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

SEPTEMBER 27, 2023

What is customer experience analytics: Fostering data-driven decision making In today’s customer-centric business landscape, understanding customer behavior and preferences is crucial for success. The data should cover both quantitative metrics (e.g., Embrace advanced analytics techniques to unlock deeper insights.

Best Practices 237

Best Practices Analytics Strategy Monitoring 237

Dynatrace

OCTOBER 30, 2023

By following key log analytics and log management best practices, teams can get more business value from their data. Challenges driving the need for log analytics and log management best practices As organizations undergo digital transformation and adopt more cloud computing techniques, data volume is proliferating.

Best Practices 254

Best Practices Analytics Artificial Intelligence Infrastructure 254

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 190

Analytics Artificial Intelligence Engineering Storage 190

Dynatrace

AUGUST 9, 2023

A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. As our experience with MOVEit shows, IoCs that remained hidden in logs alone quickly revealed themselves with observability runtime context data, such as metrics, traces, and spans.

Analytics 226

Analytics Metrics Database Storage 226

Dynatrace

FEBRUARY 15, 2023

Grail – the foundation of exploratory analytics Grail can already store and process log and business events. Now we’re adding Smartscape to DQL and two new data sources to Grail: Metrics on Grail and Traces on Grail. With Dynatrace and Smartscape for DQL, metrics are a completely different game.

Analytics 239

Analytics Social Media Metrics Efficiency 239

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. Davis topology-aware anomaly detection and alerting for your custom metrics. Seamlessly report and be alerted on topology-related custom metrics.

Metrics 246

Metrics Analytics Storage Monitoring 246

Dynatrace

SEPTEMBER 30, 2022

Leveraging business analytics tools helps ensure their experience is zero-friction–a critical facet of business success. How do business analytics tools work? IT teams have traditionally relied on internal metrics to estimate business impact. While analytics are one challenge, there remains another: silos.

Analytics 182

Analytics Best Practices Metrics IoT 182

Dynatrace

JANUARY 4, 2024

Great news: OpenTelemetry endpoint detection, analyzing OpenTelemetry services, and visualizing Istio service mesh metrics just got easier. As a CNCF open source incubating project, OpenTelemetry provides a standardized set of APIs, libraries, agents, instrumentation, and specifications for logging, metrics, and tracing.

Metrics 174

Metrics Open Source Tuning Infrastructure 174

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 196

Analytics Infrastructure Storage Efficiency 196

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 223

Analytics Storage Retail Monitoring 223

Dynatrace

FEBRUARY 16, 2023

The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says.

Analytics 195

Analytics Innovation Metrics Database 195

Dynatrace

JULY 29, 2021

The result is that IT teams must often contend with metrics, logs, and traces that aren’t relevant to organizational business objectives—their challenge is to translate such unstructured data into actionable business insights. Dynatrace extends its unique topology-based analytics and AIOps approach.

Analytics 246

Analytics Open Source Serverless Architecture 246

Dynatrace

OCTOBER 4, 2022

The only way to address these challenges is through observability data — logs, metrics, and traces. 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. Enter Grail-powered data and analytics.

Analytics 200

Analytics Software Software Storage 200

Dynatrace

DECEMBER 18, 2020

Agentless RUM, OpenKit, and Metric ingest to the rescue! Now we have performance and errors all covered: Business Analytics. What insights can we gain from usage metrics that we can feed-back to our product management teams? Digital Business Analytics can help answer those questions. App architecture. BizOpsConfigurator.

Analytics 137

Analytics Metrics IoT Monitoring 137

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 190

Analytics Storage Retail Monitoring 190

Dynatrace

MARCH 29, 2023

With this Google Cloud Ready integration, Dynatrace ensures that AlloyDB for PostgreSQL users can now ingest metrics along with existing Google Cloud data. The post Dynatrace announces support of Google Cloud’s AlloyDB for PostgreSQL metrics ingest appeared first on Dynatrace news.

Google 228

Google Metrics Cloud Analytics 228

Dynatrace

SEPTEMBER 1, 2022

Business analytics is a growing science that’s rising to meet the demands of data-driven decision making within enterprises. To measure service quality, IT teams monitor infrastructure, applications, and user experience metrics, which in turn often support service level objectives (SLO)s. What is business analytics?

Analytics 184

Analytics Ecommerce Metrics Innovation 184

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 218

Analytics Monitoring Artificial Intelligence DevOps 218

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 197

Analytics Artificial Intelligence Big Data Open Source 197

Dynatrace

DECEMBER 13, 2023

As a result, organizations need to monitor mobile app performance metrics that are meaningful and actionable by gaining adequate observability of mobile app performance. There are many common mobile app performance metrics that are used to measure key performance indicators (KPIs) related to user experience and satisfaction.

Best Practices 207

Best Practices Mobile Metrics Performance 207

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 238

Metrics Analytics Monitoring Efficiency 238

Dynatrace

JANUARY 31, 2024

With siloed data sources, heterogeneous data types—including metrics, traces, logs, user behavior, business events, vulnerabilities, threats, lifecycle events, and more—and increasing tool sprawl, it’s next to impossible to offer users real-time access to data in a unified, contextualized view. Understanding the context.

Analytics 201

Analytics Processing Transportation Storage 201

Dynatrace

NOVEMBER 18, 2021

Manual and configuration-heavy approaches to putting telemetry data into context and connecting metrics, traces, and logs simply don’t scale. With PurePath ® distributed tracing and analysis technology at the code level, Dynatrace already provides the deepest possible insights into every transaction. How to get started.

Analytics 231

Analytics Cloud Java Serverless 231

Dynatrace

FEBRUARY 15, 2023

Therefore, teams need a unified, intuitive approach to data aggregation and analysis. A modern observability and analytics platform brings data silos together and facilitates collaboration and better decision-making among teams.

Analytics 130

Analytics Storage Cloud DevOps 130

Dynatrace

JANUARY 11, 2023

To stay competitive in an increasingly digital landscape, organizations seek easier access to business analytics data from IT to make better business decisions faster. Five constraints that limit insights from business analytics data. Teams derive business metrics from many sources. Data silos.

Analytics 198

Analytics Strategy Storage Technology 198

Dynatrace

FEBRUARY 9, 2023

Luckily, Dynatrace provides in-depth memory allocation monitoring, which allows fine-grained allocation analysis and can even point to the root cause of a problem. While memory allocation analysis can show wasteful or inefficient code, it can also reveal different problems, one of which we’ll examine in this blog post.

Java 218

Java Metrics Servers Code 218

Dynatrace

FEBRUARY 25, 2020

We introduced Digital Business Analytics in part one as a way for our customers to tie business metrics to application performance and user experience, delivering unified insights into how these metrics influence business milestones and KPIs. A sample Digital Business Analytics dashboard. Dynatrace news.

Analytics 212

Analytics Metrics Best Practices Servers 212

Dynatrace

AUGUST 2, 2021

Metrics matter. 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. Examples of metric calculations. Dynatrace news.

Metrics 246

Metrics Analytics Google Code 246

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. Therefore, we filtered them out with DQL.

Analytics 205

Analytics AWS Strategy Infrastructure 205

Dynatrace

APRIL 8, 2022

Output plugins deliver logs to storage solutions, analytics tools, and observability platforms like Dynatrace. Precise, AI-powered anomaly root-cause determination based on automatic log analysis and custom user-defined events. Detailed performance analysis for better software architecture and resource allocation.

Metrics 188

Metrics Analytics Software Architecture Open Source 188

Dynatrace

MAY 21, 2024

Realizing that executives from other organizations are in a similar situation to my own, I want to outline three key objectives that Dynatrace’s powerful analytics can help you deliver, featuring nine use cases that you might not have thought possible. Change is my only constant.

Technology 210

Technology Technology Analytics Storage 210

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 261

Cloud Lambda AWS Analytics 261

Dynatrace

JANUARY 12, 2021

In Part 1 we explored how you can use the Davis AI to analyze your StatsD metrics. In Part 2 we showed how you can run multidimensional analysis for external metrics that are ingested via the OneAgent Metric API. Analyzing Prometheus metrics in Kubernetes is challenging. Unlocking the power of Prometheus metrics.

Metrics 185

Metrics Open Source Monitoring Analytics 185

Dynatrace

MARCH 16, 2022

We added monitoring and analytics for log streams from Kubernetes and multicloud platforms like AWS, GCP, and Azure, as well as the most widely used open-source log data frameworks. Whatever your use case, when log data reflects changes in your infrastructure or business metrics, you need to extract the metrics and monitor them.

Metrics 223

Metrics Lambda Infrastructure Monitoring 223

Dynatrace

OCTOBER 1, 2021

In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. If you’ve read about observability, you likely know that collecting the measurements of logs, metrics, and distributed traces are the three key pillars to achieving success.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Dynatrace

MARCH 12, 2024

If you can collect the relevant data (and that’s a big if), the problem shifts to analytics. Connecting data from different systems, stitching process steps together, calculating delays between steps, alerting on business exceptions and technical issues, and tracking SLOs are just some of the requirements for an effective analytics solution.

Processing 260

Processing Monitoring Analytics C++ 260