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Customer Experience & Network Evolution Plans

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Presentation on theme: "Customer Experience & Network Evolution Plans"— Presentation transcript:

1 Customer Experience & Network Evolution Plans
Robert Calderbank VP Research, AT&T Labs

2 AT&T Labs The Innovation Engine Behind AT&T’s World-Class Technology
6,500 of the world’s best scientists and engineers AT&T’s patent portfolio includes 1,580 granted patents 120 years of technology breakthroughs and product/service innovation Over 80% of our scientists & technologists hold a PhD or other advanced degree Currently involved with approximately 90 U.S. & international universities Middletown, NJ Menlo Park, CA Chart Owners: Beth Mihalkovitz – HR Porition Jack Klingert – Patents Info Rob Calderbank – Univ Info Last Updated Florham Park, NJ

3 Directed Research Infrastructure is Accelerating Development of End To End Solutions
Business Model*: Information and Operations Support to ABS that enables Customer Focused Operations across all Networks and Services, and across the customer lifecycle. Rapid Response to transform customer experience. Business Problems: Unique capability to monitor current market and operational process leading to dialog with Product and Operations that anticipates/frames the right questions and collaboratively provides competitive advantage. Understand and (Re)Define the Problem(s) Data Integration: Unique capability to capture, integrate and use diverse information across silos, processes and organizations at full AT&T scale Business Solutions: Unique capability to build scalable, flexible prototypes that can be used immediately and then improved based on experience and evolving needs Monitor & Control Anticipate User’s Needs Create a Solution and Iterate “Test and Learn” Data Publishing Enhance the Infrastructure Better/Quicker Solutions each time. *Shared across ABS and ACS

4 The Problem: So many places to look; so little time
Go to any work center and reps will be using lots and lots of systems Provisioning, maintenance, care Users want integration (one stop shopping) But large systems integration projects are expensive and risky Virtual integration: benefits of integration without the costs Rapid cycle times: hours rather than years Why are reps using so many systems? Typical investigation Log into many systems, and hope you have enough of a key to find something Tedious, expensive, often unsuccessful Typical scenario: Customer calls care and expects us to find their records quickly They don’t know how our databases are organized May not know product(s), primary key(s), spelling of their name in our DB(s)

5 Process System Support
VIP Architecture DBOR: Current “Factory” MetaSearch Local Interfaces External Interfaces ETE Process Models Simulation/Optimization Process Lifecycles VIP GUI Custom Views VIP Cache Data Staging Detailed ETE Process Monitor & Control Virtual Integration Tool Web Crawlers DB snapshots Direct Access Data Access ConnectVu LIFE Process Workflow PWOT CSR Martin CARE COLR SCOT MACD BMP PIC/CIC Data Sources Process System Support Current Legacy

6 Number of Queries Daily
VIT/VIP Usage Number of Queries Daily Over 10,000 queries/day – LIFE and CSR pulls

7 Process System Support
Integrated, Automated “Factory” Process Current “Factory” ETE Process Models Simulation/Optimization Process Lifecycles ETE Process Models, Monitor & Control Built off DBoR Access Detailed ETE Process Monitor & Control Virtual Integration Tool Process Workflow Process Workflow Process System Support Current Legacy DBoR POR

8 AT&T’s Focus in 2003 and Beyond
Strategy Reduce cycle time, consolidate similar functions and systems, deploy workflow, auto inventory, E-enablement, self-srv, Retire systems Scrub DBORs, Deploy MPLS, VoIP Basic + Managed System monitors, correlates and recommends action Predictive Customer Requirements Consistant & Predictable quality of service Driving Reliability & Security Flexibility & Simplicity Better SLAs System monitors correlates and takes action Adaptive Cybernated Network - Integrated Components, dynamically managed by business rules/policies Cybernated

9 Business Grade Networking
Leveraging Scale Traffic Crossing the Network and Active BGP Entries Defects per Million AT&T IP Traffic Growth: Blue Internet Core Routes: Red BGP Routes Now, I’d like to discuss some other pressure points – volume growth and revenue vs. CapEx/OpEx factors. As you can see our IP traffic is still growing exponentially. In order for us to scale, it is important that BGP routing tables growing linearly over time, and that DPMs also come down very quickly. These improvements show that IP as a basic backbone transport mechanism will scale reliably! However, if everything is to go over IP/MPLS, and IP pricing is declining at 45% per year with the growth at perhaps 80% per year, and flat Capex, there is tremendous pressure on the carrier to be highly efficient to say the least. Note the volume vs. revenue cross over points. Data traffic exceeded voice in volume several years ago, with only a recent cross-over in revenue. The problem is that we have Voice, FR, ATM, PL, IP, Optical, Signaling, …. networks, each with their own scaling and technology limits. So, it would seem that if everything could go over IP/MPLS then we would have a hope of scaling all networking for customers. The problem is one of network, feature, OSS and customer migration – no small task!

10 Reliability and Performance of AT&T Networks
Customer Acquisition and Growth MIS Acquire the Traffic Program Analysis of daily usage and content mix by potential customers, specifically large content providers such as Microsoft, Real Networks, and Speedera Web reports Discords Low level standard form (tables) Abstract network database polled queries eNetdb Router config files Automation fixing errors The “discord checks” embody the “rules” for configuring the service Customer Focused Operations – Signature Client Program Significant contraction of the time to onboard or migrate a network or customer to an AT&T network or service Optimization of IP infrastructure in AT&T MIS being upgraded to #1 ISP from a preliminary ranking of 9th in a survey of ISP conducted by Boardwatch

11 Major Applications – Backbone – Netflow Data
http nntp smtp %flows/pkts/bytes by port number ftp-data napster 443 dns 4041 Bytes 9995 4040 6970 kshell 1755 pop3 HTTP web-proxy 27005 napster Flows 2048 5000 host2-ns ftp-ctrl 1074 1044 6901 1050 1057 1027 1036 1049 6112 6701 2002 1042 2001 1025 28800 snmp netbios-ns 31501 By Customer 1672 4000 telnet 4020 49608 1075 vid 771 NNTP 2816 203 rest

12 Gigascope – Application Layer Monitoring & Analysis
Gigascope - next-generation packet monitor Non-invasive Analyzes packet data at up to OC48 link speeds AT&T’s GSQL language allows rapid development of new queries Example Monitored a particular customer application with Gigascope to determine: total number of active users, packet loss rate, etc. Results being used to understand network impact on application performance, e.g., impact of packet loss on user experience Loss rate on AT&T backbone is well within limits Optical Splitter

13 Getting to an Autonomic Network
Provide predictive applications to intelligently integrate correlate, and act on network information Detection (noticing problems as they occur) Diagnosis (identifying where and why the problem occurred) Repair (reliable analysis of possible changes to the network) A global view of the data is required to make this work Topology (routers, links, capacity) Traffic (offered load between points in the network) Routing (configuration of routing protocols) Use a data distribution bus and data warehouse to provide real time access to current and historical performance data obtain data off the data layer, rather than have each applications poll the network provide views of data for query or extract for non real time application needs such as customer traffic studies Link to other DBORs for non-performance data (e.g., INSTAR for IP customer data) Use components with open interfaces and open data models, permitting use of plug and play components at each layer

14 Systems Architecture: Instrumentation, Data, Application Layers
Product/ Sales/ Tier III Capacity Management NFO/CFO/GNOC Network Care Reporting Anomaly Detection Network Management (GCFP) Network/ Customer Traffic Studies Capacity Planning Reports Including lightweight publish/ subscribe capability Data Distribution Bus Real Time Performance Data Historical Performance Data Data Distribution Bus Data Collectors and Active Probes

15 A Global View of the Data is Critical
What happened on these peering links? A problem or an improvement? Without a network-wide view, see only "effects" of problems (e.g., change in link load, degradation in performance), not root causes, and have no basis for knowing how the network will behave after making a change. IP networks use “hot potato” routing -- packets take the “best” exit among several choices, where “best” is partly under our control, and partly under peers’ and users’ independent, dynamic control

16 SQL Slammer Worm: Why so potent
At a glance: Installed itself on vulnerable systems Exploited buffer overflow in SQL/MSDE server software Generated pseudorandom IP addresses Sent worm code to those addresses Huge installed base of vulnerable code MSDE software embedded in large number of other applications—130+ apps (e.g., Office XP, Visio) Many systems did not apply available patch Patches very difficult to apply in production systems Many admins unaware of embedded MSDE in there apps The Worm was built to probe the entire Internet Addresses were generated more uniformly from entire address space than previous worms like Code Red The Worm was built for speed cpu did little else but generate addresses and send worm payload Saturated high-speed LANs which amplified its effects MSDE (Microsoft Data Engine) is a stripped down version of SQL used for database functionality in other applications.

17 Sat 1/18/03 Sat 1/24/03 What WAS the Worm? Normal Traffic
Curve for UDP Sat 1/18/03 “SQL Slammer” worm strikes Sat 1/24/03

18 Worm Signature Used TAP traffic monitors to determine flow signature: UDP flows of size 404 bytes to port 1434 TAP infrastructure with “smart sampling” allowed us to see this traffic accurately all across the network - in real time! Also running in large customer network: was able to quickly detect hundreds of infected hosts using above signature and forward to customer for action

19 Traffic Effects of the SQL.slammer worm
Worm used UDP-based traffic Majority of internet applications are TCP based (web, chat, news, peer-to-peer file sharing) UDP traffic does not “back off” under congestion like TCP traffic does. Thus, UDP traffic can “squeeze” TCP traffic under heavy load: • 1st hour after worm: TCP traffic was 22% lower than usual • 4th hour after worm: TCP traffic was 14% lower than usual • 24 hours after worm: TCP traffic was back to normal Worm diffused across public and private networks Infection was anywhere the affected Microsoft software was running; did not discriminate by network The worm only needed to breach one badly configured firewall to go on to infect an entire Intranet

20 Effects on Other Traffic
Normal WEB Traffic Curve Sat 1/18/03 “SQL Slammer” worm strikes Sat 1/24/03

21 Traffic Effects of the SQL.slammer worm
Difference between “usual” Saturday TCP/web traffic and traffic on 1/25/03

22 Systems and Networks: Evolving to the Cybernated Network
Basic Multiple networks and systems Managed Integration of data and actions through management tools, and intensive manual analysis Predictive System monitors, correlates and recommends actions Adaptive System monitors, queries as needed for additional data, correlates and takes action Autonomic/ Cybernated Integrated components, dynamically managed by network and business rules We are here? work plan The target is here

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