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. But they struggle to store unstructured data.

Analytics 184

Analytics Infrastructure Storage Efficiency 184

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. Energy efficiency and carbon footprint outshine x86 architectures The first clear benefit of ARM in the enterprise IT landscape is energy efficiency.

Efficiency 262

Efficiency Architecture Energy Monitoring 262

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 171

Analytics Best Practices Metrics IoT 171

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 211

Analytics Storage Retail Monitoring 211

Dynatrace

OCTOBER 4, 2022

As a result, organizations need software to work perfectly to create customer experiences, deliver innovation, and generate operational efficiency. The only way to address these challenges is through observability data — logs, metrics, and traces. The next frontier: Data and analytics-centric software intelligence.

Analytics 187

Analytics Software Software Storage 187

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 184

Analytics Artificial Intelligence Big Data Open Source 184

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 217

Google Metrics Cloud Analytics 217

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 182

Analytics Innovation Metrics Database 182

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 178

Analytics Storage Retail Monitoring 178

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 205

Analytics Monitoring Artificial Intelligence DevOps 205

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 225

Metrics Analytics Monitoring Efficiency 225

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 173

Analytics Ecommerce Metrics Innovation 173

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 192

Analytics Processing Transportation Storage 192

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 185

Analytics Strategy Storage Technology 185

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 214

Cloud Lambda AWS Analytics 214

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 247

Processing Monitoring Analytics C++ 247

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. An advanced observability solution can also be used to automate more processes, increasing efficiency and innovation among Ops and Apps teams. What is observability?

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Dynatrace

FEBRUARY 28, 2024

SRG is a potent tool that automates the analysis of release impacts, ensuring validation of service availability, performance, and capacity objectives throughout the application ecosystem by examining the effect of advanced test suites executed earlier in the testing phase.

DevOps 200

DevOps Metrics Engineering Analytics 200

Dynatrace

JANUARY 4, 2024

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. It uses fault-tree analysis to identify the component events that cause outcomes at a higher level. That’s where causal AI can help. Causal AI is particularly effective in observability. How can organizations improve data quality?

Government 197

Government Analytics Benchmarking Storage 197

Dynatrace

MARCH 1, 2024

As a result, it is difficult to ensure application efficiency and ensure accurate delivery across touchpoints. Furthermore, by integrating with Adobe Experience Manager, you get quick visibility, ensuring application efficiency across all channels and the ability to scale in support of even the largest Adobe Experience Manager instances.

Analytics 186

Analytics Monitoring Website Efficiency 186

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 260

Artificial Intelligence DevOps Analytics Engineering 260

Dynatrace

NOVEMBER 23, 2020

As the application owner of an e-commerce application, for example, you can enrich the source code of your application with domain-specific knowledge by adding actionable semantics to collected performance or business metrics. New OpenTelemetry metrics exporters provide the broadest language support on the market.

Metrics 150

Metrics Open Source Tuning Analytics 150

Dynatrace

FEBRUARY 1, 2024

Centralization brings all the critical metrics and logs into one place, providing a holistic perspective over your cloud environment. Logs and metrics in context The Clouds app simplifies cloud operations by providing detailed logs and metrics in context. Metrics charts are available for each selected resource.

Cloud 201

Cloud Strategy Metrics Government 201

Dynatrace

FEBRUARY 1, 2024

To overcome these complex issues, teams must quickly find root causes among numerous alerts and metrics. Based on the topology model, detected dependencies, and thousands of events and metrics, Davis AI can pinpoint the origin of an issue. The process analysis page enables you to quickly identify problematic processes.

Infrastructure 178

Infrastructure Metrics Network Monitoring 178

Dynatrace

JANUARY 31, 2024

Removing blind spots proactively prevents security incidents and ensures that performance metrics reflect the true state of the environment. Efficient service discovery and automatic recommendations As soon as OneAgent is deployed on previously unmonitored hosts, it shows all findings gathered with lightweight eBPF Service Discovery.

Analytics 170

Analytics Infrastructure Monitoring Cloud 170

Dynatrace

APRIL 18, 2024

Rather, they must be bolstered by additional technological investments to ensure reliability, security, and efficiency. It goes beyond traditional monitoring—metrics, logs, and traces—to encompass topology mapping, code-level details, and user experience metrics that provide real-time insights.

DevOps 187

DevOps Engineering Artificial Intelligence Infrastructure 187

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. Metrics, logs , and traces make up three vital prongs of modern observability. Comparing log monitoring, log analytics, and log management.

Systems 183

Systems Cloud Analytics DevOps 183

Dynatrace

AUGUST 17, 2023

With PurePath® distributed tracing, method hotspots, service flows, memory, and GC analysis, Dynatrace earned its reputation.Since then, Spring and Dynatrace have matured and improved, especially for containers, cloud integrations, and Kubernetes. Soon after, Dynatrace built a registry for exporting Micrometer metrics.

Metrics 194

Metrics Analytics Speed Java 194

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. Achieving the ideal state with aggregated, centralized log data, metrics, traces , and other metadata is challenging—particularly for multicloud environments.

Analytics 217

Analytics Storage Infrastructure Metrics 217

Dynatrace

OCTOBER 4, 2022

These technologies are poorly suited to address the needs of modern enterprises—getting real value from data beyond isolated metrics. Grail needs to support security data as well as business analytics data and use cases. This starts with a highly efficient ingestion pipeline that supports adding hundreds of petabytes daily.

Artificial Intelligence 264

Artificial Intelligence Analytics Storage Architecture 264

Scalegrid

DECEMBER 21, 2023

Buckle up as we delve into the world of Redis® monitoring, exploring the most important Redis® metrics, discussing essential tools, and even peering into the future of Redis® performance management. Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring.

Strategy 130

Strategy Monitoring Latency DevOps 130

Dynatrace

FEBRUARY 1, 2024

Business and technology leaders are increasing their investments in AI to achieve business goals and improve operational efficiency. Every new question we ask comes with additional analysis, prediction models, and more,” Reitbauer said. “By In this example, there is a suspicious increase in scripting events.

Artificial Intelligence 182

Artificial Intelligence Analytics Efficiency Database 182

Dynatrace

NOVEMBER 20, 2023

The first goal is to demonstrate how generative AI can bring key business value and efficiency for organizations. While technologies have enabled new productivity and efficiencies, customer expectations have grown exponentially, cyberthreat risks continue to mount, and the pace of business has sped up. What is predictive AI?

AWS 206

AWS Artificial Intelligence Analytics Cloud 206

Dynatrace

APRIL 13, 2023

As organizations adopt more cloud-native technologies, observability data—telemetry from applications and infrastructure, including logs, metrics, and traces—and security data are converging. Forensics is crucial for incident response and post-incident analysis. Incomplete. Skills and expertise. Were there attack attempts?

Analytics 182

Analytics Java Infrastructure Cloud 182

Dynatrace

SEPTEMBER 21, 2023

As global warming advances, growing IT carbon footprints are pushing energy-efficient computing to the top of many organizations’ priority lists. Energy efficiency is a key reason why organizations are migrating workloads from energy-intensive on-premises environments to more efficient cloud platforms.

Energy 230

Energy Cloud Airlines Strategy 230

Dynatrace

MARCH 29, 2024

As a result, organizations are turning to AI to automate tasks—from code development to incident response—to reduce manual effort and human error, and to boost workforce efficiency. Artificial intelligence, including more recent advances in generative AI , is becoming increasingly important as organizations look to modernize how IT operates.

Artificial Intelligence 179

Artificial Intelligence DevOps Strategy Open Source 179