Dynatrace

NOVEMBER 5, 2019

Dependency agent Installation – Maps connections between servers and processes. AI engine, Davis – Automatically processes billions of dependencies to serve up precise answers; rather than processing simple time-series data, Davis uses high-fidelity metrics, traces, logs, and real user data that are mapped to a unified entity.

Azure 137

Azure Artificial Intelligence Metrics Innovation 137

Dynatrace

JANUARY 4, 2024

Improving data quality is a strategic process that involves all organizational members who create and use data. It starts with implementing data governance practices, which set standards and policies for data use and management in areas such as quality, security, compliance, storage, stewardship, and integration.

Government 200

Government Analytics Benchmarking Storage 200

Dynatrace

JANUARY 23, 2024

Deriving business value with AI, IT automation, and data reliability When it comes to increasing business efficiency, boosting productivity, and speeding innovation, artificial intelligence takes center stage. Teams face siloed processes and toolsets, vast volumes of data, and redundant manual tasks.

Performance 186

Performance DevOps Innovation Artificial Intelligence 186

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

NOVEMBER 20, 2023

Causal AI is an artificial intelligence technique used to determine the precise underlying causes and effects of events. Using Effectively automating IT processes is key to addressing the challenges of  complex cloud environments. Relying on manual processes results in outages, increased costs, and frustrated customers.

AWS 209

AWS Artificial Intelligence Analytics Cloud 209

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. Excel files. CSV files.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Dynatrace

OCTOBER 4, 2022

This architecture offers rich data management and analytics features (taken from the data warehouse model) on top of low-cost cloud storage systems (which are used by data lakes). This decoupling ensures the openness of data and storage formats, while also preserving data in context. Ingest and process with Grail. Retain data.

Artificial Intelligence 268

Artificial Intelligence Analytics Storage Architecture 268

Scalegrid

MAY 13, 2020

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. Greenplum uses an MPP database design that can help you develop a scalable, high performance deployment.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

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. Buckets are similar to folders, a physical storage location. There is a default bucket for each table.

Artificial Intelligence 262

Artificial Intelligence Analytics Metrics Storage 262

Dynatrace

FEBRUARY 12, 2024

Grail handles data storage, data management, and processes data at massive speed, scale, and cost efficiency,” Singh said. The importance of hypermodal AI to unified observability Artificial intelligence is a critical aspect of a unified observability strategy. This is Davis CoPilot.

Analytics 181

Analytics Artificial Intelligence Engineering Storage 181

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. This consistency aids not only in application deployment but also simplifies scaling processes. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

OCTOBER 4, 2022

Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. However, organizations must structure and store data inputs in a specific format to enable extract, transform, and load processes, and efficiently query this data. Massively parallel processing. Query language.

Artificial Intelligence 209

Artificial Intelligence Storage Analytics Government 209

Dynatrace

OCTOBER 4, 2022

Teams have introduced workarounds to reduce storage costs. Additionally, efforts such as lowered data retention times, two-tiered storage systems, shaky index management, sampled data, and data pipelines reduce the overall amount of stored data. Stop worrying about log data ingest and storage — start creating value instead.

Analytics 234

Analytics Artificial Intelligence Storage Serverless 234

Scalegrid

JANUARY 8, 2024

ScaleGrid offers solutions that address these difficulties by simplifying administration processes in multi-cloud environments and enabling smooth integration among various cloud platforms. Integrating data sources and applications across multiple cloud providers brings about integration hurdles due to the different platforms involved.

Strategy 147

Strategy Cloud Scalability Artificial Intelligence 147

Scalegrid

DECEMBER 21, 2023

Such as: RedisInsight – Offers an easy way for users to oversee their Redis® information with visual cues; Prometheus – Providing long-term metrics storage solutions when tracking performance trends involving your instances; Grafana – Its user-friendly interface allows advanced capabilities in observing each instance.

Strategy 130

Strategy Monitoring Latency DevOps 130

Scalegrid

JANUARY 12, 2024

In the realm of cloud-based business operations, there is an increasing dependence on complex information processing patterns. Storage is a critical aspect to consider when working with cloud workloads. Utilizing cloud platforms is especially useful in areas like machine learning and artificial intelligence research.

Cloud 130

Cloud Virtualization Storage Efficiency 130

KeyCDN

FEBRUARY 22, 2023

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. Source: web.dev 2.

Artificial Intelligence 111

Artificial Intelligence Development Serverless Website 111

Dynatrace

NOVEMBER 15, 2021

Logs can include data about user inputs, system processes, and hardware states. Log monitoring is a process by which developers and administrators continuously observe logs as they’re being recorded. Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 209

Analytics Monitoring Artificial Intelligence DevOps 209

Dynatrace

DECEMBER 22, 2021

Metrics are measures of critical system values, such as CPU utilization or average write latency to persistent storage. A database could start executing a storage management process that consumes database server resources. In this case, the best option may be to stop the process and execute it when system load is low.

Artificial Intelligence 178

Artificial Intelligence Metrics Architecture DevOps 178

All Things Distributed

DECEMBER 13, 2016

Take GoSquared , a UK startup that runs all its development and production processes on AWS, as an example. With AWS, GoSquared can process tens of billions of data points every day from four continents to provide customers with a single view. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

O'Reilly

SEPTEMBER 19, 2023

It progressed from “raw compute and storage” to “reimplementing key services in push-button fashion” to “becoming the backbone of AI work”—all under the umbrella of “renting time and storage on someone else’s computers.” ” (It will be easier to fit in the overhead storage.)

Hardware 99

Hardware Storage Big Data Blockchain 99

Abhishek Tiwari

DECEMBER 27, 2017

In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. More importantly, UDM utilizes a single storage backend with benefits of multiple storage systems which avoids moving data across systems hence data duplication, and data consistency issues.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

ACM Sigarch

DECEMBER 6, 2018

As a result of these different types of usages, a number of interesting research challenges have emerged in the domain of visual computing and artificial intelligence (AI). Orchestrate the processing flow across an end-to-end infrastructure. Generate interactive and immersive content.

Wireless 54

Wireless IoT Analytics Architecture 54

O'Reilly

JULY 25, 2023

In the end, I had to add four additional permissions—”tabs”, “storage”, “scripting”, “identity”—as well as a separate “host_permissions” field to my manifest.json. And since this setup process was so new to me, I had a hard time thinking about how to phrase my questions.

Programming 98

Programming Code Design Benchmarking 98

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. With all of these processes in place, cost optimization is also a high concern for organizations worldwide. The world’s Artificial Intelligence market is anticipated to increase from $28.42

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92