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. About Penn The University of Pennsylvania was founded by Ben Franklin in 1751 Penn is part of the Ivy League Located in western Philadelphia Community of more than 30,000 people

3. 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

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

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

6. 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

7. 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

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

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

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

11. 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?

12. 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

13. 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

14. Specific examples at Penn High Availability Services Rapid Recovery Services

15. 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)

16. 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 don’t have an easy way to transparently failover to alternate servers (eg. E-mail, Web etc)

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

18. 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 Network wiring traverses physically diverse fiber conduit pathways Use of router redundancy protocols (VRRP) & Layer- 2 path redundancy (802.1D) for high availability

19. 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.

20. High Availability: KDCs KDCs (3): 3 distinct machines (kdc1, kdc2, kdc3) Run only Kerberos AS and TGS 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

21. 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)

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

28. 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

30. 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!

31. Future Enhancements Making RR services highly available: “clustering”, IETF rserpool etc Metropolitan area DR (or better) Rolling disaster protection Others: IP Multipathing Trunking links to servers 802.3ad, SMLT, DMLT or similar Rapid Spanning Tree (IEEE 802.1w) Multi-master KADM service Improved management and monitoring infrastructure

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