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 204

Analytics Software Software Storage 204

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

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 248

Analytics AWS DevOps Cloud 248

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 245

Database DevOps Analytics Servers 245

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 198

Analytics Innovation Metrics Database 198

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

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 234

Analytics Storage Infrastructure Metrics 234

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 258

Big Data Government Processing Analytics 258

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 229

Analytics Metrics Database Storage 229

Dynatrace

MAY 28, 2024

Logs provide answers, but monitoring is a challenge Manual tagging is error-prone Making sure your required logs are monitored is a task distributed between the data owner and the monitoring administrator. Finding the right logs is cumbersome Even if your logs are monitored, you need to make sense of the vast data volume.

Analytics 194

Analytics Infrastructure Database Monitoring 194

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 226

Analytics Storage Retail Monitoring 226

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 362

Best Practices Code Testing Data Engineering 362

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 254

Latency Storage Cache Efficiency 254

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 279

Database Artificial Intelligence Metrics Monitoring 279

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 234

Analytics Cloud Java Serverless 234

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 236

Database Metrics Retail Analytics 236

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

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 193

Analytics Storage Retail Monitoring 193

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 200

Data Engineering Engineering Entertainment Big Data 200

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 217

Analytics Mobile Performance Monitoring 217

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 254

Latency Storage Big Data Tuning 254

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 213

Infrastructure Database Monitoring Metrics 213

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 208

Analytics AWS Strategy Infrastructure 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

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 203

DevOps Analytics Airlines Metrics 203

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 242

Latency Storage Traffic Tuning 242

The Netflix TechBlog

MARCH 10, 2023

This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case.

Media 245

Media Traffic Processing Design 245

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 196

DevOps Analytics Storage Metrics 196

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 200

Analytics Infrastructure Storage Architecture 200

DZone

JANUARY 13, 2023

In this tutorial, you are going to learn about QuestDB SQL extensions which prove to be very useful with time-series data. Using some sample data sets, you will learn how designated timestamps work and how to use extended SQL syntax to write queries on time-series data.

IoT 178

IoT Analytics Database Metrics 178

DZone

OCTOBER 24, 2023

The ELK stack is an abbreviation for Elasticsearch, Logstash, and Kibana, which offers the following capabilities: Elasticsearch: a scalable search and analytics engine with a log analytics tool and application-formed database, perfect for data-driven applications.

Analytics 267

Analytics Storage Infrastructure Scalability 267

All Things Distributed

JUNE 21, 2018

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

Database 167

Database AWS Games Latency 167

DZone

OCTOBER 1, 2023

Elasticsearch is an open-source search engine and analytics store used by a variety of applications from search in e-commerce stores, to internal log management tools using the ELK stack (short for “Elasticsearch, Logstash, Kibana”).

Open Source 257

Open Source Tuning Analytics Scalability 257

Dynatrace

SEPTEMBER 5, 2024

Understanding that the first mile of getting data in can often be the hardest, Dynatrace continues to invest in log ingest, offering a range of out-of-the-box solutions within the Dynatrace Platform and apps. Dynatrace ActiveGate addresses these issues by enforcing configurable security settings and ensuring data uniformity.

Innovation 273

Innovation AWS Analytics Storage 273

High Scalability

FEBRUARY 17, 2021

This is guest post by Sachin Sinha who is passionate about data, analytics and machine learning at scale. This article is to simply report the YCSB bench test results in detail for five NoSQL databases namely Redis, MongoDB, Couchbase, Yugabyte and BangDB and compare the result side by side. Author & founder of BangDB.

Benchmarking 308

Benchmarking Latency C++ Database 308