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 223

Analytics Metrics Media Monitoring 223

Dynatrace

APRIL 5, 2024

GigaOm recently released its 2024 Radar Report for Cloud Observability, which includes 21 observability solution providers and analyzes each on their current and emerging features. This enables companies to ingest, analyze, and retain massive quantities of data with powerful analytics and AI-powered answers.

Cloud 249

Cloud Analytics Monitoring Scalability 249

Dynatrace

NOVEMBER 18, 2021

Cloud-native observability is a prerequisite for companies that need to meet these expectations. With PurePath ® distributed tracing and analysis technology at the code level, Dynatrace already provides the deepest possible insights into every transaction. The example below includes analysis of a payment issue. Dynatrace news.

Analytics 234

Analytics Cloud Java Serverless 234

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 257

Best Practices Analytics Artificial Intelligence Infrastructure 257

Dynatrace

FEBRUARY 15, 2023

Exploratory analytics is an essential capability for organizations to discover the stories hiding in their data. Visual data analytics with collaborative input from IT, development, security, and business teams makes those stories reveal themselves and helps teams immediately understand—and act on—their business impact.

Analytics 130

Analytics Government Media C++ 130

Dynatrace

JANUARY 17, 2023

Second, embracing the complexity of OpenTelemetry signal collection must come with a guaranteed payoff: gaining analytical insights and causal relationships that improve business performance. This example is a good starting point for exploratory analysis with context-aware Dynatrace Davis insights. What’s ahead in 2023.

Analytics 293

Analytics Metrics Open Source Java 293

Dynatrace

MARCH 6, 2024

The latest Dynatrace report, “ The state of observability 2024: Overcoming complexity through AI-driven analytics and automation ,” explores these challenges and highlights how IT, business, and security teams can overcome them with a mature AI, analytics, and automation strategy.

Analytics 204

Analytics Innovation Strategy Storage 204

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. The ripple effect of increased risk compounds the problem. To begin, St.

Analytics 195

Analytics Engineering Cloud Traffic 195

Dynatrace

AUGUST 9, 2023

A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. With the rising complexity of cloud-native environments, manual investigation and response are too slow and inaccurate. But this limited approach causes challenges in today’s hybrid multicloud reality.

Analytics 230

Analytics Metrics Database Storage 230

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. A visual representation of what Davis uses for its own analysis. An overview of the Dynatrace unified observability and security platform.

Analytics 194

Analytics Artificial Intelligence Engineering Technology 194

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. As cloud complexity grows, it brings more volume, velocity, and variety of log data. Managing this change is difficult.

Cloud 263

Cloud Lambda AWS Analytics 263

Dynatrace

NOVEMBER 6, 2023

Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. As digital transformation accelerates and more organizations are migrating workloads to Azure and other cloud environments, they need observability and data analytics capabilities that can keep pace.

Azure 192

Azure Analytics Artificial Intelligence Innovation 192

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. Traditional log analysis evaluates logs and enables organizations to mitigate myriad risks and meet compliance regulations. Grail enables 100% precision insights into all stored data.

Analytics 201

Analytics Infrastructure Storage Architecture 201

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. This is also known as root-cause analysis. What are the use cases for log analytics? Peak performance analysis. Dynatrace news.

Analytics 227

Analytics Storage Retail DevOps 227

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. “Logging” is the practice of generating and storing logs for later analysis. What is log analytics? Dynatrace news.

Analytics 222

Analytics Monitoring Artificial Intelligence DevOps 222

Dynatrace

JANUARY 23, 2024

Companies now recognize that technologies such as AI and cloud services have become mandatory to compete successfully. AI data analysis can help development teams release software faster and at higher quality. In what follows, we explore these key cloud observability trends in 2024.

Performance 199

Performance DevOps Innovation Artificial Intelligence 199

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

JULY 29, 2021

Today’s digital businesses run on heterogeneous and highly dynamic architectures with interconnected applications and microservices deployed via Kubernetes and other cloud-native platforms. All this data is then consumed by Dynatrace Davis® AI for more precise answers, thereby driving AIOps for cloud-native environments.

Analytics 246

Analytics Open Source Serverless Architecture 246

Dynatrace

FEBRUARY 15, 2023

As organizations adopt more cloud-based technologies, the increased volume and variety of data from these ecosystems drive complexity. To tame this complexity and optimize cloud operations, teams across the organization need to manage and explore their data effectively. Here are some examples: IT infrastructure and operations.

Analytics 130

Analytics Storage Cloud DevOps 130

Dynatrace

NOVEMBER 20, 2024

As organizations adopt more cloud-native technologies, the risk—and consequences—of cyberattacks are also increasing. The Dynatrace platform has been recognized for seamlessly integrating with the Microsoft Sentinel cloud-native security information and event management ( SIEM ) solution. Audit logs.

Best Practices 275

Best Practices Innovation Azure Cloud 275

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. This is also known as root-cause analysis. What are the use cases for log analytics? Peak performance analysis. Dynatrace news.

Analytics 194

Analytics Storage Retail DevOps 194

Dynatrace

SEPTEMBER 5, 2024

The more data ingestion channels you provide to the Dynatrace Davis® AI engine, the more comprehensive Dynatrace automated root cause analysis becomes. Seamless integration with AWS Firehose Dynatrace is also enhancing our observability logs offerings for AWS services for cloud-native applications.

Innovation 273

Innovation AWS Analytics Storage 273

Dynatrace

OCTOBER 4, 2022

Much of the software developed today is cloud native. However, cloud infrastructure has become increasingly complex. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. The next frontier: Data and analytics-centric software intelligence. Real-time anomaly detection.

Analytics 204

Analytics Software Software Storage 204

Dynatrace

JANUARY 4, 2024

But while OpenTelemetry solves the problem of standardizing data instrumentation, the complexity and scale of cloud-native tools and environments mean that organizations still struggle with OpenTelemetry service observability. OpenTelemetry is also useful for getting a handle on all the third-party libraries and services an organization uses.

Metrics 178

Metrics Open Source Tuning Infrastructure 178

Dynatrace

FEBRUARY 1, 2024

Multicloud strategy: Balancing potential with complexity in modern IT ecosystems In the ever-changing digital world, cloud technologies are crucial in driving business innovation and adaptability. While cloud deployments offer benefits, they also pose management challenges—especially in multicloud strategies that use various cloud providers.

Cloud 218

Cloud Strategy Metrics Government 218

Dynatrace

FEBRUARY 2, 2023

Exploding volumes of business data promise great potential; real-time business insights and exploratory analytics can support agile investment decisions and automation driven by a shared view of measurable business goals. Traditional observability solutions don’t capture or analyze application payloads. What’s next?

Analytics 215

Analytics Metrics DevOps Storage 215

Scalegrid

JANUARY 8, 2024

Exploring artificial intelligence in cloud computing reveals a game-changing synergy. This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

JUNE 27, 2023

Logs complement metrics and enable automation Cloud practitioners agree that observability, security, and automation go hand in hand. The increasing complexity of cloud service architectures requires a rock-solid understanding of the activity, health status, and security of cloud services.

AWS 212

AWS Cloud Lambda Analytics 212

Dynatrace

FEBRUARY 16, 2023

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. Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. Kubernetes makes spans longer,” Ortner explains.

Analytics 199

Analytics Innovation Metrics Database 199

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.

Cloud 196

Cloud Systems Analytics DevOps 196

Dynatrace

JUNE 15, 2023

Cloud application security is becoming more of a critical issue as cloud-based applications gain popularity. The cloud allows a modular approach to building applications, enabling development and operations teams to create and deploy feature-rich apps very quickly. What is cloud application security?

Cloud 189

Cloud Open Source Architecture Monitoring 189

Dynatrace

NOVEMBER 17, 2020

New cloud-native technologies make observability more important than ever…. Dynatrace PurePath 4 extends automatic distributed tracing to OpenTelemetry and the latest cloud-native technologies. Automatic topology analysis. Technical complexity has shifted from the actual code to the interdependencies between services.

Analytics 164

Analytics Technology Technology Cloud 164

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. Customers also want to carry out their own analysis tailored to specific use cases and forensic needs. Ingest those Falco events into Dynatrace Grail using  falcosidekick.

Analytics 209

Analytics AWS Infrastructure Strategy 209

Dynatrace

OCTOBER 3, 2024

And when outages do occur, Dynatrace AI-powered, automatic root-cause analysis can also help them to remediate issues as quickly as possible. Hypermodal AI fuels automatic root-cause analysis to pinpoint the culprit amongst millions of service interdependencies and lines of code faster than humans can grasp.

Availability 236

Availability DevOps Analytics Cloud 236

Dynatrace

SEPTEMBER 21, 2023

Energy efficiency is a key reason why organizations are migrating workloads from energy-intensive on-premises environments to more efficient cloud platforms. But while moving workloads to the cloud brings overall carbon emissions down, the cloud computing carbon footprint itself is growing. Certainly, this is true for us.

Energy 246

Energy Cloud Airlines Strategy 246

Dynatrace

SEPTEMBER 14, 2022

Does that mean that reactive and exploratory data analysis, often done manually and with the help of dashboards, are dead? We believe that the two worlds of automated (AIOps) and manual (dashboards) data analytics are complementary rather than contradictory. Why today’s data analytics solutions still fail us.

Metrics 242

Metrics Analytics Monitoring Efficiency 242

Dynatrace

APRIL 19, 2024

Automate disk resizing operations with Davis AI predictive analytics The Dynatrace Site Reliability Engineering (SRE) team was looking for a way to automatically adjust disk space for cloud volumes on a regular basis to avoid over- or under-provisioning them. Figure 3: Funnel analysis implemented by selecting a custom user journey.

AWS 234

AWS Analytics Cloud Monitoring 234