Jolyon White GEC9 2 nd November 2010 A Tutorial Introduction to OML

Introduction, Aims What is OML? –The Orbit Measurement Library –Most current version: OML v2.4.0 (but v2.5.0 is due out in a few days) –A client library (liboml2) for instrumenting your applications; plus –A measurement server for collecting and storing measurements, remotely. By the end of this tutorial you should be able to: Understand the OML system architecture Understand how to run OML applications –How to configure your app’s measurements –How to interpret the stored results How to use OML to instrument your experiment applications 2

OML – the Orbit Measurement Library Open Source, under active development –Started at WINLAB, work continuing at NICTA (Sydney) –*NIX target (currently Linux, Mac OS X, on i386, amd64, and ARM) Network research generates lots of data Need a way to get data to a central location for storage & analysis –Need a better option than local files + scp Main design aim: Hit the “power vs. simplicity” sweet spot: 3 Simple Limited Labour-intensive, error-prone OML Simple + Powerful By Design (Too) Complex Expensive OAM Robust Lots of features

OML Deployments 4 Rutgers University, New Jersey NICTA, Sydney Deutsche Telekom TU Berlin BOWL Testbed National Broadband Network 100Mbs FTTH VoD Trial IREEL Network Education Teaching Platform Rail Bridge Monitoring Sensors NSW Road Traffic Authority Parking Discovery Rutgers Marco Gruteser

OML System Architecture 5

Separation of Concerns Instrumentation –Adding measurement points to an application Collection –Running an experiment, collecting measurements OML makes a clean distinction between these two activities Application writer and application user might be different people OML supports users to do both activities effectively An application’s measurement collection is configurable at run-time –By the experimenter (application user) 6

OML Architecture – Types All measured values in OML are typed –True for the whole measurement pipeline Supported types: OML_STRING_VALUE is for short strings (<255 bytes) OML_BLOB_VALUE is for long blobs (max ~ 2 32 bytes) … more types planned (e.g. IP addresses) 7 Numeric: –OML_INT32_VALUE –OML_UINT32_VALUE –OML_INT64_VALUE –OML_UINT64_VALUE –OML_DOUBLE_VALUE String/arbitrary data: –OML_STRING_VALUE –OML_BLOB_VALUE

OML Architecture – Measurement Points Data enters the OML measurement system via a Measurement Point (MP) –Group related measurements Each MP has a name to identify it Every time the application wants to record a measurement, it injects a value into the MP “value” == typed tuple with named fields E.g. 8 MP udp_in = (ts : OML_DOUBLE_VALUE, flow_id : OML_INT32_VALUE, seq_no : OML_UINT32_VALUE, pkt_length : OML_UINT32_VALUE, src_host : OML_STRING_VALUE, src_port : OML_STRING_VALUE )

OML Architecture – Client + Server Application or Service Measurement pointsFiltersMeasurement streams OML Server Database (SQL) Database (SQL) Database tables File OML client library 9

OML Architecture – Measurement Collection OML Server 10 Application Experiment Node OML Server Application Experiment Node Application Experiment Node Application Measurements Destination for each stream configured at run time (XML config file)

So far, so good OML’s client/server architecture is simple but Most complicated part of OML comes from –Filtering –Measurement streams –Schemas 11

OML Architecture – Filters Filters are for: –Selection –Transformation Filters are executed by liboml2, i.e. within the same process as the application Take input from an MP –Can SELECT one field or multiple fields Compute a new value based on the input –TRANSFORM to a new value Input can be multiple fields from one MP Output can have multiple fields – tuple 12

OML Architecture – Filters OML has numerous standard filters built-in Example: averaging filter (avg) Each filter has an output schema Types in the output schema can be either: –A specific type (e.g. OML_UINT32_VALUE); or –“whatever type you gave me as input” Some filters are picky (e.g. avg only accepts numeric types) 13 avg avg : DOUBLE max : DOUBLE min : DOUBLE ts : DOUBLE flow_id : INT32 seq_no : UINT32 pkt_length : UINT32 src_host : STRING src_port : STRING MP udp_in:

OML Architecture – Measurement Streams Each filter takes input from one MP Filters are grouped based on destination (more later) A Measurement Stream (MS) groups all the filter outputs from one MP to one destination Each MS has a schema –Combination of schema of filter outputs 14 MP (A, B, C) A B C (S, T) (U, V, W) (X, Y) (S, T, U, V, W, X, Y) MS Schema

OML Architecture – Schemas and the DB An OML app declares schemas for each MS to the remote server –Handled automatically by liboml2 Each application has a name Each MS schema has a name Each schema field has a name and a type Names are derived from: –App name –MP name –MP field name –Filter output field name One MS  One database table 15

OML Architecture – Schemas and the DB Example: app name is “otr2” Schema: SQL issued to the database: 16 avg avg : DOUBLE max : DOUBLE min : DOUBLE ts : DOUBLE flow_id : INT32 seq_no : UINT32 pkt_length : UINT32 src_host : STRING src_port : STRING MP udp_in: otr2_udp_in : pkt_length_avg:double pkt_length_max:double pkt_length_min:double CREATE TABLE otr2_udp_in ([other stuff], pkt_length_avg REAL, pkt_length_max REAL, pkt_length_min REAL);

OML Architecture – Filters (again) Filters operate in either count- or interval-sampling mode Filter can accumulate state over the sampling period Filter generates an output at end of sampling period E.g. 1) every 10 samples E.g. 2) every 3.5 seconds For instance, if count=10, avg filter outputs the average of the last 10 samples, then resets its internal state. See ‘—oml-samples’ and ‘—oml-interval’ command line options 17

Collection: Using and Configuring OML Applications 18

Configuring Client Applications Two options –Command line –XML config file Mandatory configuration items: –Node ID ( --oml-id ) – identify source of a measurement –Experiment ID ( --oml-exp-id ) – group related measurements in one database –Destination address (local file name or remote host:port) --oml-file --oml-server : Experiment ID == Database Name 19

Node A’Node BNode A Configuring Client Applications 20 App1, ID B, E1 App2, ID B, E1 App1, ID A, E2 App3, ID A, E2 App1, ID A, E1 App2, ID A, E1 E1 E2 OML Server

Command Line Configuration $ nmetrics_oml2 --oml-id node1 \ --oml-exp-id monitor \ --oml-file cpu.txt \ --cpu --ram 21 OML options Nmetrics options $ nmetrics_oml2 --oml-id node1 \ --oml-exp-id monitor \ --oml-server : cpu --ram

Sampling policy Count-based sampling: --oml-samples Interval-based: --oml-interval 22 $ nmetrics_oml2 --oml-id node1 \ --oml-exp-id monitor \ --oml-server :3003 \ --oml-interval cpu --ram

Sampling policy and filter configuration Command line config establishes default filters One filter for each field of each MP Default filter type depends on field type: –Numeric MP field  Averaging filter –Other types (e.g. string)  ‘First’ filter The ‘first’ filter outputs the first value in the sampling period Throws away the rest BUT: for ‘ --oml-samples 1 ’, numeric fields get a first filter instead 23

Custom configuration – config file XML First: establish destinations – Second: select MP – Third: create filters for each MP – Example: one destination, one MP, one filter 24

Config file – longer example 25

Packaged applications oml2-nmetrics – libsigar wrapper (node monitoring) oml2-trace – libtrace wrapper (including radiotap) oml2-wlanconfig – wrapper around wlanconfig(1) oml2-gps – interface to gpsd(1) for GPS location data oml2-iperf – instrumented version of iperf –Currently iperf version 1.7 –Version 2.0 (and maybe 3.0) under development otg2 / otr2 – Orbit traffic generator & receiver –Background traffic generator Open to contributions! 26

OMF Integration OMF provides support for OML applications Launching on remote nodes Automatically set node ID Automatically set experiment ID Configure measurement collection from OMF experiment script Access and visualize results –Through OMF Aggregate Manager 27

Visualization 28

Instrumentation: Writing/Modifying Applications to Use OML 29

Writing OML Applications OML applications link against liboml2 Liboml2 provides API for: –Defining Measurement Points; –Injecting measurement samples into MP’s Liboml2 also executes filters API consists of 5 main functions: –omlc_init() – initialize library –omlc_add_mp() – define measurement points –omlc_start() – start measurement sampling + filtering system –omlc_inject() – inject a sample into a measurement point –omlc_close() – shut down the OML client library 30

OML Application Phases 31 Initialize Establish MP’s Main application loop Main application loop Record measurements omlc_add_mp() omlc_init() omlc_inject() End application omlc_close()

OML Initialization omlc_init() processes command line vector –Parses and removes all ‘—oml-’ options –Sets up internal library configuration Must call omlc_init() before other OML functions Example: 32 #include int main (int argc, const char **argv) { int result = omlc_init(“myapp”, &argc, argv, NULL); /*... */ /* Process application’s own options */ /* Do the application */ return 0; }

Establishing Measurement Points After initialization, call omlc_add_mp() to create MP’s MP is defined as a C array: Final element is a sentinel to terminate the array (important!) OmlMPDef array is an input to omlc_add_mp() 33 OmlMPDef mpdef [] = { { “label”, OML_STRING_VALUE }, { “pkt_count”, OML_UINT32_VALUE }, { “throughput”, OML_DOUBLE_VALUE }, { NULL, (OmlValueT)0 } /* Terminator */ }

Establishing Measurement Points Example call omlc_add_mp(): 34 #include int main (int argc, const char **argv) { int result = omlc_init(“myapp”, &argc, argv, NULL); OmlMPDef mpdef [] = { { “label”, OML_STRING_VALUE }, { “pkt_count”, OML_UINT32_VALUE }, { “throughput”, OML_DOUBLE_VALUE }, { NULL, (OmlValueT)0 } /* Terminator */ }; OmlMP *mp = omlc_add_mp(“packets”, mpdef); /* Define more MP’s (no limit on calls to omlc_add_mp() */ return 0; }

Starting measurement and the main loop After all MP’s are initialized, call omlc_start() to kick off measurement sampling Can’t call omlc_add_mp() again after calling omlc_start() Can’t call omlc_inject() until after calling omlc_start() 35

Application main loop 36 int main (int argc, const char **argv) { int result = omlc_init(“myapp”, &argc, argv, NULL); OmlMPDef mpdef [] = {... }; OmlMP *mp = omlc_add_mp(“packets”, mpdef); omlc_start() /* Enable measurement system */ while (1) { char *label; uint32_t pkt_count; double throughput; OmlValueU v[3]; // same size as MP /* do some application logic; compute values for the 3 variables above */ omlc_set_string(v[0], label); omlc_set_uint32(v[1], pkt_count); omlc_set_double(v[2], throughput); omlc_inject (mp, v); } return 0; }

Rules on naming Application name, MP names, and MP field names must be valid C identifiers i.e. start with an underscore or letter, followed by alpha- numeric + underscore characters No spaces allowed Reason 1: spaces in names make schemas harder to parse Reason 2: these names appear in database table + column names Reason 3: we do code generation 37

Easier app definition with oml2_scaffold oml2_scaffold(1) –Generate C-code for MP definitions from declarative spec –Can also declare command line options for your app 38 defApplication('app:myapp', ’myapp') do |a| a.version(1, 0, 0) a.shortDescription = 'Application to count packets' a.description = %{ This application counts packets and measures throughput } a.defProperty('address', 'address to bind to', ?a, :type => :string) a.defProperty('port', 'port to bind to', ?p, :type => :int, :default => 2947) # Define one MP a.defMeasurement(”packets") do |m| m.defMetric('label', 'string', 'Packet label') m.defMetric('packets', 'uint32', 'Number of packets received') m.defMetric('throughput', 'double', 'Packet throughput') end

oml2_scaffold(1) oml2_scaffold automatically generates: –OmlMPDef arrays –A global struct of OmlMP pointers, g_oml_mps –A function to register all MP’s, oml_register_mps() oml2_scaffold can also generate: –A libpopt compatible command line arguments specification –A skeleton main.c –A Makefile The skeleton can actually be built and run using the Makefile Application description can be used by OMF 39

oml2_scaffold(1) More information: –man oml2_scaffold – Unix man page – Tutorial – 40

Instrumentation – General Strategies Write from scratch –Easy: build application around oml2_scaffold description Existing application – with source code –Moderate: Analyze code: –Find where to initialize OML – before app processes its command line –Find out what you want to measure Create MP’s Insert omlc_inject() statements where needed –E.g. iperf, see tutorial: Existing application – no source code –Use fork(2) & pipe(2), then parse the app’s stdout –Same, but use oml4r.rb – Ruby implementation of text protocol 41

The OML Proxy Server: Handling disconnection 42

Measurement with Mobile Nodes Sometimes only one wireless interface No dedicated control network –Measurement traffic affects experiment outcome Sporadic connectivity –What do we do with measurement traffic when disconnected? Sometimes fixed network experiments suffer similar problems –E.g. if measurement traffic > measurement network BW –Fixed nodes with only one interface 43

Measurement with Mobile Nodes Fixed Testbed Experiment network(s) Control/measurement network Measurement server

Proxy Server Buffer measurements on command –Don’t transmit to remote server Same protocol as oml2-server –Transparent to client applications Proxy server OML Server Application PAUSERESUME 45

Future directions Refactor server into a library (in progress) –Clients can also be endpoints –Servers can also be clients –Hierarchy of measurement generators & collectors Streaming queries Alternative transports: IPFIX main priority Alternative database backends: PostgreSQL in v2.6.0 Make oml2_scaffold more betterer –Generate injection function for each MP  no need for OmlValueU array –Generate OMF application descriptions –Make coffee Bindings to other languages: Ruby, Python, Java (Android!) 46

Get it now! – Links Project pages –OML: –OML Applications: Debian/Ubuntu packages – – Packages for Fedora Core 8 known to exist (PlanetLab) Source tarballs – – From the source repo: –git clone git://mytestbed.net/oml.git –git clone git://mytestbed.net/oml-apps.git 47