OverOps

MAY 15, 2019

Technical debt is bound to accumulate at every company, whether it’s a mammoth Enterprise or a bright-eyed AI-Machine-Learning-Blockchain startup. Microservices to the rescue? Microservices allow us to redesign and rewrite critical elements within a codebase in parallel to the old methods and code that’s currently in use.

Microservices 273

Microservices Weak Development Team How To Architecture 273

OverOps

JULY 1, 2019

This includes insight into which deployment or microservice an error came from, historical context around when an issue was first or last seen, correlation with system metrics, insight into the source code and state of related variables and more.

Weak Development Team 250

Weak Development Team Artificial Inteligence How To Analysis 250

Netflix Tech

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

System 90

System Machine Learning Artificial Inteligence Training 90

TechCrunch

OCTOBER 7, 2021

The underlying large-scale metrics storage technology they built was eventually open sourced as M3. Mao and co-founder Rob Skillington (CTO) founded Chronosphere on the back of early work that they started at Uber, where they built an observability platform very specific to Uber’s needs as a business.

Cloud 209

Cloud Sport Open Source Machine Learning 209

CircleCI

NOVEMBER 18, 2021

AIOps is an approach to managing the exponential growth of IT operations and the complexity of new technology through the application of artificial intelligence (AI). AIOps uses machine learning and big data to assist IT operations. Take cloud misconfiguration, for example.

Artificial Inteligence 52

Artificial Inteligence Weak Development Team Artificial Intelligence Machine Learning 52

xmatters

JANUARY 11, 2023

AIOps is the application of sophisticated analytics like natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) to automate, enhance, and optimize IT operations and workflows. Some of these metrics include CPU use, memory use, disk space use, and network bandwidth.

Artificial Inteligence 52

Artificial Inteligence Metrics Systems Review Machine Learning 52

xmatters

JANUARY 11, 2023

AIOps is the application of sophisticated analytics like natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) to automate, enhance, and optimize IT operations and workflows. Some of these metrics include CPU use, memory use, disk space use, and network bandwidth.

Artificial Inteligence 52

Artificial Inteligence Metrics Systems Review Machine Learning 52

Apiumhub

SEPTEMBER 14, 2022

This edition is still in the making and you can still submit your CFP, we are preparing our Talk about Christian Ciceri’s chapter of the book “ Software Architecture Metrics ”: Private Builds and Metrics: Tools for Surviving DevOps Transitions. <React Global> Online Summit (November 8-9).

Software 65

Software DevOps Architecture Blockchain 65

Netflix Tech

JUNE 7, 2021

Flow Exporter The Flow Exporter is a sidecar that uses eBPF tracepoints to capture TCP flows at near real time on instances that power the Netflix microservices architecture. The Flow Exporter also publishes various operational metrics to Atlas. These metrics are visualized using Lumen , a self-service dashboarding infrastructure.

Network 130

Network IPv6 Transportation AWS 130

Apiumhub

JUNE 13, 2023

Software Development Experts Interviews Inma Navas Our first interview of “Talks with Software Development Experts,” was with Inma Navas, a software engineer and the winner of our Software Architecture Metrics book giveaway. She also shared with us the aspects she would like to improve or learn this year.

Software Development 65

Software Development Software Review Software Development 65

O'Reilly Media - Ideas

MAY 1, 2019

Get hands-on training in machine learning, blockchain, cloud native, PySpark, Kubernetes, and many other topics. Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. AI and machine learning.

Course 46

Course Training Artificial Inteligence Machine Learning 46

Kentik

JANUARY 31, 2023

Network monitoring tools use various techniques for data gathering, including polling, collecting metrics from network devices, and scraping traffic logs. This data may include performance metrics and resource usage of the devices, as well as the applications and services running on them.

Network 105

Network Analysis Data Center Metrics 105

O'Reilly Media - Ideas

APRIL 3, 2019

Learn new topics and refine your skills with more than 150 new live online training courses we opened up for April and May on the O'Reilly online learning platform. AI and machine learning. Deep Learning from Scratch , April 19. Beginning Machine Learning with Pytorch , May 1. Blockchain.

Course 48

Course Artificial Inteligence Training Google Cloud 48

Netflix Tech

OCTOBER 19, 2020

Distributed Tracing: the missing context in troubleshooting services at scale Prior to Edgar, our engineers had to sift through a mountain of metadata and logs pulled from various Netflix microservices in order to understand a specific streaming failure experienced by any of our members. Trace Instrumentation: how will it impact our service?

Infrastructure 93

Infrastructure Microservices Systems Review Storage 93

Netflix Tech

OCTOBER 18, 2019

As with other traditional machine learning and deep learning paths, a lot of what the core algorithms can do depends upon the support they get from the surrounding infrastructure and the tooling that the ML platform provides. they were able to reframe the problem as a straight-forward black-box optimization problem.

Metrics 50

Metrics Policies Infrastructure Architecture 50

Netflix Tech

MAY 21, 2019

In our quest to be objective, scientific, and inline with the Netflix philosophy of using data to drive solutions for intriguing problems, we proceeded by leveraging machine learning. The metrics relevant to the training and recommendation process are reported to Atlas and visualized using Netflix’s Lumen.

Testing 65

Testing Training Continuous Integration AWS 65

Hu's Place - HitachiVantara

JANUARY 10, 2019

Hitachi’s developers are reimagining core systems as microservices, building APIs using modern RESTful architectures, and taking advantage of robust, off-the-shelf API management platforms. There are 77 performance metrics that we can provide via REST API over IP connections.

Data Center 73

Data Center Strategy Data Storage 73

CIO

JANUARY 26, 2023

The dashboard produces a collection of infographics that make it possible to study each microservice or API and determine just how much it costs to keep it running in times of high demand and low. AppDynamics also offers a proprietary machine learning engine to turn historical data into a plan for efficient deployment.

Tools 290

Tools Cloud Artificial Inteligence Artificial Intelligence 290

Netflix Tech

OCTOBER 18, 2019

As with other traditional machine learning and deep learning paths, a lot of what the core algorithms can do depends upon the support they get from the surrounding infrastructure and the tooling that the ML platform provides. they were able to reframe the problem as a straight-forward black-box optimization problem.

Metrics 40

Metrics Policies Infrastructure Architecture 40

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. In this report about how people are using O’Reilly’s learning platform, we’ll see how patterns are beginning to shift.

Trends 117

Trends Technical Review Technology Artificial Inteligence 117

AWS Machine Learning - AI

FEBRUARY 1, 2024

Full stack generative AI Although a lot of the excitement around generative AI focuses on the models, a complete solution involves people, skills, and tools from several domains. Consider the following picture, which is an AWS view of the a16z emerging application stack for large language models (LLMs).

Generative AI 108

Generative AI Disaster Recovery Artificial Inteligence AWS 108

Cloudera

JULY 18, 2022

For each transaction, NiFi makes a call to a production model in Cloudera Machine Learning (CML) to score the fraud potential of the transaction. It has a vibrant open source community that has always focused on solving the difficult streaming use cases with high throughput and extreme low latency.

Analytics 93

Analytics Data Applications System 93

OverOps

AUGUST 1, 2018

We’ve learned a lot along the way, and have grown an incredible customer base that uses the product and have been instrumental in shaping it into the offering it is today. Containers and microservices have become a default standard for the way we architect new applications. Developers love the code-aware insight that only we deliver.

DevOps 37

DevOps Microservices Machine Learning Artificial Inteligence 37

BPM

JANUARY 18, 2019

The current Artificial Intelligence (AI) fascination is unfortunately completely biased on Deep Neural Networks (DNN) and Machine Learning (ML) for everything. The microservice movement will reignite the need for orchestration. Some analyst is bound to rename BPM engines to Microservice Orchestration Engines (MOE).wait

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Honeycomb

FEBRUARY 16, 2024

APM brings this level of metric rigor to applications, recording uptime, requests received, statuses returned, latency, and resource usage for each running process. Typically, APM includes performance metrics, error detection, and—this is the ‘if you’re lucky’ part—distributed traces. Time-series metrics become very expensive.

Performance 84

Performance Applications Metrics Artificial Inteligence 84

Netflix Tech

OCTOBER 16, 2019

By Ammar Khaku Introduction In a microservice architecture such as Netflix’s, propagating datasets from a single source to multiple downstream destinations can be challenging. Data model 1 topic -> many versions The top-level construct in Gutenberg is a “topic”. for example to train machine-learned models.

Microservices 75

Microservices Weak Development Team Machine Learning Artificial Inteligence 75

O'Reilly Media - Ideas

MARCH 1, 2023

Methodology This report is based on our internal “units viewed” metric, which is a single metric across all the media types included in our platform: ebooks, of course, but also videos and live training courses. Not only was this a large category, but it also grew significantly: 26% from 2021 to 2022. growth over 2021.

Trends 135

Trends Technical Review Technology Software Review 135

OverOps

AUGUST 14, 2018

This especially becomes a stress point with the introduction of microservices. Enriching Splunk with Machine Data from OverOps. We can help developers troubleshoot more quickly, give metric and insight to DevOps to gauge the overall quality of software and fuel some new AIOps initiative.

Data 189

Data How To Metrics Artificial Intelligence 189

Netflix Tech

APRIL 29, 2019

One example is the Spectator Python client library, a library for instrumenting code to record dimensional time series metrics. data access, fact logging and feature extraction, model evaluation and publishing). The Metrics Repo is a Python framework based on PyPika that allows contributors to write reusable parameterized SQL queries.

Artificial Inteligence 111

Artificial Inteligence Machine Learning Open Source Infrastructure 111

Honeycomb

JUNE 14, 2022

Metrics – Aggregate measures tracked over time. You see, there are these things called traces, metrics, and logs, which are data about your programs that come in specific formats. I think most vendors in the observability space have an “underpants gnomes” approach to observability: Collect traces, metrics, and logs.

Weak Development Team 98

Weak Development Team Metrics System Tools 98

Altexsoft

APRIL 22, 2021

When you’re employing a lot of APIs to digitize, adopt a microservices architecture, or build your business strategy around APIs, you need to control not just one aspect of your APIs, but their full life cycle, including such tasks as: Defining API schemas and publishing them. When you’re adopting a microservices architecture.

Microservices 64

Microservices Weak Development Team Analytics Azure 64

Netflix Tech

NOVEMBER 12, 2019

Page Simulation for Better Offline Metrics at Netflix by David Gevorkyan , Mehmet Yilmaz , Ajinkya More , Gaurav Agrawal , Richard Wellington , Vivek Kaushal , Prasanna Padmanabhan , Justin Basilico At Netflix, we spend a lot of effort to make it easy for our members to find content they will love.

Metrics 49

Metrics Travel Machine Learning Artificial Inteligence 49

Confluent

FEBRUARY 13, 2019

Comparing persistence models. Do I need to use a microservices framework? Core function: Building the event streaming model for item bid activity and analytics. reactive microservices) and Lagom (an opinionated, reactive microservice framework). Do I need to use a microservices framework?

Architecture 88

Architecture Programming Microservices Serverless 88

Modus Create

JUNE 20, 2023

You can think of them as microservices but for UI. Artificial intelligence Search results for “AI” over the past five years (24 Feb 2023) Okay, I agree that “AI” and “ML” often serve as fillers on these kinds of lists. Imagine a music streaming app like Spotify. If any part of the app goes down, the entire app can fail.

Trends 98

Trends Development Serverless Technical Review 98

Netflix Tech

AUGUST 13, 2020

A metric crossed a threshold. Telltale learns what constitutes typical health for an application, no alert tuning required. Metrics are a key part of understanding application health. But sometimes you can have too many metrics, too many graphs, and too many dashboards. Client metrics and QoE changes. By Andrei U.,

Applications 84

Applications Systems Review Technical Review Metrics 84

Netflix Tech

NOVEMBER 12, 2019

Page Simulation for Better Offline Metrics at Netflix by David Gevorkyan , Mehmet Yilmaz , Ajinkya More , Gaurav Agrawal , Richard Wellington , Vivek Kaushal , Prasanna Padmanabhan , Justin Basilico At Netflix, we spend a lot of effort to make it easy for our members to find content they will love.

Metrics 40

Metrics Travel Machine Learning Artificial Inteligence 40

Netflix Tech

NOVEMBER 12, 2019

Page Simulation for Better Offline Metrics at Netflix by David Gevorkyan , Mehmet Yilmaz , Ajinkya More , Gaurav Agrawal , Richard Wellington , Vivek Kaushal , Prasanna Padmanabhan , Justin Basilico At Netflix, we spend a lot of effort to make it easy for our members to find content they will love.

Metrics 40

Metrics Travel Machine Learning Artificial Inteligence 40