Dynatrace

OCTOBER 4, 2022

However, cloud infrastructure has become increasingly complex. Further, the delivery infrastructure that makes this happen has also become complex. Traditionally, though, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

Analytics 204

Analytics Software Software Storage 204

Dynatrace

FEBRUARY 15, 2023

A modern observability and analytics platform brings data silos together and facilitates collaboration and better decision-making among teams. Here are some examples: IT infrastructure and operations. To tame this complexity and optimize cloud operations, teams across the organization need to manage and explore their data effectively.

Analytics 130

Analytics Storage Cloud DevOps 130

Dynatrace

FEBRUARY 2, 2023

Exploding volumes of business data promise great potential; real-time business insights and exploratory analytics can support agile investment decisions and automation driven by a shared view of measurable business goals. Traditional observability solutions don’t capture or analyze application payloads. What’s next?

Analytics 215

Analytics Metrics DevOps Storage 215

The Netflix TechBlog

OCTOBER 19, 2020

Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

Infrastructure 236

Infrastructure Transportation Storage Open Source 236

Dynatrace

SEPTEMBER 5, 2024

Native support for syslog messages extends our infrastructure log support to all Linux/Unix systems and network devices. Customers can also proactively address issues using Davis AI’s predictive analytics capabilities by analyzing network log content, such as retries or anomalies in performance response times.

Innovation 273

Innovation AWS Analytics Storage 273

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. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 222

Analytics Monitoring Artificial Intelligence DevOps 222

Dynatrace

JULY 29, 2021

With extended contextual analytics and AIOps for open observability, Dynatrace now provides you with deep insights into every entity in your IT landscape, enabling you to seamlessly integrate metrics, logs, and traces—the three pillars of observability. Dynatrace extends its unique topology-based analytics and AIOps approach.

Analytics 246

Analytics Open Source Serverless Architecture 246

Dynatrace

FEBRUARY 16, 2023

Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says. Logs on Grail Log data is foundational for any IT analytics. Grail and DQL will give you new superpowers.”

Analytics 199

Analytics Innovation Metrics Database 199

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 253

Analytics Storage Infrastructure Scalability 253

Dynatrace

JANUARY 12, 2022

Messaging systems are typically implemented as lightweight storage represented by queues or topics. We’ve introduced brand-new analytics capabilities by building on top of existing features for messaging systems. Start your free trial today for best-in-class APM, infrastructure monitoring, and AIOps, all in a single solution.

Analytics 200

Analytics Systems DevOps Healthcare 200

Dynatrace

OCTOBER 4, 2022

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues.

Analytics 234

Analytics Storage Infrastructure Metrics 234

Dynatrace

NOVEMBER 4, 2024

Metadata enrichment improves collaboration and increases analytic value. The Dynatrace® platform continues to increase the value of your data — broadening and simplifying real-time access, enriching context, and delivering insightful, AI-augmented analytics. Our Business Analytics solution is a prominent beneficiary of this commitment.

Analytics 157

Analytics Airlines Metrics Monitoring 157

The Netflix TechBlog

OCTOBER 8, 2024

The Key-Value Abstraction offers a flexible, scalable solution for storing and accessing structured key-value data, while the Data Gateway Platform provides essential infrastructure for protecting, configuring, and deploying the data tier. We do not use it for metrics, histograms, timers, or any such near-real time analytics use case.

Latency 236

Latency Storage Traffic Tuning 236

The Netflix TechBlog

SEPTEMBER 18, 2024

Vidhya Arvind , Rajasekhar Ummadisetty , Joey Lynch , Vinay Chella Introduction At Netflix our ability to deliver seamless, high-quality, streaming experiences to millions of users hinges on robust, global backend infrastructure. The KV data can be visualized at a high level, as shown in the diagram below, where three records are shown.

Latency 248

Latency Storage Cache Efficiency 248

Dynatrace

APRIL 28, 2023

This means compromising between keeping data available as long as possible for analysis while juggling the costs and overhead of storage, archiving, and retrieval. Infrastructure teams may need to work with host logs from recent months or quarters.

Analytics 226

Analytics Storage Infrastructure Metrics 226

Dynatrace

OCTOBER 4, 2022

Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. Unlike data warehouses, however, data is not transformed before landing in storage. A data lakehouse provides a cost-effective storage layer for both structured and unstructured data. Query language.

Artificial Intelligence 222

Artificial Intelligence Storage Analytics Government 222

Dynatrace

OCTOBER 4, 2022

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. High-performance analytics—no indexing required.

Artificial Intelligence 278

Artificial Intelligence Analytics Storage Architecture 278

Dynatrace

APRIL 8, 2024

Optimize the IT infrastructure supporting risk management processes and controls for maximum performance and resilience. The IT infrastructure, services, and applications that enable processes for risk management must perform optimally. Once teams solidify infrastructure and application performance, security is the subsequent priority.

Analytics 214

Analytics Infrastructure Efficiency Technology 214

DZone

JUNE 4, 2019

NVMe Storage Use Cases. NVMe storage's strong performance, combined with the capacity and data availability benefits of shared NVMe storage over local SSD, makes it a strong solution for AI/ML infrastructures of any size. There are several AI/ML focused use cases to highlight.

Storage 100

Storage Artificial Intelligence FinTech Performance 100

DZone

NOVEMBER 27, 2023

An open-source distributed SQL query engine, Trino is widely used for data analytics on distributed data storage. Optimizing Trino to make it faster can help organizations achieve quicker insights and better user experiences, as well as cut costs and improve infrastructure efficiency and scalability. But how do we do that?

Tuning 162

Tuning Speed Performance Open Source 162

Dynatrace

APRIL 20, 2023

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. They enable IT teams to identify and address the precise cause of application and infrastructure issues.

Analytics 201

Analytics Infrastructure Storage Architecture 201

Scalegrid

MAY 13, 2020

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. What Exactly is Greenplum? At a glance – TLDR.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

SEPTEMBER 5, 2023

They handle complex infrastructure, maintain service availability, and respond swiftly to incidents. By analyzing patterns and trends, predictive analytics helps identify potential issues or opportunities, enabling proactive actions to prevent problems or capitalize on advantageous situations. Proactive resource allocation.

Artificial Intelligence 271

Artificial Intelligence DevOps Analytics Engineering 271

Dynatrace

JUNE 6, 2023

Container Network Interface (CNI) provides a common way to seamlessly integrate various technologies with the underlying Kubernetes infrastructure. Traditional storage solutions were not created to address these requirements, which are common among modern deployments. AI-powered analytics. Acceleration of innovation.

Open Source 206

Open Source Storage Analytics Innovation 206

Dynatrace

SEPTEMBER 8, 2022

Log management is an organization’s rules and policies for managing and enabling the creation, transmission, analysis, storage, and other tasks related to IT systems’ and applications’ log data. Most infrastructure and applications generate logs. Comparing log monitoring, log analytics, and log management.

Cloud 196

Cloud Systems Analytics DevOps 196

Dynatrace

JUNE 9, 2023

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. From a technical perspective, however, cloud-based analytics can be challenging. That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth.

DevOps 196

DevOps Analytics Storage Metrics 196

Dynatrace

NOVEMBER 6, 2023

As an example, many retailers already leverage containerized workloads in-store to enhance customer experiences using video analytics or streamline inventory management using RFID tracking for improved security. The challenge of cloud-native observability at the enterprise edge In aggregate, connected devices generate huge volumes of data.

Retail 272

Retail Storage Analytics Cloud 272

Dynatrace

OCTOBER 23, 2023

Secondly, determining the correct allocation of resources (CPU, memory, storage) to each virtual machine to ensure optimal performance without over-provisioning can be difficult. Firstly, managing virtual networks can be complex as networking in a virtual environment differs significantly from traditional networking.

Efficiency 227

Efficiency Virtualization Hardware Performance 227

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. Enable the storage types, select Add property.

Analytics 141

Analytics Mobile Airlines Monitoring 141

Dynatrace

AUGUST 21, 2023

Traditional log management solution challenges Survey data suggests that teams need a modern approach to log management and analytics, which requires a unified log management solution. Organizations can be more agile when they have access to real-time data about their IT infrastructure. during 2021–2026.

Analytics 150

Analytics Innovation Infrastructure Scalability 150

Dynatrace

JANUARY 4, 2024

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. It starts with implementing data governance practices, which set standards and policies for data use and management in areas such as quality, security, compliance, storage, stewardship, and integration.

Government 213

Government Analytics Benchmarking Storage 213

Dynatrace

JUNE 27, 2023

Many AWS services and third party solutions use AWS S3 for log storage. We hear from our customers how important it is to have a centralized, quick, and powerful access point to analyze these logs; hence we’re making it easier to ingest AWS S3 logs and leverage Dynatrace Log Management and Analytics powered by Grail.

AWS 212

AWS Cloud Lambda Analytics 212

Dynatrace

OCTOBER 2, 2024

Whether it’s cloud applications, infrastructure, or even security events, this capability accelerates time to value by surfacing logs that provide the crucial context of what occurred just before an error line was logged. With Dynatrace, there is no need to think about schema and indexes, re-hydration, or hot/cold storage concepts.

Azure 187

Azure DevOps Infrastructure Cloud 187

Dynatrace

MAY 19, 2023

For cloud operations teams, network performance monitoring is central in ensuring application and infrastructure performance. If the network is sluggish, an application may also be slow, frustrating users. Worse, a malicious attacker may gain access to the network, compromising sensitive application data.

Network 228

Network Monitoring Performance Traffic 228

Dynatrace

NOVEMBER 20, 2023

How this data-driven technique gives foresight to IT teams – blog By analyzing patterns and trends, predictive analytics enables teams to take proactive actions to prevent problems or capitalize on opportunities. A modern observability platform enables teams to gain the benefits of cloud infrastructure while retaining visibility.

AWS 221

AWS Artificial Intelligence Cloud Analytics 221

Dynatrace

JUNE 14, 2024

Dynatrace, operated from Tokyo, addresses the data residency needs of the Japanese market Dynatrace operates its AI-powered unified platform for observability, security, and business analytics as a SaaS solution in 19 worldwide regions on three hyperscalers (AWS, Azure, and GCP). trillion yen into its Japanese cloud infrastructure by 2027.

AWS 238

AWS Government Azure Healthcare 238

Dynatrace

OCTOBER 3, 2024

Easy access to exception details in the context of a full trace for exception analysis Expanded log insights for your applications Only Dynatrace enables true and unified observability across all ingested logs, including infrastructure components and hyperscalers providing backend services or cloud-native frontend applications.

Performance 259

Performance Architecture Innovation Latency 259