System Z and the Cloud Storage Tier. Louis Hanna

Transcription

1 System Z and the Cloud Storage Tier Louis Hanna

2 Agenda 2 Introduction to IBM object storage Leveraging a cloud storage tier from z/os Break (30 min) OMEGAMON For Storage v5.4 The new Look and feel of IBM Storage Management for Z (statement of direction)

3 Key Topics/Terms 3 IBM Cloud Object Storage (ICOS): A Geodispursed, storage architecture which combines commodity components to enable a high availability, high scalability and high security storage platform that can be used by both mainframe and open system environment. Cloud Tape Connector (CTC): Is a ziip enabled, software only, solution which can clone active tape I/O in order to make a copy in an object store. CTC can also be used to process existing tape and sequential disk datasets to place a copy in the object store. Data resident in the object store can be retained by different expiration policy than the local copy. Advanced Archive for DFSMShsm (AHA): Is a ziip enabled specific solution for DFSMShsm which allows for selective archive of ML2 data based on criteria like creation date, last referenced date, Etc. Once archived the DFSMShsm inventory is updated to remove associated records. Should the data be needed it is returned to the DFSMShsm inventory automatically. Virtual Tape for Mainframe (VTFM): A ziip enabled software solution which emulates a virtual tape library to z/os. Supports traditional tape processing and a virtual vaulting capability which, when combined with CTC, enables use of object storage. Transparent Cloud Tiering (TCT): A DS8K hardware feature which can offload mainframe data to object storage under the direction of DFSMSdss and/or DFSMShsm.

4 Today, data is your business. How you manage and store it is critical. Storage architecture needs to manage hyper growth and evolving workloads to help unlock data value. Any app, any source, any business Flexible, massive scale without roadblocks Enabling innovation, discovery, new experiences In other words, cognitive-aware. Traditional approaches just don t measure up.

5 IBM Cloud Object Storage Redefines availability, security and economics of data storage. Always-on Availability Built-in Security Better Cloud Storage Economics Simplicity Tolerates a catastrophic regional outage without down time or intervention Continuous availability architecture Some legacy providers place the burden of data management and cost for creating and maintaining an out of region second copy on the client Protects against digital and physical breeches Provide strong data-at-rest confidentiality by combining encryption and information dispersal More cost-efficient than competitors Enterprise class support, at no additional cost We cap costs for workloads with unpredictable data access pattern Immediate consistency (v. eventual consistency) simplifies app development Integrated with the rest of IBM Cloud, IBM Bluemix, IBM Watson, IBM Video Services No black boxes, we share how our technology delivers durability, availability, security

6 Our SecureSlice and information dispersal technology redefine security and availability of stored data 1 Encrypts data * Our technology ensures: Data is available, even in the face of a regional outage Data is protected with no external key management required, even in the face of regional security breach Decrypts data * 6 * Encryption Decryption 2 Transforms, expands, slices data 3 4 X Decodes data 5 *All-Or-Nothing transform Disperses slices of data across regions X Retrieves data with a subset of the slices

7 High Density, Efficient Storage 7 How to build a highly reliable storage system for 1 Petabyte of usable data? RAID 6 + Replication IBM Cloud Object Storage Original 1.20 PB Raw Onsite mirror 1.20 PB Raw Remote copy 1.20 PB Raw 567 TB Raw 567 TB Raw 567 TB Raw 1 PB 3.6 PB x 3.6x 3 FTE Replication/backup Usable Storage Raw Storage 4TB Disks Racks Required Floor Space Ops Staffing Extra Software 1 PB 1.7 PB x 1.7x.5 FTE None $ 70% + TCO Savings

8 Leverage Object Storage to reduce cost of replication 8 Reduce cost by moving cold data on traditional storage to object storage Extend scalability while maintaining security and availability

9 IBM Cloud Object Storage Industry leading flexibility, scalability and simplicity On-Premise Single tenant Design specific to client needs Total control of system Single tenant (compliant) No datacenter space required Flexible configuration options OPEX vs CAPEX Multi-tenant Usage-based pricing Elastic capacity No data center space required. Fully managed OPEX vs CAPEX Hybrid Consistent, uniform, and open technology across on-prem, dedicated and public cloud makes it simpler and more efficient to manage data, workloads, and business processes

10 IBM Cloud Object Storage public cloud services designed for today s dynamic workloads Predictable data access pattern / workload Frequent data access Less frequent data access Minimal data access Data Access Pattern IBM Cloud Object Storage Standard IBM Cloud Object Storage Vault IBM Cloud Object Storage Cold Vault Variable data access pattern / Mixed workloads Terabytes IBM Cloud Object Storage Flex Capacity Exabytes 2017 IBM Corporation Page 10

11 11 Mainframe and Cloud Storage Mainframe shops should see cloud storage as highly available and secure Cloud object storage offers purchase flexibility; Cap-Ex, Op-Ex or both Mainframe storage arrays (disk and tape) are great for OLTP data Cloud based storage latency is typically not sustainable for an on-premise OLTP solution What types of mainframe workloads makes sense for leveraging cloud storage? Uses for cloud storage: Backup/recovery Disaster Recovery Archiving New SOA (Service Oriented Architecture) applications

12 12 Cloud Storage, For the Right Workload Cloud storage expands tradition storage tiers Flash (high cost, high speed), DASD (moderate cost, moderate speed) Tape (lower cost, lower speed) Cloud (lower cost, lowest speed, highest scalability) Flash Spinning Disk Tape/VTL Cloud

13 Cloud for Backup/Archival/Recovery - Mainframe Data 13 Cloud is viable for backup/archival/recovery scenarios Tape vaulting is difficult/expensive Cloud is geo-dispersed/geo-accessible Tape transport / storage is a problem Use network bandwidth instead Cost of off-site location On premises or Off premises Recovery point objectives Download can begin immediately, but will take longer Cost of tape / virtual tape at target location No replication of data at target location Need to be able to recover at multiple locations Geo-accessible Private vs. Public Cloud; On-Prem vs. Remote Archive or Destroy Evaluate Disposition Records Creation Maintain and Protect Use and Disseminate

14 New Cloud Storage Options for z/os Data Converged Cloud Infrastructure IBM Cloud Tape Connector for z/os TAPE Save up to 70% by using cloud over traditional storage -- Forrester 2015 Amazon S3 IBM Spectrum Protect IBM Spectrum Scale..Other Distributed Storage HDS HCP For mainframe static archival or point-in-time backup data Captures tape data; handles data blocking for cloud storage; handles storage to and retrieval from cloud. Not application specific - any tape data is eligible IBM Cloud Object Storage (Cleversafe), Softlayer, Amazon S3 clouds, HDS HCP, FTP support Handles encryption Can be public, private or hybrid cloud implementation No hardware gateway required can be single-vendor solution! 1 4

15 Cloud Tape Connector Designed to quickly and efficiently allow you to write files concurrently to tape and to a cloud repository, without having to run additional backup utilities When a copy of your tape data is in the cloud, you can recover data sets even if the tape has expired or has a physical I/O error and cannot be read When your data has been written to the cloud with Cloud Tape Connector, you can recover data sets at a Disaster Recovery (DR) site without requiring the physical tape

16 Cloud Tape Connector Processing You can back up tape data to cloud, and restore to either DASD or tape Data sets with block sizes over 32K must be restored to tape User defined parameters Cloud servers Staging options Backup filter criteria Data restore settings Other general options

17 Methods for Backing Up Data to the Cloud Capture data while it is being written to tape Through filter criteria defined in the parameter member CUZ#PARM Filter by data set name, esoteric unit, or SMS storage class Create a list of existing data sets (history data sets) to copy directly to the cloud Locate already existing sequential files and copy them directly to the cloud Currently the only supported method for copying DASD files Pre-existing sequential data sets are identified by name or masked name in the parameter member CUZ#INEX

18 Options for Capturing Data While Writing to Tape Staging data to DASD Quickly save the data to a DASD data set called a staging file After the batch job has completed, the contents of the staging file are written to the cloud by the Cloud Connector Started Task There must be enough DASD space available to contain the entire file that is being written to tape Writing data directly to the cloud Will capture a copy of the data you are writing to tape and send it to the cloud as the batch job is running If there is any delay in writing the data to the cloud, this may impact the batch job

19 19 Hierarchical Storage Management (HSM) Usage DFSMShsm (HSM) is the mainframe ILM tiering tool used on most z/os systems Reduces storage costs by migrating aging data onto slower and less expensive media Automatically moves data between higher and lower cost storage media Based on policies Based on SLAs (Service Level Agreements) Archive or Destroy Evaluate Disposition Records Creation Maintain and Protect Use and Disseminate

20 20 DFSMShsm Primary Storage (ML0) ML1 Tape/VTL ML2 Aged data moves between active disk to other levels ML1 compressed data on disk ML2 compressed data on tape Compressed data reduces space --> less cost Tape is less expensive than disk, but what is happening with all that ML2 data?

21 How much data remains in DFSMShsm 76% 58% Case 1 78% 69% Case 2 60% 55% 43% 34% 26% 37% 1yr+ 2yr+ 3yr+ 4yr+ 5yr+ 1yr+ 2yr+ 3yr+ 4yr+ 5yr+

22 22 Archiving Aging HSM Data to the Cloud Primary Storage (ML0) ML1 Create an ML3 level of archive data Where the SLA is right for you Public Private Hybrid Tape/VTL ML2 TCP/IP ML3

23 New Archive Storage Tier for DFSMShsm DFSMS IBM Advanced Archive for DFSMShsm Converged Cloud Infrastructure HSM Metadata HSM Metadata Reduce DFSMShsm TCO and exploit cost-effective Cloud archive tier! Slash HSM CPU usage with Advanced Archive for DFSMShsm -- IBM HSM Assessment Amazon S3 HDS HCP IBM Spectrum Protect IBM Spectrum Scale..Other Distributed Storage For HSM archival data: Low-overhead management of inactive data; Reduce HSM CPU resource usage; Improve Batch Window / Batch Application Wall Clock Time Automatic recall provides seamless access to applications or users Honors DFSMS Management policy (e.g. retention) And..archive on tape, virtual tape, or optionally move to cloud storage for up to 70% savings! 2 3

24 24 IBM Advanced Archive for DFSMShsm Move inactive data from DFSMShsm ML2 tape Deletes the data from ML2 Write the data to tape or cloud Reduces overhead of managing that data in HSM Decrease HSM CPU activity and CDS size Less data to recycle When you need the data again Can restore to ML0 upon access Logical extension of SMS policy Honors existing SMS policy

25 Archive Selection Batch task executed on an as needed basis On initial implementation this would be frequent to get the back log of eligible data archived On going processing would be scheduled based on the amount of new data created Reads the DFSMShsm Migration Control Data Set (MCDS) to identify the migrated data sets that are eligible based on the selection criteria Data can be selected based on Days since last reference as an extension of DFSMS Management Class Policies User specified selection criteria Supports Multiple Criteria for selection Days since creation, since last used, since migration, until expiration Data set name and Management Class patterns

26 Archive Processing Reads the MCDS and ML2 tape data for the file and writes to Archive media Deletes corresponding entries from DFSMShsm Changes the MIGRAT ICF catalog entry to RCHIVE Updates the Advanced Archive DB Optionally deletes DFSMShsm backup versions

27 IBM Total Storage VTF Mainframe Louis Hanna

28 Terminology In this topic the following terminology is used: Tape dataset - The dataset written onto a real or virtual tape. This tape dataset has an associated tape dataset name. Virtual tape - The tape entity which is similar to a reel tape or a cartridge. This virtual tape has an associated volume serial number. Virtual tape dataset - The disk dataset that contains the data written to the virtual tape. This virtual tape dataset has an associated disk dataset name. 28

29 Front-end / Back-end Concept Running under z/os VTFM Front-end (User Owned) MVS Applications Access method Tape Manager Back-end (VTFM Owned) 3390 Disk pool Virtual tape datasets Virtual tape Database (VDB) 29

30 VTFM Subsystem Dynamic Reallocation Scans batch jobs and dynamic allocations Matches allocation parameters with the dynamic reallocation rules The dynamic reallocation rules are defined in HVTRULxx Changes allocations from real devices to the virtual devices HVT306I /PROC /STEP /DDNAME /UNIT /DATACLAS/STORCLAS/MGMTCLAS ->NEWUNIT HVT306I / /COPY01 /SYSUT2 /3490 / / / ->VT90DT 30

31 Virtual Tape Mounted on a virtual device Managed by the Tape Management System Has an entry in the VDB No real tape exist Seems and used like real tape, transparent to the end user. 31

32 Virtual Tape Dataset Physical sequential multi-volume disk dataset Allocated by an equal size extents calculated from user settings. Can be spanned on up to 16 different disk volumes Dynamically allocated by the VTFM Server Cataloged in a USERCAT established for VTFM Reside on a group of disks defined as a disk pool Contains: Data written to virtual tapes by applications Access method meta-data (tapemarks, header labels and trailer labels) Virtual Tape meta-data (Disk Volume Descriptor) 32

33 VTFM FTP-eVault Introduction Traditional Vaulting Physically gather and transfer cartridges from site to site Logical Component Tape Management System Vaulting system controls which tapes to ship Physical Component Planes, trains, trucks and automobiles 33

34 The VTFM FTP-eVault Concept VTFM virtual tapes are physical sequential disk datasets Virtual tape datasets can be sent to a remote site using FTP Specific virtual tape datasets to FTP are selected using the tape management systems vault patterns as specified by the user The entire process is tracked by VTFM in it s control dataset If the process is interrupted VTFM will recover after the fault is cleared VTFM deletes the local copy once it is completely vaulted Remote copy is automatically retrieved if referenced locally Thus without requiring JCL or application changes clients eliminate the physical component of the vaulting process 34

35 The VTFM FTP-eVault Options FTP Type5 e-vault Vault target is accessed via API calls to CTC Any CTC defined target can be used Any supported object environment can be used Remote storage required = volume of data on all vaulted tapes Tapes must be returned to zseries mainframe platform to be used Either through another vaulting cycle or triggered via mount request 35

36 Transparent Cloud Tiering (DS8K feature)

37 ILM Still Utilizes a 1970 s Architecture MIPS DSS/HSM Half Data Movers 16K Blocksize DFSMS No Co-location Reorgs, Audits, Backups Continual Recycle Serial Access to Tape Online Immediate Access Offline Delayed Access 37

38 IBM DS8K Transparent Cloud Tiering Serverless, direct data movement between DS8000 & Cloud Storage No additional appliance Software Defined Microcode Update using existing Ethernet ports 38 DS8K DFSMS Cloud Tiering Policy

39 Cloud Storage Eliminates Constraints MIPS 16K Blocksizes RECYCLE HSM/DSS Dual data movement Serial Access to Tape No Colocation HSM inventory (Eliminates OCDS) 39

40 Just how many MIPS? Pre Catalog Eligibility Serialize CDS I/O 0 * Move HSM / DSS Handshake Blocking I/O MIPS / Data Set Size DFSMS I/O Small Medium Large Extra Large Post Tape Synch Scratch Catalog CDS I/O PreProcessing Data Movement Post Processing MIPS / Data Set Size Transparent Cloud Tiering Small Medium Large Extra Large PreProcessing Data Movement Post Processing * Values in graphs are not from actual tests, but rather just represent a relative comparison Data to initially Target

41 Cost of Creating a Data Set Offline Copy Standard I/O Disk > Tape Quiesce Time Elapsed Time MIPS PiT Copy Disk > Disk >Tape PiT Copy Disk > Disk > Cloud Quiesce Time Quiesce Time Elapsed Time Elapsed Time MIPS MIPS reduction at expense of throughput MIPS 41

42 DFSMShsm 42 MIGRATE DATASET(dsname) CLOUD(cloud) HSM invokes DSS to migrate data sets to the cloud HSM inventory manages the Cloud, Container and Object prefix Transparent to applications and end users No Recycle Recall works just as it does today Audit support VOLUME and STORAGEGROUP keywords also supported As today, volser will be changed to MIGRAT ISPF will display MIGRATC, as opposed to MIGRAT1 or MIGRAT2

43 DFSMShsm Migration As today, DFSMShsm will automatically Recall a data set to Primary Storage when it is referenced RECALL, HRECALL, ARCHRCAL all support recalling from the cloud. There are no parameter changes, as all information is stored within the HSM control data sets Common Recall Queue is supported Fast Subsequent Migration Remigrated data sets are just reconnected to existing migration objects if the source data set was not updated No additional data movement 43

44 44 Using Cloud for Mainframe Data The benefits of using cloud solutions for mainframe data include: (Part 1) Flexible configuration options are available to support both small and large businesses with different capacity requirements; By moving archival and back-up data to an offsite cloud storage environment, more storage capacity is available on-premise for mission-critical data; The process of storing data in the cloud has a low impact on mainframe CPU overhead; By leveraging industry leading storage appliances, an extra layer of usercontrolled security can be added to mainframe data prior to backing up or archiving to a cloud provider; Clabby Analytics 11/2014: Moving System z Data to the Cloud: A State of the-art Solution for Scalable Capacity, Back up / Recovery and Archiving

45 45 Using Cloud for Mainframe Data The benefits of using cloud solutions for mainframe data include: (Part 2) Cloud data storage represents a cost effective way to scale storage, allowing enterprises to take advantage of pay-as-you go/pay-as-you-grow pricing; Reduces the need for geo-replication and the need to transport physical media (tape) off site; and finally, Lower Total Cost of Ownership (TCO) when using a tapeless approach combined with cloud technologies Clabby Analytics 11/2014: Moving System z Data to the Cloud: A State of the-art Solution for Scalable Capacity, Back up / Recovery and Archiving

46 Managing z/os I/O From Top to Bottom With OMEGAMON XE For Storage

47 Introduction Monitoring modern z/os environments is an exercise in balancing cost and value Cost: The necessary overhead incurred to capture operational statistics of the environment While it is possible to capture every I/O to every dataset it may not be necessary or recommended Value: The ability to quickly identify operational issues, provide insight to operational trends, reduce human intervention where possible Even filtered the quantity of data presented by mainframe monitors are more like haystacks To be effective we have to leverage our tools to focus on the needles We ll take a look at three easy ways to focus on the needles We ll take a look at the newest metrics introduced to OMEGAMON XE For Storage 47

48 The Interfaces

49 The e3270 Interface 3270-based access to monitoring data Real-time, near term data Highly customizable display Customizable columns Sortable columns Consistent interface across all OMEGAMON products Tactical, high performance interface 49

50 IBM e3270 Interface 50

51 IBM e3270 Interface Active Point and shoot 51

52 IBM e3270 Interface Direct Situation Analysis 52

53 IBM e3270 Interface Navigation Options 53

54 The Enterprise Portal Browser-based access to monitoring data Ability to create intelligent alerts using conditional logic Ability to see an alert and information related to it from the same interface Reflex automation capabilities Procedural/resolution information can be provided through Expert Advice Integration of alerts from other subsystems using OMEGAMON DE Built-in TN3270 to quickly navigate to console, TSO Built-in Web Browser Real-time, near term and long term history Classic and OMEGAMON II s included with (some) XEs Consistent interface across all OMEGAMON products 54

55 IBM Enterprise Portal Interface Selectable Chart Options Navigator Personalized Views Intelligent Linking Zoom and Splitter control s Persistent customized workspaces 55

56 IBM Enterprise Portal Interface Easily edit properties 56

57 OMEGAMON XE For Storage

58 IBM OMEGAMON XE for Storage A mainframe STORAGE monitor, real-time and historical XE user interface, comes with the CUA UI component A wide breadth of mainframe storage information: Space (storage groups or user groups define your own) Performance (storage groups or user groups define your own) Tape / VTS CACHE Channels (FICON) Control Units DFSMShsm (View your HSM queues, control Datasets, etc. ) DFSMShsm / DFSMSdss / ICKDSF / IDCAMS online toolkit SMS constructs DS8000 support Ability to see all logical volumes on a physical disk Powerful applications view Powerful dataset view and action capability Integration capabilities from TEP interface (Launch to TPC in v4.1.0) 58

59 XE Storage Navigator Items The tree provides access to all of the data elements supported by XE For Storage Branches can leading to multiple supporting workspaces Smart links can take you deeper into a branch or to a completely different branch in the Storage tree Dynamic Workspace Linking works the same way, but instead will take you to branches of other installed products 59

60 Monitor Based on Application

61 Monitor From Application Point of View 61

62 Monitor From Application Point of View Two clicks to get to all users of a hot dataset 62

63 Monitor From Application Point of View Two clicks to get to all users of a hot volume 63

64 Monitor From Application Point of View Don t forget about find when you have a large display 64

65 Monitor From Application Point of View Add/Edit right from the GUI 65

66 Monitor From Application Point of View Add/Edit right from the GUI 66

67 Monitor From Application Point of View Add/Edit right from the GUI 67

68 Building Volume Groups

69 Storage Group Space (Performance view also available) SMS workspaces are built based on active configuration 69

70 User DASD Groups: Build your own for space and performance User workspaces start out empty Alerting can be based on number of volumes in an undesirable group being greater than 0 70

71 User DASD Groups: Build your own for space and performance Provide name High attribute level and based filters description, filters for volume to Persist further mask, means refine UCB your this address definition user group and will SMS remain Storage after Group a product recycle 71

72 User DASD Groups Individual operators for each attribute; GT, LT, EQ, Etc. or enumerated And many more!! 72

73 User DASD Groups: Build your own for space and performance 73

74 User DASD Groups: Build your own for space and performance 74

75 Building Dataset Groups

76 Dataset Attributes Database A snapshot view of potentially all datasets in the monitored environment Collection controlled via interface Schedule time of collection (off hours suggested) Start time End time Schedule frequency Determine if catalog information desired Exclude volumes or storage groups JES spool volumes Paging packs Determine size of product provided reports Product provided workspaces with various attribute cases Easily define your own set of datasets for a report Create situations to monitor a single dataset or a group of datasets View space in units of tracks, megabytes, or gigabytes 76

77 Dataset Attributes Collection Options 77

78 Dataset Attributes System Summary 78

79 Dataset Space Summary 79

80 Dataset Attribute Database Groups 80

81 Dataset Attribute Database Groups 81

82 Dataset Attribute Database Groups And many more!! 82

83 Dataset Attribute Database Groups 83

84 Dataset Attribute Database Groups 84

85 Enhancements available in v5.4

86 Easier Configuration + Improved Performance New Persistent Data Store (only in OMEGAMON for Storage): Houses Near-Term History Seamlessly replaces old Persistent Data Store Eliminates need to tune data collection to fit into constrained memory Foundation for future longer-term historical data collection and analysis Expected 20-25% performance improvement What is the Persistent Data Store (PDS)? 86 TDW User Interface TEMS or TEMA Address Space AGENT PDS V1 API PDS V1 or V2 The PDS is a disk data set that records near term history and includes the software that enables the agent to read from or write to the data set.

87 New Real-Time Monitoring for FICON Director Key Metrics for FICON Frame-Rate Pacing: Director Level / Control Unit Level and drill-down New Workspaces and Situations Identify problems in FICON fabric A FICON Director allows a FICON channel to access multiple Control Units. This is accomplished by establishing a dynamic connection between the CU and the FICON channel through a FICON Director or Switch. FICON Directors can be chained. Usually for XRC or PPRC. FICON Channel A FICON Channel B FICON Channel C What is a FICON Director? FICON Director Storage CU 1 Storage CU 2 Storage CU 3 Storage CU 4 87

88 Realtime Dataset Metrics (RDM) Replacement of original Dataset Attributes Database collection Minimal external changes No configuration changes APARS OA53347 OA53348 Improved timeliness of data Performance wall clock time Resource consumption CPU utilization Enable data retrieval by other User Interfaces eliminate row count restriction 88

89 Definitions 89 Term Clean Sweep Incremental Sweep VTOC Change Record Apply VTOC Change Records Synchronized Definition Disposal of all current dataset metrics and collection of metrics for all datasets in the DASD Farm Collecting the metrics of all datasets that have been referenced since the previous sweep and incrementally updating the existing dataset metrics A record indicating a change to a VTOC: allocation, scratch, extend, release, rename; gathered across the sysplex Incrementally updating the existing dataset metrics with the VTOC Change Records All systems in the sysplex have been providing VTOC change records to the collecting system since the previous sweep

90 What Changed? Dataset Attribute Database Clean sweep of DASD farm on every collection Catalog look-up for each dataset during VTOC scan Exponential CPU consumption on dataset attribute groups Data spaces Realtime Dataset Metrics Clean sweep of dasd farm on first collection only* Catalog look-up by HLQ after all VTOCs scanned Linear CPU consumption on dataset attribute groups 64 bit storage 90

91 Incremental Update of Data Store 2 Methods Can initiate sweep to update the data store, type is automatically selected If data store is synchronized; then an incremental sweep is done If data store is not synchronized, then a clean sweep is done Capture of VTOC changes at dataset level throughout the sysplex Can update the datastore with the VTOC change records*, some attributes may not be current Last reference date % used, tracks, MB, GB % free, tracks, MB, GB Allocated space is always current after any update or sweep Summary tables and User Groups are updated when datastore is updated 91

92 Benchmark Results Performance Environment 1.5 million datasets 3,000 logical volumes Sysplex with 7 z/os images Performance statistics were obtained on the Rocket Software development system in a non-scientific manner. Your environment will affect the results in your installation. You may experience better or worse results in your own environment. 92

93 Performance Comparison Function DADB CPU Seconds RDM CPU Seconds Datasets or Records Clean Sweep million 3000 volumes Comments Complete build of datastore (excludes DADB group processing) Incremental Sweep ,000 DADB always does a clean sweep Apply VTOC Change Records Dataset Attribute Database User Group n/a 13 47,900 Update datastore with VTOC changes from across the sysplex million Done after sweep or apply of change records 93

94 Increased Usage of E3270UI Use same SME environment as other OMEGAMONs Quicker time to value with less distributed-platform infrastructure Functional Parity with ITM equivalent infrastructure 94

95 TEP User Interface Changes 95

96 E3270 Changes 96

97 OMEGAMON For Storage v5.4 New Look

98 Please Note IBM s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM s sole discretion. Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision. the user s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here. The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract. The development, release, and timing of any future features or functionality described for our products remains at our sole discretion. Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in 10/16/2017

99 Upcoming Features Enhanced User Experience Target 2H 2017 Upgrade technology underneath and around OMEGAMON Storage: Modern thin web client user interface for both E3270UI and TEP Extended/expanded UI capabilities Analytics-driven space management workflow making SME tasks more efficient Simplify experience for new-to-z/os users

100 OMEGAMON Storage UI Modernization For OMEGAMON Storage: Enhanced 3270 UI and TEP UI (including customizations) are automatically rendered in web pages; New context actions are provided by the new framework (e.g. right-click on E3270UI table cell presents list of actions based on context). From here, if a Storage Group is running out of space you could right-click to launch into space management workflow

101 Upcoming Features Alice reviews the problem At the current growth rate, the group will run out of space in 14 hours. She adjusts Time Needed in order to implement the long term fix. She could also adjust the target capacity if she knew how much space was required. Adjustments can be made either by typing values, or adjusting the trend line. Alice is our persona representing a relatively new-to-z/os storage administrator; we have imagined some helpful workflows to make it easier for her to resolve a sudden space shortage issue

102 Upcoming Features Immediate Space Relief basic view The list of data sets to migrate is provided based on the capacity needed, last referenced date, and dataset size. Alice will migrate these data sets to get immediate space relief. Data listed can encompass unlimited number of lines of data (relieving current OMEGAMON limitation) In this simple view, editing of SQL to filter further is not show.

103 Upcoming Features Root Cause Analysis New analytics allow identification of the growing data set(s), and correlation to the using application and application owner. Using this built-in CICS discovery capability, Alice quickly determines that this storage group is occupied by data from a CICS application, and with the application definition, Alice sees that Lavonda in payroll is the owner.

104 Upcoming Features Application Owner Provides Input Alice is not sure how much more storage will be needed in the future for this application, so she elects to launch an optional workflow step where the CICS app owner is asked to provide capacity needs (600 GB)

105 Upcoming Features Alice makes final adjustments and approves Alice discusses the request with Lavonda and does not completely agree with her logic. Alice wants to allocate less capacity than requested, so she adjusts the capacity based on availability and her side discussion with Lavonda.

106 Upcoming Features Alice begins allocating volumes using the Capacity Wizard

107 Questions?

108 Thank You!