Dynatrace

JULY 6, 2020

With cloud deployments growing rapidly during the past few years and enterprise multi-cloud environments becoming the norm, new challenges have emerged, including: Cloud dynamics make it hard to keep up with autoscaling, where services come and go based on demand. See the health of your big data resources at a glance.

Azure 150

Azure Cloud Big Data Virtualization 150

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. Websites, mobile apps, and business applications are typical use cases for monitoring. Performance monitoring. Application monitoring. Dynatrace news.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Scalegrid

FEBRUARY 8, 2024

Real-World Use Cases of Distributed Storage Distributed storage systems are the backbone of massively scalable storage services, designed to serve both cloud-based and on-premises environments. These systems enable vast amounts of data to be spread over multiple nodes, allowing for simultaneous access and boosting processing efficiency.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

DECEMBER 15, 2022

As more organizations adopt cloud-native technologies, traditional approaches to IT operations have been evolving. Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025.

Artificial Intelligence 208

Artificial Intelligence DevOps Hardware Virtualization 208

Dynatrace

JULY 6, 2022

Scripts and procedures usually focus on a particular task, such as deploying a new microservice to a Kubernetes cluster, implementing data retention policies on archived files in the cloud, or running a vulnerability scanner over code before it’s deployed. Monitoring and logging are fundamental building blocks of observability.

Artificial Intelligence 194

Artificial Intelligence Tuning Strategy Big Data 194

Dynatrace

JULY 5, 2022

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. For example, consider the adoption of a multicloud framework that enables companies to use best-fit clouds for important operational tasks.

Artificial Intelligence 291

Artificial Intelligence Cloud Innovation Strategy 291

Dynatrace

MARCH 24, 2023

By embracing public cloud and hybrid cloud computing environments, IT teams can further accelerate development and automate software deployment and management. Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services.

Infrastructure 191

Infrastructure Open Source Operating System Cloud 191

The Netflix TechBlog

JANUARY 13, 2022

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. This has led to a dramatic reduction in the time it takes to detect issues in hardware or bugs in recently rolled out data platform software.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

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. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

Analytics 193

Analytics Infrastructure Storage Efficiency 193

Dynatrace

OCTOBER 4, 2022

Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. Even in cases where all data is available, new challenges can arise.

Analytics 240

Analytics Artificial Intelligence Storage Serverless 240

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Seer is an online system that observes the behaviour of cloud applications (using the DeathStarBench microservices for the evaluation) and predicts when QoS violations may be about to occur. ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

All Things Distributed

DECEMBER 13, 2016

The British Government is also helping to drive innovation and has embraced a cloud-first policy for technology adoption. The council has deployed IoT Weather Stations in Schools across the City and is using the sensor information collated in a Data Lake to gain insights on whether the weather or pollution plays a part in learning outcomes.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

Dynatrace

OCTOBER 4, 2022

While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses. Data warehouses were the original big data storage option.

Artificial Intelligence 214

Artificial Intelligence Storage Analytics Government 214

Testsigma

MAY 14, 2021

Cloud-based testing has become quite integral these days. Most businesses have already done the shift towards cloud-based testing. With cloud-based testing, everything resides on the cloud and therefore the testing approach also changes where all testing related activities are done on the cloud and IT is delivered as a service.

Cloud 67

Cloud Testing Testing Tools Internet 67

Dynatrace

AUGUST 10, 2021

is Dynatrace’s regional roadshow that gives APAC’s leading CIOs, CDOs, Cloud Architects, IT Operations, DevOps, SRE, and AIOps professionals access to live keynotes and breakout learning sessions with local technical experts to accelerate their digital transformation. Investing in data is easy but using it is really hard”.

DevOps 246

DevOps Innovation Big Data Cloud 246

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. Websites, mobile apps, and business applications are typical use cases for monitoring. APM can be referred to as: Application performance monitoring.

Artificial Intelligence 184

Artificial Intelligence Social Media Monitoring IoT 184

Dynatrace

FEBRUARY 16, 2023

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. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Kubernetes makes spans longer,” Ortner explains.

Analytics 191

Analytics Innovation Metrics Database 191

The Netflix TechBlog

JUNE 7, 2021

At much less than 1% of CPU and memory on the instance, this highly performant sidecar provides flow data at scale for network insight. Challenges The cloud network infrastructure that Netflix utilizes today consists of AWS services such as VPC, DirectConnect, VPC Peering, Transit Gateways, NAT Gateways, etc and Netflix owned devices.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. Analyze the data. AIOps use cases. The goal of AIOps is to automate operations across the enterprise. Execute an action plan.

DevOps 202

DevOps Artificial Intelligence Healthcare Innovation 202

Dynatrace

SEPTEMBER 15, 2020

Stefano started his presentation by showing how much cost and performance optimization is possible when knowing how to properly configure your application runtimes, databases, or cloud environments: Correct configuration of JVM parameters can save up to 75% resource utilization while delivering same or better performance!

Performance 189

Performance Java Metrics Cloud 189

Dynatrace

MARCH 14, 2022

As patient care continues to evolve, IT teams have accelerated this shift from legacy, on-premises systems to cloud technology to more build, test, and deploy software, and fuel healthcare innovation. exemplifies this trend, where cloud transformation and artificial intelligence are popular topics.

Healthcare 232

Healthcare Artificial Intelligence Innovation Strategy 232

All Things Distributed

JANUARY 6, 2016

We believe that with the launch of the Seoul Region, AWS will enable many more enterprise customers in Korea to reduce the cost of their IT operations and innovate faster in critical new areas such as big data analysis, Internet of Things, and more. Many of these enterprises are assisted by our extensive partner ecosystem in Korea.

AWS 110

AWS Cloud Games Latency 110

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” Only deterministic AIOps technology enables fully automated cloud operations across the entire enterprise development lifecycle.

Artificial Intelligence 218

Artificial Intelligence DevOps Innovation Metrics 218

The Netflix TechBlog

APRIL 29, 2019

Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud. Python is also a tool we typically use for automation tasks, data exploration and cleaning, and as a convenient source for visualization work.

Open Source 279

Open Source Network Infrastructure Big Data 279

ScaleOut Software

JULY 19, 2021

And it can maintain contextual information about every data source (like the medical history of a device wearer or the maintenance history of a refrigeration system) and keep it immediately at hand to enhance the analysis.

IoT 78

IoT Analytics Big Data Architecture 78

All Things Distributed

JANUARY 19, 2011

AWS Elastic Beanstalk: A Quick and Simple Way into the Cloud. To battle this complexity, developers who do not need control over the whole software stack often use development platforms that help them manage their application development, deployment and monitoring. All Things Distributed. By Werner Vogels on 18 January 2011 04:00 PM.

AWS 115

AWS Cloud Java Scalability 115

ACM Sigarch

MAY 31, 2023

Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. In the first phase, CXL memory should be transparent to applications without requiring changes, especially in public cloud environments.

Latency 52

Latency Hardware Cache Architecture 52

Testsigma

FEBRUARY 12, 2021

Machine Learning (ML) and Artificial Intelligence (AI) programme testing and QA teams will develop their automatic research techniques, keeping track with recurring updates — with the assistance of analytics and monitoring. Automation Via Distributed Cloud. Try Testsigma and experience the benefits of cloud-based test automation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

All Things Distributed

SEPTEMBER 5, 2013

Over the past few years, two important trends that have been disrupting the database industry are mobile applications and big data. The explosive growth in mobile devices and mobile apps is generating a huge amount of data, which has fueled the demand for big data services and for high scale databases.

Big Data 98

Big Data Mobile Latency Database 98

Testsigma

MAY 26, 2021

Scenarios 1 and 2 are the ones used for end-to-end test automation mostly, and it is advisable to use an end-to-end test automation tool that supports data-driven testing. An example of such a tool is Testsigma , a cloud-based tool that simplifies your test case creation along with your data-driven testing. Conclusion.

Testing 70

Testing Healthcare Performance Testing Website 70

All Things Distributed

FEBRUARY 25, 2011

With the launch of AWS CloudFormation today another important step has been taken in making it easier for customers to deploy applications to the cloud. They also setup Auto Scaling, EC2 and RDS Security Groups, configure CloudWatch monitoring and alarms, and use SNS for notifications. Expanding the Cloud - The AWS Storage Gateway.

AWS 121

AWS Cloud Scalability Storage 121

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

NOVEMBER 24, 2020

At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark. Every few seconds, the application servers collect batches of snapshots and write them to the database where they can be queried by dispatchers managing the fleet.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Brendan Gregg

APRIL 30, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 43

DevOps Network Best Practices Programming 43

Brendan Gregg

APRIL 29, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 40

DevOps Network Best Practices Programming 40