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 214

Analytics Storage Retail Monitoring 214

Dynatrace

FEBRUARY 15, 2023

Grail – the foundation of exploratory analytics Grail can already store and process log and business events. Introducing Metrics on Grail Despite their many advantages, modern cloud-native architectures can result in scalability and fragmentation challenges. You no longer need to split, distribute, or pre-aggregate your data.

Analytics 229

Analytics Social Media Metrics Efficiency 229

Dynatrace

APRIL 19, 2024

Increasingly, organizations are exploring unified software platforms that eliminate data silos while offering both flexibility and extensibility to safeguard their investments and streamline their diverse tools. With Automation Engine, they were able to call the cloud provider’s API to trigger the desired resizing action.

AWS 220

AWS Analytics Cloud Monitoring 220

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 198

AWS Cloud Lambda Analytics 198

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 181

Analytics Storage Retail Monitoring 181

Dynatrace

SEPTEMBER 8, 2022

In cloud-native environments, there can also be dozens of additional services and functions all generating data from user-driven events. This is critical to ensure high performance, security, and a positive user experience for cloud-native applications and services. Comparing log monitoring, log analytics, and log management.

Systems 185

Systems Cloud Analytics DevOps 185

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

MARCH 20, 2024

Rising cloud complexity has made securing cloud-native and multicloud applications significantly more difficult. Cloud applications are built with the help of a software supply chain, such as OSS libraries and third-party software. What are the key components of application security monitoring?

Monitoring 211

Monitoring Analytics Traffic Best Practices 211

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 186

Analytics Innovation Metrics Database 186

Dynatrace

DECEMBER 21, 2023

How can you reduce the carbon footprint of your hybrid cloud? energy-efficient data centers—cloud providers—achieve values closer to 1.2. Is the solution to just move all workloads to the cloud? There might not be enough cloud capacity where you need it. How will your organization respond to this global challenge?

Cloud 209

Cloud Energy Best Practices Cache 209

Dynatrace

NOVEMBER 2, 2022

Why organizations are turning to software development to deliver business value. Digital immunity has emerged as a strategic priority for organizations striving to create secure software development that delivers business value. Software development success no longer means just meeting project deadlines. Autonomous testing.

Software 195

Software Software Artificial Intelligence DevOps 195

Dynatrace

FEBRUARY 8, 2021

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Dynatrace news. Logs provide information you can’t find anywhere else.

Cloud 259

Cloud Azure Analytics AWS 259

Dynatrace

APRIL 11, 2023

Today’s organizations face increasing pressure to keep their cloud-based applications performing and secure. Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. But managing the breadth of the vulnerabilities that can put your systems at risk is challenging.

Cloud 186

Cloud DevOps Open Source Retail 186

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. How does a data lakehouse—the combination of a data warehouse and a data lake—together with software intelligence, bring data insights to life?

Analytics 221

Analytics Storage Infrastructure Metrics 221

Dynatrace

DECEMBER 13, 2023

This year, they’ve been asked to do more with less, innovate faster, and tame the ever-increasing complexities of modern cloud environments. In 2024, more organizations will experience major digital service outages due to poor-quality and insufficiently supervised software code. Technology prediction No.

Technology 203

Technology Technology Artificial Intelligence Analytics 203

Dynatrace

FEBRUARY 10, 2023

Increasingly, organizations are turning to modern observability platforms to address the complexity of, and gain visibility into, cloud environments. Further, automation has become a core strategy as organizations migrate to and operate in the cloud. Check out the guide from last year’s event. What is a data lakehouse?

Efficiency 276

Efficiency Performance Analytics DevOps 276

Dynatrace

JANUARY 31, 2024

Monitoring SAP products can present challenges Monitoring SAP systems can be challenging due to the inherent complexity of using different technologies—such as ABAP, Java, and cloud offerings—and the sheer amount of generated data. This is why Dynatrace is extending its observability capabilities for SAP with PowerConnect for SAP.

Java 188

Java Analytics Best Practices Monitoring 188

Dynatrace

NOVEMBER 20, 2023

In this AWS re:Invent 2023 guide, we explore the role of generative AI in the issues organizations face as they move to the cloud: IT automation, cloud migration and digital transformation, application security, and more. In general, generative AI can empower AWS users to further accelerate and optimize their cloud journeys.

AWS 209

AWS Artificial Intelligence Analytics Cloud 209

Dynatrace

FEBRUARY 28, 2023

Secure your hybrid cloud environments at runtime with Dynatrace using runtime vulnerability analysis, AI-assisted prioritization, runtime application protection, and log audit and forensics. At all times, in Dynatrace, we provide a unified view of relevant security events fully integrated with our SmartScape technology. Audit logs.

Analytics 147

Analytics Cloud Software Software 147

Dynatrace

FEBRUARY 1, 2024

Organizations that miss out on implementing AI risk falling behind their competition in an age where software delivery speed, agility, and security are crucial success factors. By packaging [these capabilities] into hypermodal AI, we are able to run deep custom analytics use cases in sixty seconds or less.”

Artificial Intelligence 186

Artificial Intelligence Analytics Efficiency Database 186

Dynatrace

JULY 11, 2023

Without native log support, overhead and complexity grow OpenTelemetry, the Cloud Native Computing Foundation (CNCF) incubating project, introduced standards that enable companies to instrument, generate, and export telemetry data. When combined with out-of-the-box correlation, such telemetry data provides context-rich observability.

Open Source 215

Open Source Analytics Metrics Cloud 215

Dynatrace

MARCH 13, 2024

As the pace of digital transformation accelerates, the cloud applications supporting digital infrastructure become more complex. These larger trends make it imperative to enhance and streamline application security analytics and reporting processes through intelligent automation.

Best Practices 227

Best Practices Education Strategy Analytics 227

Dynatrace

APRIL 20, 2023

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

Analytics 187

Analytics Infrastructure Storage Efficiency 187

Dynatrace

MARCH 6, 2024

Platform engineering creates and manages a shared infrastructure and set of tools, such as internal developer platforms (IDPs) , to enable software developers to build, deploy, and operate applications more efficiently. Furthermore, OneAgent observes and gathers all remaining workload logs, metrics, traces, and events.

Engineering 241

Engineering Development DevOps Infrastructure 241

Dynatrace

FEBRUARY 6, 2020

Autonomous Cloud is not another lofty marketing term. Autonomous Cloud is what enables our globally distributed development teams at Dynatrace to deliver better software faster following our NoOps approach: Fully Autonomous and as a Self-Service! Three waves of DevOps leading to Autonomous Cloud. Dynatrace news.

Cloud 184

Cloud DevOps Engineering Speed 184

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. Enter causal AI.

Performance 186

Performance DevOps Innovation Artificial Intelligence 186

Dynatrace

FEBRUARY 28, 2024

The burgeoning reliance on cloud technology stacks amplifies this challenge, creating hurdles due to budgetary constraints, time limitations, and the potential risk of human errors. Both SREs and application teams invest substantial time and effort in locating and rectifying software glitches within their local environments.

DevOps 203

DevOps Metrics Engineering Analytics 203

Dynatrace

DECEMBER 12, 2023

For example, nearly two-thirds (61%) of technology leaders say they will increase investment in AI over the next 12 months to speed software development. As they continue on this path, organizations expect other benefits , from enabling business users to easily customize dashboards (54%) to building interactive queries for analytics (48%).

Artificial Intelligence 206

Artificial Intelligence DevOps Analytics Strategy 206

Dynatrace

APRIL 18, 2024

DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. The deep visibility and insights that observability provides allow teams to take proactive measures early in the software development life cycle (SDLC).

DevOps 190

DevOps Engineering Artificial Intelligence Infrastructure 190

Dynatrace

OCTOBER 25, 2022

But advancements in modern AIOps and cloud automation are now bringing NoOps within reach. Or is it just a passing cloud? NoOps is a concept in software development that seeks to automate processes and eliminate the need for an extensive IT operations team. Can NoOps help the operations teams of today’s organizations?

DevOps 217

DevOps Big Data Cloud Innovation 217

All Things Distributed

MARCH 11, 2015

Cloud computing is enabling amazing new innovations both in consumer and enterprise products, as it became the new normal for organizations of all sizes. So many exciting new areas are being empowered by cloud that it is fascinating to watch. Cloud analytics are everywhere. Cloud enables self-service analytics.

Analytics 135

Analytics Cloud Healthcare Retail 135

Dynatrace

NOVEMBER 7, 2023

According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026. Platform engineering is on the rise. Monitoring-as-code can also be configured in GitOps fashion.

Engineering 273

Engineering DevOps Best Practices Infrastructure 273

Dynatrace

NOVEMBER 22, 2021

Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. These modern, cloud-native environments require an AI-driven approach to observability. At AWS re:Invent 2021 , the focus is on cloud modernization.

AWS 228

AWS Lambda Artificial Intelligence Serverless 228

Dynatrace

FEBRUARY 15, 2023

Cloud environments have become ever more complex, with an increasingly interconnected set of services. To tame this complexity and deliver differentiated digital experiences, IT, development, security, and business teams need automated workflows throughout these cloud ecosystems.

Code 211

Code DevOps Cloud Analytics 211

Dynatrace

FEBRUARY 12, 2024

The various presenters in this session aligned platform engineering use cases with the software development lifecycle. Standards are set by the platform engineers and ensured throughout all stages of the software development lifecycle. According to Gardner, teams gradually deliver software to user groups with progressive delivery.

Engineering 182

Engineering Development Infrastructure Cloud 182

Dynatrace

JANUARY 22, 2024

While traditional AI relies on finding correlations in data, causal AI aims to determine the precise underlying mechanisms that drive events and outcomes. Therefore, causal AI is a useful deterministic AI technique that provides concrete answers about the source of events, not probabilistic outputs. Software development.

Artificial Intelligence 207

Artificial Intelligence Healthcare Retail Government 207

Dynatrace

AUGUST 7, 2023

They can also use generative AI for cybersecurity, write prototype code, and implement complex software systems. Second, for causal AI to provide a deep and rich context to unleash GPT’s full potential for software delivery and productivity use cases.”

DevOps 185

DevOps Analytics Best Practices Java 185