Scalegrid

FEBRUARY 8, 2024

Consequently, if any node happens to fail, the remaining ones provide continued access to the saved information without risking service interruptions or permanent data loss. These distributed storage services also play a pivotal role in big data and analytics operations.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

OCTOBER 4, 2022

Generally, the storage technology categorizes data into landing, raw, and curated zones depending on its consumption readiness. The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. Support diverse analytics workloads.

Artificial Intelligence 205

Artificial Intelligence Analytics Storage Government 205

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. At Dynatrace Perform 2023 , Maciej Pawlowski, senior director of product management for infrastructure monitoring at Dynatrace, and a senior software engineer at a U.K.-based

Analytics 184

Analytics Infrastructure Storage Efficiency 184

The Netflix TechBlog

JANUARY 13, 2022

This blog will explore these two systems and how they perform auto-diagnosis and remediation across our Big Data Platform and Real-time infrastructure. Furthermore, data in Kafka streams have a finite retention period, which adds time pressure for resolving the issues to avoid data loss.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

Dynatrace

DECEMBER 15, 2022

The primary goal of ITOps is to provide a high-performing, consistent IT environment. The roles and responsibilities of ITOps team members include the following: A system administrator configures servers, installs applications, monitors the health of the system, and fixes and upgrades hardware. Performance. Functionality.

Artificial Intelligence 198

Artificial Intelligence DevOps Hardware Virtualization 198

Dynatrace

JULY 6, 2022

Monitoring and logging are fundamental building blocks of observability. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming. Similarly, digital experience monitoring is another ongoing process that lends itself to IT automation.

Artificial Intelligence 185

Artificial Intelligence Tuning Strategy Big Data 185

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 181

Artificial Intelligence Social Media Monitoring IoT 181

Dynatrace

APRIL 21, 2021

In February 2021, Dynatrace announced full support for Google’s Core Web Vitals metrics , which will help site owners as they start optimizing Core Web Vitals performance for SEO. Not everyone has expertise in performance optimization and how it can impact SEO. To do this effectively, you need a big data processing approach.

Traffic 262

Traffic Metrics Mobile Analytics 262

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

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 282

Artificial Intelligence Cloud Innovation Strategy 282

Dynatrace

JULY 6, 2020

In addition to providing AI-powered full-stack monitoring capabilities , Dynatrace has long featured broad support for Azure Services and intuitive, native integration with extensions for using OneAgent on Azure. Effortlessly optimize Azure database performance. See the health of your big data resources at a glance.

Azure 146

Azure Cloud Big Data Virtualization 146

Dynatrace

MARCH 24, 2023

This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. 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

Dynatrace

APRIL 11, 2023

Today’s organizations face increasing pressure to keep their cloud-based applications performing and secure. As data from different corners of the enterprise proliferates, teams need a better way to bring data together to identify performance and security issues, minimize security risk, and drive greater business value.

Cloud 183

Cloud DevOps Open Source Retail 183

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. Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems.

Network 325

Network Transportation AWS Cloud 325

Scalegrid

MARCH 14, 2024

Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands. On-Premises Data Center A hybrid cloud architecture necessitates that an organization retains full authority over its physical or virtual infrastructure within the private cloud segment.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 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

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. CloudOps: Applying AIOps to multicloud operations. Execute an action plan. The deviating metric is response time.

DevOps 192

DevOps Artificial Intelligence Healthcare Innovation 192

Rigor

JANUARY 13, 2020

Reading time 1 min Why share the library of the web performance books while there’s a substantial collection of fantastic websites and articles on the net? High Performance Browser Networking. This book is about performance problems and the various technologies created to fight them. High Performance Websites.

Performance 75

Performance Social Media Website Website Performance 75

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

DZone

MAY 5, 2021

Anytime, every time or sometime you would have heard someone going around with data analysis and saying maybe this could have happened because of this, maybe users did not like the feature or maybe we were wrong all the time. Any analysis and prediction in data analytics across industries experience what I call maybe syndrome.

Analytics 195

Analytics Testing Big Data Code 195

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.” A comprehensive, modern approach to AIOps is a unified platform that encompasses observability, AI, and analytics.

Artificial Intelligence 208

Artificial Intelligence DevOps Innovation Metrics 208

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. Since this analysis must be performed offline in batch jobs, it cannot respond to immediate issues and is restricted to assessing overall fleet performance.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Testsigma

FEBRUARY 12, 2021

The latest trend in hyperautomation – Gartner projects that by the year 2023, 25% of tasks by the organisations will be able to perform autonomously and hence reducing the cost. The DevOps workflow is strongly connected to continuous monitoring activities aimed to maximise the consistency of the product and eliminate corporate risk.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. Analytical databases are optimized for a low number of slow queries.

Database 40

Database Analytics Blockchain Healthcare 40

The Netflix TechBlog

JULY 26, 2021

Such a paradigm aspires to assist front-line operations personnel and stakeholders in “running the business”²; performing their tasks through means such as ad hoc analysis, decision-support, and tracking (of tasks, assets, schedules, etc). Data Mesh leverages Iceberg tables as data warehouse sinks for downstream analytics use cases.

Big Data 253

Big Data Government Analytics Processing 253

The Netflix TechBlog

APRIL 29, 2019

The service that orchestrates failover uses numpy and scipy to perform numerical analysis, boto3 to make changes to our AWS infrastructure, rq to run asynchronous workloads and we wrap it all up in a thin layer of Flask APIs. CORE The CORE team uses Python in our alerting and statistical analytical work.

Open Source 279

Open Source Network Infrastructure Big Data 279

The Netflix TechBlog

NOVEMBER 20, 2023

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing. append, overwrite, etc.).

Processing 210

Processing Big Data Efficiency Engineering 210

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