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DiscoverBest of Show 2016
2. - 3. März 2016, Düsseldorf
Backup- und Storageoptimierung mit Data Protector und Storage Optimizer
Claus NöskePresales Information Management & Governance
2. - 3. März 2016
Challenge accepted
Today‘s unstructured data challenges
How do I reduce cost associated with IT and information processes?
• Information footprint is growing exponentially along with costs to manage it
• Manual processes reduce staff efficiency and are error prone
• Storage is not optimized, data is not always stored according to value
How do I secure valuable business data and reduce risk?
• Dark data exists and is not being managed, retained or disposed appropriately
• Business critical and valuable data is not managed or secured according to its value ans sensitivity
• Classification and application of policy to data is piecemeal and often not enterprise wide
Managing storage is expensiveThe overall cost of storage is $25,000/TB
$128.000$640.000
$1.280.000
$2.560.000
$6.400.000
$12.800.000
$25.600.000
5 TB 25 TB 50 TB 100 TB 250 TB 500 TB 1000 TB
68% Operations
1%Policy Management
12%Backup
reduction
4%Regulatory
Compliance
14%Capex
Source: Enterprise Strategy Group, 2014
Why change now?
source: IDC, 2013
30% of typical IT budget is spent on data storage
60% of all enterprise space is
taken by copies
85% of storage spend is for
managing copies
8x morespent on copies as on storage
for data and analytics
We want to
OPTIMIZE storage
and help drive value
VALUE from data
Addressing issues with the Band-Aid approachFighting conventional wisdom: common symptoms and common responses
We are running out of capacity Let‘s add more disks
Upgrade infrastructur
Backup takes longer and longer Change backup infrastructure
We need to retain information
for a period of time
Keep backup tapes, keep
everything forever
Look into different resources,
recover tapesWe need to retrieve historical information
Applications are slowing down
costs€
Komplexität
Introducing HP Storage Optimizer
Policy-based storage tiering and information
optimization File analytics
An analytics-driven ‘All-HP’ storage optimization solution
that applies policy to unstructured information data, stub it, and then make it
seamless for an end user to retrieve this information as needed
Cost Containment
without Constraint
Manage unstructered dataHPE Storage Optimizer
10
HPE Storage OptimizerNo longer is storage optimization “blind.”
• Tiered Storage with stubbed documents to minimize change to business processes
• Apply complex policies to optimize storage consumption
• Manage data across different repositories and different storage tiers
• Review, approve and audit all manually and automatically applied actions
• Utilize fully integrated role based security in all processes
• Address compliance and legal concerns by converting to HPE Control Point
Remove
Retain
Optimize
Migrate
HPE Storage
Optimizer
Address multiple use cases of file analytics,
data cleanup and backup optimization, ...
HPE StorageOptimizerStorage optimization is no longer “blind.”
HPE StorageOptimizer:Filter by aged data, users and groups and decide upon corporate standards for deletion or migration
HPE Storage
Optimizer
Connect
Identify
Copy
Migrat
.. many more
Filesystems
Reduce
.. many more
Filesystems
Sources Targets
Policy based migrationReduce cost, manage risk and migrate with insight
ROT (Redundant, Obsolete, Trivia)
Lower cost
storage tier
HPE File Analysis Software
Valuable Data
Sensitive
Data
Collaborative Public
… and many more
Business value defines locality
Use Cases
14
HP Storage Optimizer use cases
Objective Results
Improve Infrastructure
Management
• Optimize storage with high levels of transparency and intelligence
• Get more life out of infrastructure without additional CapEx
Lower total IT spend • Materially lower cost on primary storage and backup-related storage
• More effectively tier storage for added cost savings
Enhance backup and
recovery
• Identify redundant, obsolete, and trivial data that is not required for
backup
• Speed-up backup up to 50% without impacting results by archiving
and stubbing files based on policies
Meet internal objectives • Increase application performance and uptime
• No noticeable impact to end users
Support information
governance initiatives
• Dispose of information that is no longer valuable or required
• Bridge gap between legal and IT
Improve infrastructure management
Business need:
– No visibility into the massive existing volumes of data
Advantages:
– No longer is storage optimization “blind.”
– Combines power of file analytics and prioritized backup in one cost-effective solution.
Business benefits:
– Optimize storage with high levels of transparency and intelligence
– Get more value out of infrastructure without additional Capex
Lower total IT spend
Business need:
– Reduce the total amount of storage needed for unstructured data
Advantages:
– Identify redundant, obsolete, and trivial data
– Move and delete selected data
– De-duplicate data across different repositories and different storage tiers
Business benefits:
– Lower the cost of primary storage and backup-related storage
– Make more effective and intelligent use of tiered storage for added cost savings.
Enhance backup and recovery
Business need:
– Backup more data in less time while reducing the cost of storage
Advantages:
– Reduce backup times by up to 50%
– Increase application performance
– No impact on end users
Business benefits:
– Speed-up backup without impacting results by archiving and stubbing files based on policies
– Identify redundant, obsolete, and trivial data that is not required for backup
Meet internal objectives
Business need:
– Meet recovery point and time objectives (RPO/RTO)
Traditional shortcomings:
– Impaired availability and performance of data center environments
– Internal demand for better and faster services
– Backup takes way to long due to volume of data
Business benefits:
– Increase application performance and uptime
– No noticeable impact to end users
– Lower backup times without impacting results
Support information governance initiatives
Business need:
– Getting more from existing infrastructure while laying future foundation in order to meet regulatory mandates
Traditional shortcomings:
– Limited or no visibility into actual usage of existing infrastructure
– No operating standards in place to optimize provisioning, backup, replication, and archiving
– No visibility into what type of data is being stored now
Business impact:
– Dispose of information that is no longer valuable or requires
– Bridge gap between legal and IT
Architecture
What differentiates us?Advanced policy definition – more than HSM or simple delete
What do I have?
Where does it live?
What should I do with it?
Is it active or inactive?
How does it relate to other information &
process
What policy applies to it?
Manage-in-place or Migrate?
Retain or Dispose?
What is its value to the business?
Simple file analysis Advanced file analysisWe can base policies on ANY of
the metadata used or created:
• Access dates
• Path ACLs (security groups)
• Titles
• Dates
• Manual tags
• Application tags
ANY metadata
• App Server / Console• Configuration / Administration• Scheduler• Policy Management• Monitoring and Auditing
File analysis platform (Windows OS)
File Archiving and Retirement Platform
Sources
– Windows NTFS
– CIFS/NFS Dateisystem
– Hadoop
– Exchange
– Sharepoint
– …
Targets
– Filesystems through CIFS/NFS connector
– Hadoop
– Sharepoint
– Exchange
– ...
Purge Archive Recall*
Metadata Index
Connector Framework
*Note: Connector functionality related to source
HPE Control Point
HPE Storage Optimizer
MS SQL
ContentIndex
Connectors & Analyse
– Exchange
– SharePoint
– Filesystem
– Hadoop
– Lotus Notes
– StoreAll
26
OpenStack API
File analytics to properly archive, protect & deleteHP Storage Optimizer
– Connectivity to large number of sources
– Scalability to 100+ TB
– Analyse and manage with actionnable actions
– Security by role, reviewprocess, audit
FileSystem
Hadoop
SharePoint
HPE RM
Exchange
…
MoveDeleteFilter SliceMetadata
Redundant, Obsolete,
Trivial
Stub
Redundant Obsolete Trivial
ROT
– Redundant
– File exists more then once in the analyzed repository
– Obsolete
– File was last accessed or modified five years ago
– Trivial
– File is an image, audio, video or system file
28
Analysis example: How much aged-data is present
Analysis example: Assuming a user left the department or company… easy to combine and understand how much aged data is available for a specific user?
Seamless Archiving and Stubbing of Filesystem Documents
Multiple archiving locations provide flexibility for automatic Disaster Recovery and High Availability
In depth analysis capability to determine which data to archive
HPE Storage Optimizer
+
HPE Data Protector
35
HPE Data Protector + HPE Storage Optimizer
– ROT Analyse
– Delete Files
– Move Files
– Stub Files
36
Reduce total amount of storage
Backup more data in less time
HPE Storage Optimizer launchable from DP GUI
The Storage Optimizer ServerName needs to be specifiedin the Global Options file.
HPE Storage Optimizer canbe launched from: Backup-> Actions -> Storage Optimizer
Backup less
– Backup files (follow stub)
– Backup nothing
39
Summary
40
SO and Empowering the Data Driven OrganizationA Gateway Application
–Storage Optimizer offers:
• Easy metadata based analysis (Create date, location title, last modified)
• Familiar application platform – IIS, SQL
• Light footprint (Compared to ControlPoint and IDOL)
– Offers rapid TTV for ROT data ID and cleanup
– Storage Optimizer is expandable
• Upgrade to ControlPoint
– Add IDOL for document conceptual analysis
• Add additional governance/analytics applications
– Records Manager
– HAVEN – Find that disruptive data
Transformto a hybrid
infrastructure
Enableworkplace
productivity
Protectyour digitalenterprise
Empowerthe data-drivenorganization
Challenge accomplished
Thank youclaus.noeske@hpe.com
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