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 184

Analytics Software Software Storage 184

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.

Analytics 182

Analytics Strategy Storage Technology 182

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 211

Analytics Metrics Database Storage 211

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 213

Analytics Storage Infrastructure Metrics 213

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 237

Database DevOps Analytics Servers 237

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 220

Database Metrics Retail Analytics 220

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

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 207

Analytics Storage Retail Monitoring 207

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 189

DevOps Analytics Airlines Metrics 189

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 188

Analytics AWS Strategy Infrastructure 188

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 263

Database Artificial Intelligence Metrics Monitoring 263

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 175

Analytics Storage Retail Monitoring 175

Scalegrid

DECEMBER 6, 2023

In the digital age, data management has transformed from locally hosted servers to cloud solutions. The choice of self-managed cloud databases vs DBaaS is a common debate among those who are looking for the best option that will cater to their particular needs.

Database 130

Database Cloud Hardware Storage 130

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 177

DevOps Analytics Storage Metrics 177

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 174

IoT Analytics Database Metrics 174

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 180

Analytics Infrastructure Storage Efficiency 180

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 130

Database Metrics Retail Analytics 130

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 217

Analytics Cloud Java Serverless 217

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 189

Data Engineering Engineering Entertainment Big Data 189

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 237

Media Traffic Processing Design 237

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 200

Analytics Mobile Performance Monitoring 200

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 255

Analytics Storage Infrastructure Scalability 255

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 135

Analytics Metrics IoT Monitoring 135

Dynatrace

MARCH 29, 2024

Dynatrace offers essential analytics and automation to keep applications optimized and businesses flourishing. By seamlessly integrating observability, AI-driven insights, and data analytics, organizations can overcome common obstacles such as operational inefficiencies, performance bottlenecks, and scalability concerns.

Google 254

Google Innovation Cloud Analytics 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 192

Infrastructure Database Monitoring Metrics 192

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 247

Open Source Tuning Analytics Scalability 247

Dynatrace

FEBRUARY 1, 2024

But organizations must also be aware of the pitfalls of AI: security and compliance risks, biases, misinformation, and lack of insight into critical metrics (including availability, code development, infrastructure, databases, and more). After updating the query to ask for log data, the engineer was able to identify attack attempts.

Artificial Intelligence 179

Artificial Intelligence Analytics Efficiency Database 179

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 243

Metrics Analytics Storage Monitoring 243

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 137

Analytics Mobile Airlines Monitoring 137

Dynatrace

MAY 17, 2023

OpenTelemetry , the open source observability tool, has become the go-to standard for instrumenting custom applications to collect observability telemetry data. For this third and final part of our series, we saved the best for last: How you can enhance telemetry data even more and with less effort on your end with Dynatrace OneAgent.

Metrics 166

Metrics Monitoring Database Network 166

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. SAP Basis teams have established best practices for managing their SAP systems.

Java 182

Java Analytics Best Practices Monitoring 182

Scalegrid

JANUARY 8, 2024

The partnership between AI and cloud computing brings about transformative trends like enhanced security through intelligent threat detection, real-time analytics, personalization, and the implementation of edge computing for quicker on-site decision-making.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

MARCH 20, 2024

These could include issues with vulnerable and outdated components, injections, and software and data integrity failures. This approach can determine malicious activity and block it by monitoring the flow of data within the application, all the way from the user to the database.

Monitoring 204

Monitoring Analytics Traffic Best Practices 204

DZone

SEPTEMBER 26, 2023

If your environment is like many others, it can often seem like your systems produce logs filled with a bunch of excess data. Since you need to access multiple components (servers, databases, network infrastructure, applications, etc.) Though it can feel like more trouble than it’s worth, sorting through logs is crucial.

Best Practices 249

Best Practices Analytics Infrastructure Network 249

DZone

MAY 19, 2023

Logs often take up the majority of a company's data assets. Examples of logs include business logs (such as user activity logs) and Operation and Maintenance logs of servers, databases, and network or IoT devices. Logs are the guardian angel of business.

IoT 130

IoT Analytics Network Database 130

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?

Cache 90

Cache Efficiency Database Monitoring 90

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