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Case Studies of Disaster Tolerance and Disaster Recovery with OpenVMS Keith Parris, HP. Case Study: 3,000-mile Cluster. Case Study: 3,000-mile Cluster. Unidentified OpenVMS customer 3,000 mile site separation distance Disaster-tolerant OpenVMS Cluster
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Case Studies of Disaster Tolerance and Disaster Recovery with OpenVMS Keith Parris, HP
Case Study: 3,000-mile Cluster • Unidentified OpenVMS customer • 3,000 mile site separation distance • Disaster-tolerant OpenVMS Cluster • Originally VAX-based, thus running for many years now, so presumably acceptable performance
Case Study: Global Cluster • Internal HP test cluster • IP network as Cluster Interconnect • Sites in India, USA, Germany, Australia, etc. at various times • Inter-site distance (India-to-USA) about 8,000 miles • Round-trip latency of about 350 milliseconds • Estimated circuit path length about 22,000 miles
HP facility, GERMANY I64G05 HP facility, USA HP facility INDIA HPVM guest NORSP Global IPCI Cluster NODEG TASHA Corporate network / internet L2/L3 switch PERK L3 Switch HUFFLE L3 Switch HP facility, Australia HP facility Bangalore, INDIA I64MOZ
Case Study: 1,400-mile Shadowing • Healthcare customer • 1,400 mile site separation distance • 1,875 mile circuit length; 23-millisecond round-trip latency • Remote Vaulting (not clustering) across distance • Independent OpenVMS Clusters at each site (not cross-site) • Synchronous Replication using Volume Shadowing • SAN Extension over OC-3 links with Cisco MDS 9000 series FCIP boxes • Writes take 1 round trip (23 millisecond write latency)
Case Study: 1,400-mile Shadowing • Did things right: tested first with inter-site distance simulated using latency of 30 milliseconds with network emulator box; 23 millisecond latency in the real-life configuration turned out to be even better • Caché database -- seems to be tolerant of high-latency writes and doesn’t let those slow writes block reads
Case Study: 1,400-mile Shadowing • Later replaced Host-Based Volume Shadowing over the 1,400-mile distance with Caché Shadowing asynchronous replication for DR purposes • Trade-off: Better performance but risk some transaction data loss in conjunction with a disaster • Still use HBVS within each site • Considering short-distance multi-site DT clusters at each end
Case Study: Proposed 600-mile Cluster • Existing OpenVMS DT cluster with 1-mile distance • One of two existing datacenters is to be closed • Proposed moving one-half of the cluster to an existing datacenter 600 miles away • Round-trip latency 13 milliseconds • Estimated circuit path length about 800 miles
Case Study: Proposed 600-mile Cluster • Month-end processing time is one of the most performance-critical tasks • Tested in OpenVMS Customer Lab using D4 • Performance impact too high: • Performance at 600 miles was unacceptable • From results of tests at shorter distances we were able to extrapolate that performance would be acceptable if the circuit path length were 150-200 miles or less
Case Study: Proposed 600-mile Cluster • Customer found a co-location site 30 miles away • Systems were moved from the one datacenter to the Co-Lo site • Network connections are via DWDM with Dual 1-Gigabit Ethernet and Dual Fibre Channel SAN links • Systems are clustered with the original site, with Volume Shadowing for data replication • This move was accomplished without any application downtime • Asynchronous replication (e.g. Continuous Access) to the site 600 miles away can be used for DR protection
Case Study: 20-mile DT Cluster • Existing OpenVMS Cluster • Needed protection against disasters • Implemented DT cluster to site 20 miles away • 0.8 millisecond round-trip latency • Estimated circuit path length about 50 miles
Case Study: 20-mile DT Cluster:Pre-existing Performance Issues • Performance of night-time batch jobs had been problematic in the past • CPU saturation, disk fragmentation, directory files of 3K-5K blocks in size, and need for database optimization were potential factors
Case Study: 20-mile DT Cluster:Post-implementation Performance Issues • After implementing DT cluster (shadowing between sites), overnight batch jobs now took hours too long to complete • Slower write latencies identified as the major new factor • Former factors still uncorrected • With default Read_Cost values, customer was getting all the detriment of Volume Shadowing for writes, but none of the potential benefit for reads
Case Study: 20-mile DT Cluster:Write Latencies • MSCP-serving was used for access to disks at remote site. Theory predicts writes take 2 round trips. • Write latency to local disk measured at 0.4 milliseconds • Write latency to remote disks calculated as: • 0.4 + ( twice 0.8 millisecond round-trip time ) = 2.0 milliseconds • Factor of 5X slower write latency
Case Study: 20-mile DT Cluster:Write Latencies • FCIP-based SAN Extension with Cisco Write Acceleration or Brocade FastWrite would allow writes in one round-trip instead of two • Write latency to remote disks calculated as: • 0.4 + ( once 0.8 millisecond round-trip time ) = 1.2 milliseconds • Factor of 3X slower write latency instead of 5X
Case Study: 20-mile DT Cluster:Read Latencies • Shadowset member disks contain identical data, so Shadowing can read from any member disk • When selecting a shadowset member disk for a read, Volume Shadowing adds the local queue length to the Read_Cost value and selects the disk with the lowest total to send the read to.
Case Study: 20-mile DT Cluster:Read Latencies • Default OpenVMS Read_Cost values: • Local Fibre Channel disks = 2 • MSCP-served disks = 501 • Difference of 499 • Queue length at local site would have to reach 499 before sending any reads across to the remote site
Case Study: 20-mile DT Cluster:Read Latencies • Question: How should Read_Cost values be set for optimal read performance with Volume Shadowing between two relatively-nearby sites? • Example: 50-mile circuit path length, 0.8 millisecond round-trip latency, average local read latency measured at 0.4 milliseconds • MSCP-served reads can be done in one round trip between sites instead of the two required for writes
Case Study: 20-mile DT Cluster:Read Latencies • Read latency to remote disks calculated as: • 0.4 + ( one 0.8 millisecond round-trip time for MSCP-served reads ) = 1.2 milliseconds • 1.2 milliseconds divided by 0.4 milliseconds is 3 (3X worse performance for remote reads) • At a local queue length of 3 you would start to get a response time equal to a remote read • so certainly at a local queue depth of 4 or more it might be beneficial to start sending some of the reads across to the remote site: • Therefore, a difference in Read_Cost values of around 4 might work well
Case Study: 20-mile DT Cluster:Workaround for High Write Latencies • Workaround: They remove remote shadowset members each evening to get acceptable performance overnight, and put them back in with Mini-Copy operations each morning. • Recovery after a failure of the main site would include re-running night-time work from the copy of data at the remote site • Business requirements in terms of RPO, RTO happen to be lenient enough to permit this strategy
Case Study: 3-site Cluster:Network configuration • Major new OpenVMS Customer, moving from HP-UX to OpenVMS • Dual DWDM links between sites • Gigabit Ethernet for SCS (cluster) traffic • Fibre Channel for storage • EVA storage shadowed between 2 sites • Quorum node at 3rd site
Case Study: 3-site Cluster:Network configuration Site A Site B Node Node LAN LAN DWDM DWDM Node Node DWDM DWDM Node Node Quorum Site Node
Case Study: 3-site Cluster:Network configuration Site A Site B Node Node LAN LAN DWDM DWDM Node Node DWDM DWDM Node Node Quorum Site Node
Case Study: 3-site Cluster:Shadowing configuration Site A Site B Node SHADOW_SITE_ID=1 Node SHADOW_SITE_ID=2 SAN SAN DWDM DWDM DWDM DWDM Node SHADOW_SITE_ID=2 Node SHADOW_SITE_ID=2 EVA EVA $SET DEVICE/SITE=1 $SET DEVICE/SITE=2
Case Study: 3-site Cluster:Shadowing configuration Site A Site B Node SHADOW_SITE_ID=1 Node SHADOW_SITE_ID=2 SAN SAN DWDM DWDM DWDM DWDM Node SHADOW_SITE_ID=2 Node SHADOW_SITE_ID=2 EVA EVA $SET DEVICE/SITE=1 $SET DEVICE/SITE=2
Case Study: 3-site Cluster:Shadowing configuration Site A Site B Node SHADOW_SITE_ID=1 Node SHADOW_SITE_ID=2 SAN SAN DWDM DWDM Reads Reads DWDM DWDM Node SHADOW_SITE_ID=2 Node SHADOW_SITE_ID=2 Reads EVA EVA $SET DEVICE/SITE=1 $SET DEVICE/SITE=2
Case Study: 3-site Cluster:Shadowing configuration Reads Site A Site B Node SHADOW_SITE_ID=1 Node SHADOW_SITE_ID=2 SAN SAN DWDM DWDM Reads Reads DWDM DWDM Node SHADOW_SITE_ID=2 Node SHADOW_SITE_ID=2 Reads EVA EVA $SET DEVICE/SITE=1 $SET DEVICE/SITE=2
Case Study: Proposed Multiple Disaster-Tolerant Clusters using HPVM
Case Study: Proposed DT Clusters using HPVM • Educational customer, state-wide network • OpenVMS systems at 29 remote sites • Proposed using HPVM on Blade hardware and storage at central site to provide 2nd site and form disaster-tolerant clusters for 29 other sites simultaneously
Case Study: Proposed DT Clusters using HPVM • Most of the time only Volume Shadowing would be done to central site • Upon failure of any of the 29 sites, the OpenVMS node/instance at the central site would take over processing for that site
Speaker contact info: E-mail: Keith.Parris@hp.com or keithparris@yahoo.com Web: http://www2.openvms.org/kparris/