The document discusses RTView Enterprise Monitor, a solution for end-to-end application performance monitoring. It has a distributed, cache-based architecture designed for low latency. The solution generates a dynamic service model and provides sophisticated cross-correlations and visualizations across tiers and vendors. Its high-performance design aims to minimize overhead and surface the most important metrics based on roles and alerts.

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© 2014 SL Corporation. All Rights Reserved.1
Redefining End-to-End Monitoring with
RTView Enterprise Monitor™
The Foundation – High-Performance Architecture

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© 2014 SL Corporation. All Rights Reserved.2
E-Commerce
App Billing App
Trading AppCustomer
Service App
Evolution of High-Performance Applications
• Resource pooling and
shared services
• Multiple tiers, multiple
vendors
• Exponential Growth In
Data Volumes and
users
• 24/7 operating
windows
• Real-time performance
requirements
• Global distributed data
centers, operations

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Silo Silo Silo Silo
Where Traditional Monitoring Fails…
Normalization, Correlation, Analysis, Prioritization,
Prediction, (Pro)Action
Hosts DBMS App
Servers
VMs
Manufacturing
App
E-Commerce
App Trading App
Manufacturing
AppTraditional Monitoring

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Real End-to-End Monitoring Requirements
Across Tiers, Across Vendors, Enterprise-wide
• High-Performance Architecture
– Distributed, cache-based architecture to minimize latency
• Integrated, Dynamic Service Model
– Auto-generated, user-validated
• Sophisticated cross-correlations and visualizations
– Both application service-centric and infrastructure-centric
views
– Visibility into the data that matter by role, criticality, severity

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High-Performance - Why the Business Cares
• Health Monitoring – Are my critical services healthy? If
not, why?
• Scalability Analysis – Is the system scaling? If not, why?
• Bottleneck Analysis – How do I continually improve?
• Event Analysis – What happened? When? Why? ---
again???
• Business alignment – Are my resources allocated to
meet Business needs?
• Performance Analysis – Am I trending in the right
direction?

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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

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Distributed, Cache-based Data Server Layer
• Flexible architecture – tuned to your needs
– Configurable collection and retention granularity
• Distributed storage optimized for large data sets
– No Central Bottleneck
– Metrics cached close to data source– no ‘dropped’ data
• Distributed rules processing = low data transfer
overhead (Deltas only)
Solution Packages (Distributed Data Servers)

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RTView
Cache
Why is Cache Capability Essential ?
• In-Memory Caching for Fast Data Capture
and Retrieval
• Only aged data written out to RDBMS
• Cache map unlocks performance and scalability
RDBMS
Fast
Slow

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Cache Architecture - Advanced Indexing
• Designed for efficient handling of real-time multidimensional data,
– optimized for the insertion/extraction of multi-dimensional time-sequenced data
– Column-oriented to leverage specialized insert functionality to ensure extremely
fast performance
• Maintains the current indexed data set for asynchronous in-memory access
– crucial for analyzing rolling averages across application server sessions

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Solution Package Architecture
Thresholds and Alert Logic Distributed
• High-overhead operations performed in
a distributed manner, close to the data
source
– Data Collection & Aggregation
– Data Correlation/Analysis
– Rules
– Historization (archiving)
• Only changed/relevant data are
transmitted back to Rules Engine and
Display Server
• Cache mapping allows for tracking
multiple caches, real time update
• REST API allows for flexible data
access to both cache and historian
(DBMS)
RTView
Cache
RDBMS
Solution
Package
Logic
Data
Source

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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 – lacking context and
ability to prioritize alerts
Organizations require a low-cost, low-overhead
architecture designed around low-latency application
characteristics

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Metadata Layer Surfaces the Data that Matter
• Metadata populates dynamic cache map and enables
distributed architecture
– Complex/composite rules aggregated and applied
centrally
– Intelligent Partitioning for optimized data access
– Cache API enables non-disruptive scalability
Rules Engine
Cache Map

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Real-time Integration and Display
• Dynamic service model population
• Metadata-driven correlation of key metrics
• Role-based selection of relevant data
• High-performance UI (HTML5/Ajax)
– Trend chart processing optimized for real-time data visualization
Display
Server
Config
Server
Alert
Server
Dev QA Ops

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Real End-to-End Monitoring Requirements
Across Tiers, Across Vendors, Enterprise-wide
• High-Performance Architecture
– Distributed, cache-based architecture to minimize latency
• Integrated, Dynamic Service Model
– Auto-generated, user-validated
• Sophisticated cross-correlations and visualizations
– Both application service-centric and infrastructure-centric
views
– Visibility into the data that matter by role, criticality, severity

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© 2012 SL Corporation. All Rights Reserved.
Select RTView Customers
Financial
Services
Other
eCommerce/
Retail
Energy/
Telecom
500+
RTView
Customers

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For More Information
Visit us at SL.com
Request a WebEx Demo
Start an Evaluation
Watch a Video

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Thank You!
Questions?

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Redefining End-to-End Monitoring with
RTView Enterprise Monitor™
The Foundation – High-Performance Architecture