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Some monitoring solutions are simply not designed for high-performance applications – they rely on agents that impose significant overhead on a production system, or use a monolithic, centralized repository for aggregating and sorting through alerts that bottlenecks the real-time visibility of crucial healthstate information. RTView is designed from the ground up for low-latency applications, relying on APIs rather than agents for data collection, and leveraging a distributed, cache-based architecture for storage, processing and retrieval of key metrics. As a result, firms that depend on high-performance applications depend on RTView to ensure optimal performance and uptime for those crucial systems.
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copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 1
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 2
E-Commerce App Billing App
Trading App Customer Service App
Evolution of High-Performance Applications
bull Resource pooling and shared services
bull Multiple tiers multiple vendors
bull Exponential Growth In Data Volumes and users
bull 247 operating windows
bull Real-time performance requirements
bull Global distributed data centers operations
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 3
Silo Silo Silo Silo
Where Traditional Monitoring Failshellip
Normalization Correlation Analysis Prioritization Prediction (Pro)Action
Hosts DBMS App
Servers VMs
Manufacturing App
E-Commerce App Trading App
Manufacturing App Traditional Monitoring
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 4
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 5
High-Performance - Why the Business Cares
bull Health Monitoring ndash Are my critical services healthy If not why
bull Scalability Analysis ndash Is the system scaling If not why
bull Bottleneck Analysis ndash How do I continually improve
bull Event Analysis ndash What happened When Why --- again
bull Business alignment ndash Are my resources allocated to meet Business needs
bull Performance Analysis ndash Am I trending in the right direction
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 6
RTView EM Architecture
Display Server
Config Server
Alert Server
Rules Engine
Cache Map
Dev QA Ops
Solution Packages (Distributed Data Servers)
EM Server Layer
Metadata Layer
Data Server Layer
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 7
Distributed Cache-based Data Server Layer
bull Flexible architecture ndash tuned to your needs
ndash Configurable collection and retention granularity
bull Distributed storage optimized for large data sets
ndash No Central Bottleneck
ndash Metrics cached close to data sourcendash no lsquodroppedrsquo data
bull Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 2
E-Commerce App Billing App
Trading App Customer Service App
Evolution of High-Performance Applications
bull Resource pooling and shared services
bull Multiple tiers multiple vendors
bull Exponential Growth In Data Volumes and users
bull 247 operating windows
bull Real-time performance requirements
bull Global distributed data centers operations
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 3
Silo Silo Silo Silo
Where Traditional Monitoring Failshellip
Normalization Correlation Analysis Prioritization Prediction (Pro)Action
Hosts DBMS App
Servers VMs
Manufacturing App
E-Commerce App Trading App
Manufacturing App Traditional Monitoring
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 4
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 5
High-Performance - Why the Business Cares
bull Health Monitoring ndash Are my critical services healthy If not why
bull Scalability Analysis ndash Is the system scaling If not why
bull Bottleneck Analysis ndash How do I continually improve
bull Event Analysis ndash What happened When Why --- again
bull Business alignment ndash Are my resources allocated to meet Business needs
bull Performance Analysis ndash Am I trending in the right direction
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 6
RTView EM Architecture
Display Server
Config Server
Alert Server
Rules Engine
Cache Map
Dev QA Ops
Solution Packages (Distributed Data Servers)
EM Server Layer
Metadata Layer
Data Server Layer
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 7
Distributed Cache-based Data Server Layer
bull Flexible architecture ndash tuned to your needs
ndash Configurable collection and retention granularity
bull Distributed storage optimized for large data sets
ndash No Central Bottleneck
ndash Metrics cached close to data sourcendash no lsquodroppedrsquo data
bull Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 3
Silo Silo Silo Silo
Where Traditional Monitoring Failshellip
Normalization Correlation Analysis Prioritization Prediction (Pro)Action
Hosts DBMS App
Servers VMs
Manufacturing App
E-Commerce App Trading App
Manufacturing App Traditional Monitoring
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 4
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 5
High-Performance - Why the Business Cares
bull Health Monitoring ndash Are my critical services healthy If not why
bull Scalability Analysis ndash Is the system scaling If not why
bull Bottleneck Analysis ndash How do I continually improve
bull Event Analysis ndash What happened When Why --- again
bull Business alignment ndash Are my resources allocated to meet Business needs
bull Performance Analysis ndash Am I trending in the right direction
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 6
RTView EM Architecture
Display Server
Config Server
Alert Server
Rules Engine
Cache Map
Dev QA Ops
Solution Packages (Distributed Data Servers)
EM Server Layer
Metadata Layer
Data Server Layer
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 7
Distributed Cache-based Data Server Layer
bull Flexible architecture ndash tuned to your needs
ndash Configurable collection and retention granularity
bull Distributed storage optimized for large data sets
ndash No Central Bottleneck
ndash Metrics cached close to data sourcendash no lsquodroppedrsquo data
bull Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 4
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 5
High-Performance - Why the Business Cares
bull Health Monitoring ndash Are my critical services healthy If not why
bull Scalability Analysis ndash Is the system scaling If not why
bull Bottleneck Analysis ndash How do I continually improve
bull Event Analysis ndash What happened When Why --- again
bull Business alignment ndash Are my resources allocated to meet Business needs
bull Performance Analysis ndash Am I trending in the right direction
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 6
RTView EM Architecture
Display Server
Config Server
Alert Server
Rules Engine
Cache Map
Dev QA Ops
Solution Packages (Distributed Data Servers)
EM Server Layer
Metadata Layer
Data Server Layer
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 7
Distributed Cache-based Data Server Layer
bull Flexible architecture ndash tuned to your needs
ndash Configurable collection and retention granularity
bull Distributed storage optimized for large data sets
ndash No Central Bottleneck
ndash Metrics cached close to data sourcendash no lsquodroppedrsquo data
bull Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 5
High-Performance - Why the Business Cares
bull Health Monitoring ndash Are my critical services healthy If not why
bull Scalability Analysis ndash Is the system scaling If not why
bull Bottleneck Analysis ndash How do I continually improve
bull Event Analysis ndash What happened When Why --- again
bull Business alignment ndash Are my resources allocated to meet Business needs
bull Performance Analysis ndash Am I trending in the right direction
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 6
RTView EM Architecture
Display Server
Config Server
Alert Server
Rules Engine
Cache Map
Dev QA Ops
Solution Packages (Distributed Data Servers)
EM Server Layer
Metadata Layer
Data Server Layer
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 7
Distributed Cache-based Data Server Layer
bull Flexible architecture ndash tuned to your needs
ndash Configurable collection and retention granularity
bull Distributed storage optimized for large data sets
ndash No Central Bottleneck
ndash Metrics cached close to data sourcendash no lsquodroppedrsquo data
bull Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 6
RTView EM Architecture
Display Server
Config Server
Alert Server
Rules Engine
Cache Map
Dev QA Ops
Solution Packages (Distributed Data Servers)
EM Server Layer
Metadata Layer
Data Server Layer
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 7
Distributed Cache-based Data Server Layer
bull Flexible architecture ndash tuned to your needs
ndash Configurable collection and retention granularity
bull Distributed storage optimized for large data sets
ndash No Central Bottleneck
ndash Metrics cached close to data sourcendash no lsquodroppedrsquo data
bull Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 7
Distributed Cache-based Data Server Layer
bull Flexible architecture ndash tuned to your needs
ndash Configurable collection and retention granularity
bull Distributed storage optimized for large data sets
ndash No Central Bottleneck
ndash Metrics cached close to data sourcendash no lsquodroppedrsquo data
bull Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 8
RTView Cache
Why is Cache Capability Essential bull In-Memory Caching for Fast Data Capture
and Retrieval bull Only aged data written out to RDBMS bull Cache map unlocks performance and scalability
RDBMS
Fast
Slow
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 9
Cache Architecture - Advanced Indexing
bull Designed for efficient handling of real-time multidimensional data ndash optimized for the insertionextraction of multi-dimensional time-sequenced data ndash Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance bull Maintains the current indexed data set for asynchronous in-memory access
ndash crucial for analyzing rolling averages across application server sessions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 10
Solution Package Architecture Thresholds and Alert Logic Distributed
bull High-overhead operations performed in a distributed manner close to the data source ndash Data Collection amp Aggregation ndash Data CorrelationAnalysis ndash Rules ndash Historization (archiving)
bull Only changedrelevant data are transmitted back to Rules Engine and Display Server
bull Cache mapping allows for tracking multiple caches real time update
bull REST API allows for flexible data access to both cache and historian (DBMS)
RTView Cache
RDBMS
Solution Package
Logic
Data Source
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 11
RTView Low Overhead = No Instrumentation
Other solutions include code injection and agents as a means of gaining visibility into execution details
- Both approaches incur unacceptably high overhead
- Both introduce instability into your code
- Inability to reduce the noise ndash lacking context and ability to prioritize alerts
Organizations require a low-cost low-overhead
architecture designed around low-latency application characteristics
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 12
Metadata Layer Surfaces the Data that Matter
bull Metadata populates dynamic cache map and enables distributed architecture
ndash Complexcomposite rules aggregated and applied centrally
ndash Intelligent Partitioning for optimized data access
ndash Cache API enables non-disruptive scalability
Rules Engine
Cache Map
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 13
Real-time Integration and Display
bull Dynamic service model population bull Metadata-driven correlation of key metrics bull Role-based selection of relevant data bull High-performance UI (HTML5Ajax)
ndash Trend chart processing optimized for real-time data visualization
Display Server
Config Server
Alert Server
Dev QA Ops
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 14
Real End-to-End Monitoring Requirements Across Tiers Across Vendors Enterprise-wide
bull High-Performance Architecture ndash Distributed cache-based architecture to minimize latency
bull Integrated Dynamic Service Model ndash Auto-generated user-validated
bull Sophisticated cross-correlations and visualizations ndash Both application service-centric and infrastructure-centric
views
ndash Visibility into the data that matter by role criticality severity
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 15
copy 2012 SL Corporation All Rights Reserved
Select RTView Customers
Financial Services
Other
eCommerce Retail
Energy Telecom
500+ RTView
Customers
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 16
For More Information
Visit us at SLcom
Request a WebEx Demo
Start an Evaluation
Watch a Video
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 17
Thank You
Questions
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture
copy 2012 SL Corporation All Rights Reserved
copy 2014 SL Corporation All Rights Reserved 18
Redefining End-to-End Monitoring with RTView Enterprise Monitortrade The Foundation ndash High-Performance Architecture