Remove Artificial Intelligence Remove Azure Remove Infrastructure Remove Open Source
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. Open Source. Major Use Cases.

Big Data 321
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What is observability? Not just logs, metrics and traces

Dynatrace

In these modern environments, every hardware, software, and cloud infrastructure component and every container, open-source tool, and microservice generates records of every activity. Observability is also a critical capability of artificial intelligence for IT operations (AIOps).

Metrics 363
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Web Development Trends in 2023

KeyCDN

Source: web.dev 2. Artificial intelligence and machine learning Artificial intelligence (AI) and machine learning (ML) are becoming more prevalent in web development, with many companies and developers looking to integrate these technologies into their websites and web applications.

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AWS Re:Invent 2021 guide: Multicloud modernization and digital transformation

Dynatrace

Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. With AIOps , practitioners can apply automation to IT operations processes to get to the heart of problems in their infrastructure, applications and code.

AWS 228
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What is APM?

Dynatrace

Millions of lines of code comprise these apps, and they include hundreds of interconnected digital services and open-source solutions , and run in containerized environments hosted across multiple cloud services. Virtual desktop infrastructure (VDI) monitoring to maximize the productivity of employees using VDI.

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Generative AI in the Enterprise

O'Reilly

16% of respondents working with AI are using open source models. Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. We’ll say more about this later.)