VMUGIT UC 2013 - 05a VMware vFabric

© 2009 VMware Inc. All rights reserved
VMware Cloud Application Platform
Filippo Lambiente,
Sr. Systems Engineer, vFabric, Cloud Application Platform
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2
Traditional Applications – a sample
VMware Confidential
Java EE
My-Application.war
RDBMS
Front-end
Order
Inventory
Shipping
§  Lack of scalability
•  Scale through replication
•  Can’t scale different parts of the application differently
§  Lack of deployability
•  Deploy it all in one go, lots of communication &
coordination
•  Increased risk of something breaking
§  Applications are brittle
•  Store can’t accept orders unless all services are
available
•  Failure (e.g. memory leak) in one component can
take down every other
§  Vendor Lock-in
•  Long-term commitment to technology stack

3
The Database is Being Stretched
Big Data Flexible Data
§  Petabytes vs.
Gigabytes
§  Democratize BI
§  Multi-structured data
§  Developer productivity
Fast Data
§  Low latency expectations
§  Horizontal scale
Cloud Delivery
§  Virtualized

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Trends Driving Change in IT
VMware Confidential
Cloud Delivery
•  Offered “as-a-Service”
•  Virtualization
Developer Productivity
New application frameworks driving
increase in application development
New Application Types
•  Mobile, SaaS, social
•  Apps released early and often
Data Volume
•  Web orientation drives exponential
data volumes
•  Reduced latency and new types of data

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Modern Application

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VMware vFabric: Build, Run, Manage Modern Application
VMware Confidential
Virtual Datacenter
Cloud Infrastructure and Management
Rich
Web
Programming
Model
Social and
Mobile
Data
Access
Integration
Patterns
Batch
Framework
WaveMakerSpring
Tool Suite
Cloud
Foundry
App Monitoring
(Spring Insight)
Performance Mgmt
(Hyperic)
Automated
App Provisioning
(AppDirector)
Java
Optimizations
(EM4J, …)
Java Runtime
(tc Server)
Web Runtime
(ERS)
Messaging
(RabbitMQ)
Global Data
(GemFire)
In-mem SQL
(SQLFire)

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Build
Spring
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8
Productive Programming Model Across Wide Range of Apps
Web
Batch
Integration
Security
Social
Media
Cloud
Platform
Services
Mobile

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Spring Integration
§  Spring Integration provides an extension of the
Spring programming model to support the well-
known enterprise integration patterns
§  Light-weight messaging framework
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Spring Data
10
Data bottlenecks
require to change
Proliferation of
«Solutions»
How to choose?

11
Spring Data
11
Traditional
Architecture
Complex
Heterogeneous
Database
Architecture

12
Spring Data
Provide a familiar and consistent Spring based programming model while
retaining store-specific features and capabilities

13
Spring Web and Spring Mobile

14
Run
tcServer

15
Enough is Enough
Too many clients spend far too much time and effort trying to find the
products with the most features. Lean shops look for just enough, no
more.
“ ”

16
tc Server: Replace Legacy Java Servers and Apache Tomcat
Efficient, lean, fit-to-purpose runtime platform
Lower cost and complexity
Enterprise capabilities on Apache Tomcat-compatible base
vmware.com/go/tcPDF compression, OCR, web optimization using a watermarked evaluation copy of CVISION PDFCompressor

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vFabric tc Server: Key Highlights
Developer
Efficiency
Familiar Spring + Tomcat experience
Deep performance insight into Spring apps
Agile Spring development experience via STS
Enhanced build process via Maven plugin
Operational
Control
Performance & SLA management of Spring apps
Application provisioning and server administration
Rich alert definition, workflows, and control actions
Group availability & event dashboards
Secure unidirectional agent communications
Deployment
Flexibility
Lean server (10 MB) ideal for virtual environments
Template-driven server instance creation
Integrated experience with VMware environments
Open, secure API for all operations

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Imagine a Java app taking customer orders
Guest OS
Java App
vSphere Host
!
!
!
?

19
Spring Insight
Guest OS
Java App
vSphere Host

20
Which app is slow?

21
Which parts of my app is slow?

22
Is the problem isolated to one server?

23
Are problems affecting all users, or just some?

24
Is the database a bottleneck?

25
Which parts of code are causing latency?

26
Operational Control: Production Deployment Architecture
Web
Dashboard
Hyperic Monitoring
Web Servers, App Servers, Databases, Caching,
Messaging, Directories, Virtualization, etc.
Server 1
Agent
tc Server
Instance 1
tc Server
Instance 1
tc Server
Instance 1
Server 1
Agent
tc Server
Instance 1
Spring
tc Server
Instance 1
Spring
tc Server
Instance 1
Spring
Server 2
Agent
tc Server
Instance 1
tc Server
Instance 1
tc Server
Instance 1
Open API
Management Server
Administration,
Provisioning, Groups,
Metrics, Alerts, Events,
Access Control, Agent
Upgrades, etc.
Inventory,
Metric,
Audit, …
Spring
Spring

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Operational Control: Application Provisioning
" Provision applications to single server or group of servers
" Manage deployed applications
" View application status
" Start, stop, reload, and undeploy applications

28
Operational Control: Server Administration & Configuration
" Centralized administration of server configuration and defaults
" Out of box pre-tuned configurations
" JVM Options, production configurations, automated boot scripts, Windows service wrapper
" Server Instance Templates

29
Operational Control: Alert Workflows and Control Actions

30
Use ESX to Share Memory Between VMs Running Java
Elastic Memory for Java (EM4J)
Description
•  Higher consolidation through memory over-commit for
Java workloads
•  Protect Java applications against workload spikes
without wasting memory
•  Lets you give Java more memory than it needs under
normal load. Memory your application doesn’t need is
returned to ESX but remains available in case it is
needed to avoid Java out-of-memory errors
•  Use virtualization to
overcome the
limitation of Java’s
static heap
•  New ‘memory balloon’
runs inside JVM to
capture unused
memory and return it
to ESX
•  Memory returned to
JVM when it is under
pressure

31
Run
RabbitMQ

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Modern Messaging for the Cloud
Cloud-scale Message Bus
RabbitMQ Message Broker
AMQP, HTTP, HTTPS, STOMP, SMTP, XMPP …
Point -to-point and pub-sub
Virtual hosts, dynamic configuration
Cloud Services DevicesApplications

33
C# C Hundreds of
other clients
RabbitMQ runs practically everywhere
Integrate apps built on different technologies, running on different stacks

34
Run
SQLFire

35
What’s the Problem?
How do you
scale
the data tier?

36
vFabric SQLFire in a Nutshell
Databases Other Data SystemsFile Systems
Conventional Data Storage Systems
vFabric SQLFire Data Fabric
High Throughput Low Latency High Scalability Continuous Availability
Reliable Event Notification Shared Nothing SQL Parallel Execution
WAN Distribution
Enterprise Data Consuming Applications
Data Durability

37
CREATE TABLE FLIGHTS (
FLIGHT_ID CHAR(6) NOT NULL,
SEGMENT_NUMBER INTEGER
NOT NULL,
ORIG_AIRPORT CHAR(3),
DEST_AIRPORT CHAR(3)
DEPART_TIME TIME,
FLIGHT_MILES INTEGER NOT
NULL)
PARTITION BY
COLUMN(FLIGHT_ID)
REDUNDANCY 1;
Partitioning/Replication/Co-Location/Redundancy of Tables
CREATE TABLE FLIGHTAVAILABILITY (
FLIGHT_AVAILABILITY_ID CHAR(6)
NOT NULL
….
Foreign key FLIGHT References Flights
(FLIGHT_ID)
PARTITION BY COLUMN (FLIGHT_ID)
COLOCATE WITH (FLIGHTS);
CREATE TABLE AIRLINES (
AIRLINE CHAR(2) NOT NULL
PRIMARY KEY,
AIRLINE_FULL VARCHAR(24),
BASIC_RATE DOUBLE PRECISION,
DISTANCE_DISCOUNT DOUBLE
PRECISION,…. )
REPLICATE;

38
CREATE TABLE AIRLINES (
AIRLINE CHAR(2) NOT NULL PRIMARY KEY,
AIRLINE_FULL VARCHAR(24),
BASIC_RATE DOUBLE PRECISION,
DISTANCE_DISCOUNT DOUBLE PRECISION,…. )
REPLICATE;
Replicated Tables
§  Tables that have static data,
such as code tables,
lookup tables, or
metadata, are typically
replicated
§  In this example, Airlines is
replicated to three servers
that are in the distributed
system
SQLFire Server 1 SQLFire Server 2 SQLFire Server 3
Airlines Airlines Airlines

39
SEGMENT_NUMBER INTEGER NOT NULL,
DEST_AIRPORT CHAR(3),
DEPART_TIME TIME,
FLIGHT_MILES INTEGER NOT NULL)
PARTITION BY COLUMN(FLIGHT_ID);
Partitioning Tables
SQLFire Server 1 SQLFire Server 2 SQLFire Server 3
Several partitioning options, you can
partition by any of the following
§  PARTITION BY PRIMARY KEY
§  PARTITION BY RANGE (FLIGHT_MILES)
(VALUES BETWEEN 0 AND 100,
VALUES BETWEEN 100 AND 500,
VALUES BETWEEN 500 AND 1000);
§  PARTITION BY LIST (ORIG_AIRPORT)
(VALUES (‘PDX’, ‘LAX’)
VALUES (‘AMS’, ‘DUB’));
§  PARTITION BY
(HOUR(DEPART_TIME);
Flights Flights Flights

40
Redundancy
§  Create redundant partitions on other
SQLFire members
§  SQLFire attempts to place copies of the
same bucket onto hosts with different IP
addresses to protect against machine failure
§  Setting the enforce-unique-host boot
property prevents SQLFire from ever
placing multiple copies on the
same machine
Airlines
Flights R
Airlines
Flights R
Airlines
Flights R
DEST_AIRPORT CHAR(3),
DEPART_TIME TIME,
FLIGHT_MILES INTEGER NOT NULL)
PARTITION BY COLUMN(FLIGHT_ID)
REDUNDANCY 1;

41
CREATE TABLE FLIGHTAVAILABILITY (
FLIGHT_DATE DATE NOT NULL,
ECONOMY_SEATS_TAKEN INTEGER DEFAULT 0,
…)
PARTITION BY COLUMN (FLIGHT_ID)
COLOCATE WITH (FLIGHTS);
Partitioning Co-Location Tables
§  What if there is a parent
child relationship between
FlightAvailability and
Flights tables?
Airlines
Flights R
Airlines
Flights R
Airlines
Flights R
FlightAvailability FlightAvailability FlightAvailabilityFlightAvailabilityRFlightAvailabilityRFlightAvailabilityR

42
Disk Persistence
§  Additional redundant backups
§  Speed up recovery of data from disk versus loading from RDBMS
Airlines
Flights R
Airlines
Flights R
Airlines
Flights R
FlightAvailability FlightAvailability FlightAvailabilityFlightAvailabilityRFlightAvailabilityRFlightAvailabilityR

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Manage
Application Director

44
What is Application Director?
An application provisioning solution that provides deployment automation
and self-service provisioning
OS

•  Windows

•  Red
Hat

•  CentOS

Custom
or

Packaged
App

binaries,
conﬁg

.war,
.jar,
.tar,
.zi
p
etc

Middleware

App
servers,

messaging,
web

servers,
databases,

load
balancers,
etc


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Manage
Hyperic

46
If You Can Measure It, You Can Manage It
Identify,
Organize
KPMs
Establish
Baselines
Define
Alerts,
Automate
Response
Define
Escalation
Workflows
Learn
from Data
Identify,
Organize
KPMs
Establish
Baselines
Define
Alerts,
Automate
Response
Define
Escalation
Workflows
Learn
from Data

47
How do you keep your monitored system inventory current?
Hyperic Auto-Discovery
•  Continuously discovers new and modified ESX Hosts, Guests OSs, and Physical Servers.
•  Automatically adds to and updates inventory. Automatically adjusts monitoring.
•  Can use to trigger alerts.

48
Application Frameworks
Application Servers
Web Servers / Caches
Messaging Middleware
Databases
Directory Services
Email Servers
Operating Systems
Virtualization
Hyperic collects a broad set of application performance data…

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Establish Baselines and Automate Anomaly Detection
Hyperic SmartTrend
•  Automatic baselining for any period.
•  Set alerts
•  Analyze trends
•  Measure SLA compliance
Out of Bounds Metrics
Identified
and Bubble-up
to Dashboard

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Learn more at www.vmware.com
flambiente@vmware.com

VMUGIT UC 2013 - 05a VMware vFabric

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