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

PDF compression, OCR, web optimization using a watermarked evaluation copy of CVISION PDFCompressor

http://www.cvisiontech.com

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



4

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



5

Modern Application



6

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

WaveMaker Spring 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)



7

Build Spring

VMware Confidential PDF compression, OCR, web optimization using a watermarked evaluation copy of CVISION PDFCompressor


8

Productive Programming Model Across Wide Range of Apps

Web

Batch

Integration

Security Social Media

Cloud Platform Services

Mobile



9

Spring Integration

§  Spring Integration provides an extension of the Spring programming model to support the well-known enterprise integration patterns

§  Light-weight messaging framework

9 PDF compression, OCR, web optimization using a watermarked evaluation copy of CVISION PDFCompressor


10

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/tc PDF compression, OCR, web optimization using a watermarked evaluation copy of CVISION PDFCompressor


17

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



18

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


Server 1


Spring


Spring


Spring

Server 2




Open API

Management Server Administration, Provisioning, Groups, Metrics, Alerts, Events, Access Control, Agent Upgrades, etc.

Inventory, Metric,

Audit, …

Spring

Spring



27

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



32

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 Devices Applications



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 Systems File 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

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);

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

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;



41

CREATE TABLE FLIGHTAVAILABILITY ( FLIGHT_ID CHAR(6) NOT NULL, SEGMENT_NUMBER INTEGER NOT NULL, 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 FlightAvailability FlightAvailabilityR FlightAvailabilityR FlightAvailabilityR



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 FlightAvailability FlightAvailabilityR FlightAvailabilityR FlightAvailabilityR



43

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, .zip etc

Middleware App servers, messaging, web servers, databases, load balancers, etc



45

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…



49

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



50

Learn more at www.vmware.com

[email protected]



Technology

VMUGIT UC 2013 - 05a VMware vFabric