Dok Talks #117 - Why you should care about data mesh

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https://go.dok.community/slack https://dok.community ABSTRACT OF THE TALK Data mesh is a new approach for designing modern data architectures by embracing organizational constructs as well as technological aspects, data management, governance, etc. The idea is that data should be easily accessible and interconnected across the entire business. This talk will look at the concept of data mesh architecture. It will discuss implementing data mesh architecture in organizations and will relate data mesh to updates at TerminusDB. BIO Co-founder of TerminusDB, the open source document graph database. KEY TAKE-AWAYS FROM THE TALK Data mesh TerminusDB Document graphs Git for data https://terminusdb.com/blog/

Luke Feeney
Founder @ TerminusDB

Everything
as code
Managing Databases in a
CI/CD pipeline is a
nightmare. Migration
scripts are better than
making changes on running
servers, but become hard
to manage in complex
modern pipelines.

But what could cause such terror?

Come
to
Freddy

Data is
Still in the
Dark Ages

Domain Focus

Data is a product

Self-service Data

Governance

JSON Documents are central to software developers

Easy in, Easy out

Documents can have links

Documents can have links

Static and dynamic linking

Interlinking Data Products

Versions

Branches

Time Travel

Collaboration: rebase

Document Graphs enable the mesh

Dok Talks #117 - Why you should care about data mesh

Dok Talks #117 - Why you should care about data mesh

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Leveraging Running Stateful Workloads on Kubernetes for the Benefit of Develo...

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Why run Postgres in Kubernetes?

Why run Postgres in Kubernetes?

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What's New in Kubernetes Storage

What's New in Kubernetes Storage

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What we've learned from running a PostgreSQL managed service on Kubernetes

What we've learned from running a PostgreSQL managed service on Kubernetes

Weathering The Cloud Storm: Modern Data Management Patterns for Reliability a...

Weathering The Cloud Storm: Modern Data Management Patterns for Reliability a...

Weathering The Cloud Storm: Modern Data Management Patterns for Reliability a...

Using Kubernetes to deliver a “serverless” service

Using Kubernetes to deliver a “serverless” service

Using Kubernetes to deliver a “serverless” service

The many uses of Kubernetes cross cluster migration of persistent data

The many uses of Kubernetes cross cluster migration of persistent data

The many uses of Kubernetes cross cluster migration of persistent data

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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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1. Luke Feeney Founder @ TerminusDB

2. Everything as code Managing Databases in a CI/CD pipeline is a nightmare. Migration scripts are better than making changes on running servers, but become hard to manage in complex modern pipelines.

3.

4.

5.

6.

7. But what could cause such terror?

8.

9.

10. Come to Freddy

11.

12. Data is Still in the Dark Ages

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23. Domain Focus

24. Data is a product

25. Self-service Data

27.

28.

29.

30. JSON Documents are central to software developers

31. Easy in, Easy out

32. Documents can have links

33. Documents can have links

34. Static and dynamic linking

35. Interlinking Data Products

38. Time Travel

39. Collaboration: rebase

40. Document Graphs enable the mesh