Dynatrace

FEBRUARY 16, 2023

That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization. Traditional cloud monitoring methods can no longer scale to meet organizations’ demands, as multicloud architectures continue to expand.

Artificial Intelligence 193

Artificial Intelligence Analytics Cloud Innovation 193

Dynatrace

OCTOBER 30, 2023

The resulting vast increase in data volume highlights the need for more efficient data handling solutions. Consolidate log management tools into a unified observability platform As businesses increasingly shift toward software-centric models, the number of specialized IT monitoring tools to manage cloud environments has proliferated.

Best Practices 243

Best Practices Analytics Artificial Intelligence Infrastructure 243

Scalegrid

FEBRUARY 8, 2024

It utilizes methodologies like DStore, which takes advantage of underused hard drive space by using it for storing vast amounts of collected datasets while enabling efficient recovery processes. These systems enable vast amounts of data to be spread over multiple nodes, allowing for simultaneous access and boosting processing efficiency.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. A data lakehouse, therefore, enables organizations to get the best of both worlds.

Artificial Intelligence 208

Artificial Intelligence Analytics Storage Government 208

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

NOVEMBER 22, 2021

Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. Many organizations that have taken on DevOps methodologies still struggle with efficiency given tool fragmentation. AWS made better through AIOps.

AWS 228

AWS Lambda Artificial Intelligence Serverless 228

Dynatrace

OCTOBER 6, 2023

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Adopting this level of data segmentation helps to maximize Grail’s performance potential.

Artificial Intelligence 261

Artificial Intelligence Analytics Metrics Storage 261

Dynatrace

OCTOBER 1, 2021

The goal of observability is to understand what’s happening across all these environments and among the technologies, so you can detect and resolve issues to keep your systems efficient and reliable and your customers happy. What is the difference between monitoring and observability? In short, no.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Scalegrid

JANUARY 12, 2024

This article analyzes cloud workloads, delving into their forms, functions, and how they influence the cost and efficiency of your cloud infrastructure. Utilizing cloud platforms is especially useful in areas like machine learning and artificial intelligence research.

Cloud 130

Cloud Virtualization Storage Efficiency 130

Scalegrid

JANUARY 8, 2024

Real-world examples like Spotify’s multi-cloud strategy for cost reduction and performance, and Netflix’s hybrid cloud setup for efficient content streaming and creation, illustrate the practical applications of each model. Thus making it an ideal choice for businesses seeking a successful implementation of their multi-cloud strategy.

Strategy 147

Strategy Cloud Scalability Artificial Intelligence 147

Dynatrace

JUNE 1, 2021

Application performance monitoring (APM) is the practice of tracking key software application performance metrics using monitoring software and telemetry data. Mobile apps, websites, and business applications are typical use cases for monitoring. APM can be referred to as: Application performance monitoring.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

O'Reilly

NOVEMBER 28, 2023

While the source code and weights for the LLaMA models are available online, the LLaMA models don’t yet have a public API backed by Meta—although there appear to be several APIs developed by third parties, and both Google Cloud and Microsoft Azure offer Llama 2 as a service. The next most needed skill is operations for AI and ML (54%).

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108