Dynatrace

OCTOBER 2, 2023

Limits of a lift-and-shift approach A traditional lift-and-shift approach, where teams migrate a monolithic application directly onto hardware hosted in the cloud, may seem like the logical first step toward application transformation. However, the move to microservices comes with its own challenges and complexities.

Architecture 228

Architecture Artificial Intelligence Cloud Open Source 228

Scalegrid

FEBRUARY 8, 2024

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. This integration enhances the flexibility of cloud services while bolstering their computational and storage functions.

Storage 130

Storage Systems Big Data Azure 130

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 205

Analytics Monitoring Artificial Intelligence DevOps 205

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

Testsigma

MAY 19, 2021

DevOps and cloud-based computing have existed in our life for some time now. Today, we are here to talk about the successful amalgamation of DevOps and cloud-based technologies that is amazing in itself. Why Opt For Cloud-Based Solutions and DevOps? Cloud-based solutions are extremely fast when combined with DevOps.

DevOps 59

DevOps Cloud Artificial Intelligence Infrastructure 59

ACM Sigarch

APRIL 26, 2018

Dataflow Processing Unit (DPU) is the product of Wave Computing, a Silicon Valley company which is revolutionizing artificial intelligence and deep learning with its dataflow-based solutions. HPU: Holographic Processing Unit (HPU) is the specific hardware of Microsoft’s Hololens. GPU can also be considered as a special SPU.

Hardware 99

Hardware Artificial Intelligence Architecture Google 99

All Things Distributed

SEPTEMBER 4, 2017

In the case of artificial intelligence (AI) and machine learning (ML), this is different. Secondly, there is enough affordable computing capacity in the cloud for companies and organizations, no matter what their size, to use intelligent applications. Artificial intelligence helps to satisfy the customer.

Artificial Intelligence 147

Artificial Intelligence Transportation Education Airlines 147

All Things Distributed

DECEMBER 20, 2017

Developments like cloud computing, the internet of things, artificial intelligence, and machine learning are proving that IT has (again) become a strategic business driver. Marketers use big data and artificial intelligence to find out more about the future needs of their customers.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

O'Reilly

JANUARY 16, 2024

I’ve been diligent about data backup throughout my life, but my files are fragmented amongst different media over the years—burning CDs and DVDs back in the day, several generations of external hard drives (that are in various states of decay), university servers, Dropbox, and other cloud services.

Entertainment 73

Entertainment Internet Internet Design 73

O'Reilly

NOVEMBER 28, 2023

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. This is an area where cloud providers already bear much of the burden, and will continue to bear it in the future.

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

O'Reilly

SEPTEMBER 19, 2023

Cloud computing? Doubly so as hardware improved, eating away at the lower end of Hadoop-worthy work. And then there was the other problem: for all the fanfare, Hadoop was really large-scale business intelligence (BI). Google goes a step further in offering compute instances with its specialized TPU hardware.

Hardware 99

Hardware Storage Big Data Blockchain 99

Abhishek Tiwari

DECEMBER 27, 2017

With the arrival of new cloud-native tools and platform, ETL is becoming obsolete. Apache Arrow's in-memory columnar layout is specifically optimized for data locality for better performance on modern hardware like CPUs and GPUs. Leveraging the recent hardware advances. Machine learning meets data integration.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

O'Reilly

JULY 20, 2021

Until we acknowledge that hardware put in a home is different from a cloud service, we will never get it right. This is a collision between the expectations of consumers who put something in their home; those expectations run directly against the way rent-to-use services are pitched. Lots of problems, now what?

Google 121

Google Games Technology Technology 121