Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.

Analytics 214

Analytics Monitoring Artificial Intelligence DevOps 214

Dynatrace

OCTOBER 4, 2022

This approach enables organizations to use this data to build artificial intelligence (AI) and machine learning models from large volumes of disparate data sets. Data lakehouses take advantage of low-cost object stores like AWS S3 or Microsoft Azure Blob Storage to store and manage data cost-effectively. Data management.

Artificial Intelligence 214

Artificial Intelligence Storage Analytics Government 214

Dynatrace

OCTOBER 30, 2023

The growing challenge in modern IT environments is the exponential increase in log telemetry data, driven by the expansion of cloud-native, geographically distributed, container- and microservice-based architectures. Organizations need a more proactive approach to log management to tame this proliferation of cloud data.

Best Practices 249

Best Practices Analytics Artificial Intelligence Infrastructure 249

Scalegrid

FEBRUARY 8, 2024

Real-World Use Cases of Distributed Storage Distributed storage systems are the backbone of massively scalable storage services, designed to serve both cloud-based and on-premises environments. Amazon S3 and Microsoft Azure Blob Storage leverage distributed storage solutions.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

NOVEMBER 22, 2021

In fact, Gartner predicts that cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives by 2025 — up from less than 40% in 2021. These modern, cloud-native environments require an AI-driven approach to observability. At AWS re:Invent 2021 , the focus is on cloud modernization.

AWS 233

AWS Lambda Artificial Intelligence Serverless 233

Dynatrace

OCTOBER 1, 2021

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. Observability relies on telemetry derived from instrumentation that comes from the endpoints and services in your multi-cloud computing environments.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Dynatrace

JUNE 1, 2021

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. Why cloud-native applications make APM challenging. Cloud-native apps also produce many kinds of data.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

O'Reilly

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. The shift to cloud native design is transforming both software architecture and infrastructure and operations. Still cloud-y, but with a possibility of migration.

Software Architecture 132

Software Architecture DevOps Data Engineering Architecture 132

O'Reilly

NOVEMBER 28, 2023

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. 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.

Open Source 106

Open Source Artificial Intelligence Google Infrastructure 106