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. These next-generation cloud monitoring tools present reports — including metrics, performance, and incident detection — visually via dashboards.

Cloud 222

Cloud Monitoring Best Practices Infrastructure 222

The Netflix TechBlog

MAY 4, 2023

The second phase involves migrating the traffic over to the new systems in a manner that mitigates the risk of incidents while continually monitoring and confirming that we are meeting crucial metrics tracked at multiple levels. The batch job creates a high-level summary that captures some key comparison metrics.

Traffic 339

Traffic Latency Tuning Systems 339

Dynatrace

OCTOBER 4, 2022

Even in cases where all data is available, new challenges can arise. When one tool monitors logs, but traces, metrics, security, audit, observability, and business data sources are siloed elsewhere or monitored using other tools, teams can struggle to align or deliver a single version of the truth.

Analytics 233

Analytics Artificial Intelligence Storage Serverless 233

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. To do this effectively, you need a big data processing approach. Segregation of data by mobile and desktop. Dynatrace news. 28-day lookbacks.

Traffic 263

Traffic Metrics Mobile Analytics 263

Dynatrace

SEPTEMBER 9, 2019

JavaScript errors are emotionless with simple data points of metrics. And it’s easy to ignore or argue metrics because they can’t argue back. I still love data, but I am starting to love emotion-filled data. Big” data helps us make the right decisions and focus on the right things.

Big Data 148

Big Data Metrics Virtualization Monitoring 148

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. Database-service views provide all the metrics you need to set up high-performance database services. See the health of your big data resources at a glance.

Azure 147

Azure Cloud Big Data Virtualization 147

DZone

AUGUST 4, 2022

Spark-Radiant will help optimize performance and cost considering catalyst optimizer rules, enhance auto-scaling in Spark, collect important metrics related to a Spark job, Bloom filter index in Spark, etc. Spark-Radiant is Apache Spark Performance and Cost Optimizer. Spark-Radiant is now available and ready to use.

Performance 246

Performance Metrics Availability Big Data 246

Dynatrace

APRIL 20, 2023

Using Grail to heal observability pains Grail logs not only store big data, but also map out dependencies to enable fast analytics and data reasoning. Business leaders can decide which logs they want to use and tune storage to their data needs. Seamless integration. Fast, precise answers. ” Watch session now!

Analytics 186

Analytics Infrastructure Storage Efficiency 186

Dynatrace

AUGUST 14, 2023

Metrics like the net promoter score (NPS) or customer satisfaction (CSAT) score encapsulate this kind of customer feedback into measurable analytics. Dynatrace enables organizations to understand user behavior with big data analytics based on gap-free data, eliminating the guesswork involved in understanding the user experience.

Analytics 228

Analytics Social Media Website IoT 228

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. The deviating metric is response time. Let’s say, for example, an application is experiencing a slowdown in receiving its search requests.

DevOps 195

DevOps Artificial Intelligence Healthcare Innovation 195

Dynatrace

SEPTEMBER 15, 2020

The integration with Dynatrace has two sides: first, it pulls metrics from Dynatrace while Akamas is executing an experiment. This data then flows into their AI and Machine Learning Engine to decide which configurations to change next: Akamas pulls in full stack Dynatrace data to make configuration change decisions for upcoming experiments.

Performance 185

Performance Java Metrics Cloud 185

Dynatrace

JANUARY 16, 2023

In general, metrics collectors and providers are most common, followed by log and tracing projects. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch. Across all categories in the Kubernetes survey, open source projects rank among the most frequently used solutions.

Open Source 342

Open Source Java Operating System Programming 342

Dynatrace

DECEMBER 15, 2022

ITOps teams use more technical IT incident metrics, such as mean time to repair, mean time to acknowledge, mean time between failures, mean time to detect, and mean time to failure, to ensure long-term network stability. In general, you can measure the business value of ITOps by evaluating the following: Usability. ITOps vs. AIOps.

Artificial Intelligence 201

Artificial Intelligence DevOps Hardware Virtualization 201

Dynatrace

APRIL 19, 2023

.” Accelerating maturity with Business Insights Partnering with Dynatrace Business Insights has resulted in on-demand, automated real user monitoring (RUM) and end-to-end observability of their high-value, big-money players, including key metrics, session replay , and monthly reporting.

Entertainment 157

Entertainment Analytics Healthcare Games 157

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. But AIOps also improves metrics that matter to the bottom line. What is AIOps, and how does it work? For example: Greater IT staff efficiency.

Artificial Intelligence 284

Artificial Intelligence Cloud Innovation Strategy 284

The Netflix TechBlog

JUNE 7, 2021

The Flow Exporter also publishes various operational metrics to Atlas. These metrics are visualized using Lumen , a self-service dashboarding infrastructure. The runtime behavior of the Flow Exporter can be dynamically managed by configuration changes via Fast Properties. So how do we ingest and enrich these flows at scale ?

Network 325

Network Transportation AWS Cloud 325

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.” This means data sources typically come from disparate infrastructure monitoring tools and second-generation APM solutions.

Artificial Intelligence 211

Artificial Intelligence DevOps Innovation Metrics 211

Dynatrace

JUNE 29, 2022

A hybrid cloud, however, combines public infrastructure and services with on-premises resources or a private data center to create a flexible, interconnected IT environment. Hybrid environments provide more options for storing and analyzing ever-growing volumes of big data and for deploying digital services.

Infrastructure 181

Infrastructure Cloud Azure AWS 181

Scalegrid

MARCH 14, 2024

Workloads from web content, big data analytics, and artificial intelligence stand out as particularly well-suited for hybrid cloud infrastructure owing to their fluctuating computational needs and scalability demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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. Writing memos is a big part of Netflix culture, which I’ve found has been helpful for sharing ideas, soliciting feedback, and documenting project details.

Analytics 223

Analytics Education Innovation Engineering 223

Dynatrace

JUNE 1, 2020

Dynatrace provides out-of-the box complete observability for dynamic cloud environment, at scale and in-context, including metrics, logs, traces, entity relationships, UX and behavior in a single platform. With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. Advanced Cloud Observability.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

Dynatrace

APRIL 11, 2023

This includes collecting metrics, logs, and traces from all applications and infrastructure components. One key to augmenting DevSecOps collaboration is to take a platform approach that converges observability and security with big data analytics that can scale without compromising data fidelity.

Cloud 186

Cloud DevOps Open Source Retail 186

Dynatrace

JUNE 1, 2020

Dynatrace provides out-of-the box complete observability for dynamic cloud environment, at scale and in-context, including metrics, logs, traces, entity relationships, UX and behavior in a single platform. With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. Advanced Cloud Observability.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

The Netflix TechBlog

MARCH 2, 2021

I started working at a local payment processing company after graduation, where I built survival models to calculate lifetime value and experimented with them on our brand new big data stack. I was doing data science without realizing it. Data scientists can take on any aspect of an experimentation project.

Analytics 207

Analytics C++ Innovation Engineering 207

All Things Distributed

NOVEMBER 15, 2016

The cost and complexity to implement, scale, and use BI makes it difficult for most companies to make data analysis ubiquitous across their organizations. QuickSight is a cloud-powered BI service built from the ground up to address the big data challenges around speed, complexity, and cost. Enter Amazon QuickSight.

Analytics 152

Analytics Availability Media Social Media 152

Highly Scalable

MAY 1, 2012

On the other hand, when one is interested only in simple additive metrics like total page views or average price of conversion, it is obvious that raw data can be efficiently summarized, for example, on a daily basis or using simple in-stream counters. what is the cardinality of the data set)? Heavy Hitters: Stream-Summary.

Analytics 191

Analytics Traffic Big Data Efficiency 191

SQL Server According to Bob

JANUARY 15, 2020

The metrics collection showed the ~5 hour gap and the more troubleshooting I did the more it was clear that every pod on the same node encountered the same paused ​​ behavior. ​​​​ Bob Dorr.

Servers 40

Servers Metrics Big Data Operating System 40

Rigor

JANUARY 13, 2020

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. How to pioneer new metrics and create a culture of performance. Time is Money. High Performance Websites.

Performance 75

Performance Social Media Website Website Performance 75

The Netflix TechBlog

OCTOBER 15, 2019

Operating Delta applications is made simple for users as the framework provides resilience and failure tolerance out of the box and collects many granular metrics that can be used for alerts. Optimization can be made in a way that is transparent to users, and bugs can be fixed without requiring any changes to user code (UDFs).

Transportation 192

Transportation Architecture Processing Storage 192

All Things Distributed

AUGUST 22, 2011

Amazon Cloudwatch can be used to get detailed metrics about the performance of the Cache Nodes. Driving down the cost of Big-Data analytics. Scaling the total memory in the Cache Cluster is under complete control of the customers as Caching Nodes can be added and deleted on demand. No Server Required - Jekyll & Amazon S3.

Cloud 117

Cloud Cache AWS Storage 117

Rigor

SEPTEMBER 11, 2019

Developers representing hundreds of companies work together at these meetups to become masters in performance metrics and the latest trends in measuring site speed.) And, of course, you should follow him on Twitter @ igrigorik for in-depth insights on web performance metrics, user experience, and industry news. Maximiliano Firtman.

Performance 89

Performance Education Google Website 89

Highly Scalable

MARCH 10, 2015

Although these problems are very different, we are trying to establish a common framework that helps to design optimization and data mining tasks required for solutions. Moreover, gross margin is not the only performance metric that is important for retailers. The gross margin metric, in the sense it is used in the equations (1.2)

Retail 152

Retail C++ Analytics Metrics 152

The Netflix TechBlog

APRIL 29, 2019

One example is the Spectator Python client library, a library for instrumenting code to record dimensional time series metrics. 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

The Netflix TechBlog

JULY 26, 2021

A daily process ranks the records by timestamp to generate a data frame of compacted records. Old data files are overwritten with a set of new data files that contain only the compacted data. Data Quality Data Mesh provides metrics and dashboards at both the processor and pipeline level for operational observability.

Big Data 253

Big Data Government Analytics Processing 253

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

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

Smashing Magazine

JULY 29, 2019

This metric is a little difficult to comprehend, so here’s an example: if the average cost of broadband packages in a country is $22, and the average download speed offered by the packages is 10 Mbps, then the cost ‘per megabit per month’ would be $2.20. For reference, the metric is $1.19 in the UK and $1.26 in the USA.

Cache 96

Cache Google Mobile Network 96