Dynatrace

NOVEMBER 1, 2022

DevOps and ITOps teams rely on incident management metrics such as mean time to repair (MTTR). Here’s what these metrics mean and how they relate to other DevOps metrics such as MTTA, MTTF, and MTBF. Mean time to respond (MTTR) is the average time it takes DevOps teams to respond after receiving an alert.

DevOps 212

DevOps Artificial Intelligence Metrics Network 212

Dynatrace

DECEMBER 13, 2023

That’s why many organizations are turning to generative AI—which uses its training data to create text, images, code, or other types of content that reflect its users’ natural language queries—and platform engineering to create new efficiencies and opportunities for innovation. 6: Platform engineering becomes mission-critical.

Technology 208

Technology Technology Artificial Intelligence Analytics 208

Dynatrace

MAY 17, 2023

For example, it can help DevOps and platform engineering teams write code snippets by drawing on information from software libraries. Engineering teams will, therefore, always need to check the code they get from GPTs to ensure it doesn’t risk software reliability, performance, compliance, or security.

Innovation 265

Innovation Software Software Artificial Intelligence 265

Dynatrace

JULY 7, 2022

AIOps and observability—or artificial intelligence as applied to IT operations tasks, such as cloud monitoring—work together to automatically identify and respond to issues with cloud-native applications and infrastructure. Think’ with artificial intelligence. This is where artificial intelligence (AI) comes in.

Artificial Intelligence 185

Artificial Intelligence Automotive DevOps Infrastructure 185

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 233

Artificial Intelligence DevOps Azure Cloud 233

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. Chaos engineering.

Software 201

Software Software Artificial Intelligence DevOps 201

Dynatrace

JANUARY 23, 2024

Composite’ AI, platform engineering, AI data analysis through custom apps This focus on data reliability and data quality also highlights the need for organizations to bring a “ composite AI ” approach to IT operations, security, and DevOps. Enter causal AI.

Performance 191

Performance DevOps Innovation Artificial Intelligence 191

Dynatrace

MAY 24, 2023

Instead of immediately firing off an alert for all raw events, the Davis root-cause engine follows each violating service’s causal relationships. DevOps teams use this page to quickly identify and remediate unexpected incidences. Usually, the journey doesn’t stop here.

Artificial Intelligence 192

Artificial Intelligence DevOps Metrics Infrastructure 192

Dynatrace

SEPTEMBER 21, 2022

Site reliability engineering seeks to bridge the gap between developers and operations teams, embedding reliability and resiliency into each stage of the software development lifecycle. Site reliability engineering (SRE) is a key component of digital transformation. Key finding #1: SRE is maturing, but not fast enough.

Artificial Intelligence 234

Artificial Intelligence Benchmarking DevOps Engineering 234

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

NOVEMBER 22, 2021

Having recently achieved AWS Machine Learning Competency status in the new Applied Artificial Intelligence (Applied AI) category for its use of the AWS platform, Dynatrace has demonstrated success building AI-powered solutions on AWS. Its approach to serverless computing has transformed DevOps. DevOps/DevSecOps with AWS.

AWS 232

AWS Lambda Artificial Intelligence Serverless 232

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 230

Cloud Artificial Intelligence DevOps Scalability 230

Dynatrace

DECEMBER 15, 2022

ITOps vs. DevOps and DevSecOps. ITOps is responsible for all an organization’s IT operations, including the end users’ IT needs, while DevOps is focused on agile continuous integration and delivery (CI/CD) practices and improving workflows. DevOps works in conjunction with IT. ITOps vs. AIOps.

Artificial Intelligence 208

Artificial Intelligence DevOps Hardware Virtualization 208

Dynatrace

JANUARY 19, 2022

In contrast, a modern observability platform uses artificial intelligence (AI) to gather information in real-time and automatically pinpoint root causes in context. Understanding the difference between observability and monitoring helps DevOps teams understand root causes and deliver better applications. What is DevOps?

Artificial Intelligence 184

Artificial Intelligence DevOps Performance Games 184

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 213

Code Artificial Intelligence Government Performance Testing 213

Dynatrace

JANUARY 12, 2021

IT, DevOps, and SRE teams are racing to keep up with the ever-expanding complexity of modern enterprise cloud ecosystems and the business demands they are designed to support. Dynatrace news. Leaders in tech are calling for radical change.

Monitoring 197

Monitoring Artificial Intelligence DevOps Serverless 197

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. How organizations benefit from automating IT practices.

Artificial Intelligence 194

Artificial Intelligence Tuning Strategy Big Data 194

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 201

DevOps Artificial Intelligence Healthcare Innovation 201

Dynatrace

JULY 18, 2022

The OpenTelemetry project was created to address the growing need for artificial intelligence-enabled IT operations — or AIOps — as organizations broaden their technology horizons beyond on-premises infrastructure and into multiple clouds. Dynatrace news. At industrial supply giant W.W. Start small.

Artificial Intelligence 198

Artificial Intelligence Open Source Analytics Monitoring 198

Alex Podelko

DECEMBER 19, 2019

– Performance engineering as it done at Alibaba – which emerging as a major cloud provider. How is DevOps changing the Modern Software Development Landscape? , – Clearly a hot topic – and the most interesting point here would be how it is changing performance engineering. a Panel Discussion.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

Scalegrid

DECEMBER 21, 2023

Redis® Monitoring in DevOps Practices Integrating Redis® monitoring into DevOps practices is a highly effective way of increasing the system’s overall reliability and enabling continual enhancement. In short, incorporating this sort of continuous analysis into your CI/CD workflows proves invaluable.

Strategy 130

Strategy Monitoring Latency DevOps 130

Testsigma

FEBRUARY 12, 2021

The usage by advanced techniques such as RPA, Artificial Intelligence, machine learning and process mining is a hyper-automated application that improves employees and automates operations in a way which is considerably more efficient than conventional automation. Hyperautomation. Autonomous Test Automation. billion in 2019 to $40.74

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Dynatrace

FEBRUARY 16, 2023

That’s why teams need a modern observability approach with artificial intelligence at its core. “We And if you do, and if you have an AIOps engine [which brings AI to IT operations] that enables that process to be effective, then that makes you so much more powerful in the management of that ecosystem.”

Artificial Intelligence 199

Artificial Intelligence Analytics Cloud Innovation 199

Scalegrid

MARCH 14, 2024

Workloads from web content, big data analytics, and artificial intelligence stand out as particularly well-suited for hybrid cloud infrastructure owing to their fluctuating computational needs and scalability demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Testsigma

JANUARY 7, 2022

QAOps is a term derived by combining the two processes – the DevOps and QA into one. DevOps aims at developing software and combining IT operations with it. When we fuse QA into the DevOps process the newly integrated process is called QAOps. AI and Machine learning-based testing. AI and ML are no new words today.

Artificial Intelligence 89

Artificial Intelligence IoT Software Software 89

Dynatrace

NOVEMBER 5, 2019

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. AI engine to detect anomalies and perform root-cause analysis, enabling AIOps.

Azure 139

Azure Artificial Intelligence Metrics Innovation 139

Dynatrace

NOVEMBER 24, 2020

To bring higher-quality information to Well-Architected Reviews and to establish a strategic advanced observability solution to support the Well-Architected Framework 5-pillars, Dynatrace offers a fully automated, software intelligence platform powered by Artificial Intelligence.

AWS 146

AWS Artificial Intelligence Best Practices Lambda 146

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. Davis—the Dynatrace AI engine —uses the application topology and service flow maps together with high-fidelity metrics to perform a fault tree analysis. Dynatrace news.

AWS 146

AWS Cloud Artificial Intelligence Innovation 146

Dynatrace

MAY 27, 2022

As a result, many IT teams are turning to artificial intelligence for IT operations (AIOps) , which integrates AI into operations to automate systems across the development lifecycle. This automatic analysis enables engineers to spend more time innovating and improving business operations.

Artificial Intelligence 192

Artificial Intelligence Innovation Servers Database 192

Dynatrace

NOVEMBER 8, 2021

Artificial intelligence for IT operations (AIOps) for applications. Dynatrace is built on a unified data model to enable sophisticated automation and intelligence — two capabilities that ITOps and DevOps teams are finding increasingly important as the complexity of application and cloud environments exponentially increases.

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

Testsigma

JULY 14, 2020

While the automation test engineer is working on the test scripts, any team member with knowledge of AUT can maintain and update the test data file without any dependency on the test scripts. In the Agile and DevOps environment, shorter development cycles need quick decisions and quick resolution of issues. Broader test-coverage.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Dynatrace

JUNE 1, 2021

According to Gartner , “Application performance monitoring is a suite of monitoring software comprising digital experience monitoring (DEM), application discovery, tracing and diagnostics, and purpose-built artificial intelligence for IT operations.” Improved infrastructure utilization. Concrete business benefits.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

TechBeacon Testing

JANUARY 28, 2020

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. Test automation tools have been steadily evolving—a trend that shows no sign of slowing down in the coming year.

Testing 120

Testing Engineering Artificial Intelligence Processing 120

InfoQ

APRIL 15, 2024

At the QCon London 2024 conference, Félix GV from LinkedIn discussed the AI/ML platform powering the company’s products. He specifically delved into Venice DB, the NoSQL data store used for feature persistence. The presenter shared the lessons learned from evolving and operating the platform, including cluster management and library versioning.

Artificial Intelligence 105

Artificial Intelligence Big Data Data Engineering Latency 105

O'Reilly

MARCH 2, 2020

The most important is discovering how to work with data science and artificial intelligence projects. This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Coincidence?

Artificial Intelligence 21

Artificial Intelligence Software Architecture Programming Infrastructure 21

O'Reilly

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Also: infrastructure and operations is trending up, while DevOps is trending down. Coincidence? Interestingly, R itself continues to decline.

Software Architecture 134

Software Architecture DevOps Data Engineering Architecture 134