 鼎DP,� rely upon snapshots -- point in time data captures at intervals within the continuum. The primary problems with relying upon snapshots (backups are a form of snapshot) are data loss and uncertainty. Because they capture only points within the continuum and not the continuum itself, states that existed between those points are lost and cannot be recovered. High risk guesswork ensues. The user must guess how many snapshots or backups to schedule and at what times to take them within any given time frame. This is akin to photographing a sporting event by setting your camera in advance of the event to automatically take photographs at specified intervals. You may be able to avoid taking a bunch of photographs during halftime, but for the most part you have got to hope you are lucky enough to capture the action you want.
The gap problem is exacerbated because of the relationship between the growing volume of data and the time it takes to do a snapshot or backup, and the inverse relationship that snapshot/backup time has to productivity. The more data an enterprise has, the more time it takes to do a snapshot or backup, and the more time they take, the less often they are done. The longer it takes to do a backup, the longer production systems are disrupted, because production systems must be stopped and applications quiesced while taking the snapshot or backup. The greater the negative impact on production of doing snapshots and backups, the less often they are done. When snapshots and backups are performed less often, gaps and the risk of losing data in those gaps grow. As a result, ironically, the gap problem is often at its worst in the places that can least afford the risk of gaps: highly productive, data dependent enterprises.
Traveller solves the gap problem. Traveller captures the entire data continuum for the period defined by the user. Because it has 兎verything� there are no gaps and there is no guessing. Moreover, Traveller features Timeshifting which, among other things, allows snapshots and backups to be performed with 奴ero-impact� to production systems. With Timeshifting, a virtual 溺akeTime Volume� is created from the precise state selected from the captured data continuum. The snapshot or backup can then be performed using the MakeTime Volume with no impact to production. Decisions like when to snapshot, when to backup, how often, are easier because they can be made or changed after Traveller has already captured the data continuum from which they will be created. To carry forward the previous snapshot analogy, with Traveller, you致e brought a video camera instead of a still camera to the sporting event, set it to automatically record the whole game, and it does so (while you are eating popcorn, drinking beer and doing 禅he Wave�). Then you can go home and replay any of the action you want, whenever you want.
Easy 船ial Back the Clock� Time Travel � 禅rue State� Recapture
Traveller痴 泥ial Back the Clock� simplicity allows users to travel in time back to any specific date, hour and minute within the captured continuum easily, permitting 吐ine tuning� to find the precise data sought. Even if the user does not know exactly where along the data timeline the data resides, Traveller makes it possible for the user to travel back and forth along the timeline, take a peek, and go to another point until the desired data is located. That type of precision is made practical by Traveller痴 ease of use, illustrated below, and the speed at which Traveller can create a complete, working MakeTime Volume of the state selected. In addition to offering (by definition) any state, Traveller works at disk speed to dramatically reduce the time it takes to recover a state, typically from days to minutes.
Unlike CDP and other products currently available, DataCore痴 Traveller returns the state coherently, without the use of agents, which is a compelling advantage. Other solutions either lack coherency across data sets, requiring complicated, error prone and production disruptive coordination measures, or are administratively burdensome because they use agents on each server that must be managed individually to provide that coordination. These impacts are serious impediments to any attempt to use these solutions for continuous protection and recovery, and prohibit their regular use to improve work flow productivity.
In contrast, Traveller MakeTime Volumes capture a cross-server, cross-application and cross-storage group view of the data at exactly the same moment in time 紡 coherent data set image. This enables systems and applications to recover reliably, when recovery is the objective, and to immediately begin working with the MakeTime Volume when improved productivity through Timeshifting is the objective.
Making Time for More Productivity � Timeshift to Parallel Workflow
Traveller MakeTime Volumes create opportunities for better productivity through parallel workflow. Production continues unimpacted while the current state or any historical state in the continuum is captured in one or more MakeTime Volumes for use by non-production systems. As a result, work that previously had to be scheduled to take place after production hours (during shifts that are inconvenient to individuals and costly to businesses) can now be scheduled to run concurrently with production. In addition, tasks that previously would not be accomplished because they could not occur during production hours, but didn稚 justify incurring the post-production staffing costs, can now be accomplished during production hours quickly and easily. Tuesday痴 11:59 pm backup can occur on Wednesday at 10:00 am from a Tuesday, 11:59 pm MakeTime Volume. The Word file that the Senior Partner is sure was 屠ust fine� about a week ago, but is now hopelessly damaged, can be quickly recovered without ever having to consider how to justify the expense of paying someone overtime this weekend to pour through backup restores on the chance that a good copy can be recovered. Testing, Data Mining and Business Analytics can all be supported with 杜oments ago� data from MakeTime Volumes created while production systems roll on unimpacted, undiverted.
To Harness the Data Timeline � Traveller is Required
It is easy to get started traveling the data timeline with Traveller. Unlike other revolutionary, standard setting, innovations, the user does not have to discard or restructure its current data protection regime to begin using Traveller to protect against the high risk data gaps that exist inherently within that regime, or make any substantial investment in new equipment. Traveller is software that runs on standard PC servers and works with all types of storage. Existing processes and schedules can be maintained at the outset and evolved based upon Traveller痴 capabilities to more efficient and less disruptive processes, without in any way compromising Traveller痴 ability to capture and produce MakeTime Volumes of any prior state within the continuum for True State recovery or parallel workflow.
While sci-fi writers and other data protection vendors speculate about a future in which people can control and travel the timeline, DataCore has created a time machine of its own in Traveller. Traveller gives you the power to harness the data timeline to quickly and reliably select with specificity any and all protected states and to immediately use those states for recovery, restoration, improved productivity and other useful tasks. Traveller is a practical necessity for highly productive, data dependent enterprises and a compelling advantage for all others.
Traveller CPR: Business Continuance, Data Protection, Disaster Recovery, Virtualization and a MakeTime Productivity Engine All In One
|
|
