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Enhancing Performance in Shibboleth Origin: A Comprehensive Approach

Learn about optimizing Shibboleth's performance through caching, library optimizations, and hardware accelerators. Discover how JuiCE improves latency and throughput, offering substantial speed enhancements. Explore best practices and pitfalls to avoid.

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Enhancing Performance in Shibboleth Origin: A Comprehensive Approach

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  1. Improving Shibboleth Origin Performance Walter Hoehn Internet2 Spring Member Meeting 2004

  2. Origin Transaction Overhead • 50-75% of transaction time falls into one of 3 categories • SSL (browser->HS & SHAR->AA) • Performance considerations are well understood • Multiple processors, load distribution, hardware accelerators • AA communication with backend data sources • Cost is variable, depending on infrastructure • Optimization is site dependant • We implemented caching in v1.0 • Signing Operations in HS (public key encryption) • Low hanging fruit

  3. Apache XML Security Library • Implements W3c XML Security standards • XML Encryption Syntax & Processing • XML Signature Syntax & Processing • Uses the JCA/JCE interfaces for crypto • Digitally signs SAML AuthN Assertions • Performance Bottleneck • Latency • Throughput • Library Optimizations included in 1.1

  4. JuiCE • JCE -> OpenSSL using JNI • Plugs into existing java apps without modification • Apache, here we come! • OpenSSL Engine

  5. Enough talk, show me the numbers… • Solaris - Sun Netra X1, 500mhz, 1gb RAM • 160.3 ms - Sun JCE Provider • 40.1 ms - JuiCE • OSX - Mac Dual 2ghz G5, 1gb RAM • 12.3 ms- Sun JCE Provider • 8.1 ms - JuiCE • Linux - 2.3 ghz Pentium 4, 1gb RAM • 30 ms- Sun JCE Provider • 9.4 ms - JuiCE

  6. More numbers… • Solaris • 75% improvement • Mac • 34% improvement • Linux • 69% improvement Averages 3 times faster!

  7. Where do we go from here? • Further development of JuiCE • Support for hardware crypto accelerators • Further optimization of XML Security Library • Shibboleth performance FAQ • Best practices for configuration • Hardware/Software platform recommendations • Metrics • Pitfalls

  8. Walter Hoehn wassa@memphis.edu shib-users@internet2.edu juice-dev@xml.apache.org

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