Dynatrace

MARCH 5, 2025

To continue down the carbon reduction path, IT leaders must drive carbon optimization initiatives into the hands of IT operations teams, arming them with the tools needed to support analytics and optimization. Power usage effectiveness (PUE) is derived from data provided by the cloud providers and data center operators.

Energy 223

Energy Analytics Traffic Cloud 223

Dynatrace

NOVEMBER 18, 2024

AI transformation, modernization, managing intelligent apps, safeguarding data, and accelerating productivity are all key themes at Microsoft Ignite 2024. Adopting AI to enhance efficiency and boost productivity is critical in a time of exploding data, cloud complexities, and disparate technologies.

Cloud 263

Cloud Azure Artificial Intelligence Innovation 263

Dynatrace

JUNE 10, 2024

As a result, organizations are implementing security analytics to manage risk and improve DevSecOps efficiency. Fortunately, CISOs can use security analytics to improve visibility of complex environments and enable proactive protection. What is security analytics? Why is security analytics important? Here’s how.

Analytics 264

Analytics Network Open Source Hardware 264

Dynatrace

AUGUST 20, 2024

Driven by that value, Dynatrace brings real-time observability, security, and business data into context and makes sense of it so our customers can get answers, automate, predict, and prevent. Executives are sitting on a goldmine of data, and they don’t know it. Common business analytics incur too much latency.

Analytics 285

Analytics Latency Processing Systems 285

Scalegrid

MAY 13, 2020

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

OCTOBER 2, 2024

Existing siloed tools lead to inefficient workflows, fragmented data, and increased troubleshooting times. Rather than relying on disparate tools for each environment and team, Dynatrace integrates all data into one cohesive platform. There is no need to think about schema and indexes, re-hydration, or hot/cold storage.

Analytics 304

Analytics AWS DevOps Cloud 304

Dynatrace

OCTOBER 4, 2022

Software and data are a company’s competitive advantage. But for software to work perfectly, organizations need to use data to optimize every phase of the software lifecycle. The only way to address these challenges is through observability data — logs, metrics, and traces. Teams interact with myriad data types.

Analytics 246

Analytics Software Software Storage 246

Dynatrace

JANUARY 31, 2024

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. However, there are many obstacles and limitations along the way to becoming a data-driven organization. Understanding the context.

Analytics 272

Analytics Processing Transportation Storage 272

DZone

APRIL 11, 2023

Data processing in the cloud has become increasingly popular due to its scalability, flexibility, and cost-effectiveness. This article will explore how these technologies can be used together to create an optimized data pipeline for data processing in the cloud.

Azure 246

Azure Analytics Storage Cloud 246

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.

Analytics 264

Analytics Storage Infrastructure Metrics 264

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.

Analytics 246

Analytics Innovation Metrics Database 246

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.

Analytics 264

Analytics Artificial Intelligence Storage Serverless 264

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 246

Analytics Storage Retail DevOps 246

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 245

Analytics Storage Retail DevOps 245

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.

Artificial Intelligence 290

Artificial Intelligence Analytics Storage Architecture 290

DZone

SEPTEMBER 14, 2023

In today's data-driven world, efficient data processing plays a pivotal role in the success of any project. Apache Spark , a robust open-source data processing framework, has emerged as a game-changer in this domain.

Big Data 279

Big Data Processing Open Source Games 279

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

DZone

JUNE 3, 2024

In an era where data is the new oil, effectively utilizing data is crucial for the growth of every organization. It is not enough to store these data durably, but also to effectively query and analyze them. Without a querying capability, the data stored in S3 would not be of any benefit.

Big Data 278

Big Data AWS Storage Analytics 278

Dynatrace

MARCH 6, 2024

They create an explosion of data that is extremely challenging to manually capture, analyze, and act on. Fragmented monitoring and analytics can’t keep up The continued reliance on fragmented monitoring tools and manual analytics strategies is a particular pain point for IT and security teams.

Analytics 246

Analytics Innovation Strategy Storage 246

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 264

Analytics Monitoring DevOps Artificial Intelligence 264

Scalegrid

FEBRUARY 6, 2025

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. Both serve distinct purposes, from managing message queues to ingesting large data volumes. What is RabbitMQ?

Latency 147

Latency Analytics Architecture Storage 147

Dynatrace

FEBRUARY 2, 2023

Should business data be part of your observability solution? Technology and business leaders express increasing interest in integrating business data into their IT observability strategies, citing the value of effective collaboration between business and IT.

Analytics 246

Analytics Metrics DevOps Storage 246

Dynatrace

JULY 29, 2021

The complexity of such deployments has accelerated with the adoption of emerging, open-source technologies that generate telemetry data, which is exploding in terms of volume, speed, and cardinality. 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

The Netflix TechBlog

SEPTEMBER 18, 2024

Cassandra serves as the backbone for a diverse array of use cases within Netflix, ranging from user sign-ups and storing viewing histories to supporting real-time analytics and live streaming. Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns.

Latency 260

Latency Storage Cache Servers 260

Dynatrace

AUGUST 9, 2023

The massive volumes of log data over months, sometimes years, of a breach have made this a complicated and expensive problem to solve. A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. and “was any sensitive data stolen?”

Analytics 246

Analytics Metrics Database Storage 246

The Netflix TechBlog

FEBRUARY 14, 2025

Every image you hover over isnt just a visual placeholder; its a critical data point that fuels our sophisticated personalization engine. This nuanced integration of data and technology empowers us to offer bespoke content recommendations. This queue ensures we are consistently capturing raw events from our global userbase.

Tuning 166

Tuning Latency Efficiency Storage 166

Scalegrid

JULY 17, 2020

It is an open standard format which organizes data into key/value pairs and arrays detailed in RFC 7159. JSON is the most common format used by web services to exchange data, store documents, unstructured data, etc. You can also check out our Working with JSON Data in PostgreSQL vs. JSONB Patterns & Antipatterns.

Storage 321

Storage Database Efficiency Processing 321

Dynatrace

JUNE 9, 2023

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. All of these factors challenge DevOps maturity.

DevOps 246

DevOps Analytics Storage Metrics 246

Dynatrace

APRIL 28, 2023

Optimize cost and availability while staying compliant Observability data like logs and metrics provide automated answers, root cause detection, and security issues. Customer decisions about data retention are often determined by important security, privacy, and legal issues.

Analytics 246

Analytics Storage Infrastructure Metrics 246

DZone

FEBRUARY 10, 2025

Microsoft Azure SQL is a robust, fully managed database platform designed for high-performance querying, relational data storage, and analytics. An application software generates user metrics on a daily basis, which can be used for reports or analytics.

Metrics 165

Metrics Azure Analytics Storage 165

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 245

Analytics Artificial Intelligence Engineering Technology 245

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.

Government 263

Government Analytics Benchmarking Storage 263

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Dynatrace

APRIL 19, 2023

Creating an ecosystem that facilitates data security and data privacy by design can be difficult, but it’s critical to securing information. When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration.

Design 246

Design Storage Programming Analytics 246

The Netflix TechBlog

OCTOBER 8, 2024

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 239

Latency Storage Traffic Tuning 239

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 246

Analytics Infrastructure Storage Architecture 246

Dynatrace

SEPTEMBER 23, 2022

But IT teams need to embrace IT automation and new data storage models to benefit from modern clouds. As they enlist cloud models, organizations now confront increasing complexity and a data explosion. Log management and analytics have become a particular challenge. Data explosion hinders better data insight.

Cloud 245

Cloud Artificial Intelligence Innovation Architecture 245