Dynatrace

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

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Analytics Innovation Metrics Database 182

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.

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Cloud Lambda AWS Analytics 214

Dynatrace

FEBRUARY 10, 2023

Data proliferation—as well as a growing need for data analysis—has accelerated. They now use modern observability to monitor expanding cloud environments in order to operate more efficiently, innovate faster and more securely, and to deliver consistently better business results. We’ll post news here as it happens!

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Efficiency Performance Analytics DevOps 272

Dynatrace

OCTOBER 4, 2022

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. But on their own, logs present just another data silo as IT professionals attempt to troubleshoot and remediate problems. Data volume explosion in multicloud environments poses log issues.

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Analytics Storage Infrastructure Metrics 217

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. As organizations add more tools, it creates a demand for common tooling, shared data, and democratized access. But getting the value out of the data is not easy.

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Analytics Strategy Storage Technology 185

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

FEBRUARY 12, 2024

However, these environments can drown enterprises in data, forcing them to adopt multiple tools and services to manage and secure it. 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.

Analytics 178

Analytics Artificial Intelligence Engineering Storage 178

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

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Analytics Artificial Intelligence Storage Serverless 231

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. Legacy data center infrastructure and software support have kept all the benefits of ARM at, well… arm’s length.

Efficiency 262

Efficiency Architecture Energy Monitoring 262

Percona

APRIL 14, 2023

A shared characteristic in most (if not all) databases, be them traditional relational databases like Oracle, MySQL, and PostgreSQL or some kind of NoSQL-style database like MongoDB, is the use of a caching mechanism to keep (a copy of) part of the data in memory. So, how do you know if your hot data is in memory? MySQL does.

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Cache Efficiency Database Monitoring 93

Dynatrace

JANUARY 4, 2024

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical.

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Government Analytics Benchmarking Storage 197

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 211

Analytics Storage Retail Monitoring 211

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 173

Analytics Ecommerce Metrics Innovation 173

Dynatrace

OCTOBER 4, 2022

Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Work with different and independent data types. Thus, Grail was born.

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Artificial Intelligence Analytics Storage Architecture 264

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.

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Google Metrics Cloud Analytics 217

Dynatrace

SEPTEMBER 14, 2022

As an industry leader, Dynatrace promotes primarily using software and AI to deal with this complexity at scale instead of just putting data on dashboards. Does that mean that reactive and exploratory data analysis, often done manually and with the help of dashboards, are dead? Why today’s data analytics solutions still fail us.

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Metrics Analytics Monitoring Efficiency 225

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

OCTOBER 6, 2023

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Tables are a physical data model, essentially the type of observability data that you can store.

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Artificial Intelligence Analytics Metrics Storage 258

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. based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data.

Analytics 184

Analytics Infrastructure Storage Efficiency 184

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 178

Analytics Storage Retail Monitoring 178

Dynatrace

MARCH 29, 2024

Dynatrace offers essential analytics and automation to keep applications optimized and businesses flourishing. AI innovation elevates efficiency and performance of Google Cloud AI adoption is increasingly critical for any organization. Learn more.

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Google Innovation Cloud Analytics 258

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. Logs can include data about user inputs, system processes, and hardware states. What is log analytics? Log monitoring vs log analytics.

Analytics 205

Analytics Monitoring Artificial Intelligence DevOps 205

Dynatrace

FEBRUARY 15, 2023

As organizations adopt more cloud-based technologies, the increased volume and variety of data from these ecosystems drive complexity. This complexity creates silos that affect the ability of IT, development, security, and business teams to achieve the awareness they need to make data-driven decisions.

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Analytics Storage Cloud DevOps 130

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!

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Data Engineering Engineering Processing Games 264

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. As teams begin collecting and working with observability data, they are also realizing its benefits to the business, not just IT. What is observability?

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Metrics Open Source Monitoring Infrastructure 363

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.

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Analytics Java Infrastructure Cloud 182

Dynatrace

MAY 20, 2020

Dynatrace collects a huge number of metrics for each OneAgent-monitored host in your environment. Depending on the types of technologies you’re running on individual hosts, the average number of metrics is about 500 per computational node. Running metric queries on a subset of entities for live monitoring and system overviews.

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Metrics Operating System Tuning Monitoring 224

Dynatrace

APRIL 8, 2024

This blog explores how vertically integrated risk management solutions that use AI and automation enable unparalleled visibility, control, and efficiency for risk management in banking. Collect data automatically and pre-processed from a range of sources: application programming interfaces, integrations, agents, and OpenTelemetry.

Analytics 197

Analytics Infrastructure Efficiency Technology 197

Dynatrace

MARCH 12, 2024

They can be expensive to implement and maintain, rely on fragile data pipelines, and require highly skilled data analysts to ensure ongoing relevance. First and foremost, it’s a data problem. Locked away in disparate systems, difficult to access, and with different formats, business data can be days or weeks old.

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Processing Monitoring Analytics C++ 247

Dynatrace

SEPTEMBER 7, 2022

Dynatrace and the Dynatrace Intelligent Observability Platform have added support for the newly introduced Amazon VPC Flow Logs to Amazon Kinesis Data Firehose. This support enables customers to define specific endpoint delivery of real-time streaming data to platforms such as Dynatrace. What is VPC Flow Logs? Why Dynatrace?

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Traffic AWS Network Cloud 212

Dynatrace

FEBRUARY 1, 2024

Many of our customers face challenges due to using various tools that are not integrated, making it difficult to track their cloud services and correlate data from different sources. Centralization brings all the critical metrics and logs into one place, providing a holistic perspective over your cloud environment.

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Cloud Strategy Metrics Government 201

The Netflix TechBlog

SEPTEMBER 18, 2020

Part of our series on who works in Analytics at Netflix?—?and and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley.

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Analytics Education Innovation Engineering 223

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

FEBRUARY 1, 2024

Business and technology leaders are increasing their investments in AI to achieve business goals and improve operational efficiency. By packaging [these capabilities] into hypermodal AI, we are able to run deep custom analytics use cases in sixty seconds or less.” In this example, there is a suspicious increase in scripting events.

Artificial Intelligence 182

Artificial Intelligence Analytics Efficiency Database 182

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.

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Metrics Open Source Tuning Analytics 150

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.

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AWS Artificial Intelligence Analytics Cloud 206

Dynatrace

FEBRUARY 15, 2023

Teams can now use an observability platform to unify operations, business, and development data to gain automatic, precise answers about cloud environments and user experience. As a result, these leaders can ask different questions of the same data. Additionally, its modern architecture delivers cost-effective storage and compute.

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Analytics Storage Cloud Code 130