Dynatrace

FEBRUARY 10, 2022

The need for automation and orchestration across the software development lifecycle (SDLC) has increased, but many DevOps and SRE (site reliability engineering) teams struggle to unify disparate tools and cut back on manual tasks. Now, Security, DevOps, and SRE teams can automate their delivery pipeline. Atlassian Bitbucket.

Artificial Intelligence 231

Artificial Intelligence DevOps Azure Cloud 231

Dynatrace

NOVEMBER 2, 2022

As a result, many organizations have turned to DevOps (the alignment of development and operations teams) and DevSecOps (the alignment of development, security and operations teams) methodologies to enable more efficient and high-quality software development. Autonomous testing. Chaos engineering.

Software 197

Software Software Artificial Intelligence DevOps 197

Dynatrace

MAY 17, 2023

For example, it can help DevOps and platform engineering teams write code snippets by drawing on information from software libraries. 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?”

Innovation 262

Innovation Software Software Artificial Intelligence 262

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. DevOps can benefit from AIOps with support for more capable build-and-deploy pipelines. Dynatrace news.

Artificial Intelligence 214

Artificial Intelligence DevOps Innovation Metrics 214

Dynatrace

FEBRUARY 28, 2024

The VAPO platform is used to develop, test, and deploy containerized application and middleware workloads that support 400,000 VA employees and 20 million veterans. VAPO relies on Dynatrace and its integration with Red Hat to monitor application development and testing within containers to ensure optimal performance and security.

Monitoring 185

Monitoring Artificial Intelligence Performance Healthcare 185

DZone

MAY 3, 2019

With the introduction of the agile methodology and transformation into the digital world, the software development lifecycle is changing rapidly and increasing the need for better software testing capabilities. In 2019, we are expecting a lot of new changes in the web and this further poses a challenge in the testing cycle.

Artificial Intelligence 174

Artificial Intelligence Testing Virtualization Website 174

Testsigma

FEBRUARY 12, 2021

With the latest developments in IT sector services, the sector of QA testing has seen significant improvement and growth. The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. Many changes are rendered through automated testing. IoT Test Automation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Dynatrace

APRIL 26, 2022

To combat Kubernetes complexity and capitalize on the full benefits of the open-source container orchestration platform, organizations need advanced AIOps that can intelligently manage the environment. Cloud-native observability and artificial intelligence (AI) can help organizations do just that with improved analysis and targeted insight.

Cloud 227

Cloud Artificial Intelligence DevOps Scalability 227

Dynatrace

JULY 31, 2023

We believe integrating Rookout into the Dynatrace platform and leveraging the artificial intelligence and automation capabilities Dynatrace is known for will accelerate this mission.

Code 210

Code Artificial Intelligence Government Performance Testing 210

Testsigma

JANUARY 7, 2022

2014 saw the trend of mobile app testing as they were becoming a multi-billion dollar business all over the world. 2015 saw the trend of scriptless testing and IoT focussed methodologies. So the trend of mobile web testing came into the picture. DevOps aims at developing software and combining IT operations with it.

Artificial Intelligence 89

Artificial Intelligence IoT Software Software 89

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. DevOps: Applying AIOps to development environments. DevOps can benefit from AIOps with support for more capable build-and-deploy pipelines.

DevOps 198

DevOps Artificial Intelligence Healthcare Innovation 198

Dynatrace

JULY 6, 2022

IT automation, DevOps, and DevSecOps go together. DevOps and DevSecOps methodologies are often associated with automating IT processes because they have standardized procedures that organizations should apply consistently across teams and organizations. Testing automation can be painstaking.

Artificial Intelligence 191

Artificial Intelligence Tuning Strategy Big Data 191

Testsigma

MAY 19, 2021

DevOps and cloud-based computing have existed in our life for some time now. DevOps is a casket that contains automation as its basic principle. 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?

DevOps 59

DevOps Cloud Artificial Intelligence Infrastructure 59

Dynatrace

NOVEMBER 15, 2021

DevOps teams often use a log monitoring solution to ingest application, service, and system logs so they can detect issues at any phase of the software delivery life cycle (SDLC). With the help of log monitoring software, teams can collect information and trigger alerts if something happens that affects system performance and health.

Analytics 211

Analytics Monitoring Artificial Intelligence DevOps 211

Alex Podelko

DECEMBER 19, 2019

How is DevOps changing the Modern Software Development Landscape? , 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.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

TechBeacon Testing

JANUARY 8, 2021

Automated testing has emerged as one of the most important technologies for scaling DevOps, companies are investing enormous time and effort to build end-to-end software delivery pipelines, and containers and their ecosystem are holding up on their early promise. The last decade has seen a relentless push to deliver software faster.

Software 142

Software Software Testing DevOps 142

Dynatrace

JUNE 1, 2022

Many of these libraries have not been adequately tested before deployment. As a result, CISOs see artificial intelligence and automation as key to their vulnerability management arsenal to address Log4Shell-type incidents. Automation for real-time vulnerability identification and prioritization.

Artificial Intelligence 182

Artificial Intelligence Java Strategy Cloud 182

Dynatrace

MAY 4, 2023

Moreover, the demand for rapid software delivery is putting additional stress on DevOps teams. Integrating security into development and operations frameworks also improves testing, validation, and distribution practices with a continual feedback loop. Watch the full session, Break down DevSecOps silos with intelligent automation.

DevOps 215

DevOps Speed Innovation Open Source 215

Dynatrace

NOVEMBER 5, 2019

Our DEM offering also includes: Synthetics – Run browser-based workflow tests from multiple geographic locations for scoring availability of your applications before end-users experience issues. Strong integrations into common DevOps practices. Organic scalability of the monitoring platform with the applications.

Azure 138

Azure Artificial Intelligence Metrics Innovation 138

Dynatrace

OCTOBER 1, 2021

As a result, IT operations, DevOps , and SRE teams are all looking for greater observability into these increasingly diverse and complex computing environments. Observability is also a critical capability of artificial intelligence for IT operations (AIOps). But what is observability?

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Testsigma

DECEMBER 8, 2019

In this article, we will be talking about the technologies and techniques that are expected to become test automation trends in 2020. The highlights of the top test automation trends that we will be discussing in this article are: Integration of Automation of different processes to enable improved and enhanced end to end automation for eg.

IoT 78

IoT Software Software Artificial Intelligence 78

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 233

Artificial Intelligence Monitoring Infrastructure Cloud 233

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 144

AWS Cloud Artificial Intelligence Innovation 144

DZone

NOVEMBER 2, 2020

Remember when test automation was being peddled as a silver bullet for testing bugbears? Of course, those vendors really meant test execution automation. Automating test execution was going to increase coverage, minimize testing time, and overall reduce the amount of money being spent on testing.

Testing 133

Testing Processing Artificial Intelligence DevOps 133

TechBeacon Testing

JANUARY 28, 2020

Test automation tools have been steadily evolving—a trend that shows no sign of slowing down in the coming year. Several key advances to watch for over the next 12 months should make life easier for test automation engineers, consultants and tool vendors say, while others to watch out for are only likely to add confusion.

Testing 120

Testing Engineering Artificial Intelligence Processing 120

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. Ensuring the flow.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

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

O'Reilly

MARCH 2, 2020

Fetishizing unit testing. The most important is discovering how to work with data science and artificial intelligence projects. Development timelines for these projects aren’t as predictable as traditional software; they stretch the meaning of “testing” in strange ways; they aren’t deterministic.

Artificial Intelligence 21

Artificial Intelligence Software Architecture Programming Infrastructure 21