Dynatrace

OCTOBER 30, 2023

The growing challenge in modern IT environments is the exponential increase in log telemetry data, driven by the expansion of cloud-native, geographically distributed, container- and microservice-based architectures. Organizations need a more proactive approach to log management to tame this proliferation of cloud data.

Best Practices 256

Best Practices Analytics Artificial Intelligence Infrastructure 256

DZone

FEBRUARY 5, 2024

In today's cloud computing world, all types of logging data are extremely valuable. Logs can include a wide variety of data, including system events, transaction data, user activities, web browser logs, errors, and performance metrics. This innovative service is transforming the way organizations handle their log data.

Analytics 278

Analytics Innovation Strategy Efficiency 278

DZone

SEPTEMBER 14, 2023

In today's data-driven world, efficient data processing plays a pivotal role in the success of any project. Apache Spark , a robust open-source data processing framework, has emerged as a game-changer in this domain.

Big Data 279

Big Data Processing Open Source Games 279

Dynatrace

JANUARY 17, 2023

OpenTelemetry signals are often analyzed in data silos with missing context and relationships between the data and underlying topology. This leads to significant time wasted in connecting data with application workloads by manually applying labels, or by building crosslinks between the dashboards of incompatible tools.

Analytics 293

Analytics Metrics Open Source Java 293

Dynatrace

MAY 1, 2023

With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.

Analytics 201

Analytics Artificial Intelligence Big Data Open Source 201

Dynatrace

OCTOBER 4, 2022

Software and data are a company’s competitive advantage. As a result, organizations need software to work perfectly to create customer experiences, deliver innovation, and generate operational efficiency. But for software to work perfectly, organizations need to use data to optimize every phase of the software lifecycle.

Analytics 204

Analytics Software Software Storage 204

Dynatrace

OCTOBER 4, 2022

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. But on their own, logs present just another data silo as IT professionals attempt to troubleshoot and remediate problems. Data volume explosion in multicloud environments poses log issues.

Analytics 234

Analytics Storage Infrastructure Metrics 234

Dynatrace

NOVEMBER 6, 2023

Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. requires Azure observability Data has become a pivotal asset in the current IT landscape, and AI has unequivocally become the linchpin for differentiation. Digital transformation 2.0

Azure 191

Azure Analytics Artificial Intelligence Innovation 191

Dynatrace

JANUARY 31, 2024

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. However, there are many obstacles and limitations along the way to becoming a data-driven organization. Understanding the context.

Analytics 203

Analytics Processing Transportation Storage 203

DZone

JULY 14, 2021

Authors: Ruoxi Sun (Tech Lead of Analytical Computing Team at PingCAP). TiDB is a Hybrid Transaction/Analytical Processing (HTAP) database that can efficiently process analytical queries. Fei Xu (Software Engineer at PingCAP).

Analytics 223

Analytics Software Engineering Performance Database 223

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 246

Analytics Artificial Intelligence Storage Serverless 246

Dynatrace

OCTOBER 4, 2022

Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Work with different and independent data types. Thus, Grail was born.

Artificial Intelligence 278

Artificial Intelligence Analytics Storage Architecture 278

Dynatrace

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 198

Analytics Innovation Metrics Database 198

Dynatrace

APRIL 22, 2024

In trans-Atlantic and global business relationships, the privacy frameworks and regulations in various regions must be aligned to allow efficient collaboration between enterprises and other involved institutions. To enable participating organizations to meet the EU requirements for transferring personal data to the U.S., What’s next?

Government 237

Government Programming Analytics Efficiency 237

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 226

Analytics Storage Retail Monitoring 226

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 222

Analytics Monitoring Artificial Intelligence DevOps 222

Dynatrace

MARCH 6, 2024

They create an explosion of data that is extremely challenging to manually capture, analyze, and act on. Fragmented monitoring and analytics can’t keep up The continued reliance on fragmented monitoring tools and manual analytics strategies is a particular pain point for IT and security teams.

Analytics 204

Analytics Innovation Strategy Storage 204

Dynatrace

DECEMBER 18, 2024

As cloud complexity increases and security concerns mount, organizations need log analytics to discover and investigate issues and gain critical business intelligence. But exploring the breadth of log analytics scenarios with most log vendors often results in unexpectedly high monthly log bills and aggressive year-over-year costs.

Analytics 155

Analytics Best Practices Efficiency Storage 155

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse?

Artificial Intelligence 221

Artificial Intelligence Storage Analytics Government 221

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. tactical) in nature.

Big Data 258

Big Data Government Processing Analytics 258

Dynatrace

MAY 3, 2024

Real-time streaming needs real-time analytics As enterprises move their workloads to cloud service providers like Amazon Web Services, the complexity of observing their workloads increases. Log data—the most verbose form of observability data, complementing other standardized signals like metrics and traces—is especially critical.

Cloud 263

Cloud Lambda AWS Analytics 263

The Netflix TechBlog

SEPTEMBER 18, 2024

Cassandra serves as the backbone for a diverse array of use cases within Netflix, ranging from user sign-ups and storing viewing histories to supporting real-time analytics and live streaming. Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns.

Latency 254

Latency Storage Cache Efficiency 254

Dynatrace

SEPTEMBER 5, 2023

Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. By analyzing patterns and trends, predictive analytics helps identify potential issues or opportunities, enabling proactive actions to prevent problems or capitalize on advantageous situations.

Artificial Intelligence 271

Artificial Intelligence DevOps Analytics Engineering 271

Dynatrace

NOVEMBER 4, 2024

There’s a goldmine of business data traversing your IT systems, yet most of it remains untapped. To unlock business value, the data must be: Accessible from anywhere. Data has value only when you can access it, no matter where it lies. Agile business decisions rely on fresh data. Easy to access. Contextualized.

Analytics 174

Analytics Airlines Metrics Monitoring 174

Dynatrace

DECEMBER 5, 2023

This growth was spurred by mobile ecosystems with Android and iOS operating systems, where ARM has a unique advantage in energy efficiency while offering high performance. Legacy data center infrastructure and software support have kept all the benefits of ARM at, well… arm’s length. For the simplest quickstart, select Show rules.

Efficiency 276

Efficiency Architecture Energy Monitoring 276

Dynatrace

SEPTEMBER 14, 2022

As an industry leader, Dynatrace promotes primarily using software and AI to deal with this complexity at scale instead of just putting data on dashboards. Does that mean that reactive and exploratory data analysis, often done manually and with the help of dashboards, are dead? Why today’s data analytics solutions still fail us.

Metrics 241

Metrics Analytics Monitoring Efficiency 241

DZone

AUGUST 23, 2023

Monitoring Time-Series IoT Device Data Time-series data is crucial for IoT device monitoring and data visualization in industries such as agriculture, renewable energy, and meteorology. In this tutorial, we will guide you through the process of setting up a monitoring system for IoT device data.

IoT 241

IoT Energy Open Source Analytics 241

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 254

Latency Storage Big Data Tuning 254

The Netflix TechBlog

SEPTEMBER 18, 2020

Part of our series on who works in Analytics at Netflix?—?and and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley.

Analytics 232

Analytics Education Innovation Engineering 232

The Netflix TechBlog

OCTOBER 8, 2024

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 242

Latency Storage Traffic Tuning 242

Dynatrace

FEBRUARY 16, 2024

The growing complexity of modern multicloud environments has created a pressing need to converge observability and security analytics. Security analytics is a discipline within IT security that focuses on proactive threat prevention using data analysis. Clair determined what log data was available to her.

Analytics 194

Analytics Engineering Cloud Traffic 194

Dynatrace

FEBRUARY 12, 2024

However, these environments can drown enterprises in data, forcing them to adopt multiple tools and services to manage and secure it. 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.

Analytics 193

Analytics Artificial Intelligence Engineering Technology 193

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 193

Analytics Storage Retail Monitoring 193

Dynatrace

NOVEMBER 29, 2024

Dynatrace continues to deliver on its commitment to keeping your data secure in the cloud. Enhancing data separation by partitioning each customer’s data on the storage level and encrypting it with a unique encryption key adds an additional layer of protection against unauthorized data access.

Storage 202

Storage AWS Azure Architecture 202

The Netflix TechBlog

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. What is late-arriving data? Let’s dive in!

Data Engineering 273

Data Engineering Engineering Processing Games 273

The Netflix TechBlog

JUNE 20, 2024

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

Data Engineering 209

Data Engineering Engineering Entertainment Software Engineering 209

Dynatrace

JANUARY 4, 2024

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical.

Government 212

Government Analytics Benchmarking Storage 212