Dynatrace

FEBRUARY 1, 2024

Business and technology leaders are increasing their investments in AI to achieve business goals and improve operational efficiency. By packaging [these capabilities] into hypermodal AI, we are able to run deep custom analytics use cases in sixty seconds or less.”

Artificial Intelligence 186

Artificial Intelligence Analytics Efficiency Database 186

Scalegrid

JANUARY 8, 2024

Discover how AI is reshaping the cloud and what this means for the future of technology. Key Takeaways AI integration in cloud computing increases operational efficiency by automating processes, optimizing resource allocation, and improving scalability, leading to cost savings and allowing IT teams to concentrate on strategic initiatives.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

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. The sheer number of permutations can break traditional databases. What is DevOps maturity?

DevOps 184

DevOps Analytics Storage Metrics 184

Dynatrace

FEBRUARY 1, 2024

Any problem, such as a simple software update overburdening a critical database, can cause a ripple effect that degrades the performance of dependent services or applications. For example, an unnoticed database strain could slow down the response time of a web frontend, resulting in poor user experience.

Infrastructure 181

Infrastructure Metrics Network Monitoring 181

Dynatrace

OCTOBER 7, 2020

Seamlessly report and be alerted on non-topology-related custom metrics, using Dynatrace as a metric database. Topology metrics are related to specific entities in your Smartscape topology (for example, the number of successful and failed batch jobs processed by a host). Topology and non-topology metrics—what’s the difference?

Metrics 245

Metrics Analytics Storage Monitoring 245

Dynatrace

JANUARY 31, 2024

It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security. While off-the-shelf models assist many organizations in initiating their journeys with generative AI (GenAI), scaling AI for enterprise use presents formidable challenges.

Cache 204

Cache Azure Infrastructure Monitoring 204

ScaleOut Software

AUGUST 5, 2020

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

Analytics 69

Analytics Azure Processing Speed 69

VoltDB

FEBRUARY 28, 2018

And the landscape will only become more crowded as the world’s largest companies work through the R&D process. At first glance, it may seem like a new type of database. However, a closer look shows that blockchain and translytical databases are better together. Blockchain as a Database Isn’t Enough for the Enterprise.

Blockchain 45

Blockchain Technology Technology Database 45

Dynatrace

AUGUST 28, 2023

Let’s shift our focus to the backend systems and business processes, the behind-the-scenes heroes of end-to-end customer experience. These retail-business processes must work together efficiently to orchestrate customer satisfaction: Inventory management ensures you can anticipate and meet dynamic customer demand.

Retail 202

Retail Logistics Innovation Analytics 202

VoltDB

FEBRUARY 28, 2018

And the landscape will only become more crowded as the world’s largest companies work through the R&D process. At first glance, it may seem like a new type of database. However, a closer look shows that blockchain and translytical databases are better together. Blockchain as a Database Isn’t Enough for the Enterprise.

Blockchain 40

Blockchain Technology Technology Database 40

High Scalability

JANUARY 11, 2022

We will use a graph database such as Neo4j to store the information. Additionally, we can use columnar databases like Cassandra to store information like user feeds, activities, and counters. There are two major processes which gets executed when a user posts a photo on Instagram. System Components. Component Design. API Design.

Design 334

Design Media Storage Logistics 334

The Netflix TechBlog

JULY 15, 2021

In this post, Kevin talks about his extensive experience in content analytics at Netflix since joining more than 10 years ago. What keeps me engaged and enjoying data engineering is giving super-suits and adrenaline shots to analytics engineers and data scientists. What drew you to Netflix?

Data Engineering 189

Data Engineering Engineering Entertainment Big Data 189

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance.

Big Data 154

Big Data Processing Lambda Database 154

Dynatrace

SEPTEMBER 30, 2021

As an AWS Advanced Technology Partner , this was a great opportunity for Dynatrace developers to sharpen their AWS skills and pursue or up-level their Amazon certifications. Major cloud providers such as AWS offer certification programs to help technology professionals develop and mature their cloud skills. Data analytics.

AWS 209

AWS Best Practices Analytics Cloud 209

Scalegrid

JANUARY 11, 2024

Key Takeaways Cloud security monitoring is a comprehensive approach involving both manual and automated processes to oversee servers, applications, platforms, and websites, using tools that are customized to fit unique cloud architectures. Get ready for actionable insights that balance technical depth with practical advice.

Best Practices 130

Best Practices Cloud Monitoring Strategy 130

Dynatrace

FEBRUARY 8, 2021

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Dynatrace news. Logs provide information you can’t find anywhere else.

Cloud 259

Cloud Azure Analytics AWS 259

Dynatrace

SEPTEMBER 12, 2022

This placement recognizes Dynatrace’s focus on customers and pushing the art of what’s possible in AI and automation as it’s applied to observability, security, and business analytics. Dynatrace’s core technologies, such as OneAgent , receive data from everything along your application delivery. Why is Dynatrace ahead of the pack?

Strategy 130

Strategy DevOps Analytics Cloud 130

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

DECEMBER 21, 2023

A structured approach Reducing carbon emissions involves a combination of technology, practice, and planning. And while these examples were resolved by just asking a few questions, in many cases, the answers are more elusive, requiring real-time and historical drill-downs into the processes and dependencies specific to each host.

Cloud 209

Cloud Energy Best Practices Cache 209

High Scalability

NOVEMBER 23, 2018

has been a key to success in many technological endeavors and to lead in many scientific domains. Waqas Dhillon : The goal of in-database machine learning is to bring popular machine learning algorithms and advanced analytical functions directly to the data, where it most commonly resides – either in a data warehouse or a data lake.

Internet 174

Internet Internet Scalability Analytics 174

Dynatrace

JULY 6, 2020

In addition to providing visibility for core Azure services like virtual machines, load balancers, databases, and application services, we’re happy to announce support for the following 10 new Azure services, with many more to come soon: Virtual Machines (classic ones). Effortlessly optimize Azure database performance.

Azure 148

Azure Cloud Big Data Virtualization 148

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. Hadoop is quickly becoming the preferred tool for this type of large scale data analytics.

Big Data 111

Big Data Analytics AWS Cloud 111

Dynatrace

MAY 1, 2023

With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.

Analytics 188

Analytics Artificial Intelligence Big Data Open Source 188

Dynatrace

OCTOBER 4, 2022

IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. With a data and analytics approach that focuses on performance without sacrificing cost, IT pros can gain access to answers that indicate precisely which service just went down and the root cause. Don’t reinvent the wheel.

Analytics 191

Analytics Software Software Storage 191

Dynatrace

FEBRUARY 16, 2023

The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity.

Analytics 186

Analytics Innovation Metrics Database 186

ScaleOut Software

APRIL 6, 2021

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. This simplifies the installation process and ensures portability across operating systems.

IoT 52

IoT Azure Analytics Healthcare 52

ScaleOut Software

NOVEMBER 24, 2020

Here’s a typical telematics architecture for processing telemetry from a fleet of trucks: Each truck today has a microprocessor-based sensor hub which collects key telemetry, such as vehicle speed and acceleration, engine parameters, trailer parameters, and more. ” “How long has the driver been on the road?”

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Dynatrace

SEPTEMBER 17, 2019

Cluster and container Log Analytics. Their technology stack looks like this: Spring Boot-based Microservices. In order to filter these dashboards by tenant all they need is a Dynatrace Management Zone , which is based on meta data extracted by Dynatrace from e.g. k8s tags, container labels or process environment variables.

AWS 127

AWS Monitoring Ecommerce Lambda 127

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. This application cannot be implemented by most streaming analytics platforms. A database service to host state information for each user. Can the web front end process notifications (which involve recursive chaining) without impacting responsiveness?

Development 52

Development Analytics Database Programming 52

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. This application cannot be implemented by most streaming analytics platforms. A database service to host state information for each user. Can the web front end process notifications (which involve recursive chaining) without impacting responsiveness?

Development 52

Development Analytics Database Programming 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require. It’s not enough to just pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.

Logistics 52

Logistics Retail Analytics Azure 52

Dynatrace

NOVEMBER 18, 2021

Logs include critical information that can’t be found elsewhere, like details on transactions, processes, users, and environment changes. With PurePath ® distributed tracing and analysis technology at the code level, Dynatrace already provides the deepest possible insights into every transaction.

Analytics 224

Analytics Cloud Java Serverless 224

Scalegrid

DECEMBER 6, 2023

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 as a Service (DBaaS) and managed databases offer distinct advantages along with certain challenges.

Database 130

Database Cloud Hardware Storage 130

The Netflix TechBlog

JANUARY 10, 2024

Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. The Netflix video processing pipeline went live with the launch of our streaming service in 2007. The Netflix video processing pipeline went live with the launch of our streaming service in 2007.

Processing 229

Processing Media Latency Innovation 229

Dynatrace

JANUARY 6, 2020

In a pilot project, the system will likely be analyzing a narrow set of technologies, processing data that’s typically static and confined when compared with the dynamism of full production environments. But these environments rarely have a chance to expose the limitations that lead to intellectual debt. The result?

Artificial Intelligence 145

Artificial Intelligence Efficiency Analytics Innovation 145