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

Dynatrace

SEPTEMBER 5, 2023

Technology and operations teams work to ensure that applications and digital systems work seamlessly and securely. Predictive AI uses statistical algorithms and other advanced machine learning techniques to anticipate what might happen next in a system. Predictive analytics can anticipate potential failures and security breaches.

Artificial Intelligence 266

Artificial Intelligence DevOps Analytics Engineering 266

Dynatrace

AUGUST 9, 2023

In this blog post, we’ll use Dynatrace Security Analytics to go threat hunting, bringing together logs, traces, metrics, and, crucially, threat alerts. However, our customers often want to augment the data Dynatrace provides with data from third-party tools.

Analytics 201

Analytics AWS Strategy Infrastructure 201

DZone

JUNE 7, 2023

ERP systems are crucial in modern software development because they integrate various organizational departments and functions. They provide a centralized platform that promotes seamless communication and data exchange between software applications, reducing data silos.

Systems 169

Systems Software Software Development 169

Dynatrace

FEBRUARY 2, 2023

Should business data be part of your observability solution? Technology and business leaders express increasing interest in integrating business data into their IT observability strategies, citing the value of effective collaboration between business and IT.

Analytics 206

Analytics Metrics DevOps Storage 206

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 186

Analytics Storage Retail Monitoring 186

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 264

Data Engineering Engineering Processing Games 264

DZone

FEBRUARY 1, 2023

Built on Azure Blob Storage, Azure Data Lake Storage Gen2 is a suite of features for big data analytics. Azure Data Lake Storage Gen1 and Azure Blob Storage's capabilities are combined in Data Lake Storage Gen2. For instance, Data Lake Storage Gen2 offers scale, file-level security, and file system semantics.

Azure 243

Azure Storage Big Data Analytics 243

Dynatrace

JUNE 9, 2023

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. All of these factors challenge DevOps maturity.

DevOps 188

DevOps Analytics Storage Metrics 188

Dynatrace

SEPTEMBER 1, 2022

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

Analytics 180

Analytics Ecommerce Metrics Innovation 180

Dynatrace

SEPTEMBER 8, 2022

Log management is an organization’s rules and policies for managing and enabling the creation, transmission, analysis, storage, and other tasks related to IT systems’ and applications’ log data. In cloud-native environments, there can also be dozens of additional services and functions all generating data from user-driven events.

Systems 189

Systems Cloud Analytics DevOps 189

DZone

JUNE 6, 2023

This can include the use of cloud computing, artificial intelligence, big data analytics, the Internet of Things (IoT), and other digital tools. One of the significant challenges that come with digital transformation is ensuring that software systems remain reliable and secure. This is where software testing comes in.

Artificial Intelligence 130

Artificial Intelligence Systems IoT Testing 130

Dynatrace

MAY 2, 2024

Across the globe, privacy laws grant individuals data subject rights, such as the right to access and delete personal data processed about them. Successful compliance with privacy rights requests involves tracking and verifying requests across the entire data ecosystem, including third-party services.

Tuning 132

Tuning Scalability Efficiency Processing 132

DZone

JANUARY 13, 2023

In this tutorial, you are going to learn about QuestDB SQL extensions which prove to be very useful with time-series data. Using some sample data sets, you will learn how designated timestamps work and how to use extended SQL syntax to write queries on time-series data.

IoT 174

IoT Analytics Database Metrics 174

Dynatrace

APRIL 13, 2023

The massive volumes of log data associated with a breach have made cybersecurity forensics a complicated, costly problem to solve. As organizations adopt more cloud-native technologies, observability data—telemetry from applications and infrastructure, including logs, metrics, and traces—and security data are converging.

Analytics 190

Analytics Java Infrastructure Cloud 190

Dynatrace

JANUARY 23, 2024

AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

Performance 191

Performance DevOps Innovation Artificial Intelligence 191

The Netflix TechBlog

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer on the Product Data Science and Engineering team.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

The Netflix TechBlog

JANUARY 13, 2022

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. As our subscribers grow worldwide and Netflix enters the world of gaming , the number of batch workflows and real-time data pipelines increases rapidly.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

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. Data indicates these technology trends have taken hold.

Technology 208

Technology Technology Artificial Intelligence Analytics 208

Dynatrace

MARCH 20, 2024

Application security monitoring is the practice of monitoring and analyzing applications or software systems to detect vulnerabilities, identify threats, and mitigate attacks. These could include issues with vulnerable and outdated components, injections, and software and data integrity failures.

Monitoring 217

Monitoring Analytics Traffic Best Practices 217

Dynatrace

APRIL 8, 2024

If system failures occur, teams must resolve them quickly and resolutely. Maximizing a strong foundation of IT infrastructure performance and security means effectively utilizing all the data that these systems produce to drive risk management processes and decision-making.

Analytics 206

Analytics Infrastructure Efficiency Technology 206

Dynatrace

JUNE 26, 2023

In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. We also discuss the role of AI for IT operations (AIOps) and more.

Software 192

Software Software Analytics Big Data 192

Dynatrace

MARCH 29, 2024

Dynatrace offers essential analytics and automation to keep applications optimized and businesses flourishing. By seamlessly integrating observability, AI-driven insights, and data analytics, organizations can overcome common obstacles such as operational inefficiencies, performance bottlenecks, and scalability concerns.

Google 266

Google Innovation Cloud Analytics 266

Dynatrace

OCTOBER 7, 2020

Dynatrace recently opened up the enterprise-grade functionalities of Dynatrace OneAgent to all the data needed for observability, including metrics, events, logs, traces, and topology data. Ingest data via OneAgent rather than our REST API. Dynatrace news. curl -d " batchjobs.execution.fails,jobname=payslip 1 " [link].

Metrics 246

Metrics Analytics Storage Monitoring 246

Dynatrace

DECEMBER 5, 2023

Streamline privacy requirements with flexible retention periods Data retention is a critical aspect of data handling, and it’s not just about privacy compliance—it’s about having the flexibility to optimize data storage times in Grail for your Dynatrace use cases. Grail buckets function like folders in a file system.

Storage 170

Storage Healthcare Best Practices Speed 170

Dynatrace

DECEMBER 21, 2023

Make better decisions by providing managers with real-time data about the business. In fact, most business processes still rely on multiple systems, long ago outgrowing the capabilities of built-in platform-centric monitoring. Code changes are often required to expose important business data, delaying implementation.

Processing 218

Processing Monitoring Retail Analytics 218

DZone

JUNE 5, 2023

Cybercrime is big business; hackers are breaking into systems and stealing data using ever-more-advanced methods. AI can assist in identifying new threats as they emerge in real-time and even foresee future assaults before they happen by employing machine learning algorithms and predictive analytics.

Artificial Intelligence 300

Artificial Intelligence Analytics Network Technology 300

Dynatrace

MARCH 6, 2024

IBM i, formerly known as iSeries, is an operating system developed by IBM for its line of IBM i Power Systems servers. It is based on the IBM AS/400 system and is known for its reliability, scalability, and security features. Some tools demand the installation of agents on those systems and provide complex, disconnected views.

Monitoring 240

Monitoring Infrastructure Metrics Analytics 240

Dynatrace

FEBRUARY 12, 2024

The OMB memo states that agencies must meet specific goals based on the five pillars of the Cybersecurity and Infrastructure Security Agency (CISA) Zero Trust Maturity Model : identity, devices, networks, applications/workloads, and data. A quick refresher: what is zero trust?

Government 184

Government Analytics Network Traffic 184

Dynatrace

JANUARY 9, 2024

public sector, always-on, fully optimized systems are imperative to safeguard our nation’s security. Disruptions to mission-critical applications affect citizen services, including healthcare, utility grids, and transportation systems. public sector systems and data. For the U.S.

Government 174

Government Healthcare Transportation Education 174

Dynatrace

FEBRUARY 10, 2023

Data proliferation—as well as a growing need for data analysis—has accelerated. According to recent Dynatrace data, 59% of CIOs say the increasing complexity of their technology stack could soon overload their teams without a more automated approach to IT operations. Digital transformation shows no signs of slowing down.

Efficiency 281

Efficiency Performance Analytics DevOps 281

Dynatrace

FEBRUARY 28, 2024

In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices.

Analytics 215

Analytics Metrics Media Monitoring 215

DZone

MAY 19, 2023

Logs often take up the majority of a company's data assets. On the one hand, they provide system risk alerts and help engineers quickly locate root causes in troubleshooting. Examples of logs include business logs (such as user activity logs) and Operation and Maintenance logs of servers, databases, and network or IoT devices.

IoT 130

IoT Analytics Network Database 130

DZone

SEPTEMBER 26, 2023

If your environment is like many others, it can often seem like your systems produce logs filled with a bunch of excess data. If you don’t have the right tools, it can feel like you’re stuck with a bunch of disparate, hard-to-parse data. Though it can feel like more trouble than it’s worth, sorting through logs is crucial.

Best Practices 249

Best Practices Analytics Infrastructure Network 249

Scalegrid

JANUARY 8, 2024

The partnership between AI and cloud computing brings about transformative trends like enhanced security through intelligent threat detection, real-time analytics, personalization, and the implementation of edge computing for quicker on-site decision-making.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

OCTOBER 14, 2022

Log data provides a unique source of truth for debugging applications, optimizing infrastructure, and investigating security incidents. This contextualization of log data enables AI-powered problem detection and root cause analysis at scale. Dynamic landscape and data handling requirements result in manual work.

Storage 232

Storage Government Network Infrastructure 232

Dynatrace

APRIL 18, 2024

Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior. For example, an observability solution can track and analyze usage data to help engineers understand how and when to scale resources based on system demand.

DevOps 184

DevOps Engineering Artificial Intelligence Infrastructure 184