This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
In softwareengineering, we've learned that building robust and stable applications has a direct correlation with overall organization performance. The data community is striving to incorporate the core concepts of engineering rigor found in software communities but still has further to go. Posted with permission.
Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding. Data scientists at Netflix relish our culture that empowers them to work autonomously and use their judgment to solve problems independently. How could we improve the quality of life for data scientists?
And the last sentence of the email was what made me want to share this story publicly, as it’s a testimonial to how modern softwareengineering and operations should make you feel. In our case that includes the login to our SaaS tenants and exploring captured data. Let me start with the end-user impact.
Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. Curious to learn more about other Data Science and Engineering functions at Netflix?
Structured Query Language (SQL) is a simple declarative programming language utilized by various technology and business professionals to extract and transform data. Visualization & Reporting: Can the tool generate reports or visual representations like ER diagrams, data charts, or query execution plans?
AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?
by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.
Build an umbrella for Development and Operations In modern softwareengineering, the discipline of platform engineering delivers DevSecOps practices to developers to bridge the gaps between development, security, and operations and enhance the developer experience. However, other data formats, like logs, can also be employed.
As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. Why: Data Makes It Different. All ML projects are software projects. The new category is often called MLOps.
Softwareengineering for machine learning: a case study Amershi et al., More specifically, we’ll be looking at the results of an internal study with over 500 participants designed to figure out how product development and softwareengineering is changing at Microsoft with the rise of AI and ML. ICSE’19.
Cloud complexity and data proliferation are two of the most significant challenges that IT teams are facing today. Computing environments are scaling to new heights, resulting in more data that makes pinpointing root causes and vulnerabilities even more challenging. Why is developer observability important for engineers?
In today’s complex, data-driven world, many security vulnerabilities and attacks can jeopardize an organization’s data. To ensure the safety of their customers, employees, and business data, organizations must have a strategy to protect against zero-day vulnerabilities. Application logs are a good data source for this method.
For softwareengineering teams, this demand means not only delivering new features faster but ensuring quality, performance, and scalability too. One way to apply improvements is transforming the way application performance engineering and testing is done. Industry apps explosion. Here is a shortlist to get you started.
Platform engineering is on the rise. According to leading analyst firm Gartner, “80% of softwareengineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026. Monitoring-as-code can also be configured in GitOps fashion.
These workflows are then implemented as traditional software, which can be tested, versioned, and maintained. This approach is well understood in softwareengineering and contrasts sharply with building agents that rely on runtime decisionsan inherently less reliable and harder-to-maintain model. Are they still in transit?
As a result, teams can focus on writing code and building features rather than dealing with infrastructure nuances. They shouldn’t worry about the platform; they should just start writing code.” The Dynatrace Operator automatically ingests all observability data from OpenTelemetry and Prometheus.
DataEngineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “DataEngineers of Netflix” interview series, where our very own dataengineers talk about their journeys to DataEngineering @ Netflix. For example?—?clinical
By helping teams release new software more frequently, DevOps practices are an essential component of digital transformation. Yet, ensuring code quality and breaking down silos are some of the many challenges that come with DevOps methodologies. Automation versus orchestration. Get started with DevOps orchestration.
Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding. Data scientists at Netflix relish our culture that empowers them to work autonomously and use their judgment to solve problems independently. How could we improve the quality of life for data scientists?
We sat together with Armin Ruech and Daniel Dyla, softwareengineers at Dynatrace and leaders within the OpenTelemetry community, to hear about their involvement with the second most active CNCF project. My name is Armin Ruech, I’m a SoftwareEngineer at Dynatrace and I started as a software developer around 3.5
These resources generate vast amounts of data in various locations, including containers, which can be virtual and ephemeral, thus more difficult to monitor. Lambda is Amazon’s event-driven, functions-as-a-service (FaaS) compute service that runs code when triggered for application and back-end services. And why it matters.
OpenTelemetry provides a standard way to instrument and collect telemetry data so you can get normalized data from different monitoring solutions. This uniform approach to collecting data helps you make sense of these different viewpoints so you can tell just what happened and what to do about it.
Application security is a softwareengineering term that refers to several different types of security practices designed to ensure applications do not contain vulnerabilities that could allow illicit access to sensitive data, unauthorized code modification, or resource hijacking. Dynatrace news.
Observability-driven development Yarden Laifenfeld, senior softwareengineer at Dynatrace, presented the first use case for the software development lifecycle (SDLC): observability-driven development, which is the process of integrating observability and security before the first line of code is even written.
This shift is leading more organizations to hire site reliability engineers to guarantee the reliability and resiliency of their services. How site reliability engineering affects organizations’ bottom line SRE applies the disciplines of softwareengineering to infrastructure management, both on-premises and in the cloud.
As softwareengineers, we are always striving for high performance and efficiency in our code. Whether it’s optimizing algorithms or fine-tuning data structures, every decision we make can have a significant impact on the overall performance of our applications.
This gives you seamless end-to-end distributed tracing for AWS Lambda functions without touching any code through auto-instrumentation, thereby helping you to better understand potential issues that may impact your end users’ experience. – Robert Trueman, Head of SoftwareEngineering at CDL. high-fidelity data,?which
However, getting reliable answers from observability data so teams can automate more processes to ensure speed, quality, and reliability can be challenging. According to recent Dynatrace research , organizations expect to make software updates 58% more frequently in the coming year. What is DevOps?
The Metaflow GUI allows data scientists to monitor their workflows in real-time, track experiments, and see detailed logs and results for every executed task. link] Metaflow is a full-stack framework for data science that we started developing at Netflix over four years ago and which we open-sourced in 2019.
This approach has also allowed us to build strong relationships with central engineering teams at Netflix (Data Platform, Developer Tools, Cloud Infrastructure, IAM Product Engineering) that will continue to serve as central points of leverage for security in the long term.
By Karen Casella, Director of Engineering, Access & Identity Management Have you ever experienced one of the following scenarios while looking for your next role? You study and practice coding interview problems for hours/days/weeks/months, only to be asked to merge two sorted lists. This is a conversation, not an inquisition!
Now that you’ve deployed your code, it’s time to monitor it, collect data, and analyze your metrics. The first step to gather this type of data is application monitoring. Once you have data though, it’s important to analyze it correctly. You’ve just released your new app into the wild, live in production. If so, where?
Our very first mobile app is called Prodicle and was built for Android & iOS using the same reactive architecture in both platforms, which allowed us to build 2 apps from scratch in 3 months with 4 softwareengineers. It was extremely important to the team that we did not completely change the way our engineers write Android code.
by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.
Triplebyte lets exceptional softwareengineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. Scalyr is a lightning-fast log management and operational data platform.
ML algorithms can be only as good as the data that we provide to it. This post will focus on the large volume of high-quality data stored in Axion?—?our Figure 1: Netflix ML Architecture Fact: A fact is data about our members or videos. An example of data about members is the video they had watched or added to their My List.
Triplebyte lets exceptional softwareengineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Watch a demo and learn how Etleap can save you on engineering hours and decrease your time to value for your Amazon Redshift analytics projects. Who's Hiring? Apply here.
Upstream systems had to reopen the tokens to identify the user logging in and potentially manage multiple parallel identity data structures, which could easily get out of sync. There were no checks in place to ensure the integrity of the tokens or the data contained therein. We are serving over 2.5
Triplebyte lets exceptional softwareengineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Watch a demo and learn how Etleap can save you on engineering hours and decrease your time to value for your Amazon Redshift analytics projects. Who's Hiring? Apply here.
Triplebyte lets exceptional softwareengineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. Scalyr is a lightning-fast log management and operational data platform.
Commit Cycle Time refers to the average time for a code or configuration change until it’s deployed into production and accessible to users. Microservices are often the best approach to breaking down software. The code is smaller, and every softwareengineer makes production changes on an ongoing basis.
Triplebyte lets exceptional softwareengineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. Scalyr is a lightning-fast log management and operational data platform.
Triplebyte lets exceptional softwareengineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Watch a demo and learn how Etleap can save you on engineering hours and decrease your time to value for your Amazon Redshift analytics projects. Who's Hiring? Apply here.
Triplebyte lets exceptional softwareengineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. Scalyr is a lightning-fast log management and operational data platform.
We organize all of the trending information in your field so you don't have to. Join 5,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content