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Designing High Availability Networks, Systems, and Software for the University Environment Deke Kassabian and Shumon Huque The University of Pennsylvania.

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Presentation on theme: "Designing High Availability Networks, Systems, and Software for the University Environment Deke Kassabian and Shumon Huque The University of Pennsylvania."— Presentation transcript:

1 Designing High Availability Networks, Systems, and Software for the University Environment Deke Kassabian and Shumon Huque The University of Pennsylvania January 14, 2004

2 Copyright D.Kassabian and S.Huque [2004]. This work is the intellectual property of the authors. Permission is granted for this material to be shared for non-commercial, educational purposes, provided that this copyright statement appears on the reproduced materials and notice is given that the copying is by permission of the author. To disseminate otherwise or to republish requires written permission from the authors.

3 About Penn The University of Pennsylvania was founded by Ben Franklin in 1740 Penn is part of the Ivy League Located in western Philadelphia Community of more than 35,000 people

4 General Goals Networked services available as expected by our users Minimized time to repair (TTR) for when outages do occur Ability to perform maintenance and upgrades (planned downtime) non- disruptively Cost effectiveness in meeting these goals

5 Definitions Availability High Availability (HA) Rapid Recovery (RR) Disaster Recovery (DR) Basic Systems

6 Definitions Disaster Recovery (DR) -The process of restoring a service to full operation after an interruption in service

7 Definitions Basic System - a Basic System is a {Network, System, Service} with only the most basic of protections against outages Examples: A network recoverable using spare parts A single computer system with RAID disk A service recoverable from tape backups

8 Definitions Availability - the percentage of total time that a {Network, System, Service} is available for use Related points: Advertised periods of availability Availability as advertised Absolute availability

9 Definitions High Availability (HA) - a {Network, System, Service} with specific design elements intended to keep availability above a high threshold (eg, 99.99%)

10 Definitions Rapid Recovery (RR) - a {Network, System, Service} with specific design elements intended to recover from downtime very quickly (eg, 15 minutes)

11 Metrics Economics of high availability (the costs of non-available) Calculating availability How availability measurements are performed

12 Economics of high availability What is the cost of an outage in your Student Courseware systems and student record systems Financial systems Primary campus web site and Email servers DNS, DHCP and AuthN systems Internet connection(s) Development / Gifts systems How much should you be willing to spend to minimize downtime of any or all of these?

13 Calculating availability Availability can be measured directly through periodic polling (eg, SNMP, Mon, Nagios) A formula for predicting availability of a single component MTBF (MTBF+TTR) 1 TTR (MTBF+TTR) or

14 Design Principals Towards HA Minimize points of catastrophic failure Maximize redundancy Minimize fault zones Minimize complexity and cost Applying the above principles to Networks Systems Services

15 Specific examples at Penn High Availability Services Rapid Recovery Services

16 High Availability Design Strategies employed to achieve HA: Server redundancy Hardware component redundancy Storage redundancy (RAID) Network redundancy Redundant power, A/C, cooling etc Application protocols that can transparently failover to alternate servers Secondary offsite hosting (of some services like DNS)

17 Rapid Recovery Design Strategies employed to achieve RR: Standby servers and storage Some HA design elements: Hardware redundancy, storage redundancy, network redundancy, power, A/C redundancy etc Note: services deployed in the RR model typically dont have an easy way to transparently failover to alternate servers (eg. E-mail, Web etc)

18 Network Aggregation Point Abbreviation: NAP Machine rooms in separate campus locations that house critical network electronics and servers. Good environmentals and connectivity to campus fiber-optic cable plant Both HA and RR services utilize multiple NAPs

19 Central Infra. Networks AKA NOC Networks (historical name) 3 highly redundant IP networks that house systems providing critical infrastructure services Each network is triply connected to campus routing core via distinct NAP locations Use of router redundancy protocols (VRRP) & Layer-2 path redundancy (802.1D) for high availability

20 HA Server Platforms Two sets of three replicated servers 3 KDC servers: central authentication 3 NOC servers: everything else Kerberos runs on separate systems mainly for security reasons.

21 High Availability: KDCs KDCs (3): 3 distinct machines (kdc1, kdc2, kdc3) Each located in a different campus machine room Each connected to a distinct IP network Via a distinct IP core router Additionally each network is triply connected to the campus routing core via 3 NAPs

22 High Availability: NOCs 3 NOC systems (a historical name) Provide: DNS, DHCP, NTP, RADIUS plus a few homegrown services Same physical and network connectivity as the KDCs In addition: some servers have a secondary interface on a different NOC network (for reasons to be explained later)

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28 HA Application Failover Kerberos DNS RADIUS NTP DHCP Current spec supports only 2 failover systems Non-HA homegrown services: PennNames

29 Rapid Recovery service Example: E-mail and Web service A set of servers and storage is replicated at two sites: primary and standby Primary site: active servers and storage Secondary site: standby servers and replicated storage Data from 1st site is synchronously replicated to 2nd Two separate fibrechannel networks interconnect systems and storage at both sites Catastrophic failure event: system can be manually reconfigured to use the standby servers and/or secondary storage ( ~ 30 minutes) Servers are located on the HA primary infrastructure network

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31 Experiences at Penn Where these approaches have been helpful Higher availability, non-disruptive maintenance Where they have not Complexity can be hard to manage! Where cost has been high Replicated systems and networks, high-end storage solutions Real availability experience DNS, a critical service, went from 99.0% to 99.999% availability!

32 Future Enhancements Making RR services highly available: clustering, IETF rserpool etc Metropolitan area DR (or better) Others: IP Multipathing Trunking links to servers 802.1ad, SMLT, DMLT or similar Rapid Spanning Tree (IEEE 802.1w) Multi-master KADM service Improved management and monitoring infrastructure

33 Feedback Questions, comments Your designs, experiences, successes Contact Info: deke@isc.upenn.edu shuque@isc.upenn.edu


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