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1. © 2011 VMware Inc. All rights reserved
vFabric 5 Sales Enablement – Level 200
Al Sargent
Sr. Product Marketing Manager, vFabric Cloud Application Platform
asargent@vmware.com
Tuesday, July 28, 2015
Non-Disclosure Agreement for VMware Partners.
This VMware vFabric information that is being provided to you, our partner, is under a
Non-Disclosure Agreement which is in effect until the product is announced. No part of
this information should be shared with any other third party unless permission is
obtained from VMware in writing.
VMware
Internal
until
6/15/11

2. 2
Agenda
Application Platform Market
vFabric Overview
vFabric 5 Announcement
GemFire
SQLFire
tc Server
RabbitMQ
Hyperic
Next Steps

3. 3
VMware’s Three Strategic Focus Areas
Evolve the Core Infrastructure
Modernize Application Development
Re-think End-User Computing
Private
Clouds
Public
CloudsEnable Hybrid

4. 4
The Application Platform Market

5. 5
What trends are driving the application platform market?
New Frameworks & Languages
• Increase developer productivity
• Reduce time to market
New Devices and Domains
• Mobile, social, and SaaS integration
New Data Types and Requirements
• Data deluge driving data tier elasticity
• Flexible NoSQL data solutions
• Realtime data
New Infrastructures
• Virtualization & Cloud

6. 6
Core Components of Application Infrastructure
Clients
Web Servers
App Servers
Databases
Monitoring
App Framework
Message Servers

7. 7
vFabric Overview

8. 8
The vFabric Approach to Application Infrastructure
Clients
vFabric
Web Server
vFabric
SQLFire
vFabric
RabbitMQ
vFabric
tc Server
GemFire App Cache Node
Elastic Memory for Java
Spring Insight Operations
vFabric Hyperic

9. 9
vFabric 5 Announcement

10. 10
What are we announcing…and when?
vFabric 5: Application Infrastructure for the Cloud Generation
• LICENSED for virtual and cloud
• PACKAGED for simplicity and reuse
• ENGINEERED for vSphere and Spring
SQLFire beta
Announcement: Tuesday June 14th. GA: Tuesday August 16th

11. 11
vFabric 5: Licensed for Virtual and Cloud
vFabric Standard
$1,200 per VM (perpetual)
+ 21% / 25% SnS
Hyperic
Server-Level Monitoring
tc Server Spring Edition
Tomcat Java Application Server
+ Spring Insight Operations
Web Server
Apache HTTP Server
GemFire App Cache Node
Session and Hibernate Caching
Standard
SQLFire Professional Edition
Memory-oriented data management
vFabric Advanced
$1,800 per VM (perpetual)
+ 21% / 25% SnS
Per VM pricing: an industry first for application infrastructure
Up to 2 vCPUs per VM. More than 2 vCPUs in a VM? Divide by 2 then round up.
RabbitMQ
Message Broker
Elastic Memory for Java (EM4J)
Elastic Memory Management
Metric =
New

12. 12
vFabric 5: Optimized for Spring and vSphere
Optimized for vSphere
• tc Server
• Elastic Memory 4 Java (EM4J)
• Pools memory across tc Server instances
• Allows increased Server Consolidation ratios for tc Server on vSphere
• Reduces out of memory errors that can cripple your applications
Optimized for Spring
• tc Server
• Spring Insight Operations
• Spring Insight technology, now engineered for production use cases
• Tomcat 7
• Parallel Deployment for zero-downtime application upgrades
• Hyperic
• Includes Spring Insight Operations metrics

13. 13
vFabric Forecasted Timeline (subject to change)
June July August September October
vFabric
Announcement
June 14 2011
Channel pricelist
published vFabric GA
August 16 2011
(all but SQLFire)
SQLFire
GA

14. 14
vFabric GemFire
Elastic In-Memory Data Management

15. 15
Runtime Challenge: Avoiding Bottlenecks at the Data Layer
How to scale the data
tier?

16. 16
Enabling Extreme Data Scalability & Elasticity
Application Data
Lives Here
File Systems Databases Mainframes / other
Application Data
Sleeps Here
Primary Use Cases
 Web Session Cache, L2 Cache
• Shopping Cart state management
 App Data Cache, In-memory DB
• High performance OLTP
 Grid Data Fabric: Client Compute
• Shared data grid accessed by many
clients executing app logic
 Grid Data Fabric: Fabric
Compute
• Shared data grid where app logic is
executed within the data fabric itself

17. 17
GemFire
1. Peer-to-Peer
 the cache is embedded within the application process and shares
the heap space with the application
 Session replication and L2 cache
Primary GemFire Topologies Use Cases
OS
Java APP
JVM
A/S
OS
Java APP
JVM
A/S

18. 18
GemFire
JVM
2. Client/Server
 A central cache is managed in one distributed system tier by a number of servers
 Session replication and L2 cache, data intensive apps, DR, continuous availability…
Primary GemFire Topologies Use Cases
OS
Java APP
JVM
A/S C/S topology
supports native
clients (C#, C++)
OS
Java APP
JVM
A/S
Win
C# APP
CLR
.NET
OS OS
JVM

19. 19
3. Multi-site caching
 Distribution of cached data between sites is seamless to the applications within each
distributed system. If any system becomes unavailable, the rest of the installation
continues to operate.
Primary GemFire Topologies Use Cases
WANGemFireJVM
OS
Java APP
JVM
A/S
OS
Java APP
JVM
A/S
Win
C# APP
CLR
.NET
OS OS
JVM GemFireJVM
OS
Java APP
JVM
A/S
OS
Java APP
JVM
A/S
Win
C# APP
CLR
.NET
OS OS
JVM

20. 20
Develop / Manage vFabric GemFire

21. 21
Add caching with Spring
Spring 3.1 Cache abstraction – declaratively add caching
@Cacheable
public Owner loadOwner(int id);
@Cacheable(condition="name.length < 10")
public Owner loadOwner(String name);
@CacheInvalidate
public void deleteOwner(int id);

22. 22
Quick Start examples
 community.gemstone.com

23. 23
Replicated Caching Example
 Replicated caching gives you a complete copy of your data in each
JVM in the distributed system that hosts the replicated region.
2 Confidential

24. 24
Spring GemFire Integration Project

25. 25
© 2011 VMware Inc. All rights reservedProprietary and Confidential
Useful tools for GemFire
JMX Agent
Web Browser
Statistics Files
Third Party/Open Source
JMX Tools
GFMon
Control, Charts, Graphs, Alerts VSD
Historical Analysis, Run Comparison
Support Tool
Hyperic plug-in

26. 26
vFabric SQLFire beta
Fast, Scalable SQL Data in The Cloud

27. 27
Standard SQL
• Easily incorporate a
memory-oriented approach
to data management for
applications
• Leverage existing tools to
accelerate app
development
High Performance
• Eliminate disk I/O
performance constraints:
data at the speed of
memory
• Enables distributed data
access: move data closer to
apps to reduce latency
Horizontal Scale
• Near-linear scale to
accommodate application
demand
• Supports global WAN
connectivity
Leverage broad SQL
knowledge – reduce time
to market
Accommodate shifting
user load
Data at cloud scale
Key SQLFire Positioning
New

28. 28
vFabric SQLFire beta community site
 http://communities.vmware.com/community/vmtn/appplatform/vfabric_sqlfire

29. 29
vFabric tc Server
The Best Place to Build and Run
Spring Applications

30. 30
Spring and tc Server (Enterprise Tomcat)
 Efficient, lean, fit-to-purpose runtime platform
 Lower cost and complexity
 Enterprise capabilities on Tomcat-compatible base
 Best platform to run Spring applications

31. 31
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.“ ”

32. 32
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

33. 33
Deep Performance Insight into Spring Apps
Spring Insight Operations
Description Benefits
• Helps pinpoint performance problems coming from
problems in code
• Tracing available in production minimizes need to
reproduce problems in the lab
• Common view between developers and operations
simplifies escalations
• Transparently
instrument Spring
applications at the
code level
• Roll up data from
multiple application
nodes with filters and
drill down
• Hyperic integration for
unified operational
view and robust
alerting

34. 34
How is each part of my
app performing over time?
Are the response times
within expected SLAs?
Are problems occurring for
all users, or just some?
Is the database a
bottleneck?
Is one of my
servers running
apps slowly?
Which parts of
my app are
slow?
Is client
performance a
problem?
What parts of my code are
responsible for slow
performance?
Which app are slow?

35. 35
Use ESX to Share Memory Between VMs Running Java
Elastic Memory for Java (EM4J)
Description Benefits
• 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

36. 36
Ensure Java Runs Well on vSphere
Java Best Practice Analyzer
Description Benefits
• Eliminates misconfiguration, the #1 cause of slow Java
performance on vSphere
• Enables vSphere admin to see in one place whether
the vSphere-level and Java-level configurations follow
best practices
• Tells you what the problems are and how to solve them
• Helps admins make best use of EM4J
• vSphere client plug-in
to check and control
settings on the VM,
inside the OS, and on
the JVM.
• Identifies common
configuration and
deployment problems.
• Monitors and controls
EM4J

37. 37
Sample Benefits of Lightweight Java Approach
Task Heavy J2EE Lightweight Java
Simplest possible application
(“Hello World”)
500 MB 50 MB
App Server Installation footprint 700 MB / 1.7 GB 15 MB
1 Assumes ops intervention due to server complexity, vs. self-service model.
2 Estimate based on reduced server complexity / test cases / customization.
Time-to-
market
Elasticity
Server
Consolid-
ation
Server startup time1 minutes / hours seconds
Server provisioning 1 hours / days seconds / minutes
Application installs 1 hours / days seconds / minutes
Installation & configuration scripts
overhead, per release
~ 60,000 LoC ~ 1500 LoC

38. 38
vFabric RabbitMQ
Messaging That Just Works

39. 39
Estimate 300-500 in production, 15-20,000 in dev
Customers love RabbitMQ – banking, web, social media, ...

40. 40
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

41. 41
RabbitMQ and AMQP: A simple view
Consumers create queues; these buffer
messages for push to consumers
Queues are stateful, ordered, and can be
persistent, transient, private, shared.
Exchanges are stateless routing tables.
Consumers tell queues to bind to named
exchanges; each binding has a pattern e.g.
“tony” or “*.ibm.*”
Producers send messages to exchanges
with a routing key e.g. “tony”, or ordered set
of keys e.g. “buy.ibm.nyse”
Exchanges route messages to queues
whose binding pattern matches the
message routing key or keys

42. 42
C# C Hundreds of
other clients
RabbitMQ runs practically everywhere

43. 43
Spring with RabbitMQ
 The Spring AMQP project applies core Spring concepts to the
development of AMQP-based messaging solutions
 Spring AMQP provides a "template" as a high-level abstraction for
sending and receiving messages
 Spring AMQP also provides support for Message-driven POJOs
 These libraries facilitate management of AMQP resources while
promoting the use of dependency injection and declarative
configuration
 In all of these cases, you will see similarities to the JMS support in
the Spring Framework
 The Spring AMQP project consists of both Java and .NET versions
to support simple interoperability between Spring Applications
deployed in both environments

44. 44
vFabric Hyperic
Monitor Application Infrastructure

45. 45
Monitoring Today: Different tools for Different Teams
Web Servers App Servers Databases
No monitoring App Infrastructure
Monitoring Tool #2
Database Admins
Monitoring Tool #3
App Support
Monitoring Tool #1
Application

46. 46
Hyperic collects a broad set of application performance data…
Performance
Database
Availability
Performance
Configuration changes
Events
Log entries
Application Frameworks
Application Servers
Web Servers / Caches
Messaging Middleware
Databases
Directory Services
Email Servers
Operating Systems
Virtualization

47. 47
Application Frameworks
Application Servers
Web Servers / Caches
Messaging Middleware
Databases
Directory Services
Email Servers
Operating Systems
Virtualization
… for infrastructure layers from App to ESX

48. 48
Next Steps

49. 49
vFabric on VMware Partner Central:
http://j.mp/vfabricpartner
vFabric on VMware.com:
http://vmware.com/go/vfabric
Engage your vFabric partner specialist:
Shawn Sickler
ssickler@vmware.com

50. 51

51. 52
Backup

52. 53
Introduction to Cloud Foundry
Platform as a Service

53. 54
Emergence of Platform as a Service (PaaS)
 Friction-free deployment
 No machines or middleware to manage
 Latest high productivity frameworks
 Choice of application services
 Cloud portability
 More responsive to developers
 Elastic and dynamically scalable
 Improved efficiency
 Digest future cloud advances
 Cloud portability
Application Developers
“Write code, not tickets”
IT Operations
“IT as a service provider”
Boost
application
velocity

54. 55
Cloud Foundry – The Open Platform-as-a-Service
Private
Clouds
Public
Clouds
Micro
Clouds
.js
GemFire
Services
Other
Services
RabbitMQ
Services

55. 56
Cloud Foundry – Options Available Today
cloudfoundry.org
• Community Driven OSS
project at
www.cloudfoundry.org
• Source code may be
compiled and deployed on
infrastructure of your
choice
• Ideal for enterprises
looking to develop their
own flavor of Cloud
Foundry
• Available Now
Micro Cloud
• Downloadable VM to
run on any computer
or server
• Single developer
instance of Cloud
Foundry
• Ideal for small test/dev
cycles
• Available in Q2, 2011
cloudfoundry.com
• Multi-tenant PaaS for
developers
• Ideal for developers who
need to start app
development right away
• Limited Beta Now

56. 57
VMware’s Open Platform as a Service Strategy
1. Build your application
2. Deploy it
3. Move as needed
Downloadable
Micro Cloud
Cloud FoundryvFabric
Service Provider
Private Cloud
vSphere
Hybrid Cloud
vSphere
vCloud
partners
Cloud FoundryvFabric Cloud FoundryvFabric
Ruby App
Java App
www.cloudfoundry.com

57. 58
App Platform for the Cloud Era: Platform-as-a-Service (PaaS)
 Integrated stack for application development
• Simplifies development
• Makes developers more productive by allowing them to focus on code
 No upfront investment in infrastructure or technology
• Curated, updated, managed and maintained as a service
• Flexible consumption models keeps cost low
 Grows with business
• Elastic to meet the needs of your business no matter what stage of growth
• Elastic scale up and down making management and operations easier

58. 59
Cloud Foundry – The first open platform-as-a-service
 Self-service application execution engine
• Build applications with latest high productivity frameworks
 Automation engine for deployment and lifecycle management
• Deploy and cloud-scale applications in seconds
 Open architecture
• Choice of clouds for deployment
• Choice of industry-standard frameworks
• Choice of application infrastructure services
• Extensible architecture to “digest” future cloud innovation
• Available as open source

59. 60
Data
Services
Other
Services
Private
Clouds
Public
Clouds
Micro
Clouds
Msg
Services
The Open Platform-as-a-Service

60. 61
Cloud Foundry – Optimize Application Delivery
 Increase responsiveness while managing risk
• IT can respond to developers’ need for multiple frameworks and programming
languages through curated stack
• With VMware as a trusted partner, there’s no risk to applications and
datacenter
 Increase choice while reducing datacenter complexity
• Cloud Foundry’s open PaaS supports multiple frameworks and programming
languages giving developers the choice and flexibility they seek
• Option to use Cloud Foundry in datacenter or private, public or hybrid clouds
gives IT a real option to reduce datacenter complexity
 Increase operational efficiency while reducing cost
• Cloud Foundry’s ability to host multiple apps on single VM provide increased
efficiency at lower cost
• Built-in elasticity allows applications to grow or shrink according to user
demand

61. 62
Cloud Foundry
Cloud Foundry – Conceptual Architecture
Router
Management&
Monitoring
Application Instance cvApplication InstanceUser Apps
Automation
Developers App Traffic
Application Instance
Execution EnvironmentServices
Datacenter or IaaS Cloud

62. 63
Cloud Foundry – Options Available at Launch
cloudfoundry.org
• Community Driven OSS
project at
www.cloudfoundry.org
• Source code may be
compiled and deployed on
infrastructure of your
choice
• Ideal for enterprises
looking to develop their
own flavor of Cloud
Foundry
• Available Now
Micro Cloud
• Downloadable VM to
run on any computer
or server
• Single developer
instance of Cloud
Foundry
• Ideal for small test/dev
cycles
• Available in Q2, 2011
cloudfoundry.com
• Multi-tenant PaaS for
developers
• Ideal for developers who
need to start app
development right away
• Limited Beta Now

63. 64
Introduction to
WaveMaker

64. 65
WaveMaker Studio
 Browser-based design environment
• WYSIWYG, drag & drop UI design
 Complete RAD platform
• Bind UI to data services
• Integrate DB & web services
 Complete web environment
• Includes Java server (Tomcat)
• Includes testing database (HSQLDB)
 Download & run on any computer
• Windows, Mac, Linux
WaveMaker Studio
Database
Web
pages
(HTML, JS)
Web
Services
Java
Code
Security
Service
(LDAP, SSO)
Visual Development of Web Apps!
Browser-based
Drag & drop components
Widgets
Properties
Services

65. 66
WaveMaker Common Artifacts
Visual, drag and
drop development
● DB Schema
● Web Services
● Java classes
● Custom Widgets
● Database schema
● Project zip file
● Custom widgets
● Standard web files:
● index.html
● myproject.js
● myproject.css
● Standard Java file
● myproject.war
Import
Export
Generated App

66. 67
WaveMaker Architecture
 Open Source Components
• Dojo: Ajax widgets
• JSON: async messaging
• Spring: Java container
• Hibernate: database access
• JaxWS: web services access
• Spring Security: user authentication
 Enterprise Components
• Role-based access, multi-tenancy
• LDAP, JOSSO, SSO
• WebSphere, WebLogic
• Oracle, DB2, SQL Server
WaveMaker JavaScript Widgets
Dojo Toolkit
WaveMaker Framework
HibernateSecurity JAXWS
JSON
Request
Database
WaveMaker Client
WaveMaker Server
Web
pages
(HTML, JS)
JSON data
Response
Custom JavaScript
Custom Java
Spring Framework
Web
Services
Java
Code
Security
Service
(LDAP, SSO)

67. 68
Introduction to
Code2Cloud Services

68. 69
Changes/Trends in Development
1. Move to Agile development
• Tighter collaboration with all
functions, especially IT
• Expanding role of Developer
• Multiple iterations in a release
(versus just one in waterfall)
• Goal: Shippable product at the end
of each iteration
• Continuous integration is now the
norm – build minutes soaring
2. Increased pace of change
• Agile development – “faster time to
failure”
• Pressure for faster time to market
• Prototyping new technologies
3. Higher expectations for software
access
• Develop once, deploy anywhere (multi-
destination, multi-device)
• Rush to “SaaS-ify” existing apps to
satisfy end users’ need for immediate
and consistent access across devices
4. Changing maintenance models
(DevOps)

69. 70
Developers’ Reality
Before building software, developers must first build/integrate their
software development environment:
 Choose a version control system for code, plus an issue tracker
 Configure continuous integration tool
 Decide where to keep documentation and how to collaborate with team
members – assign roles and access
And maintain it going forward…
 Monitor security, availability, access, upgrades/compatibility of all components

70. 71
Code2Cloud: Development in the New World
Code2Cloud provides a hosted ready-to-use platform for software
development, so developers can forget about integrating and
maintaining their tools and focus on building great software.
1 2 3
Create an
Account
Create a Project
Start Using Your Project:
Everything There for You

71. 72
Code2Cloud – What’s in it?
 Critical developer services – provided in a single, ready-to-use hosted
environment with enterprise-level security and uptime
 Comprised of popular open source developer tools and services;
Code2Cloud application will also be open sourced (Apache 2)
 Ability to publish to Cloud Foundry, tcServer, VMforce (more coming…)
Code2Cloud
Source Code Control
Git
Continuous Integration
Hudson
Task Management
Mylyn
Bug and Issue Tracking
Bugzilla-compatible
Documentation
Mylyn WikiText
Team Mgmt & Activity
Dashboarding
Publish App to Cloud Foundry, tcServer, VMforce
(more to come)
Code2Cloud
application binds,
provisions, and
orchestrates all
components.

72. 73
Code2Cloud – Web Interface
All project
components
are
integrated
and easily
accessible.

73. 74
Code2Cloud – Spring Tool Suite (STS) Rich Client Interface

74. 75
Code2Cloud: Dev / Test Services in the Cloud
CloudFoundry
vFabric Partner
Clouds
vFabric
on-premise
Browser
Developer Dev / Test Services Deployment Platforms
• Developer artifacts
• Collaboration
• Service Registry
• Common Objects
Non-coders
Source Code Control
Git
Continuous Integration
Hudson
Task Management
Mylyn
Bug and Issue Tracking
Bugzilla-compatible
Wiki
Powered by Mylyn WikiText

75. 76
Introduction to Spring Core,
Integration, and Batch

76. 77
Spring Core
Problem: EJBs lack the APIs needed to build fully functional,
enterprise applications, and they are not TDD friendly or lightweight.
Solution: One-stop-shop for building enterprise ready applications.
Acronym Meaning
IoC Inversion of Control
DI Dependency Injection
MVC Model, View,
Controller
AOP Aspect Oriented
Programming

77. 78
Spring Integration
Problem: An enterprise service bus (ESB) is often
overkill for most application integration scenarios.
Solution: Extend the Spring programming model
to deliver EIP (Enterprise Integration Patterns)
Pattern Description
Splitter Split one message into multiple
messages
Aggregator Combine multiple messages into a
single message
Wire Tap Inspect point to point messages
CBR Route a message based on content
Transformer Transform message content into a
different form

78. 79
Key Features
 Allows you to add an integration layer to your app
• An embedded message bus that runs within any Spring ApplicationContext
where all components are Spring beans
• Endpoints delegate to Spring-managed beans, framework handles message
reception and method invocation
 Comprehensive support for EIP
• Channel, Router, Filter, Transformer, Splitter, Aggregator
• High-level configuration DSL built around these patterns
 Provides a portable abstraction across multiple channel adapters
• AMQP, JMS, File, Mail, HTTP, FTP
 Support for asynchronous / parallel workloads
• Point-to-Point and Publish-Subscribe Channels
• Polling and Event-Driven Message Endpoints

79. 80
Spring Batch
Problem: Move batch jobs off of the mainframe and onto
commodity systems with a well known, trusted Java API.
Solution: Extend the Spring programming model to
deliver batch jobs on x86 and a lightweight runtime.
Pattern Description
Small Single Chunk Simple, stateless jobs
Small Chunked Transaction per chunk and stateful
Large, single platform Use Spring Integration to process partitions on
separate threads
Large, multiple
platform
Use Spring Integration to process partitioned data on
JMS queues and deliver elastic scaling

80. 81
Key Features
 Repeat and retry operations
 Support for flat files, XML streaming, & DB queries
 Well-defined domain for:
• Jobs – list of steps
• Step – reader/writer wrapper
• Factory beans for fault tolerance – retry, skip
 Job execution and management
• Simple JobLauncher that can be initiated via JMX, command line or scheduler
• Persistence of job meta-data
• Branching and decision support for non-sequential jobs
 Remote chunking and Partitioning support
• Master-Slave compute grid processing in distributed data partitions

81. 82

82. 83
Where to Start?
High Volume Web Apps
Mobile and Multi-Device
Next-generation Integration
Modern Batch Processing
Modern
Cloud-friendly
Applications
High
Performance
Data
Low-latency Data Management
Distributed Data Grids
High-scale In-memory Data Processing
Platform
as a
Service
Simple, Self-service
Application Platform
Optimize App Velocity
Increase App Efficiency