telestax: processing billions of sms records daily for a top tier telecom

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Telecom Big Data Processing Billions of SMS Records Daily with Cassandra NoSQL Ivelin Ivanov CEO, co-founder Athar Rafiq Sr Manager - IT, UFone, Etisalat Group

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Telecom Big Data Processing Billions of SMS Records Daily with

Cassandra NoSQL

Ivelin IvanovCEO, co-founder

Athar Rafiq Sr Manager - IT, UFone, Etisalat Group

About Ufone

● Ufone is a wholly owned subsidiary of Pakistan Telecommunication Company Limited (PTCL).

● Started operations in January 2001● Built a subscriber base of over 24 million in less

than a decade● As a result of PTCL's privatization, Ufone became

a part of the Etisalat in 2006.● Ufone offers Pakistan's fastest growing 3G

network services

The Business Challenge

● New business use case for SMS marketing● Requires processing of hundreds of millions of

SMS per day and billions of CDR records● Too expensive to purchase additional legacy

infrastructure for SMS

The Technical Challenge

● Legacy telecom infrastructure● Black boxes that cannot be extended● Legacy inflexible and very very expensive vendor

Objective

To deploy a cost effective, highly robust and carrier proven SMSC that can be integrated with Ufone’s Campaign Management Solution.

Telestax SMSC in Ufone

● Very Robust handling 40-50 M SMS/day● Cost Effective/virtual Infrastructure● Highly Reliable● Store & Forward● Integrated with IBM’s Omni Channel Marketing

(formerly known as UNICA)● Handling Multiple LA (short codes)

Future Plans

● Expansions in existing capacity● Integrating Telestax SMSC with Digital Services

Platforms● Applications access to Big Data analytics using

APIs

About Telestax

The #1 Open Source Communications

Middleware

Restcomm.com

Worldwide customers

9

Telestax Customers

Direct paying customers in over 50 countries. Not counting sales via channel partners.

Powered by the TeleStax Communications Platform based on Mobicents

RestComm allows Service Providers and Enterprises to

improve end user experience and optimize business workflows

via Real Time Communications

The Road From Blag Box to Big Data

Early failures

● Started with RDBMS, soon faced below challenges○ How to be

■ Scalable with massive writes and reads■ Distributed■ Control over performance characteristics■ High Availability■ Low Latency■ Low hardware + software cost

○ No strict ACID requirements. Doesn’t matter much if SMS is not delivered instantaneously.

Early failures

● Started with naive NoSQL use - Cassandra● Beginners mistake of using normalized data

structures as SQL habits advise● Inserts were super fast● Reads failed horribly● Deletes were amazingly slow

Final solution

● Forget normalization!● Single Table, dynamically add columns

○ One Table each for live (retry) SMS and archived (delivered or permanently failed) SMS

● Tables created for each day○ Easy management ○ Archiving○ Fast Read

DestinationNumber TimeSlot SMS1 SMS2 SMS3 ... ... ...

15129999999 t1 xxx yyy zzz ... ... ...

Dynamically add columns

Composite Primary Key

Final solution (cont.)

● Never Delete rows!○ SSTables are immutable. We can’t remove rows○ Cassandra creates Tombstones for deleted data

● Any SMS failed, is inserted in new row with new timeslot

● Drop Tables

DestinationNumber TimeSlot SMS3 ... ... ... ... ...

15129999999 (t1+10) zzz ... ... ... ... ...

Dynamically add columns

Composite Primary Key

Final solution - Architecture

Final solution - Architecture

Lessons Learned

● Can’t ignore Cassandra’s internal workings● Read performance is heavily dependent on the

temporal patterns of your writes● Various write patterns make read performance

slowly decrease● Avoid deleting data, instead think of ways where

the whole table can be dropped

● Sales. Improving web site user conversion rates via intelligent integration of web calls data into marketing funnel.

● Support. Improving customer support by replacing archaic 1-800 menus and blind transfers into contextual intelligent agent response.

● Marketing. Measuring campaigns by intelligently blending call data with web and mobile app user data.

● We are barely scratching the surface of RTC analytics

Future Opportunities in Telco Analytics

From Dreaded Telecom to Programmable Contextual RTC