TechBeacon Testing

AUGUST 28, 2020

Organizations that adopt artificial intelligence (AI) in testing of microservices-based applications gain better accuracy, faster results, and greater operational efficiency.

Artificial Intelligence 142

Artificial Intelligence Testing Efficiency 142

Dynatrace

OCTOBER 4, 2023

Certain technologies can support these goals, such as cloud observability , workflow automation , and artificial intelligence. Companies that exploit these technologies can discover risks early, remediate problems, and to innovate and operate more efficiently are likely to achieve competitive advantage.

Artificial Intelligence 173

Artificial Intelligence Innovation Strategy Efficiency 173

Dynatrace

MARCH 14, 2022

As patient care continues to evolve, IT teams have accelerated this shift from legacy, on-premises systems to cloud technology to more build, test, and deploy software, and fuel healthcare innovation. exemplifies this trend, where cloud transformation and artificial intelligence are popular topics. Emerging security threats.

Healthcare 232

Healthcare Artificial Intelligence Innovation Strategy 232

Alex Podelko

DECEMBER 19, 2019

Marrying Artificial Intelligence and Automation to Drive Operational Efficiencies by Priyanka Arora, Asha Somayajula, Subarna Gaine, Mastercard. – Application of Artificial Intelligence to operations – as done at Mastercard. . – Another presentation on resource optimization – this one from Salesforce.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

Dynatrace

JANUARY 13, 2022

More seamless handoffs between tasks in the toolchain can improve DevOps efficiency, software development innovation, and better code quality. At Dynatrace Perform, the annual software intelligence platform conference, we will highlight new integrations that eliminate toolchain silos, tame complexity, and automate DevOps practices.

DevOps 272

DevOps Speed Artificial Intelligence Innovation 272

Dynatrace

APRIL 21, 2023

Critical application outages negatively affect citizen experience and are costly on many fronts, including citizen trust, employee satisfaction, and operational efficiency. By detecting errors and bugs before they’re deployed to production, we save money on development and testing and better serve the citizens of our state.”

Innovation 188

Innovation Speed Artificial Intelligence Government 188

Dynatrace

NOVEMBER 2, 2022

Organizations have increasingly turned to software development to gain competitive edge, to innovate and to enable more efficient operations. Autonomous testing. As teams develop software more quickly, they can’t rely on manual methods to test applications. Chaos engineering.

Software 201

Software Software Artificial Intelligence DevOps 201

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Testing automation can be painstaking. It’s also crucial to test frequently when automating IT operations so that you don’t automatically replicate mistakes. Read eBook now!

Artificial Intelligence 194

Artificial Intelligence Tuning Strategy Big Data 194

Dynatrace

MAY 17, 2023

The technology lets people learn about solutions by typing questions into a search bar, such as, “How do I import and export test cases between my environments?” Achieving this precision requires another type of artificial intelligence: causal AI. and “What’s the best way to integrate this solution with my toolchain?”

Innovation 265

Innovation Software Software Artificial Intelligence 265

Testsigma

MAY 15, 2021

As the complexities of the software applications increased, the need for software testing became more and more apparent. That was when Manual testing of software applications came into being. Soon, when the software was big and hefty, manual testing became a hectic and time-consuming job too.

Testing Tools 52

Testing Tools Artificial Intelligence Testing Programming 52

Dynatrace

NOVEMBER 1, 2022

Most IT incident management systems use some form of the following metrics to handle incidents efficiently and maintain uninterrupted service for optimal customer experience. This measurement includes time spent testing until the service is fully functional again. Mean time to repair. Mean time to recovery.

DevOps 212

DevOps Artificial Intelligence Metrics Network 212

Testsigma

DECEMBER 21, 2020

As the world moves forward, it wants to progress, more efficiency, more speed, and the same is the case with the software development industry. Software Testing being a major part of software development also needs more efficiency. There are plenty of regression testing automation tools available in the market today.

Artificial Intelligence 52

Artificial Intelligence Testing Testing Tools Efficiency 52

TechBeacon Testing

AUGUST 18, 2021

has brought machines, software, the Internet, and people into a hyper-connected ecosystem that needs to be tested from end to end. The tests you create for the devices and associated software in those ecosystems needs to be automated for both agility and boosting the efficiency and reliability of the tests themselves.

Testing 106

Testing Internet Internet Efficiency 106

Dynatrace

DECEMBER 16, 2019

Perhaps the most common examples lie in the pharmaceutical world; drugs are sometimes tested and approved based on statistically meaningful outcomes on patients, even though nobody knows how they work. “We We’ll also present the case that efficiency alone isn’t the best approach to judging value. We have an answer; it seems to work.

Artificial Intelligence 151

Artificial Intelligence Traffic Efficiency Innovation 151

Dynatrace

MARCH 10, 2021

This week Dynatrace achieved Amazon Web Services (AWS) Machine Learning Competency status in the new Applied Artificial Intelligence (Applied AI) category. See Dynatrace for yourself – take test drive with our free trial. Dynatrace news.

AWS 146

AWS Cloud Artificial Intelligence Innovation 146

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.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Dynatrace

NOVEMBER 8, 2021

Artificial intelligence for IT operations (AIOps) for applications. To deliver flawless user experiences, an APM solution should be able to delve into real-user monitoring and synthetic testing, with the ability to replay session-level details. Application discovery, tracing, and diagnostics (ADTD). User experience diagnostics.

Artificial Intelligence 236

Artificial Intelligence Monitoring Infrastructure Cloud 236

DZone

MAY 8, 2020

Earlier in my career (though it seems like yesterday), product teams I was a part of did everything “on-prem”, and angst-ridden code compiles took place every few months. We’d burn down bugs using manual QA and push to production after several long nights before taking a long nap and doing it all again next quarter.

Efficiency 147

Efficiency Engineering Code Artificial Intelligence 147

Adrian Cockcroft

NOVEMBER 30, 2020

This is becoming topical as governments and public companies around the world are looking for efficient and standardized ways to report their sustainability impact, and investors and asset managers are looking for common datasets and models to base their risk analysis on. Test drive the Accenture EV roaming platform IOT205 ?—?How

AWS 52

AWS Artificial Intelligence IoT Energy 52

Tech News Gather

JULY 18, 2023

These apps offer several benefits for both patients and providers including convenience, accessibility, efficiency, and cost-effectiveness. Healthcare web apps improve the quality and efficiency of healthcare services as they bring down costs, and improve patient satisfaction and positive engagement.

Healthcare 52

Healthcare Social Media Development Artificial Intelligence 52

Testsigma

SEPTEMBER 21, 2019

In layman terms, AI or Artificial intelligence is the area of computer science that focuses on making machines “intelligent.” And by intelligence, it means making the system capable of learning and taking decisions like humans. Why does Software Testing industry Need AI? No more flaky tests! What is AI?

Software 51

Software Software Testing Artificial Intelligence 51

Dynatrace

MAY 4, 2023

But without intelligent automation, they’re running into siloed processes and reduced efficiency. Integrating security into development and operations frameworks also improves testing, validation, and distribution practices with a continual feedback loop. However, silos have become a problem for many DevSecOps frameworks.

DevOps 218

DevOps Speed Innovation Open Source 218

O'Reilly

JULY 11, 2023

If 20% of your time is spent coding, and AI-based code generation makes you 50% more efficient, then you’re really only getting about 10% of your time back. Testing and debugging—well, if you’ve played with ChatGPT much, you know that testing and debugging won’t disappear. Furthermore, it doesn’t really eliminate programming.

Programming 99

Programming Code Design Software 99

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

Dynatrace

APRIL 22, 2024

DevOps automation eliminates extraneous manual processes, enabling DevOps teams to develop, test, deliver, deploy, and execute other key processes at scale. It includes questions relating to vulnerability prioritization, attack detection and response, application testing, and other central aspects of security.

DevOps 191

DevOps Artificial Intelligence Government Innovation 191

Dynatrace

OCTOBER 14, 2021

Artificial intelligence for IT operations (AIOps) is an IT practice that uses machine learning (ML) and artificial intelligence (AI) to cut through the noise in IT operations, specifically incident management. Dynatrace news. But what is AIOps, exactly? And how can it support your organization? What is AIOps?

Artificial Intelligence 217

Artificial Intelligence DevOps Innovation Metrics 217

Dynatrace

OCTOBER 31, 2023

In attempting to address this difficult workforce challenge, chief information security officers (CISOs) are considering automation and artificial intelligence (AI) defense tools as a cost-effective, highly efficient option. We will track every single individual on their proficiency levels,” said Gorak.

Artificial Intelligence 189

Artificial Intelligence Energy Government Technology 189

Testsigma

MARCH 12, 2021

Robotic Process Automation and Test Automation are two confusing terms in testing processes. Similar to TDD and BDD processes, RPA and test automation seem like a single branch of the test segment which is common to be exchanged in communication during planning. The word “automation” seems to be a culprit in this case.

Artificial Intelligence 97

Artificial Intelligence Testing Energy Analytics 97

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 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. But before that new code can be deployed, it needs to be tested and reviewed from a security perspective. Taking AIOps to the next level.

DevOps 201

DevOps Artificial Intelligence Healthcare Innovation 201

Dynatrace

OCTOBER 30, 2023

The resulting vast increase in data volume highlights the need for more efficient data handling solutions. Application performance monitoring (APM) , infrastructure monitoring, log management, and artificial intelligence for IT operations (AIOps) can all converge into a single, integrated approach.

Best Practices 249

Best Practices Analytics Artificial Intelligence Infrastructure 249

Dynatrace

NOVEMBER 15, 2021

Whether a situation arises during development, testing, deployment, or in production, it’s important to work with a solution that can detect conditions in real-time so teams can troubleshoot issues before they slow down development or impact customers. Together, they provide continuous value to the business. Accelerated innovation.

Analytics 214

Analytics Monitoring Artificial Intelligence DevOps 214

Percona

DECEMBER 14, 2023

Will 2023 be called the year of Generative Artificial Intelligence (AI)? Google Bard vs. MongoDB and MySQL challenge This was my first test of Bard ever, and I had pretty high expectations due to the fact that it can reach the online information, as opposed to ChatGPT, which operates on limited data. to previous versions.

Database 84

Database Artificial Intelligence Servers Operating System 84

Testsigma

SEPTEMBER 28, 2021

Even though they were managing quite well with manual testers and in-house test automation setup, they know this arrangement cannot work for long. They also know that automation testing is gaining popularity and it is one of the strategies to get hold of ROI faster. Test creation – Easier with a friend.

Testing Tools 52

Testing Tools Mobile Testing Artificial Intelligence 52

O'Reilly

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. Programmers have always developed tools that would help them do their jobs, from test frameworks to source control to integrated development environments. We’d like to see more companies test for fairness.

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

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. Observability is also a critical capability of artificial intelligence for IT operations (AIOps).

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Testsigma

MAY 19, 2021

Thinking back on how SDLC started and what it is today, the only reasons for its success can be accounted to efficiency, speed and most importantly automation – DevOps and cloud-based solutions can be considered major contributors here (after all DevOps is 41% less time-consuming than traditional ops ). . Centralizes the Processes.

DevOps 59

DevOps Cloud Artificial Intelligence Infrastructure 59