Ahead of the Pack: the Pacemaker High-Availability Stack
This configuration protects against both resource and node failure. If one of the virtual domains crashes, Pacemaker recovers the KVM instance in place. If a whole node goes down, Pacemaker reshuffles the resources so the remaining nodes take over the services that the failed node hosted. In the screen dump below, charlie has failed and bob has duly taken over the virtual machine that charlie had hosted:
============ Last updated: Sat Feb 4 16:18:00 2012 Stack: openais Current DC: bob - partition with quorum Version: 1.1.6-4.el6-89678d4947c5bd466e2f31acd58ea4e1edb854d5 3 Nodes configured, 2 expected votes 9 Resources configured. ============ Online: [ alice bob ] OFFLINE: [ charlie ] Full list of resources: Clone Set: cl_iscsi [p_iscsi] Started: [ alice bob ] Stopped: [ p_iscsi:2 ] p_ipmi_alice (stonith:external/ipmi): Started bob p_ipmi_bob (stonith:external/ipmi): Started alice p_ipmi_charlie (stonith:external/ipmi): Started alice p_xray (ocf::heartbeat:VirtualDomain): Started bob p_yankee (ocf::heartbeat:VirtualDomain): Started bob p_zulu (ocf::heartbeat:VirtualDomain): Started alice
Figure 1. Normal operation; virtual domains spread across all three cluster nodes.
Figure 2. Node charlie has failed; alice has automatically taken over virtual domain zulu.
Once the host charlie recovers, resources can optionally shift back to the recovered host automatically, or they can stay in place until an administrator reassigns them at the time of her choosing.
In this article, I barely scratched the surface of the Linux high-availability stack's capabilities. Pacemaker supports a diverse set of recovery policies, resource placement strategies and cluster constraints, making the stack enormously powerful.
Node: in cluster terminology, any system (typically a server) that participates in cluster communications and can potentially host cluster resources.
Fencing: a means of coordinating access to shared resources in the face of communications failure. Once a node stops responding to cluster messages unexpectedly (as opposed to gracefully signing off), other nodes shut it down to ensure it no longer has access to any shared resources. Usually enabled by making an out-of-band connection to the offending node and flipping the virtual power switch, IPMI-over-LAN being the most widely used implementation.
Resource: anything that a cluster typically manages. Resources can be very diverse, from simple IP addresses to complex database instances or dæmons.
Ring: in Totem protocol terminology, one of the (typically redundant) links over which cluster messaging communicates.
"The Totem Single-Ring Ordering and Membership Protocol" (research paper explaining the Totem protocol): http://www.cs.jhu.edu/~yairamir/tocs.ps
"Clusters From Scratch" (hands-on documentation for Pacemaker novices): http://www.clusterlabs.org/doc/en-US/Pacemaker/1.1/html/Clusters_from_Scratch
"Pacemaker Configuration Explained" (reference documentation of Pacemaker configuration internals, not for the faint at heart): http://www.clusterlabs.org/doc/en-US/Pacemaker/1.1/html/Pacemaker_Explained
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
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