Connected Analytics for Network Deployment

Dale Bender, Senior Product Manager, Cisco Data and Analytics Group

Connected Analytics for Network Deployment

2 © 2015 Cisco and/or its affiliates. All rights reserved. Cisco Confidential

Connected Analytics for Network Deployment is … “Analytics for proactively managing network disruption risk”


“Analytics for proactively managing network disruption risk”

•  Used to proactively manage future risk •  Uses data and analytics to ID network

changes that lower the disruption risk profile


“Analytics for proactively managing network disruption risk”

•  SaaS application •  Uses customer data + Cisco proprietary data and IC •  Big data systems for workload processing


Starting out

Advanced Services Focus •  Assessing current network risk •  Combing through data, applying

SME expertise •  Bug scrubs •  HW/SW lifecycle •  Toxic configs •  PSIRTs

Delivery

Detailed, manual analysis via intensive, periodic engagements

But customers were asking for …

•  Proactive risk management

•  Risk assessment without complex engagements

•  Focus on future risk (not just “today”)


Applying R&D

What we found •  Traditional IC and methods were

not particularly effective for managing future risk

•  Managing to a consistent network deployment correlated to higher operational predictability and lower network disruptions

•  The more complex the configs, the higher the correlation (consistency and network disruption risk)

Compare all HW (incl parts)

Determine which devices to compare

For a network with 1000’s of devices

Based on role (core, access, DC, campus, branch) Identify devices to exclude (lab, isolated role, etc.) For comparable groups- match WH profiles Chassis based devices can have dozens of components

Compare all SW and configs

Typical for large networks to have 50 SW versions deployed Each device has 30-100 features enabled

So that’s good news … Right?


Disrupting NetOps for deployment risk management

Traditional Method

Data Analytics Method

•  Use readily available data •  Systematically apply IC •  Develop analytical models for

clustering and computing network consistency, complexity

•  UI workflows focused on outcomes

•  Write scripts for collecting data

•  Load data into BI or database •  SME’s apply IC assets (config

decoding, HW profiling, bugs, etc.)

•  SME’s create reports (MOP-based)

•  SME’s provide reports to NetOps stakeholders


Disrupting NetOps for deployment risk management

•  Use readily available data •  Systematically apply IC •  Develop analytical models for

clustering and computing network consistency, complexity

•  UI workflows focused on outcomes

•  Write scripts for collecting data

•  Load data into BI or database •  SME’s apply IC assets (config

decoding, HW profiling, bugs, etc.)

•  SME’s create reports (MOP-based)

•  SME’s provide reports to NetOps stakeholders

Level of automation

Traditional Method

Data Analytics Method

Consistency of analysis

Repeatability

Scope

Level of automation

Consistency of analysis

Repeatability

Scope

Customization Customization


Network Disruption Index

A measure of severity of network disruption (outages, degradation, etc.) Cisco/Customer SR Data

•  Service request severity •  Time to resolution •  Escalation level •  Outages

Higher score/volatility indicates unwanted service outages and/or degradation. Viewable by type (e.g., hardware, software, and operations).

A measure of how devices performing similar functions in the network are deployed

Network Device Data

•  Device hardware choices •  Device software choices •  Technology configurations

Higher score indicates increasing drift from policy and similar devices in a role. Drill down on roles and families to find outliers

Network Consistency Index

Measures network sophistication via weighted score of device technologies and features

Network Device Data

•  #/Types of features enabled •  Feature complexity weights by

domain experts at Cisco

Higher score indicates network is delivering increasingly complex business services and sensitive to risk from the other indices

Feature Utilization Index

Data Source

Attributes Analyzed

Insight

Definition

Connected Analytics for Network Deployment (KPI’s)


Network Disruption Index

Network Consistency

Index

Feature Utilization

Index

Cisco Analytics Platform

Review technology

choices

Assess KPIs and

trends

Prioritize fixes

Find disruption

risks Simulate changes

Compare KPIs to industry

Connected Analytics for Network Deployment (workflows)


Network Data Features in use

Tech Support Cases

Hardware inventory

SW deployed

Network Disruption

Score

Consistency Score

Feature Utilization

Score

Consistency Simulation

Industry benchmarks

Service Contracts

Industry benchmarks Industry

benchmarks

Connected Analytics for Network Deployment (data)


Using Connected Analytics for Network Deployment


CAND’s interactive portal shows your KPIs – disruption, consistency, and feature utilization – at a glance. Drill down for on-demand visibility into incident and device details - roles, families, platforms, software, features, severity level, and more. Automatic clustering of devices into network roles shows groups with devices potentially contributing to disruption.

Dashboard with Benchmarks, KPIs and Trends Support cases by severity, platform, software version,

and more At a glance view of KPIs and trends, by hardware, software,

and features


View entire network or drill down to investigate risk and opportunities for proactive mitigation. •  Product line •  Product family •  Internal designation •  Product •  Device

Analysis Workflow for Identifying Opportunities for Risk Mitigation

View and select groupings to drill down

Products grouped into roles/families, size

corresponds to device footprint in network


View consistency outliers that cause network disruptions and impact business operations. Analytics rank groups which likely contribute most to disruptions and locates outliers in each group.


Portion of policy outliers in the role/family

Consistency score can reference a policy device or majority configuration observed for the role



Zoom to see individual devices including outliers

SW release versions




Simulate the Effects of Software Changes Standard or optional custom

simulation analyzes effect of fixes to outliers on consistency scores CAND provides the ability to

model changes to software configurations, a common vector of network disruption.


Analyze Network Changes Over Time

CAND identifies changes over time on-demand, enabling you to identify and address unplanned changes. Changes are classified as additions, removals and modifications in hardware, software and feature configuration.


What’s next …


Monitoring / Alerts setup

Search Risk View

Business Risk

Predictive Risk

Reports library

Configs EoX SR’s Devices

SW Upgrade

HW Change

Config Change

HW SW Configuration SR

Device Clustering

Bus

ines

s R

isk

DP

MH

EoX

Bug

s/Fi

eld

Not

ices

Simulation workflow

SW upgrade recommendations

HW consistency and risk change analysis

Config consistency and risk change analysis

Comparison Workflow

Application Setup

CAND 1.6 core competencies

CAND 1.6 focus

Disruption Risk Management

Con

sist

ency

Consistency View

SW HW Configuration

Outlier identification

Analysis workspace

Drilldown Analysis

“Outcomes” Workflows

NDI Focus


Monitoring / Alerts setup

Search Risk View

Business Risk

Predictive Risk

Reports library

Configs EoX SR’s Devices

SW Upgrade

HW Change

Config Change

HW SW Configuration SR

Device Clustering

Bus

ines

s R

isk

DP

MH

EoX

Bug

s/Fi

eld

Not

ices

Simulation workflow

SW upgrade recommendations

HW consistency and risk change analysis

Config consistency and risk change analysis

Comparison Workflow

Application Setup

Proposed CAND “MVP+” state

CAND 1.6 focus

Disruption Risk Management

Con

sist

ency

Consistency View

SW HW Configuration

Disruption risk analysis report

Analysis workspace

Drilldown Analysis

“Outcomes” Workflows

Predictive Risk Focus

NEW

Based on existing NetOps business Processes