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I have long held very strong opinions about the Critical CSS pattern. In theory, in a perfect world, with all things being equal, it’s demonstrably a Good Idea™. However, in practice, in the real world, it often falls short as a fragile and expensive technique to implement, which seldom provides the benefits that many developers expect. Let’s look at why.
by Jasmine Omeke , Obi-Ike Nwoke , Olek Gorajek Intro This post is for all data practitioners, who are interested in learning about bootstrapping, standardization and automation of batch data pipelines at Netflix. You may remember Dataflow from the post we wrote last year titled Data pipeline asset management with Dataflow. That article was a deep dive into one of the more technical aspects of Dataflow and didn’t properly introduce this tool in the first place.
In this blog post, we will show you a step-by-step guide on how to install and set up a MySQL server both manually on the Ubuntu 20.04 operating system, as well as by using ScaleGrid’s managed database service. In the following sections of this tutorial, we will help you through every step to successfully set […].
Observability is a mindset that lets you use data to answer questions about business processes. In short, collecting as much data as possible from the components of your business — including applications and key business metrics — then using an AI-powered tool to help consolidate and make sense of this huge volume of data gives you observability into your business.
Dynatrace news. Dynatrace Cloud Native Full Stack injection for Kubernetes, now officially released, provides unparalleled flexibility and scale for onboarding teams to AI-powered observability. By taking advantage of native Kubernetes standards, Dynatrace Cloud Native Full Stack injection empowers you to precisely provide the data that your teams need in exceptionally fast and automated ways.
Today, I am publishing the Distributed Computing Manifesto, a canonical document from the early days of Amazon that transformed the architecture of Amazon's ecommerce platform. It highlights the challenges we were facing at the end of the 20th century, and hints at where we were headed.
When I worked at Google, fleet-wide profiling revealed that 25-35% of all CPU time was spent just moving bytes around: memcpy, strcmp, copying between user and kernel buffers in network and disk I/O, hidden copy-on-write in soft page faults, checksumming, compressing, decrypting, assembling/disassembling packets and HTML pages, etc. If data movement were faster, more work could be done on the same processors.
Time-based grouping and aggregation are common in analyzing data using T-SQL—for example, grouping sales orders by year or by week and computing order counts per group. When you apply time-based grouping, you often group the data by expressions that manipulate date and time columns with functions such as YEAR, MONTH, and DATEPART. Such manipulation typically inhibits the optimizer’s ability to rely on index order.
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Time-based grouping and aggregation are common in analyzing data using T-SQL—for example, grouping sales orders by year or by week and computing order counts per group. When you apply time-based grouping, you often group the data by expressions that manipulate date and time columns with functions such as YEAR, MONTH, and DATEPART. Such manipulation typically inhibits the optimizer’s ability to rely on index order.
Today I will share some of the software engineering soft skills I have learned from my first 10 years on Google Chrome, where I am a Senior Staff Engineering Manager
You do not need a bug tracking system. In fact, a bug tracking system is a symptom of a deeper problem—insufficient focus on quality. In general, I fix bugs the moment they appear (not in a drop-everything sense, but as soon as I can get to it—usually within a few hours, but sometimes in a… The post Don’t track bugs, fix them appeared first on Allen Holub.
This is a guest post by Ankit Sirmorya. Ankit is working as a Machine Learning Lead/Sr. Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. Ankit has been working on applying machine learning to solve ambiguous business problems and improve customer experience. For instance, he created a platform for experimenting with different hypotheses on Amazon product pages using reinforcement learning techniques.
If you’ve been a web developer for any reasonable amount of time, you’ve more likely than not come across an async snippet before. At its simplest, it looks a little like this: var script = document. createElement ( ' script ' ); script. src = ' [link] ' ; document. head. appendChild ( script ); Here, we…. create a element…. whose src attribute is [link] …. and append it to the.
By Vadim Filanovsky and Harshad Sane In one of our previous blogposts, A Microscope on Microservices we outlined three broad domains of observability (or “levels of magnification,” as we referred to them)?—?Fleet-wide, Microservice and Instance. We described the tools and techniques we use to gain insight within each domain. There is, however, a class of problems that requires an even stronger level of magnification going deeper down the stack to introspect CPU microarchitecture.
Understanding the Postgres EXPLAIN cost EXPLAIN is very useful for understanding the performance of a Postgres query. It returns the execution plan generated by PostgreSQL query planner for a given statement. The EXPLAIN command specifies whether the tables referenced in a statement will be searched using an index scan or a sequential scan. Some of […].
Image Source. Why Is Kubernetes Performance Tuning Needed? As Kubernetes becomes a basic infrastructure for many organizations, performance tuning for Kubernetes clusters is becoming more important. Kubernetes is a highly scalable open-source platform for orchestrating containerized workloads in server environments. It enables declarative configuration and automation of computing resources.
Kubernetes is used by many organizations to build, deploy, and manage large-scale distributed applications. However, the overwhelming advantage of running applications on Kubernetes comes at a cost. Progressive rollouts, rollbacks, storage orchestration, bin packing, self-healing, cost efficiency, and access to the Cloud Native Computing Foundation (CNCF) ecosystem carry heavy observability challenges.
By: Ankush Gulati , David Gevorkyan Additional credits: Michael Clark , Gokhan Ozer Intro Netflix has more than 220 million active members who perform a variety of actions throughout each session, ranging from renaming a profile to watching a title. Reacting to these actions in near real-time to keep the experience consistent across devices is critical for ensuring an optimal member experience.
This is a guest post by Ankit Sirmorya. Ankit is working as a Machine Learning Lead/Sr. Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. Ankit has been working on applying machine learning to solve ambiguous business problems and improve customer experience. For instance, he created a platform for experimenting with different hypotheses on Amazon product pages using reinforcement learning techniques.
This is a guest post by Ankit Sirmorya. Ankit is working as a Machine Learning Lead/Sr. Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. Ankit has been working on applying machine learning to solve ambiguous business problems and improve customer experience. For instance, he created a platform for experimenting with different hypotheses on Amazon product pages using reinforcement learning techniques.
This is a guest post by Ankit Sirmorya. Ankit is working as a Machine Learning Lead/Sr. Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. Ankit has been working on applying machine learning to solve ambiguous business problems and improve customer experience. For instance, he created a platform for experimenting with different hypotheses on Amazon product pages using reinforcement learning techniques.
Dynatrace news. As organizations look to speed their digital transformation efforts, automating time-consuming, manual tasks is critical for IT teams. Therefore, many organizations are evaluating the benefits of AIOps. Artificial intelligence for IT operations (AIOps) uses machine learning and AI to help teams manage the increasing size and complexity of IT environments through automation.
By Soheil Esmaeilzadeh , Negin Salajegheh , Amir Ziai , Jeff Boote Introduction Streaming services serve content to millions of users all over the world. These services allow users to stream or download content across a broad category of devices including mobile phones, laptops, and televisions. However, some restrictions are in place, such as the number of active devices, the number of streams, and the number of downloaded titles.
Never fear, HighScalability is here! 1958: An engineer wiring an early IBM computer 2021: An engineer wiring an early IBM quantum computer. @enclanglement. My Stuff: I'm proud to announce a completely updated and expanded version of Explain the Cloud Like I'm 10 ! This version adds 2x more coverage, with special coverage of AWS, Azure, GCP, and K8s.
What is DevSecOps and what is a DevSecOps maturity model? DevSecOps brings development, operations, and security teams together in the software development lifecycle (SDLC). This approach enables teams to focus on speed and agility in software development without compromising security. A DevSecOps approach advances the maturity of DevOps practices by incorporating security considerations into every stage of the process, from development to deployment.
Dynatrace news. As businesses take steps to innovate faster, software development quality—and application security—have moved front and center. This is fueling key DevSecOps trends in 2022. In order for software development teams to balance speed with quality during the software development cycle (SDLC), development, security, and operations teams (or DevSecOps teams) need to ensure that their practices align with modern cloud environments.
As more organizations embrace microservices-based architecture to deliver goods and services digitally, maintaining customer satisfaction has become exponentially more challenging. Implementing service-level objectives (SLOs) has become a vital method for meeting service-level agreements that ensure great user experiences. A service-level objective is a key element within a larger service-level agreement, or contract of sorts, between a provider and a customer.
Dynatrace news. Ansible automation has changed the game for IT operations. But the Red Hat Ansible Automation Platform integration with the Dynatrace Software Intelligence Platform takes automated remediation to a whole new level. Early in my IT career, I worked in IT Ops and DevOps roles, building release deployment solutions for repeatable outcomes.
For the longest time, hosting static files on CDNs was the de facto standard for performance tuning website pages. The host offered browser caching advantages, better stability, and storage on fast edge servers across strategic geolocations. Not only did it have performance benefits, but it was also convenient for developers. Recent developments, however, show that self-hosting static files such as Ajax (Asynchronous JavaScript and XML) and jQuery libraries, CSS styles, and other include directi
Dynatrace news. Full-stack observability is fast becoming a must-have capability for organizations under pressure to deliver innovation in increasingly cloud-native environments. As organizations grapple with mounting cloud complexity, IT teams know they must identify and respond to evolving issues across the entire technology stack—from mainframes to multicloud environments.
by Christos G. Bampis , Li-Heng Chen and Zhi Li When you are binge-watching the latest season of Stranger Things or Ozark, we strive to deliver the best possible video quality to your eyes. To do so, we continuously push the boundaries of streaming video quality and leverage the best video technologies. For example, we invest in next-generation, royalty-free codecs and sophisticated video encoding optimizations.
The containerization craze has continued for enterprises, with benefits such as portability, efficiency, and scalability. In fact, according to a Gartner forecast , revenue for global container management software and services will reach $944 million in 2024 — up from $465.8 million in 2020. With the significant growth of container management software and services, enterprises need to find ways to simplify the process.
Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Existing observability and monitoring solutions have built-in limitations when it comes to storing, retaining, querying, and analyzing massive amounts of data.
By: Peter Cioni (Netflix), Alex Schworer (Netflix), Mac Moore (Conductor Tech.), Rachel Kelley (AWS), Ranjit Raju (AWS) Rendering is core to the the VFX process VFX studios around the world create amazing imagery for Netflix productions. Nearly every show that is produced today includes digital visual effects, from the creatures in Stranger Things , to recreating historic London in Bridgerton.
Dynatrace news. Every organization’s goal is to keep its systems available and resilient to support business demands. A service-level objective ( SLO ) is the new contract between business, DevOps, and site reliability engineers (SREs). However, many teams struggle with knowing which ones to use and how to incorporate them into the processes. Below, several Dynatrace customers shared their SLO management journey and discussed the resulting dashboards they rely on daily to manage their mission-cr
Dynatrace news. Dynatrace, together with an industry consortium including top feature flagging management solutions , has submitted a new open standard for feature flagging as a CNCF sandbox project. Feature flags are an essential tool in the modern software delivery lifecycle for cloud-native applications. This new standard will provide a vendor-neutral and future-proof approach for integrating feature flagging and management solutions to simplify, accelerate, and ultimately automate release cy
HornetQ 2.0 broke records and defeated top-ranked messaging services in benchmark tests. Why wasn't it widely adopted? Software vendors make all kinds of claims about their products, but what developers care about is proof. When testing a new product, it's important to see how it stacks up against its competition. For years, researchers at UT Darmstadt have compared the performance of message-oriented middleware servers based on Java Messaging Service (JMS).
Dynatrace news. Takeaways from this article on DevOps practices: DevOps practices bring developers and operations teams together and enable more agile IT. Still, while DevOps practices enable developer agility and speed as well as better code quality, they can also introduce complexity and data silos. Automating DevOps practices and workflows is critical to eliminating silos.
Over the years, the whole idea of software testing has evolved. And the evolution not only has called for modern testing strategies and tools but a detailed-oriented process with the inclusion of test methodologies. However, the only thing that defines the success or failure of a test strategy is the precise selection of tools, technology, and a suitable methodology to aid the entire QA process.
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