Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Logs can include data about user inputs, system processes, and hardware states. What is log analytics? Log monitoring vs log analytics.

Analytics 264

Analytics Monitoring DevOps Artificial Intelligence 264

Dynatrace

OCTOBER 4, 2022

IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. With a data and analytics approach that focuses on performance without sacrificing cost, IT pros can gain access to answers that indicate precisely which service just went down and the root cause.

Analytics 246

Analytics Software Software Storage 246

Dynatrace

FEBRUARY 28, 2024

Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices. The next challenge is harnessing additional AI techniques to make exploratory data analytics even easier. Discovery using global search.

Analytics 246

Analytics Metrics Media Monitoring 246

Dynatrace

SEPTEMBER 1, 2022

Business analytics is a growing science that’s rising to meet the demands of data-driven decision making within enterprises. But what is business analytics exactly, and how can you feed it with reliable data that ties IT metrics to business outcomes? What is business analytics? Why business analytics matter.

Analytics 245

Analytics Ecommerce Metrics Innovation 245

Dynatrace

JULY 29, 2022

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 246

Analytics Storage Retail DevOps 246

Dynatrace

JULY 29, 2022

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 245

Analytics Storage Retail DevOps 245

Dynatrace

FEBRUARY 14, 2022

Mobile app monitoring and mobile analytics make this possible. By providing insight into how apps are operating and why they crash, mobile analytics lets you know what’s happening with your apps and what steps you can take to solve potential problems. What is mobile analytics? Why use mobile analytics and app monitoring?

Mobile 245

Mobile Analytics Monitoring Best Practices 245

Dynatrace

FEBRUARY 16, 2023

The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity.

Analytics 246

Analytics Innovation Metrics Database 246

Dynatrace

FEBRUARY 12, 2024

With unified observability and security, organizations can protect their data and avoid tool sprawl with a single platform that delivers AI-driven analytics and intelligent automation. Grail handles data storage, data management, and processes data at massive speed, scale, and cost efficiency,” Singh said. This is Davis CoPilot.

Analytics 245

Analytics Artificial Intelligence Engineering Technology 245

Dynatrace

AUGUST 9, 2023

A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. Security Analytics and automation deal with unknown-unknowns With Security Analytics, analysts can explore the unknown-unknowns, facilitating queries manually in an ad hoc way, or continuously using automation.

Analytics 246

Analytics Metrics Database Storage 246

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. What is Apache Kafka?

Latency 147

Latency Analytics Architecture Storage 147

The Netflix TechBlog

FEBRUARY 14, 2025

It requires a state-of-the-art system that can track and process these impressions while maintaining a detailed history of each profiles exposure. In this multi-part blog series, we take you behind the scenes of our system that processes billions of impressions daily.

Tuning 165

Tuning Latency Efficiency Storage 165

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. Kickstarting the dashboard creation process is, however, just one advantage of ready-made dashboards.

Social Media 263

Social Media Metrics Network Analytics 263

Dynatrace

JUNE 28, 2022

Mobile analytics can help organizations optimize their mobile application performance, earning customer accolades and increasing revenue in the process. Learn how one Dynatrace customer leveraged mobile analytics to ensure a crash-free, five-star mobile application. Here’s the approach they chose.

Mobile 246

Mobile Analytics Best Practices Software Engineering 246

Scalegrid

MAY 13, 2020

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. 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. What Exactly is Greenplum? At a glance – TLDR.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

OCTOBER 12, 2023

The best thing: the whole process is performed on read when the query is executed, which means you have full flexibility and don’t need to define a structure when ingesting data. >> It helps create patterns, provides instant feedback, and allows you to save and reuse DPL patterns, for faster access to data analytics use cases.

Speed 235

Speed AWS C++ Availability 235

Dynatrace

FEBRUARY 10, 2023

In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics. From data lakehouse to an analytics platform Traditionally, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

Efficiency 306

Efficiency Performance Analytics DevOps 306

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. Ingest and process with Grail. Retain data.

Artificial Intelligence 290

Artificial Intelligence Analytics Storage Architecture 290

DZone

NOVEMBER 25, 2023

Factors like read and write speed, latency, and data distribution methods are essential. For instance, rapid read and write operations are crucial for applications requiring real-time data analytics. Yet, they are often evaluated in isolation, removed from the business context.

Database 278

Database Latency Speed Metrics 278

DZone

SEPTEMBER 18, 2023

The demand for faster, more reliable, and efficient testing processes has grown exponentially with the increasing complexity of modern applications. To address these challenges, AI has emerged as a game-changing force, revolutionizing the field of automated software testing.

Artificial Intelligence 279

Artificial Intelligence Software Software Testing 279

Dynatrace

OCTOBER 4, 2022

These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues. Each process could generate multiple log entries, adding up to terabytes of data every day. A modern approach to log analytics stores data without indexing.

Analytics 264

Analytics Storage Infrastructure Metrics 264

Dynatrace

FEBRUARY 13, 2020

We’re able to help drive speed, take multiple data sources, bring them into a common model and drive those answers at scale.”. Ability to create custom metrics and events from log data, extending Dynatrace observability to any application, script or process. We’ve seen a doubling of Kubernetes usage in the past six months,” Steve said.

Performance 278

Performance Mobile Analytics Innovation 278

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. However, organizations must structure and store data inputs in a specific format to enable extract, transform, and load processes, and efficiently query this data. Data management.

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

Dynatrace

OCTOBER 15, 2020

The scale and speed of the program triggered challenges for these banks that they had never before imagined. Speed up loan processing to deliver critically needed relief to small businesses? Full speed ahead. Let your Dynatrace Sales Engineer know you want to get started with Digital Business Analytics.

Small Business 264

Small Business Programming Analytics Speed 264

The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Processing 214

Processing Big Data Efficiency Engineering 214

DZone

NOVEMBER 20, 2023

ETL—Extract, Transform, Load—is far more than a set of operations; it's a complex dance that transforms raw data into valuable insights, serving as the critical backbone for a range of applications, from data analytics and business intelligence to real-time decision-making platforms. It’s a multidimensional answer that goes beyond speed.

Processing 124

Processing Performance Analytics Speed 124

Dynatrace

JUNE 26, 2023

This, in turn, accelerates the need for businesses to implement the practice of software automation to improve and streamline processes. In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? What is software automation?

Software 246

Software Software Analytics Big Data 246

Dynatrace

OCTOBER 4, 2024

Today, development teams suffer from a lack of automation for time-consuming tasks, the absence of standardization due to an overabundance of tool options, and insufficiently mature DevSecOps processes. This process begins when the developer merges a code change and ends when it is running in a production environment.

Software 278

Software Software Development Performance 278

Dynatrace

APRIL 8, 2024

Deploy risk-based estimates and models with confidence, accuracy, transparency, and speed. Optimize the IT infrastructure supporting risk management processes and controls for maximum performance and resilience. The IT infrastructure, services, and applications that enable processes for risk management must perform optimally.

Analytics 246

Analytics Infrastructure Efficiency Technology 246

Dynatrace

JULY 2, 2024

Log collection platforms, such as Fluent Bit, give organizations a much-needed solution for quickly gathering and processing log data to make it available in different backends for further analytics. Speed up your troubleshooting processes Log analysis is typically the first step in the troubleshooting process.

Open Source 264

Open Source Analytics Cloud Innovation 264

Dynatrace

FEBRUARY 23, 2022

In order for software development teams to balance speed with quality during the software development cycle (SDLC), development, security, and operations teams (or DevSecOps teams) need to ensure that their practices align with modern cloud environments. That can be difficult when the business climate can prioritize speed.

Serverless 312

Serverless Infrastructure Innovation DevOps 312

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. “At one point, we saw a process that was causing a lot of CPU contention.

Cloud 243

Cloud Ecommerce Performance Retail 243

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 2, 2021

But without complex analytics to make sense of them in context, metrics are often too raw to be useful on their own. To achieve relevant insights, raw metrics typically need to be processed through filtering, aggregation, or arithmetic operations. As objective measurements, they allow us to make data-driven decisions.

Metrics 246

Metrics Analytics Google Code 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 19, 2023

Using vulnerability management, DevSecOps automation, and attack detection and blocking in your application security process can proactively improve your organization’s overall security posture. Vulnerability management Vulnerability management is the process of identifying, prioritizing, rectifying, and reporting software vulnerabilities.

Best Practices 264

Best Practices Benchmarking Speed Infrastructure 264

Dynatrace

JULY 29, 2024

Our guide covers AI for effective DevSecOps, converging observability and security, and cybersecurity analytics for threat detection and response. AI significantly accelerates DevSecOps by processing vast amounts of data to identify and classify potential threats, leading to proactive threat detection and response.

Analytics 245

Analytics Government DevOps Efficiency 245