Dynatrace

AUGUST 16, 2021

Automatically collect and evaluate business, service, and architectural indicator metrics to promote or roll back deployments. Successful DevOps teams have figured out that “delivering more with less” requires careful management of release risks and automation to scale. SLO validation – ?Automatically Topics in this blog series.

Software 246

Software Software Open Source Azure 246

Dynatrace

NOVEMBER 15, 2021

Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes. 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).

Analytics 205

Analytics Monitoring Artificial Intelligence DevOps 205

Dynatrace

FEBRUARY 10, 2021

Software companies who have already been following and adopting DevOps and site reliability engineering (SRE) practices alongside their shared ancestry in agile concepts came out on top – especially if they adopted those practices across the whole organization and customer value stream. Automated release inventory and version comparison.

Cloud 165

Cloud DevOps Speed Azure 165

Dynatrace

FEBRUARY 12, 2024

Each use case provides its own unique value and impact, and whoever sees value in the use cases can adopt it—whether they are a platform engineer, DevOps engineer, performance engineer, or a site reliability engineer (SRE). When releasing into production, Gardner said it’s important to think beyond performance metrics.

Engineering 179

Engineering Development Infrastructure Cloud 179

Dynatrace

JANUARY 5, 2022

This guest blog is authored by Raphael Pionke , DevOps Engineer at T-Systems MMS. While the test step, use case, and thread group name context are helpful we also want to speed up the analysis of individual requests that fail. It automatically sends JMeter metrics to the Dynatrace cluster via the Metrics Ingest API.

Testing 214

Testing Open Source Metrics Infrastructure 214

Dynatrace

JULY 12, 2022

After moving to Microsoft Azure for many of its production-stage applications, Park ‘N Fly’s IT teams experienced blind spots. “We Several team members had to pore through logs, metrics, and other data to identify issues. “We IT automation speeds code development. Previously, Park ‘N Fly had to manually troubleshoot.

Innovation 216

Innovation Infrastructure DevOps Azure 216

Dynatrace

NOVEMBER 29, 2021

Self-hosted Kubernetes installations or services — such as Amazon EKS, Azure Kubernetes Service, or the Google Kubernetes Engine — make it possible for enterprises to select and implement best-fit functions. OpenShift, DevOps, and CI/CD. Enhances DevOps productivity. Speeds up development.

Monitoring 147

Monitoring DevOps Infrastructure Metrics 147

Dynatrace

SEPTEMBER 13, 2023

And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? Storing frequently accessed data in faster storage, usually in-memory caching, improves data retrieval speed and overall system performance. Beyond

AWS 243

AWS Efficiency Azure Cloud 243

Dynatrace

NOVEMBER 22, 2021

Not just logs, metrics and traces. Its approach to serverless computing has transformed DevOps. DevOps/DevSecOps with AWS. Successful DevOps is as much about tactics as it is technology. 2021 DevOps Report. The need for speed has never been more urgent in today’s hyper-digital age. What is observability?

AWS 225

AWS Lambda Artificial Intelligence Serverless 225

Dynatrace

NOVEMBER 10, 2022

Cloud-native architecture is a structural approach to planning and implementing an environment for software development and deployment that uses resources and processes common with public clouds like Amazon Web Services, Microsoft Azure, and Google Cloud Platform. The principles of cloud-native architecture. Stateless whenever possible.

Cloud 162

Cloud Architecture Serverless Infrastructure 162

Tasktop

JULY 17, 2019

Contrast this available telemetry with teams practicing DevOps who know their recovery time, their change failure and success rates, and their cycle times – all of which help teams identify opportunities for continuous improvement. The answer is Flow Metrics. 5 Everyday Problems Exposed by Flow Metrics.

Metrics 40

Metrics Software Software DevOps 40

Scalegrid

MARCH 14, 2024

It provides significant advantages that include: Offering scalability to support business expansion Speeding up the execution of business plans Stimulating innovation throughout the company Boosting organizational flexibility, enabling quick adaptation to changing market conditions and competitive pressures.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

NOVEMBER 20, 2023

Why this deterministic AI approach is critical to business success – blog Today’s organizations need to go beyond a traditional, correlation-driven approach to identify the underlying causes and effects of an event or behavior and drive better DevOps automation. Enter causal AI.

AWS 206

AWS Artificial Intelligence Analytics Cloud 206

Dynatrace

MAY 28, 2020

Kubernetes, OpenShift, Cloud Foundry or Azure Web Apps then install the OneAgent by following the OneAgent PaaS installation options. These tags will allow us to create dashboards, request attributes or calculate service metrics specifically for our application under test. If your apps are deployed in a PaaS Platform, e.g:

Engineering 189

Engineering Performance Metrics Best Practices 189

Tasktop

JUNE 20, 2019

Clever Value Stream Architecture designs for speed, visibility and traceability and it relies on APIs and abstraction. Here are some examples: • Incidents created in ServiceNow are automatically synchronized to Azure DevOps as bugs. Requirements defined in Jama flow are synchronized as Stories to Jira. Learn more.

Development 45

Development DevOps Google Innovation 45

High Scalability

NOVEMBER 25, 2019

To add elasticity, reliability and durability, these data centers are connected to Google Cloud platform using high speed, secure Google Interconnect network. Tens of petabytes of data stored in our servers and other object stores such as GCS, S3 and Azure Blobstore. Data interdependence. Level of concurrent reads. Cloud Platform.

Architecture 52

Architecture Cache Azure Storage 52