Immutable Infrastructure

DZone

You may also like: Gaining a Systemic View of Immutable Infrastructure Tooling. devops performance integration docker openshift immutable openshift container immutable infrastructure deployments deployment solutionMake your infrastructure.immutable?

Byte Down: Making Netflix’s Data Infrastructure Cost-Effective

The Netflix TechBlog

cloud-storage data data-infrastructure aws netflixBy Torio Risianto, Bhargavi Reddy, Tanvi Sahni, Andrew Park Continue reading on Netflix TechBlog ».

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Expand application and infrastructure observability with operational insights into Kubernetes pods

Dynatrace

In Kubernetes environments, operating and successfully running your production applications and microservices requires getting additional insights into your Kubernetes infrastructure including the cluster, nodes, and pods that encapsulate and run the apps. Dynatrace news.

Monitoring of Kubernetes Infrastructure for day 2 operations

Dynatrace

One of the promises of container orchestration platforms is to make i t easier for the developers to accelerate the deployment of their app lication s without having to worry about scalability and infrastructure dependencies. Dynatrace news.

Infrastructure monitoring for enterprise cloud – 4 key requirements

Dynatrace

If you’re doing it right, cloud represents a fundamental change in how you build, deliver and operate your applications and infrastructure. And that includes infrastructure monitoring. This also implies a fundamental change to the role of infrastructure and operations teams.

Davis AI now detects infrastructure availability issues as root cause

Dynatrace

But what happens if a service work perfectly but the underlying infrastructure, such as processes and hosts, experience an outage? Davis combines APM incident and impact detection with infrastructure monitoring root-cause detection at the process and host level. Dynatrace news.

Extend infrastructure observability with JMX Extensions and additional full-stack metrics

Dynatrace

Infrastructure exists to support the backing services that are collectively perceived by users to be your web application. Issues that manifest themselves as performance degradation on a user’s device can often be traced back to underlying infrastructure issues. Dynatrace news.

Uber Infrastructure in 2019: Improving Reliability, Driving Customer Satisfaction

Uber Engineering

Architecture General Engineering CPU Infrastructure Observability Productivity Reliability Search Infrastructure Storage Uber Eats Velocity

The Importance of Validating the Testing Infrastructure

Abstracta

The post The Importance of Validating the Testing Infrastructure appeared first on Abstracta Software Testing Services. Performance Engineering Software Testing Performance Performance Testing test infrastructure

Scaling Infrastructure Management with Grail

Uber Engineering

To build and maintain infrastructure at scale, easy access to the current state of the system is paramount. As Uber’s business continues to expand, our infrastructure has grown in size and complexity, making it more difficult to get all the … The post Scaling Infrastructure Management with Grail appeared first on Uber Engineering Blog.

How to Build a Distributed Load Testing Infrastructure with AWS, Docker, and JMeter

DZone

Before we get into the tutorial hands-on, I would like to mention that this topic is not new. It has been covered in various helpful articles like the ones from TestAutomationGuru.

Extend the AI and automation core of Dynatrace with host extensions to resolve infrastructure problems

Dynatrace

So that we can expand our coverage of infrastructure-related problems, we plan to work on more built-in infrastructure extensions, available out of the box with Dynatrace. Looking for ways to solve some of your infrastructure-related problems? Dynatrace news.

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Mapping micro-services interactions, entities from real time infrastructure, and ML infrastructure and other non traditional data stores are few such examples.

How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

Central engineering teams enable this operational model by reducing the cognitive burden on innovation teams through solutions related to securing, scaling and strengthening (resilience) the infrastructure. All these micro-services are currently operated in AWS cloud infrastructure.

IaaS vs PaaS: Infrastructure as a Service VS Platform as a Service

DZone

Infrastructure as a service. To begin with, many businesses are going online. They are relying heavily on the cloud to facilitate their clients, which demands to collect, storing, and processing a vast amount of data before it can be presented to the end-user as information.

Gandalf: an intelligent, end-to-end analytics service for safe deployment in cloud-scale infrastructure

The Morning Paper

Gandalf: an intelligent, end-to-end analytics service for safe deployment in cloud-scale infrastructure , Li et al., NSDI’20. Modern software systems at scale are incredibly complex ever changing environments.

Components of Effective Software Monitoring: App Logs, Infrastructure Telemetry, Health-Check Reports

DZone

At Logicify , we are proud to be software monitoring geeks. We love to monitor both the apps we develop and the ones we use internally. Not because they are sloppy. Not because we don’t trust our code.

Scaling for Growth: A Q&A with Uber’s VP of Core Infrastructure, Matthew Mengerink

Uber Engineering

As the Vice President of Engineering for Uber’s Core Infrastructure group, Matthew Mengerink faces a daunting task. He oversees 350 engineers across four teams tasked with not only maintaining the platform on which 3,500 microservices run, but also figuring out … The post Scaling for Growth: A Q&A with Uber’s VP of Core Infrastructure, Matthew Mengerink appeared first on Uber Engineering Blog.

Update to Chrome 73 and infrastructure upgrade

Dareboost

It will include an update to Chrome 73, a revised access management policy for detailed reports and a technical architecture revamped to meet the growing needs of our … Continue reading Update to Chrome 73 and infrastructure upgrade → Service UpdatesAfter several months of intensive work (and a new coffee machine), we are pleased to announce the next update of our service: June 13th (03:00 AM UTC).

ScaleGrid DigitalOcean Support for MySQL, PostgreSQL and Redis™ Now Available

Scalegrid

The open source model is not only popular with the developer market, but also enterprise companies looking to modernize their infrastructure and reduce spend. PALO ALTO, Calif.,

Comparing PostgreSQL DigitalOcean Performance & Pricing – ScaleGrid vs. DigitalOcean Managed Databases

Scalegrid

As an open source database, it’s a highly popular choice for enterprise applications looking to modernize their infrastructure and reduce their total cost of ownership, along with startup and developer applications looking for a powerful, flexible and cost-effective database to work with. ScaleGrid for PostgreSQL is architectured to leverage-high performance SSD disks on DigitalOcean, and is finely tuned and optimized to achieve the best performance on DigitalOcean infrastructure.

Eliminate inefficiencies and innovate faster by optimizing hybrid mainframe environments on IBM Z

Dynatrace

With the release of Dynatrace 1.194, we’ve added CPU related infrastructure metrics for LPARs (host metrics) and regions (process metrics) and expanded our multidimensional analysis to IBM Z systems, including CICS, IMS, and the CICS transaction gateway. . Dynatrace news.

ScaleGrid DBaaS Expands MySQL Hosting Services Through AWS Cloud

Scalegrid

Over the years, migrating data to the cloud has become a top priority for organizations looking to modernize their infrastructure for improved security, performance, and agility, closely followed by the trending shift from commercial database management systems to open source databases.

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Hyper Scale VPC Flow Logs enrichment to provide Network Insight

The Netflix TechBlog

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. data-engineering cloud-networking big-data cloud-infrastructure netflix

Follower Clusters – 3 Major Use Cases for Syncing SQL & NoSQL Deployments

Scalegrid

This helps save massively on infrastructure costs. Follower clusters are a ScaleGrid feature that allows you to keep two independent database systems (of the same type) in sync. Unlike cloning or replication, this allows you to maintain an active, point-in-time copy of your production data. This extra cluster, known as a follower cluster, can be leveraged for multiple use cases, including for analyzing, optimizing and testing your application performance for MongoDB , MySQL and PostgreSQL.

How to Improve MySQL AWS Performance 2X Over Amazon RDS at The Same Cost

Scalegrid

As organizations continue to migrate to the cloud, it’s important to get in front of performance issues, such as high latency, low throughput, and replication lag with higher distances between your users and cloud infrastructure. AWS is the #1 cloud provider for open-source database hosting, and the go-to cloud for MySQL deployments.

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Everything as Code

Dynatrace

And, this is even more apparent due to the ever-increasing infrastructure complexity enterprises are dealing with. On-demand infrastructure: The ability to deploy infrastructure whenever it’s required. Dynatrace news.

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Intro to Redis Cluster Sharding – Advantages, Limitations, Deploying & Client Connections

High Scalability

Redis Cluster is the native sharding implementation available within Redis that allows you to automatically distribute your data across multiple nodes without having to rely on external tools and utilities. At ScaleGrid, we recently added support for Redis Clusters on our platform through our fully managed Redis hosting plans.

MySQL High Availability Framework Explained – Part III: Failover Scenarios

High Scalability

In this three-part blog series, we introduced a High Availability (HA) Framework for MySQL hosting in Part I, and discussed the details of MySQL semisynchronous replication in Part II.

2019 PostgreSQL Trends Report: Private vs. Public Cloud, Migrations, Database Combinations & Top Reasons Used

High Scalability

PostgreSQL is an open source object-relational database system that has soared in popularity over the past 30 years from its active, loyal, and growing community. For the 2nd year in a row, PostgreSQL has kept the title of #1 fastest growing database in the world according to the DBMS of the Year report by the experts at DB-Engines. So what makes PostgreSQL so special, and how is it being used today?

Follower Clusters – 3 Major Use Cases for Syncing SQL & NoSQL Deployments

High Scalability

Here are a few critical ways in which it differs from replication: Analytics Cluster Appliction monitoring Cloning Clustering Database Database Development Database Reporting Database Testing DevOps Follower Cluster MongoDB Monitoring MySQL Postgres Production Data Replication admin analytics best platform cluster clusters database database replication database scalability databases deployment infrastructure mysql mysql cluster mysql load optimization postgresql replication sql testing

M3: Uber’s Open Source, Large-scale Metrics Platform for Prometheus

Uber Engineering

As part of our robust and scalable metrics infrastructure, we built … The post M3: Uber’s Open Source, Large-scale Metrics Platform for Prometheus appeared first on Uber Engineering Blog. Architecture Open Source Grafana Infrastructure M3 M3 Coordinator M3DB Metrics Platform OSS Prometheus Uber Infrastructure

Self-Host Your Static Assets

CSS Wizardry

One of the quickest wins—and one of the first things I recommend my clients do—to make websites faster can at first seem counter-intuitive: you should self-host all of your static assets, forgoing others’ CDNs/infrastructure.

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Uber’s Data Platform in 2019: Transforming Information to Intelligence

Uber Engineering

Architecture Uber Data Big Data Data Analytics Data Platform EoY Infrastructure Product Platform Uber Engineering

2019 Open Source Database Report: Top Databases, Public Cloud vs. On-Premise, Polyglot Persistence

Scalegrid

Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Cloud Infrastructure Analysis : Public Cloud vs. On-Premise vs. Hybrid Cloud. Cloud Infrastructure Breakdown by Database. Now, let’s take a look at the cloud infrastructure setup breakdown by database management systems. So, which cloud infrastructure is right for you? Average Number of Database Types Used by Infrastructure.

Real-World Effectiveness of Brotli

CSS Wizardry

They were either running their own infrastructure and installing and deploying Brotli everywhere proved non-trivial, or they were using a CDN who didn’t have readily available support for the new algorithm.

Employing QUIC Protocol to Optimize Uber’s App Performance

Uber Engineering

Architecture Mobile bufferbloat Cronet HTTP/2 HTTP/3 Infrastructure Internet Engineering Task Force mobile engineering QUIC retransmission timeout Transmission Control Protocol Uber MobileUber operates on a global scale across more than 600 cities, with our apps relying entirely on wireless connectivity from over 4,500 mobile carriers.

Less is More: Engineering Data Warehouse Efficiency with Minimalist Design

Uber Engineering

Architecture Uber Data Big Data Data Engineering Data Infrastructure data science Data Warehouse Engineering EfficiencyMaintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage.

Scaling Uber’s Apache Hadoop Distributed File System for Growth

Uber Engineering

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis. Architecture Apache Hadoop Big Data Big Data Analysis Garbage Collection Hadoop Hadoop Distributed File System Hadoop Infra & Analytics Team HBase HDFS HDFS Federation HIVE Hoodie Infrastructure JAR Jenkins NameNode PRC Puppet Router-based Federation Uber Uber Data Foundation Team Uber Engineering View File System WebHDFS YARN

Databook: Turning Big Data into Knowledge with Metadata at Uber

Uber Engineering

Architecture Uber Data Cassandra Data Management Data Storage Data Warehouse Databook Dropwizard Gradle HDFS HIVE Infrastructure Kafka Metadata MySQL Postgres Quartz Queryparser RESTful API Uber Uber Data Knowledge Uber Engineering VerticaFrom driver and rider locations and destinations, to restaurant orders and payment transactions, every interaction on Uber’s transportation platform is driven by data.

Introducing QALM, Uber’s QoS Load Management Framework

Uber Engineering

Architecture CoDel CPU critical request Goroutine graceful degradation Infrastructure Jaeger load management load shedding Memory overload detector QALM QoS Quality of Service ridesharing RPC layer Uber for Business Uber Freight UberFx YARPCMuch of Uber’s business involves connecting people with people, making the reliability of our customer platform crucial to our success. The customer platform supports everything from ridesharing and Uber Eats , to Uber Freight and Uber for Business.

Aarhus Engineering Internship: Building Aggregation Support for YQL, Uber’s Graph Query Language for Grail

Uber Engineering

Architecture Culture Aarhus Aarhus University Denmark Grail Infrastructure Lau Skorstengaard Ph.D. Lau Skorstengaard is a Ph.D. student at Aarhus University who pursued a 2018 internship with Uber Engineering’s Aarhus, Denmark office.

Code Migration in Production: Rewriting the Sharding Layer of Uber’s Schemaless Datastore

Uber Engineering

Architecture Data Store Datastore Design Flask Frontless Go Golang Goroutine Infra Infrastructure Mezzanine NGINX Python Schemaless Sharding Uber Uber Engineering uWSGIIn 2014, Uber Engineering built Schemaless , our fault-tolerant and scalable datastore, to facilitate the rapid growth of our company. For context, we deployed more than 40 Schemaless instances and many thousands of storage nodes in 2016 alone.