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

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. As a result, dedicated data pipeline tools are unnecessary for preprocessing data before ingestion.

Analytics 304

Analytics AWS DevOps Cloud 304

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

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

DZone

NOVEMBER 25, 2023

We often dwell on the technical aspects of database selection, focusing on performance metrics , storage capacity, and querying capabilities. Yet, the impact of choosing the right NoSQL database goes beyond these parameters; it affects your business outcomes. How do these metrics translate into real-world value for your business?

Database 278

Database Latency Speed Metrics 278

DZone

FEBRUARY 4, 2025

Understanding Teradata Data Distribution and Performance Optimization Teradata performance optimization and database tuning are crucial for modern enterprise data warehouses.

Performance 173

Performance Tuning Analytics Strategy 173

DZone

AUGUST 1, 2024

Editor's Note: The following is an article written for and published in DZone's 2024 Trend Report, Database Systems: Modernization for Data-Driven Architectures. Time series data has become an essential part of data collection in various fields due to its ability to capture trends, patterns, and anomalies.

Database 260

Database Analytics Software Software 260

Dynatrace

APRIL 21, 2022

While applications are built using a variety of technologies and frameworks, there is one thing they usually have in common: the data they work with must be stored in databases. Now, Dynatrace has gone a step further and expanded its coverage and intelligent observability into the next layer: database infrastructure.

Database 246

Database DevOps Analytics Servers 246

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

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

DZone

JULY 14, 2021

Authors: Ruoxi Sun (Tech Lead of Analytical Computing Team at PingCAP). TiDB is a Hybrid Transaction/Analytical Processing (HTAP) database that can efficiently process analytical queries. Fei Xu (Software Engineer at PingCAP).

Analytics 223

Analytics Software Engineering Performance Database 223

Scalegrid

JUNE 11, 2019

Ready to transition from a commercial database to open source, and want to know which databases are most popular in 2019? Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Polyglot Persistence Trends : Number of Databases Used & Top Combinations.

Open Source 55

Open Source Database Cloud Infrastructure 55

Dynatrace

FEBRUARY 9, 2021

How do I solve issues quickly while meeting every regional data privacy regulation? Most monitoring tools lack stringent data privacy controls, which could impact the data privacy of end-users. How do I connect the dots between mobile analytics and performance monitoring? Location data masking. IP address masking.

Analytics 276

Analytics Mobile Performance Monitoring 276

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 257

Big Data Government Processing Analytics 257

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

The Netflix TechBlog

DECEMBER 3, 2022

by Jasmine Omeke , Obi-Ike Nwoke , Olek Gorajek Intro This post is for all data practitioners, who are interested in learning about bootstrapping, standardization and automation of batch data pipelines at Netflix. You may remember Dataflow from the post we wrote last year titled Data pipeline asset management with Dataflow.

Best Practices 361

Best Practices Code Testing Data Engineering 361

DZone

FEBRUARY 10, 2025

Microsoft Azure SQL is a robust, fully managed database platform designed for high-performance querying, relational data storage, and analytics. For a typical web application with a backend, it is a good choice when we want to consider a managed database that can scale both vertically and horizontally.

Metrics 165

Metrics Azure Analytics Storage 165

Dynatrace

NOVEMBER 18, 2021

A key element of effectively leveraging observability is analyzing telemetry data in context. Manual and configuration-heavy approaches to putting telemetry data into context and connecting metrics, traces, and logs simply don’t scale. PurePath traces provide a transaction-centric view across all telemetry data.

Analytics 246

Analytics Cloud Java Serverless 246

Dynatrace

SEPTEMBER 8, 2023

In part 2, we’ll show you how to retrieve business data from a database, analyze that data using dashboards and ad hoc queries, and then use a Davis analyzer to predict metric behavior and detect behavioral anomalies. However, as we highlighted previously, business data can be significantly more complex than simple metrics.

Database 290

Database Artificial Intelligence Metrics Monitoring 290

Dynatrace

AUGUST 10, 2023

They frequently articulate the need for real-time visibility into business data to support agile business decisions. But existing business intelligence (BI) tools often lack the broad context, ease of data access, and real-time insights needed to understand and improve customer experience and complex business processes.

Database 246

Database Metrics Retail Analytics 246

The Netflix TechBlog

SEPTEMBER 18, 2024

Central to this infrastructure is our use of multiple online distributed databases such as Apache Cassandra , a NoSQL database known for its high availability and scalability. Over time as new key-value databases were introduced and service owners launched new use cases, we encountered numerous challenges with datastore misuse.

Latency 260

Latency Storage Cache Servers 260

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

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. However, our customers often want to augment the data Dynatrace provides with data from third-party tools.

Analytics 246

Analytics AWS Infrastructure Strategy 246

Dynatrace

JANUARY 31, 2024

I have ingested important custom data into Dynatrace, critical to running my applications and making accurate business decisions… but can I trust the accuracy and reliability?” ” Welcome to the world of data observability. At its core, data observability is about ensuring the availability, reliability, and quality of data.

DevOps 272

DevOps Analytics Airlines Metrics 272

Dynatrace

DECEMBER 9, 2020

If you’re running SAP, you’re likely already familiar with the HANA relational database management system. HANA maintains all the business and analytics data that your business runs on. Today we’re proud to announce that we’ve extended our SAP monitoring capabilities to support SAP HANA databases.

Infrastructure 246

Infrastructure Database Monitoring Metrics 246

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

MARCH 12, 2025

It provides an easy way to select, integrate, and customize foundation models with enterprise data using techniques like retrieval-augmented generation (RAG), fine-tuning, or continued pre-training. Full-stack tracing: Track each user request across multiple FMs, vector databases, orchestrators (LangChain), and custom business logic.

Metrics 165

Metrics Serverless Analytics Innovation 165

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

DECEMBER 18, 2020

There are no hosts, no backend, no database – just HTML, CSS, and JavaScript. The app pulls all of the data from GitHub and Dynatrace APIs. With that simple copy-paste, I now have all the performance, errors, and user experience data for BizOpsConfigurator! Now we have performance and errors all covered: Business Analytics.

Analytics 200

Analytics Metrics IoT Monitoring 200

Scalegrid

OCTOBER 18, 2024

Structured Query Language (SQL) is a simple declarative programming language utilized by various technology and business professionals to extract and transform data. To conclude, GUIs are a vital addition to ease the lives of database users and developers.

Open Source 147

Open Source Database Cloud Operating System 147

The Netflix TechBlog

JULY 15, 2021

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Kevin Wylie is a Data Engineer on the Content Data Science and Engineering team.

Data Engineering 197

Data Engineering Engineering Entertainment Big Data 197

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 252

Latency Storage Big Data Tuning 252

Dynatrace

FEBRUARY 9, 2021

As an application owner, product manager, or marketer, however, you might use analytics tools like Adobe Analytics to understand user behavior, user segmentation, and strategic business metrics such as revenue, orders, and conversion goals. Common examples of data points that makes sense to have in many systems are: Session IDs.

Analytics 208

Analytics Mobile Airlines Monitoring 208

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. Seamlessly report and be alerted on non-topology-related custom metrics, using Dynatrace as a metric database. Dynatrace news.

Metrics 246

Metrics Analytics Storage Monitoring 246

Dynatrace

APRIL 9, 2025

SSRF can lead to unauthorized access to sensitive data, such as cloud metadata, internal databases, and other protected resources. Notable breaches, such as the Capital One data breach, have demonstrated the severe impact of SSRF, where attackers exploited an SSRF vulnerability to access AWS metadata and gain privileged access.

Java 147

Java Programming Architecture Cloud 147