Scalable high availability technologies. Gergely Tomka
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1 Scalable high availability technologies Gergely Tomka
2 Session Outline What is high availability (a practical approach) Variations: Hardware solutions Hot/Cold clusters Large clusters Requirements, implementations and results 2
3 High availability The service must be available when we want it 24/7/365 availability is it real? Problems: How to detect a service failure? How to detect if the service is working? How to stop the service reliably? How to start a service reliably? Where is the single point of failure? 3
4 Single Point Of Failure Desktop machine: one disk, one NIC, one CPU, one PSU Server machine: one motherboard/system bus, multiple cpus, psus, nics Mainframe: three cores, two is working on the same issue, and the third is checking if the results are the same. Two node cluster from server machines: no SPOF in hardware! Are you sure? 4
5 Hardware redundancy Every cable must be duplicated Every network device must be replicated The network protocol must be able to handle the loss of a link SAN connections and devices most be doubled too System operators must be redundant and available too, no lonely heroes... 5
6 Single Point Of Failure Problems with the two nodes: Connection for checking service availability Common resources, mostly SAN disks Different levels of disaster: citywide? Or just a small fire in the serverroom? Price Example of risk assesment: A huge bomb could make 20 km destruction Place the two servers at least 30 km away If there was more than one 10 Mt H- bomb, trading will stop anyway. 6
7 Hot/Cold clusters Two nodes, one is working, one is waiting for trouble Users must define: Resources: disks, network interfaces, processes Scripts: for checking, starting and stopping the service or the resources Veritas Cluster Services or Coyote could be used for this purpose Failover is when the roles are changed Heartbeat: various solutions to allow the nodes to check on each other, usually via network. 7
8 Failure modes of Hot/cold clusters Maintenance script issues: service is down, but the script shows it up, etc. Solution: better scripts Owner issues: The users usually can manage the service without VCS, which means a service is not under control. Hard to detect, as the service is up, but the VCS tools are not in sync with reality Good recipe for disaster Lost connection: lost heartbeat, can lead to split brain Network or overload Split brain: when the two nodes are both hot Perfect recipe for disaster, especially with shared storage Gazelle/SCSI disk reservation Failed resources 8
9 Special cases Hot/hot node: two services, one is the default for each nodes. Various fencing solutions: Human: only manual failover SCSI disk reservation 9
10 Multinode clusters Ultimately one server is not powerful enough Variations: Load-balancing clusters Grids ESX Applications must be modified Performance limit is the sky Can be made efficiently 10
11 Load balancing 11
12 Load balancers The load balancer is a tool to distribute load between computing nodes Works with multiple clients, small jobs (transactions) It is, in itself a single point of failure Clustering, quick failover, preservation of states is important Methods for distributing the load: DNS : slow, not flexible, easy Router: quick, flexible, but the traffic must go through the load balancer Layer 7/App level load balancing: the load balancer must examine the traffic, not just passing it to the nodes 12
13 Load balancers Selecting nodes: Round robin Least loaded Standby nodes F5 could be used, but the Linux Virtual Server is also very good for testing 13
14 Grid In simple terms a grid is a group of computers working on the same tasks Works with big customers and parallel tasks Distributing the tasks and collecting the results is a big task Overloaded fileservers Torrent-like task and input data distribution Bandwidth The application must be rewritten for hundreds of independent nodes 14
15 Grid Nodes must be: Cheap Efficient Easy to replace Properly monitored 15
16 Grid effect 16
17 Grid Management Managing hundreds of nodes is a different art No individual alerts for errors No hardware repairs Statistical analysis of logfiles Geospatial analysis: find broken rooms/racks/networks/buildings 17
18 Sample Grid troubleshooting /afs/grid_utils/bin/search "Waiting for busy volume" /var/log/syslog /afs/grid_utils/bin/message_filter.pl Shows that it occurs times a day on hosts, roughly 3/host/day, winner has 13/day. So it's not a small group of hosts, not a single personality, not application related, probably not a huge deal at all, just background noise. Is it AFS-cell related? No, the distribution of the error is even among AFS cells: $ cut -d" " -f15 afs.txt sort uniq -c Is it tied to a single or few AFS volumes? Not sure, we have 157 volumes with the error per day but only 12 with errors, 20 with errors, the rest less than 3. Top AFS volume IDs: , , $ cut -d" " -f11 afs.txt sort uniq -c sort -nr Is it tied to a certain time of the day? I cut out the hours:minutes from the timestamp. Not really, it's nicely distributed throughout the day, every hour has a few, however it stands out, that it always occurs at :00 minutes, every hour, with higher activity at 7:00, 15:00, 21:00 - now that's suspicious. $ cut -d" " -f4 afs cut -d":" -f1,2 sort uniq -c 18
19 ESX VmWare ESXi is one of the current solutions for virtualized desktops Advantages of virtual desktops: Smaller, quieter devices in the workspace (thin client, old desktop machines) Desktop applications could be closer to the data Disadvantages: Added complexity Very new idea, lots of new problems 19
20 ESX Effects on teamwork: Windows desktops Vcenter is running on Windows servers ESXi is a stripped down Linux Storage is on netapp filers 20
21 ESX clusters Vmotion seamless migration of virtual hosts between nodes Vcenter software is necessary Cluster size is only 16 nodes A Vcenter can handle only 300 nodes Good for maintenance and for performance Vcenter is a serious disadvantage when you need hundreds of nodes Thousands of desktops are troublesome Very different culture in maintenance (reboot!) Disk activity, scheduled tasks (antivirus) 21
22 Storage solutions Cache systems Can help on read operations Cannot help on write operations Deduplication For ESX Need more CPU to recognize similar blocks/files, but it s using less space Speed Handmade NFS fileserver, 10GB writes got saturated immediately 22
23 Q & A 23
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