Dynatrace

JUNE 26, 2023

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

Software 183

Software Software Analytics Big Data 183

The Morning Paper

DECEMBER 13, 2020

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. Dynamic approaches schedule block processing on the fly to maximise efficiency. ACM Computing Surveys, Dec.

Big Data 83

Big Data Open Source Processing Analytics 83

Scalegrid

FEBRUARY 8, 2024

It utilizes methodologies like DStore, which takes advantage of underused hard drive space by using it for storing vast amounts of collected datasets while enabling efficient recovery processes. This strategy reduces the volume needed during retrieval operations.

Storage 130

Storage Systems Big Data Azure 130

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. Individual samplers need to be built to be high throughput and memory efficient.

Big Data 57

Big Data Analytics Latency Azure 57

High Scalability

SEPTEMBER 14, 2020

This is a guest post by Limor Maayan-Wainstein , a senior technical writer with 10 years of experience writing about cybersecurity, big data, cloud computing, web development, and more. High performance computing (HPC) enables you to solve complex problems which cannot be solved by regular computing. What Is HPC?

Cloud 261

Cloud Big Data Virtualization Efficiency 261

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. APM can also be referred to as: Application performance management. Performance monitoring. Dynatrace news. Application monitoring.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data warehouses.

Artificial Intelligence 205

Artificial Intelligence Analytics Storage Government 205

The Netflix TechBlog

OCTOBER 28, 2021

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. Moreover, its petabyte scale also brings unique engineering challenges.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis and Memcached both provide high performance with sub-millisecond response times. Managed DBaaS solutions like ScaleGrid.io

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. IT automation tools can achieve enterprise-wide efficiency. Read eBook now!

Artificial Intelligence 185

Artificial Intelligence Tuning Strategy Big Data 185

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Finally, we show that Seer can identify application level design bugs, and provide insights on how to better architect microservices to achieve predictable performance. ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. past 3 hours or 10 days).

Processing 210

Processing Big Data Efficiency Engineering 210

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. “The weakness of a data lake is they fail when you need to access them fast,” Pawlowski said.

Analytics 183

Analytics Infrastructure Storage Efficiency 183

Dynatrace

JANUARY 11, 2023

With more organizations taking the multicloud plunge, monitoring cloud infrastructure is critical to ensure all components of the cloud computing stack are available, high-performing, and secure. These next-generation cloud monitoring tools present reports — including metrics, performance, and incident detection — visually via dashboards.

Cloud 219

Cloud Monitoring Best Practices Infrastructure 219

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. However, this cannot be done without efficient, scalable data analytics.

Big Data 111

Big Data Analytics AWS Cloud 111

Dynatrace

OCTOBER 4, 2022

Several pain points have made it difficult for organizations to manage their data efficiently and create actual value. Limited data availability constrains value creation. Traditional solutions and approaches are inefficient given the number of manual tasks that are required for effective log data ingest. Create filters.

Analytics 230

Analytics Artificial Intelligence Storage Serverless 230

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

Artificial Intelligence 281

Artificial Intelligence Cloud Innovation Strategy 281

Dynatrace

OCTOBER 25, 2022

Organizations adopt DevOps, where developers and operations work together in a continuous loop, so they can develop software and resolve issues efficiently before they affect users. This meant there were still operations, only they were performed by someone else!

DevOps 213

DevOps Big Data Cloud Innovation 213

The Netflix TechBlog

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

Dynatrace

DECEMBER 15, 2022

The primary goal of ITOps is to provide a high-performing, consistent IT environment. Organizations measure these factors in general terms by assessing the usability, functionality, reliability, and performance of products and services. Performance. What does IT operations do? ITOps vs. AIOps.

Artificial Intelligence 198

Artificial Intelligence DevOps Hardware Virtualization 198

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. Effortlessly optimize Azure database performance. Database-service views provide all the metrics you need to set up high-performance database services. Azure Front Door.

Azure 146

Azure Cloud Big Data Virtualization 146

Dynatrace

MARCH 14, 2022

The healthcare industry is embracing cloud technology to improve the efficiency, quality, and security of patient care, and this year’s HIMSS Conference in Orlando, Fla., AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively.

Healthcare 224

Healthcare Artificial Intelligence Innovation Strategy 224

Dynatrace

FEBRUARY 16, 2023

As observability and security data converge in modern multicloud environments, there’s more data than ever to orchestrate and analyze. The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes.

Analytics 182

Analytics Innovation Metrics Database 182

The Netflix TechBlog

JULY 26, 2021

Operational Reporting is a reporting paradigm specialized in covering high-resolution, low-latency data sets, serving detailed day-to-day activities¹ and processes of a business domain. At Netflix Studio, teams build various views of business data to provide visibility for day-to-day decision making. tactical) in nature.

Big Data 253

Big Data Government Analytics Processing 253

Dynatrace

MARCH 24, 2023

Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. Apache Mesos with the Marathon DC/OS is popular for large-scale production clusters running existing workloads on big data systems, such as Hadoop, Kafka, and Spark.

Infrastructure 182

Infrastructure Open Source Operating System Cloud 182

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 203

Storage Latency Efficiency Data Engineering 203

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. The sidecar has been implemented by leveraging the highly performant eBPF along with carefully chosen transport protocols to consume less than 1% of CPU and memory on any instance in our fleet.

Network 325

Network Transportation AWS Cloud 325

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. APM can be referred to as: Application performance monitoring. Application performance management. Performance monitoring. Dynatrace news.

Artificial Intelligence 181

Artificial Intelligence Social Media Monitoring IoT 181

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. These limitations create an opportunity for real-time device tracking to fill the gap.

IoT 78

IoT Analytics Big Data Architecture 78

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. Alert fatigue and chasing false positives are not only efficiency problems. Execute an action plan.

DevOps 192

DevOps Artificial Intelligence Healthcare Innovation 192

Percona

JANUARY 19, 2023

While the technologies have evolved and matured enough, there are still some people thinking that MySQL is only for small projects or that it can’t perform well with large tables. With disks being faster nowadays and CPU and memory resources being cheaper, we could easily say MySQL can handle TBs of data with good performance.

Open Source 87

Open Source Storage Database Big Data 87

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. This is required for understanding how I intend to improve the efficiency of (manual) alert ticket handling. The raw event and problem data from Dynatrace for analysis stored in InfluxDB. But that didn’t work for me.

Tuning 262

Tuning Architecture Monitoring Big Data 262

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202

Java Scalability Traffic Architecture 202

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. Jason Lowe-Power (UC Davis) discussed smart memory management and the need for an efficient interface for it.

Latency 52

Latency Hardware Cache Architecture 52

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. Orchestration The Big Data Orchestration team is responsible for providing all of the services and tooling to schedule and execute ETL and Adhoc pipelines.

Open Source 279

Open Source Network Infrastructure Big Data 279

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166