Richer Data History in Groovy with Event Sourcing

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As Grails developers we reflexively lean on the default pattern for data storage: a single row represents the current state of a Domain Object. For most applications, only ever knowing the current state is just fine. However, understanding the manipulations that got your data to that state are just as important as the current state itself, especially in a large system with multiple users. Enter Event Sourcing: instead of persisting the current state of our Domain Objects, we store historical events about our data. In this talk I will discuss the basic concepts of Event Sourcing. We will discuss the advantages – particularly around performance and analytics – and disadvantages of using this pattern. We will see how easily it can be implemented in Groovy and used within a Grails application. Finally, we’ll examine some practical use cases and when one would consider implementation. Additionally, there's a code demo that is not covered in the slides, but can be found here: https://github.com/spember/greach2014-es-demo

Groovier Data History with Event
Sourcing
Greach 2014

Web / Business Analytics
Meet Bob
2

7
What do you have to offer?

8
State of Your Data

14
Balance: $100

15
Balance: -$100

20
Maintaining Only the Current State is a limitation
Historical Data can be important

21
Event Sourcing

No Direct Manipulation of State

Events are a Timeline

34
Current State Is Only
One PROJECTION

35
Create other Views

IT
HURTS
37

Grocery Store shopping cart
38

E Commerce Shopping cart
39

Scenarios:
42
• Discover if Users are Adding and Removing Products: Give them a
discount to encourage purchase
• Time between adding products and purchase
• Frequency between cart events and other system events

Bob is
Pleased
43

Not a New Concept

49
Wait, what about
those transaction logs?

52
Audit Log will tell the history
Events tell you the Intent of history

53
Implementation

62
Creating an Event Store

63
Aggregate
(it’s like a Domain Instance)

Events
65

70
Snapshots: essential optimization

73
Choosing a Persistance Layer

74
No real need for an ORM

Data base agnostic

Consider Using a Relational Database
76

79
Demo Time

80
… But Should I use it?

Use it only for Business-Critical data

Make Bob Happy
82

Thank You!

Questions
?

Image References
(Multiple Newspapers): http://www.kba.com/gb/news/detail/article/30-kba-newspaper-customers-carry-off-quality-awards-2/back/50/
(Harbor): http://www.dredgingtoday.com/2013/09/06/corps-highlights-economic-benefits-of-savannah-harbor-dredging-usa/
(Sad Bob) http://workerscompensationwatch.com/2012/12/
(Logs in River / Log Driving) http://www.flickr.com/photos/foresthistory/
(Data Base Transaction Log) http://yutechnet.com/?p=96
(Amazon Shopping Cart) http://www.amazon.com
(Ha, Ha, Business) http://www.quickmeme.com
(crowd of people) http://www.flickr.com/photos/jamescridland/613445810/
(skeptical dog) http://loltheists.com/?p=2427
(brick layer) http://www.torange.us/photo/4/13/brick-mud-brick-building-1259649354_44.jpg

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TECUNIQUE: Success Stories: IT Service provider

TECUNIQUE: Success Stories: IT Service provider

TECUNIQUE: Success Stories: IT Service provider

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AI & Machine Learning Presentation Template

AI & Machine Learning Presentation Template

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A great deal of attention in medical devices has shifted towards cybersecurity with the ratification of section 524B of the FD&C act. This new law enables the FDA to enforce cybersecurity controls in any medical device that is capable of networked communications or that has software. In this webinar we will recap the process for managing vulnerabilities, identify categories of vulnerabilities and solutions and more.

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VTU technical seminar 8Th Sem on Scikit-learn

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In the realm of real-time applications, Large Language Models (LLMs) have long dominated language-centric tasks, while tools like OpenCV have excelled in the visual domain. However, the future (maybe) lies in the fusion of LLMs and deep learning, giving birth to the revolutionary concept of Large Action Models (LAMs). Imagine a world where AI not only comprehends language but mimics human actions on technology interfaces. For example, the Rabbit r1 device presented at CES 2024, driven by an AI operating system and LAM, brings this vision to life. It executes complex commands, leveraging GUIs with unprecedented ease. In this presentation, join me on a journey as a software engineer tinkering with WebRTC, Janus, and LLM/LAMs. Together, we’ll evaluate the current state of these AI technologies, unraveling the potential they hold for shaping the future of real-time applications.

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

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At the recent Microsoft Ignite 2023 conference, Microsoft unveiled a groundbreaking strategy that will redefine enterprise work management. The plan involves integrating Microsoft’s key planning tools, Microsoft To Do, Microsoft Planner, and Microsoft Project for the web into a unified experience called “Microsoft Planner.” What does this new strategy from Microsoft mean for current users? Join us and learn how best to take advantage of this announcement while gaining a clear path on how to elevate the current state of Microsoft Planner from a basic task manager to a comprehensive tool for Enterprise Work Management using OnePlan. Learn how OnePlan’s integration with Microsoft Planner allows for strategic alignment with business goals through advanced features like strategic planning, portfolio management, resource management, financial management, and more!

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

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Unlocking the Future of AI Agents with Large Language Models

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Many specialized tools cater to distinct stages within the software development lifecycle (SDLC). These tools target various aspects of development, delivery, and operations, each with its unique strengths. Uniting these diverse testing needs into a single continuous testing platform presents several challenges. Such a platform must seamlessly integrate with various development tools and environments, accommodate different testing methodologies, and remain flexible to adapt to organizational processes and quality standards.

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Richer Data History in Groovy with Event Sourcing

1. Groovier Data History with Event Sourcing Greach 2014

2. Web / Business Analytics Meet Bob 2

7. 7 What do you have to offer?

8. 8 State of Your Data

14. 14 Balance: $100

15. 15 Balance: -$100

20. 20 Maintaining Only the Current State is a limitation Historical Data can be important

21. 21 Event Sourcing

22. No Direct Manipulation of State

25. Events are a Timeline

34. 34 Current State Is Only One PROJECTION

35. 35 Create other Views

37. IT HURTS 37

38. Grocery Store shopping cart 38

39. E Commerce Shopping cart 39

42. Scenarios: 42 • Discover if Users are Adding and Removing Products: Give them a discount to encourage purchase • Time between adding products and purchase • Frequency between cart events and other system events

43. Bob is Pleased 43

44. Not a New Concept

49. 49 Wait, what about those transaction logs?

52. 52 Audit Log will tell the history Events tell you the Intent of history

53. 53 Implementation

62. 62 Creating an Event Store

63. 63 Aggregate (it’s like a Domain Instance)

70. 70 Snapshots: essential optimization

73. 73 Choosing a Persistance Layer

74. 74 No real need for an ORM

75. Data base agnostic

76. Consider Using a Relational Database 76

79. 79 Demo Time

80. 80 … But Should I use it?

81. Use it only for Business-Critical data

82. Make Bob Happy 82

84. Questions ?

85. Image References (Multiple Newspapers): http://www.kba.com/gb/news/detail/article/30-kba-newspaper-customers-carry-off-quality-awards-2/back/50/ (Harbor): http://www.dredgingtoday.com/2013/09/06/corps-highlights-economic-benefits-of-savannah-harbor-dredging-usa/ (Sad Bob) http://workerscompensationwatch.com/2012/12/ (Logs in River / Log Driving) http://www.flickr.com/photos/foresthistory/ (Data Base Transaction Log) http://yutechnet.com/?p=96 (Amazon Shopping Cart) http://www.amazon.com (Ha, Ha, Business) http://www.quickmeme.com (crowd of people) http://www.flickr.com/photos/jamescridland/613445810/ (skeptical dog) http://loltheists.com/?p=2427 (brick layer) http://www.torange.us/photo/4/13/brick-mud-brick-building-1259649354_44.jpg