Scalegrid

MAY 13, 2020

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. Greenplum Architectural Design. Greenplum Advantages.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

OCTOBER 4, 2022

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. High-performance analytics—no indexing required.

Artificial Intelligence 290

Artificial Intelligence Analytics Storage Architecture 290

Dynatrace

OCTOBER 4, 2022

A data lakehouse features the flexibility and cost-efficiency of a data lake with the contextual and high-speed querying capabilities of a data warehouse. The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. What is a data lakehouse?

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

Dynatrace

JUNE 14, 2023

And specifically, how Dynatrace can help partners deliver multicloud performance and boundless analytics for their customers’ digital transformation and success. Organizations are evacuating data centers and going towards the cost, speed, and capability advantages that they can get from the cloud.

Programming 245

Programming Best Practices Innovation Analytics 245

Dynatrace

OCTOBER 17, 2023

Data, AI, analytics, and automation are key enablers for efficient IT operations Data is the foundation for AI and IT automation. The data is stored with full context, which enables AI to deliver precise answers with speed and analytics to give rich insights with efficiency. 5) in the Gartner report.

Monitoring 278

Monitoring Artificial Intelligence Performance Analytics 278

Dynatrace

AUGUST 22, 2024

As end-to-end observability has become critical, we believe this placement reflects our commitment to delivering innovation that helps our customers solve their most complex business challenges with AI-powered observability, analytics, and automation.

Analytics 246

Analytics Innovation Website Scalability 246

Dynatrace

JULY 29, 2024

Our guide covers AI for effective DevSecOps, converging observability and security, and cybersecurity analytics for threat detection and response. A unified observability and security analytics strategy can guide organizations toward a more proactive security posture at scale. Discover more insights from the 2024 CISO Report.

Analytics 245

Analytics Government DevOps Efficiency 245

Dynatrace

APRIL 10, 2023

Kiran Bollampally, site reliability and digital analytics lead for ecommerce at Tractor Supply Co., shifted most of its ecommerce and enterprise analytics workloads to Kubernetes-managed software containers running in Microsoft Azure. Rural lifestyle retail giant Tractor Supply Co. ” Three years ago, Tractor Supply Co.

Cloud 243

Cloud Ecommerce Performance Retail 243

Dynatrace

AUGUST 2, 2021

But without complex analytics to make sense of them in context, metrics are often too raw to be useful on their own. Often referred to as calculated metrics (see Adobe Analytics and Google Analytics ), such metric processing takes one or more existing metrics as input to create a new user-defined metric. Dynatrace news.

Metrics 246

Metrics Analytics Google Code 246

Dynatrace

APRIL 28, 2020

In addition to APM , th is platform offers our customers infrastructure monitoring spanning logs and metrics, digital business analytics, digital experience monitoring, and AIOps capabilities. T he Dynatrace Software Intelligence Platform includes multiple modules, underpinned by a common data model.

DevOps 264

DevOps Innovation Monitoring Analytics 264

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. This improves query speeds and reduces related costs for all other teams and apps.

Artificial Intelligence 279

Artificial Intelligence Metrics Analytics Storage 279

Dynatrace

NOVEMBER 20, 2023

How this data-driven technique gives foresight to IT teams – blog By analyzing patterns and trends, predictive analytics enables teams to take proactive actions to prevent problems or capitalize on opportunities. What is predictive AI? What is AIOps?

AWS 277

AWS Artificial Intelligence Cloud Analytics 277

Dynatrace

NOVEMBER 7, 2023

Provide self-service platform services with dedicated UI for development teams to improve developer experience and increase speed of delivery. In addition, Dynatrace effortlessly collects crucial DORA metrics, SLOs, and business analytics data via its robust unified data platform, Dynatrace Grail™. Automation, automation, automation.

Engineering 306

Engineering DevOps Best Practices Infrastructure 306

Dynatrace

MAY 15, 2020

Overcoming the barriers presented by legacy security practices that are typically manually intensive and slow, requires a DevSecOps mindset where security is architected and planned from project conception and automated for speed and scale throughout where possible. Today, security teams often employ SIEMs for log analytics.

Government 278

Government DevOps Infrastructure Network 278

Dynatrace

MARCH 6, 2024

IBM i is designed to integrate seamlessly with legacy and modern applications, allowing businesses to run critical workloads and applications. IBM i, formerly known as iSeries, is an operating system developed by IBM for its line of IBM i Power Systems servers.

Monitoring 264

Monitoring Infrastructure Metrics Operating System 264

Dynatrace

MAY 23, 2022

As a result, organizations are weighing microservices vs. monolithic architecture to improve software delivery speed and quality. As developers move to microservice-centric designs, components are broken into independent services to be developed, deployed, and maintained separately. Consider the following: Teams want service speed.

Architecture 263

Architecture DevOps Monitoring Programming 263

Scalegrid

FEBRUARY 6, 2025

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. Kafka is optimized for high-throughput event streaming , excelling in real-time analytics and large-scale data ingestion.

Latency 147

Latency Analytics Architecture Storage 147

The Netflix TechBlog

JULY 15, 2021

In this post, Kevin talks about his extensive experience in content analytics at Netflix since joining more than 10 years ago. What keeps me engaged and enjoying data engineering is giving super-suits and adrenaline shots to analytics engineers and data scientists. What drew you to Netflix?

Data Engineering 193

Data Engineering Engineering Entertainment Big Data 193

Dynatrace

NOVEMBER 6, 2023

Digital transformation is only going to speed up, not slow down, and companies must remain on top of it. As we continue to evolve into an edge economy, it’s imperative that enterprise teams are evaluating and investing in solutions designed for innovation to proactively prepare for the next evolution.

Azure 244

Azure Technology Technology Cloud 244

Dynatrace

JANUARY 31, 2024

Data observability is crucial to analytics and automation, as business decisions and actions depend on data quality. At its core, data observability is about ensuring the availability, reliability, and quality of data. Keeping track of the field count in a new metric (data.observability.fields) using Workflows and Typescript.

DevOps 272

DevOps Analytics Airlines Metrics 272

Dynatrace

OCTOBER 16, 2024

Our latest enhancements to the Dynatrace Dashboards and Notebooks apps make learning DQL optional in your day-to-day work, speeding up your troubleshooting and optimization tasks. This app provides advanced analytics, such as highlighting related surrounding traces and pinpointing the root cause, as illustrated in the example below.

Social Media 263

Social Media Metrics Network Analytics 263

Dynatrace

NOVEMBER 24, 2021

To help you speed up MTTR, there are several levels of visualization to help slice and dice through information: Instances. The Generic network device and the Cisco router extensions are designed to easily extend observability to all the basic and popular devices. And is that because of a spike in total requests? ”. Pool nodes.

Network 246

Network Infrastructure Virtualization Metrics 246

Dynatrace

JULY 5, 2022

As organizations look to speed their digital transformation efforts, automating time-consuming, manual tasks is critical for IT teams. Like the development and design phases, these applications generate massive data volumes that offer relevant and actionable insights. Dynatrace news. For example: Greater IT staff efficiency.

Artificial Intelligence 325

Artificial Intelligence Cloud Innovation Strategy 325

Dynatrace

NOVEMBER 2, 2022

This methodology combines software design, development, automation, operations, and analytics to boost customer experience, increase application security, and reduce downtime that affects business outcomes. Software development success no longer means just meeting project deadlines. The five elements of digital immunity.

Software 246

Software Software Artificial Intelligence DevOps 246

Dynatrace

MARCH 22, 2023

Insecure design This broad category refers to fundamental design flaws in the application caused by a failure to implement necessary security controls during the design stage. Use a safe development life cycle with secure design patterns and components. Apply threat modeling and plausibility checks.

Open Source 246

Open Source Artificial Intelligence Internet Internet 246

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. And the ability to easily create custom apps enables teams to do any analytics at any time for any use case.

Performance 246

Performance DevOps Innovation Energy 246

Jos

JUNE 2, 2018

At the same time, they open a door to lots of concepts that might be overwhelming: PRPL, RAIL, Paint Timing API, TTI, HTTP/2, Speed Index, Priority Hints and more … Why Performance doesn’t get Prioritized Web performance at organizations is a real challenge. Ideally, shoot for 30% speed improvements. A screenshot of Lighthouse 3.0,

Performance 237

Performance Speed Google Media 237

Dynatrace

DECEMBER 20, 2021

Improved analytic context. While data analysis tools such as Google Analytics provide statistics based on user experiences, they lack details about what the user is doing and experiencing. Conversely, if users encounter functional issues or poor UI design that frustrate common actions, replays provide clear evidence.

Mobile 264

Mobile Website Analytics Cache 264

Dynatrace

JANUARY 19, 2022

Still, while DevOps and DevSecOps practices enable development agility and speed, they can also fall victim to tool complexity and data silos. Successful DevOps orchestration is a constant evolution of tools, processes, and communication on a journey to speed, stability, and scale. AIOps solution. But not all AI is created equal.

Artificial Intelligence 245

Artificial Intelligence DevOps Performance Games 245

Dynatrace

OCTOBER 25, 2022

NoOps is an advanced transformation of DevOps where many of the functions needed to manage, optimize and secure IT services and applications are automated within the design. Competing in a digital ecosystem means delivering products and services at speed and at scale. Thus, the concept of NoOps takes DevOps a step further.

DevOps 246

DevOps Big Data Cloud Innovation 246

Dynatrace

DECEMBER 15, 2022

ITOps refers to the process of acquiring, designing, deploying, configuring, and maintaining equipment and services that support an organization’s desired business outcomes. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. Reliability. Performance. What does IT operations do?

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

OCTOBER 5, 2022

Implementing a well-designed vulnerability management practice throughout all stages of the software development lifecycle (SDLC) can provide an organization’s development team with significant benefits. Vulnerability management. How a unified software intelligence platform delivers on cybersecurity best practices and DevSecOps productivity.

Best Practices 246

Best Practices Education Monitoring Government 246

DZone

JULY 17, 2023

Apache Spark is a leading platform in the field of big data processing, known for its speed, versatility, and ease of use. Understanding Apache Spark Apache Spark is a unified computing engine designed for large-scale data processing. However, getting the most out of Spark often involves fine-tuning and optimization.

Big Data 130

Big Data Performance Open Source Tuning 130

Dynatrace

MAY 23, 2024

Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively. We designed experimental scenarios inspired by chaos engineering. Fault tolerance stands as a critical requirement for continuously operating production systems.

Engineering 245

Engineering Tuning Latency Open Source 245

Smashing Magazine

DECEMBER 17, 2020

Search engine optimization (SEO) is an essential part of a website’s design, and one all too often overlooked. Implementing SEO best practice doesn’t just give you the best chance possible of ranking well in search engines; it makes your websites better by scrutinizing quality, design, accessibility, and speed, among other things.

Engineering 135

Engineering Google Website Mobile 135

Dynatrace

FEBRUARY 2, 2022

To avoid this, start the SLO discussion early in the design process. Simply performing eyeball analytics by looking at multiple dashboards slows down the quality evaluation process and introduces a higher risk of failures. Push for SLO evaluation to be incorporated into the CI/CD pipeline and not just in production.

DevOps 246

DevOps Metrics Best Practices Latency 246

Dynatrace

SEPTEMBER 20, 2019

Welcome back to the blog series in which we show how you can easily solve three common problem scenarios by using Dynatrace and xMatters Flow Designer. In doing so, they automate build processes to speed up delivery, and minimize human involvement to prevent error. Step 6 — Flow Designer rolls back through keptn. Dynatrace news.

Systems 38

Systems Traffic DevOps Database 38