DZone

JANUARY 19, 2023

Because with the advent of cloud providers, we are less worried about managing data centers. This leads to an increase in the size of data as well. Big data is generated and transported using various mediums in single requests. Everything is available within seconds on-demand. We need to cut down on transportation.

Best Practices 255

Best Practices Transportation Big Data Latency 255

Dynatrace

MAY 1, 2023

In addition to improved IT operational efficiency at a lower cost, ITOA also enhances digital experience monitoring for increased customer engagement and satisfaction. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.

Analytics 188

Analytics Artificial Intelligence Big Data Open Source 188

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. 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

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 188

Software Software Analytics Big Data 188

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

DZone

DECEMBER 27, 2023

In this kickoff post, we delve into the intricacies of Apache Airflow and AWS EMR, a managed cluster platform for big data processing. Working together, they form the backbone of many modern data engineering solutions.

Best Practices 130

Best Practices Data Engineering Big Data Games 130

Alex Podelko

DECEMBER 19, 2019

Boris has unique expertise in that area – especially in Big Data applications. Marrying Artificial Intelligence and Automation to Drive Operational Efficiencies by Priyanka Arora, Asha Somayajula, Subarna Gaine, Mastercard. How to select appropriate IT Infrastructure to support Digital Transformation by Boris Zibitsker, BEZNext.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

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. When coupled with the cloud, HPC is made more affordable, accessible, efficient and shareable. What Is HPC?

Cloud 261

Cloud Big Data Virtualization Efficiency 261

Uber Engineering

AUGUST 14, 2019

Maintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility?

Efficiency 110

Efficiency Engineering Design Storage 110

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. You can learn more about it from my talk at the Flink forward conference.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

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 112

Big Data Analytics AWS Scalability 112

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 189

Artificial Intelligence Tuning Strategy Big Data 189

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 209

Artificial Intelligence Storage Analytics Government 209

Scalegrid

MARCH 28, 2024

Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup. On the other hand, an append-only file ensures data safety by recording every write operation that modifies the dataset, allowing for complete data reconstruction in the event of a restart. Data transfer technology.

Cache 130

Cache Storage Scalability Architecture 130

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 188

Analytics Infrastructure Storage Efficiency 188

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

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. He meant that more and more developers are now becoming responsible for operations, and operations are becoming ingrained in developers’ job descriptions.

DevOps 218

DevOps Big Data Cloud Innovation 218

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.

Analytics 235

Analytics Artificial Intelligence Storage Serverless 235

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: Greater IT staff efficiency. What is AIOps, and how does it work? million per year by automating key processes.

Artificial Intelligence 286

Artificial Intelligence Cloud Innovation Strategy 286

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., ASPLOS’19. When Seer does need to turn on its lower level instrumentation to pinpoint the likely cause of a predicted QoS violation, it has two different modes for doing this.

Big Data 45

Big Data Cloud Performance Hardware 45

Dynatrace

JANUARY 11, 2023

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. What is cloud monitoring? ” The post What is cloud monitoring?

Cloud 223

Cloud Monitoring Best Practices Infrastructure 223

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. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 148

Azure Cloud Big Data Virtualization 148

Dynatrace

DECEMBER 15, 2022

Adding application security to development and operations workflows increases efficiency. AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations. ITOps vs. AIOps.

Artificial Intelligence 203

Artificial Intelligence DevOps Hardware Virtualization 203

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20.

Cloud 104

Cloud Big Data Latency Architecture 104

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 228

Healthcare Artificial Intelligence Innovation Strategy 228

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 186

Infrastructure Open Source Operating System Cloud 186

The Netflix TechBlog

JUNE 1, 2021

clinical data was often small enough to fit into memory on an average computer and only in rare cases would its computation require any technical ingenuity or massive computing power. There was not enough scope to explore the distributed and large-scale computing challenges that usually come with big data processing.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

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. Alert fatigue and chasing false positives are not only efficiency problems. SecOps: Applying AIOps to secure applications in real time.

DevOps 196

DevOps Artificial Intelligence Healthcare Innovation 196

The Netflix TechBlog

SEPTEMBER 18, 2020

I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. They are continuously innovating compression algorithms to efficiently send high quality audio and video files to our customers over the internet. Is the benefit uniform, or do certain cohorts of members?—?such

Analytics 223

Analytics Education Innovation Engineering 223

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

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 186

Analytics Innovation Metrics Database 186

Percona

JANUARY 19, 2023

For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. In this blog post, we will review key topics to consider for managing large datasets more efficiently in MySQL. InnoDB will sort the data in primary key order, and that will serve to reference actual data pages on disk.

Open Source 89

Open Source Storage Database Big Data 89

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. With R (or RStudio) you can efficiently perform analysis on large data sets. But that didn’t work for me.

Tuning 263

Tuning Architecture Monitoring Big Data 263

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

JUNE 7, 2021

The data is also used by security and other partner teams for insight and incident analysis. Summary Providing network insight into the cloud network infrastructure using eBPF flow logs at scale is made possible with eBPF and a highly scalable and efficient flow collection pipeline.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

JUNE 1, 2020

With answers at your fingertips, data backed decisions, and real-time visibility into business KPIs, Dynatrace enables you to consistently deliver better digital business outcomes across all your channels more efficiently than ever before. Dynatrace APM – Named a Leader in APM and yet, we’re much more.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

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.” But what is AIOps, exactly? And how can it support your organization? What is AIOps?

Artificial Intelligence 213

Artificial Intelligence DevOps Innovation Metrics 213