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Evolution of Java Usage at Netflix
Evolution of Java Usage at Netflix
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Netflix is predominantly a Java shop.
Every backend application at Netflix is a Java application. This includes:
Internal applications
The software that powers one of the largest film studios in the world and is used to produce movies
The Netflix streaming app
However, this doesn’t mean that the Java stack at Netflix is static. Over the years, it has evolved significantly.
In this post, we will look at the evolution of Java usage at Netflix in light of the overall architectural changes that have taken place to support the changing requirements.
The Groovy Era with BFFs
It’s common knowledge that Netflix has a microservice architecture.
Every piece of functionality and data is owned by a microservice and there are thousands of microservices. Also, multiple microservices communicate with each other to realize some of the more complex functionalities.
For example, when you open the Netflix application, you see the LOLOMO screen. Here, LOLOMO stands for list-of-list-of-movies and it is essentially built by fetching data from many microservices such as:
Service that returns a list of top 10 movies
Artwork service that provides personalized images for each movie
Movie metadata service that returns the movie titles, actor details, and descriptions
LOLOMO service that provides what lists to actually render for a user’s home page.
The below diagram shows this situation.
It’s quite possible that rendering just one screen on the Netflix app may involve calling 10 services.
However, calling so many services from your device (such as the television) or mobile app is typically inefficient. Making 10 network calls doesn’t scale and results in a poor customer experience. Many streaming apps suffer from such performance issues.
To avoid these issues, Netflix used a single front door for the various APIs. The device makes a call to this front door that performs the fanout to all the different microservices. The front door acts as a gateway and Netflix used Zuul for this purpose.
This approach works because the call to the multiple microservices takes place on the internal network which is very fast, thereby eliminating the performance implications.
However, there was another problem to solve.
All of the different devices users can use to access Netflix have different requirements in subtle ways. While Netflix tried to keep a consistent look and feel for the UI and its behavior on every device, each device still has different limitations when it comes to memory or network bandwidth and therefore, loads data in slightly different ways.
It’s hard to create a single REST API that can work on all these different devices. Some of the problems are as follows:
REST APIs Either fetch too much or too little data
Even if they created one REST API to take care of all data needs, it was going to be a bad experience because they would be wasting a lot of data
In the case of multiple APIs, it would mean multiple network calls
To handle this, Netflix used the backend for frontend (BFF) pattern.
In this pattern, every frontend or UI gets its own mini backend. The mini backend is responsible for performing the fanout and fetching the data that the UI needs at that specific point.
The below diagram depicts the concept of the BFF pattern.
In the case of Netflix, the BFFs were essentially a Groovy script for a specific screen on a specific device.
The scripts were written by UI developers since they knew what exact data they needed to render a particular screen. Once written, the scripts were deployed on an API server and performed the fanout to all the different microservices by calling the appropriate Java client libraries. These client libraries were wrappers for either a gRPC service or a REST client.
The below diagram shows this setup.
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The Use of RxJava and Reactive Programming
The Groovy scripts helped perform the fanout.
But doing such a fanout in Java is not trivial. The traditional approach was to create a bunch of threads and try to manage the fanout using minimal thread management.
However, things got complicated quickly because of fault tolerance. When dealing with multiple services, you can have one of them not responding quickly enough or failing, resulting in a situation where you’ve to clean up threads and make sure things work properly.
This is where RxJava and reactive programming helped Netflix handle fanouts in a better way by taking care of all the thread management complexity.
On top of RxJava, Netflix created a fault-tolerant library named Hystrix that took care of failover and bulkheading. Even though reactive programming was complicated, it made a lot of sense for the time and the architecture allowed them to serve most of the traffic needs of Netflix.
However, there were some important limitations to this approach:
There was a script for each endpoint resulting in a lot of scripts to maintain and manage
UI developers had to create all the mini backends and they didn’t like working in the Groovy Java space with RxJava. It’s not the primary language they use on a daily basis that makes things difficult
Reactive programming is generally hard and has a steep learning curve.
The Move to GraphQL Federation
Over the last few years, Netflix has been migrating to a completely new architecture when it comes to its Java services. The centerpiece of this new architecture is GraphQL Federation.
When you compare GraphQL to REST, the major difference is that GraphQL always has a schema. This schema helps define some key aspects such as:
All the operations along with the various queries and mutations
Fields available from the types that are being returned from the queries
For example, in the case of Netflix, you may have a query for all the shows that return a show type. It has a show as a title and also contains reviews, which may be another type.
With GraphQL, the client has to be explicit about the field selection. You can’t just ask for shows and get all the data from shows. Instead, you have to specifically mention that you want to get the title of the show and the score of various reviews. If you don’t ask for a field, you won’t get the field.
With REST, this was the opposite because you get whatever the REST service decides to send.
While it’s more work for the client to specify the query in GraphQL, it solves the whole problem around over-fetching where you get a lot more data than you might actually need. This paves the way to create one API that can serve all the different UIs.
To augment GraphQL, Netflix went one step further and used GraphQL Federation to fit it back into their microservices architecture.
The below diagram shows the setup with GraphQL Federation.
As you can see, the microservices are now called DGS or Domain Graph Service.
DGS is an in-house framework developed by Netflix to build GraphQL services. When they started moving to GraphQL and GraphQL Federation, there wasn’t any Java framework that was mature enough to use at the Netflix scale. Therefore, they built on top of the low-level GraphQL Java framework and augmented it with features like code generation for schema types and support for federation.
At its core, a DGS is just a Java microservice with a GraphQL endpoint and a schema.
While there are multiple DGSs, there’s just one big GraphQL schema from the perspective of a device such as the TV. This schema contains all the possible data that can be rendered. The device doesn’t need to worry about all the different microservices that are part of the schema in the backend.
For example, the LOLOMO DGS can define a type show with just the title. Then, the images DGS can extend that type show and add an artwork URL to it. The two different DGSs don’t know anything about each other. All they need to do is publish their schema to the federated gateway. The federated gateway knows how to talk to a DGS because all of them have a GraphQL endpoint.
There are several advantages to this setup:
There’s no API duplication anymore.
There is no need for a backend-for-frontend (BFF) because GraphQL as an API is flexible enough to support different devices due to the field selection feature.
No need for any server-side development by UI engineers. The backend developers and the UI developers just collaborate on the schema.
There is no need for any client libraries in Java anymore. This is because the federated gateway knows how to talk to a generic GraphQL service without the need to write specific code.
Java Versions at Netflix
Recently, Netflix has migrated from Java 8 to Java 17. After the migration, they saw about 20% better CPU usage on Java 17 versus Java 8 without any code changes. This was because of improvements in the G1 garbage collector. At the scale of Netflix, a 20% better CPU utilization is a big deal in terms of cost benefits.
Contrary to popular belief, Netflix doesn’t have its own JVM. They’re just using the Azul Zulu JVM which is an OpenJDK build.
Overall, Netflix has around 2800 Java applications that are mostly microservices of varying sizes. Also, they have around 1500 internal libraries. Some of them are actual libraries while many of them are just client libraries sitting in front of a gRPC or REST service.
For the build system, Netflix relies on Gradle. On top of Gradle, they use Nebula which is a set of open-source Gradle plugins. The most important aspect of Nebula is in the resolution of libraries. Nebula helps with version locking that helps with reproducible builds.
More recently, Netflix has been actively testing and rolling out changes with Java 21. Comparing the move from Java 8 to Java 17, it’s significantly easy to go from Java 17 to 21. Java 21 also provides a few important features such as:
Virtual threads allow server-side applications written in a thread-per-request style to scale at optimal hardware utilization. In a thread-per-request style, a request comes and the server provides a thread for it. All of the work for the request happens in this thread
An updated ZGC garbage collector that focuses on low pause times and works well in a broader variety of use cases.
Data-oriented programming with a combination of records and pattern-matching
Use of Spring Boot at Netflix
Netflix is famous for its use of Spring Boot.
In the last year or so, they have completely moved out of their homegrown Java stack based on Guice and completely standardized on Spring Boot.
Why Spring Boot?
It’s the most popular Java framework and has been very well maintained over the years.
Netflix found a lot of benefits in leveraging the huge open-source community of the Spring framework, existing documentation, and training opportunities that are easily available. The evolution of Spring and its features align very well with the core Netflix principle of “highly aligned, loosely coupled”.
Netflix uses the latest version of OSS Spring Boot and their goal is to stay as close as possible to the open source community. However, to integrate closely with the Netflix ecosystem and infrastructure, they have also created Spring Boot Netflix which is a bunch of modules built on top of Spring Boot.
Spring Boot Netflix has support for several things such as:
gRPC client
Server support integrated with the Netflix SSO stack for AuthZ and AuthN
Observability in the form of tracing, metrics, and distributed logging
HTTP clients that support mTLS
Service discovery with Eureka
AWS/Titus integration
Kafka, Cassandra and Zookeeper integration
Conclusion
There’s no singular Netflix stack.
The Netflix Java stack has been evolving over the last several years, beginning from in-house frameworks to Groovy-era microservices and more recently, moving to GraphQL Federation.
All the changes have been made to solve problems from the previous approach. For example, the move to RxJava was to handle fanouts in a better way and the move to GraphQL Federation was to solve the issues of complexity due to RxJava.
Along with these changes, there has also been a parallel evolution in terms of Java language versions from Java 8 to 17 and now 21+. A lot of it has also been prompted by Spring Boot version 3 finally moving beyond Java 8 and forcing the entire ecosystem to upgrade.
These changes have allowed them to build more performant applications that can save CPU costs and
Overall, the theme has been towards standardization of the approach in building microservices across the organization. However, considering the constant challenges faced in operating at their scale while staying ahead of the competition, the evolution will continue.
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Represent: A leader’s guide to women’s experiences at work
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As the sun sets on the month of March—also known as Women’s History Month—it’s an opportune time to reflect on women’s contributions at work. Women are an undeniable force in the modern workplace, as the business case for gender-diverse leadership teams grows ever stronger. After pandemic-fueled burnout prompted many working mothers to leave the labor force altogether, women’s participation is now hitting all-time highs. While we know that women are just as eager to advance in their careers as men, they remain vastly underrepresented at higher levels of the organization. This week, we upend misconceptions about women at work and suggest ways in which leaders can really move the needle.
For nearly a decade, McKinsey’s Women in the Workplace research has shed light on the contradictions, challenges, and promise of being a woman in the corporate world. According to senior partners Alexis Krivkovich and Lareina Yee, the latest results help demystify four myths about women at work: that women feel less ambitious than they did before the pandemic (they aren’t), that only women care about flexible working conditions (men do, too), and that microaggressions don’t meaningfully affect women (they do). The fourth myth? Krivkovich and Yee point to the leadership pipeline. Rather than the glass ceiling, “the biggest inequity in advancement remains the broken rung—the very first step up into a manager position,” Krivkovich says. “The reason we only have 28 percent women in the C-suite is because we aren’t building that leadership path at the very beginning of [women’s] careers, to create a talent pool that would be available and ready for those opportunities when they open up.” To course correct, they recommend companies approach gender representation as they would any other business problem: dig into the data, run postmortems on who’s getting promoted, and ask tough questions about the structural biases that may be standing in women’s way.
That’s the average number of years a woman spends in poor health during her lifetime. According to McKinsey Health Institute research from senior partners Kweilin Ellingrud and Lucy Pérez and their colleagues, women are most likely to be affected by a sex-specific health condition in their working years. With the average person spending one-third of their life at work, improving employee health is critical to improving global health, both as a moral imperative and a precondition for economic prosperity. What’s at stake in addressing the health gap between women and men? Healthier women are more likely to participate in the workforce, thus more likely to improve outcomes for themselves, their families, and the economy, which stands to gain at least $1 trillion of global economic opportunity by 2040—the equivalent of 137 million women in full-time jobs—if the gap is closed.
For all our focus on career paths, it’s important to remember that not everyone’s professional trajectory follows a straight line—especially in a time of so much disruption. Rather than concentrating on a single career ladder to climb, ask yourself what you want to be known for at work, instead of what your next job title should be, and encourage your team to do the same. Focusing on the things you like doing at work, and the things that give you meaning, can lead to more happiness, both in and out of your role.
Lead by fixing the broken rung.
– Edited by Daniella Seiler, executive editor, Washington, DC
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Humans in the loop. While gen AI can handle a lot, it’s important to remember that it can’t replace human know-how. People still need to be involved to ensure that the final product is manufacturable and meets users’ needs. To use gen AI effectively, companies should focus on doing consumer research, developing effective prompts, refining the technology’s outputs, parsing the best concepts, and making sure to blend human empathy into the mix. Learn how gen AI can boost creativity and productivity in product development, and visit McKinsey Digital for more insights.
—Edited by Jana Zabkova, senior editor, New York
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Our top ten articles this quarter look at the women’s health gap, unsung digital and AI ideas, and more. At No. 1, McKinsey’s Shaun Callaghan, Anna Pione, Warren Teichner, and coauthors take a deep dive into the results of the latest Future of Wellness survey in “The trends defining the $1.8 trillion global wellness market in 2024.”
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THIS MONTH’S PAGE-TURNERS ON BUSINESS AND BEYOND
What distinguishes the best CEOs from the rest? In March 2022, McKinsey senior partners Carolyn Dewar, Scott Keller, and Vikram Malhotra set out to answer that question in CEO Excellence: The Six Mindsets That Distinguish the Best Leaders from the Rest (Scribner/Simon & Schuster, 2022). The book, which examined more than two decades of data on 7,800 CEOs in 70 countries, became an international business bestseller. Recently, the authors chatted with McKinsey Global Publishing leader Raju Narisetti to revisit the mindsets that have helped CEOs and aspiring leaders deliver impact. Check out the first and second installments of this discussion. Read more on the third installment below.
In this edition of Readers & Leaders, enhance your leadership skills and learn ways to set the direction of your team. Dewar, Keller, and Malhotra revisit the leadership lessons of the most successful CEOs, and Grace Puma shares how women can shatter the glass ceiling, despite only occupying 28 percent of C-suite positions. Philip Kotler and Giuseppe Stigliano present a new direction to help retailers meet the needs of consumers in the post-digital age, Chris Dixon outlines a vision for a decentralized internet that could inspire a new direction for innovation and growth, and Charles Duhigg explains the role that improved communication plays in relationship building.
Read on to find out more about how you can change your approach to leadership and inspire others to align with your vision.STAY TUNED
“There’s a body of thinking here that can be a handbook, that’s grounded in facts, that’s grounded in experience, that everyone should feel confident drawing from. Someone reading [CEO Excellence] can get the wisdom from all of those voices in one place.”
—Carolyn Dewar, McKinsey senior partner, in the third and final installment of CEO Excellence revisited, coming in April.IN CASE YOU MISSED IT
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1. IBM’s Ginni Rometty on leading with ‘good power’
2. Ron Shaich shares leadership lessons on what matters most and why
3. How people-first leadership can make the sky the limit
4. Moshik Temkin on power, purpose, and the public goodAs Women’s History Month comes to a close, read these interviews with women leaders:
1. Suzanne Heywood rides the waves of resilience
2. Dr. Fei-Fei Li sees ‘worlds’ of possibilities in a multidisciplinary approach to AI
3. Lisa Sun explains why confidence is your superpower
4. Netta Jenkins asks, ‘Is there a seat at the table?’BUSINESS BESTSELLERS TOP
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by "McKinsey Readers & Leaders" <publishing@email.mckinsey.com> - 11:48 - 30 Mar 2024 -
EP105: The 12 Factor App
EP105: The 12 Factor App
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ACID Properties in Databases With Examples (Youtube video)
Have you heard of the 12-Factor App?
What does API gateway do?
How does Redis architecture evolve?
Cloud Cost Reduction Techniques
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Have you heard of the 12-Factor App?
The "12 Factor App" offers a set of best practices for building modern software applications. Following these 12 principles can help developers and teams in building reliable, scalable, and manageable applications.
Here's a brief overview of each principle:
Codebase:
Have one place to keep all your code, and manage it using version control like Git.
Dependencies:
List all the things your app needs to work properly, and make sure they're easy to install.Config:
Keep important settings like database credentials separate from your code, so you can change them without rewriting code.Backing Services:
Use other services (like databases or payment processors) as separate components that your app connects to.Build, Release, Run:
Make a clear distinction between preparing your app, releasing it, and running it in production.Processes:
Design your app so that each part doesn't rely on a specific computer or memory. It's like making LEGO blocks that fit together.Port Binding:
Let your app be accessible through a network port, and make sure it doesn't store critical information on a single computer.Concurrency:
Make your app able to handle more work by adding more copies of the same thing, like hiring more workers for a busy restaurant.Disposability:
Your app should start quickly and shut down gracefully, like turning off a light switch instead of yanking out the power cord.Dev/Prod Parity:
Ensure that what you use for developing your app is very similar to what you use in production, to avoid surprises.Logs:
Keep a record of what happens in your app so you can understand and fix issues, like a diary for your software.Admin Processes:
Run special tasks separately from your app, like doing maintenance work in a workshop instead of on the factory floor.
Over to you: Where do you think these principles can have the most impact in improving software development practices?
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What does API gateway do?
The diagram below shows the detail.
Step 1 - The client sends an HTTP request to the API gateway.
Step 2 - The API gateway parses and validates the attributes in the HTTP request.
Step 3 - The API gateway performs allow-list/deny-list checks.
Step 4 - The API gateway talks to an identity provider for authentication and authorization.
Step 5 - The rate limiting rules are applied to the request. If it is over the limit, the request is rejected.
Steps 6 and 7 - Now that the request has passed basic checks, the API gateway finds the relevant service to route to by path matching.
Step 8 - The API gateway transforms the request into the appropriate protocol and sends it to backend microservices.
Steps 9-12: The API gateway can handle errors properly, and deals with faults if the error takes a longer time to recover (circuit break). It can also leverage ELK (Elastic-Logstash-Kibana) stack for logging and monitoring. We sometimes cache data in the API gateway.
Over to you:What’s the difference between a load balancer and an API gateway?
Do we need to use different API gateways for PC, mobile and browser separately?
How does Redis architecture evolve?
Redis is a popular in-memory cache. How did it evolve to the architecture it is today?
2010 - Standalone Redis
When Redis 1.0 was released in 2010, the architecture was quite simple. It is usually used as a cache to the business application.
However, Redis stores data in memory. When we restart Redis, we will lose all the data and the traffic directly hits the database.2013 - Persistence
When Redis 2.8 was released in 2013, it addressed the previous restrictions. Redis introduced RDB in-memory snapshots to persist data. It also supports AOF (Append-Only-File), where each write command is written to an AOF file.2013 - Replication
Redis 2.8 also added replication to increase availability. The primary instance handles real-time read and write requests, while replica synchronizes the primary's data.2013 - Sentinel
Redis 2.8 introduced Sentinel to monitor the Redis instances in real time. is a system designed to help managing Redis instances. It performs the following four tasks: monitoring, notification, automatic failover and configuration provider.2015 - Cluster
In 2015, Redis 3.0 was released. It added Redis clusters.
A Redis cluster is a distributed database solution that manages data through sharding. The data is divided into 16384 slots, and each node is responsible for a portion of the slot.Looking Ahead
Redis is popular because of its high performance and rich data structures that dramatically reduce the complexity of developing a business application.
In 2017, Redis 5.0 was released, adding the stream data type.
In 2020, Redis 6.0 was released, introducing the multi-threaded I/O in the network module. Redis model is divided into the network module and the main processing module. The Redis developers the network module tends to become a bottleneck in the system.
Over to you - have you used Redis before? If so, for what use case?
Cloud Cost Reduction Techniques
Irrational Cloud Cost is the biggest challenge many organizations are battling as they navigate the complexities of cloud computing.
Efficiently managing these costs is crucial for optimizing cloud usage and maintaining financial health.
The following techniques can help businesses effectively control and minimize their cloud expenses.
Reduce Usage:
Fine-tune the volume and scale of resources to ensure efficiency without compromising on the performance of applications (e.g., downsizing instances, minimizing storage space, consolidating services).Terminate Idle Resources:
Locate and eliminate resources that are not in active use, such as dormant instances, databases, or storage units.Right Sizing:
Adjust instance sizes to adequately meet the demands of your applications, ensuring neither underuse nor overuse.Shutdown Resources During Off-Peak Times:
Set up automatic mechanisms or schedules for turning off non-essential resources when they are not in use, especially during low-activity periods.Reserve to Reduce Rate:
Adopt cost-effective pricing models like Reserved Instances or Savings Plans that align with your specific workload needs.Bonus Tip: Consider using Spot Instances and lower-tier storage options for additional cost savings.
Optimize Data Transfers:
Utilize methods such as data compression and Content Delivery Networks (CDNs) to cut down on bandwidth expenses, and strategically position resources to reduce data transfer costs, focusing on intra-region transfers.
Over to you: Which technique fits in well with your current cloud infra setup?
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by "ByteByteGo" <bytebytego@substack.com> - 11:36 - 30 Mar 2024 -
How does the UK’s arts sector contribute to its economy?
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Dynamic impact. The UK is a cultural powerhouse, reflect Tunde Olanrewaju—the managing partner for McKinsey’s UK, Ireland, and Israel offices—and coauthors. McKinsey analysis found that in 2022, the UK arts sector contributed £49 billion in gross value added to the UK economy—a significant sum. The industry has a definite impact on UK society, influencing the economy, people’s lives, and communities. A 2023 survey by the Department for Culture, Media, and Sport found that 91% of UK adults had participated in artistic activities over the prior 12 months.
—Edited by Vanessa Burke, editor, Atlanta
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by "Only McKinsey" <publishing@email.mckinsey.com> - 01:08 - 29 Mar 2024 -
Serving a greater purpose, productivity growth, sustainable offerings in e-commerce, and more: The Daily Read Weekender
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Brought to you by Liz Hilton Segel, chief client officer and managing partner, global industry practices, & Homayoun Hatami, managing partner, global client capabilities
The weekend is near, so get ready to catch up on the week’s highlights on revisiting CEO Excellence, productivity growth, the new net-zero reality, and more.
QUOTE OF THE DAY
chart of the day
Ready to unwind?
—Edited by Joyce Yoo, editor, New York
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by "McKinsey Daily Read" <publishing@email.mckinsey.com> - 10:13 - 28 Mar 2024 -
Investing in productivity growth
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by "McKinsey Global Institute" <publishing@email.mckinsey.com> - 12:51 - 28 Mar 2024 -
A Crash Course in IPv4 Addressing
A Crash Course in IPv4 Addressing
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Welcome to our latest issue on IPv4 addressing. In this issue, we'll learn about the basic parts of IPv4 addressing, including its structure, the role of subnet masks, and the meaning of network, broadcast, and host addresses. IP is used to send packets from the source to their final destination, either within the same network or across multiple networks.
So, without further ado, let’s jump right into IPv4 addressing.
IPv4 Address Structure
An IPv4 address is written using dotted decimal notation, but it is actually a 32-bit address. This gives us a total of about 4.29 billion possible addresses. We divide the 32-bit address into four 8-bit sections called octets. Then we convert each octet into a decimal value. This is called dotted decimal notation, and that's how we write IPv4 addresses.
The range of an IPv4 address can be from four 0s (0.0.0.0) in dotted decimal notation to four 255s (255.255.255.255).
IPv4 Address and Subnet Mask
An IPv4 address has two main parts:
A network portion
A host portion
The subnet mask (also called the prefix length) separates the network portion from the host portion of the IPv4 address.
A subnet mask is 32 bits long. It has a group of 1s followed by a group of 0s. The 1s indicate the network portion of the IP address, and the 0s indicate the host portion.
How to Write a Subnet Mask
There are two ways to write a subnet mask:
Dotted Decimal Notation
We can use dotted decimal notation, just like for IPv4 addresses.
Example: 255.255.0.0
Slash Notation or Prefix Length
We can also use a slash notation, which shows the number of 1 bits in the mask.
Example:
/16 (indicating 16 one bits)
172.18.0.0/16
Using the slash notation if more common nowadays.
Finding the IPv4 Network Address Using the Subnet Mask
Let’s say we have a host IPv4 address (192.168.1.100) and a subnet mask (255.255.255.0). How do we find the network address from the host address using the subnet mask?
In binary notation, we perform a bitwise AND operation between the host address and the subnet mask. For each bit position, if both the address and mask bits are 1, the result is 1. Otherwise, the result is 0. The result gives us the network address.
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How 10x Banking proactively detects issues with New Relic
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10x Banking runs on New Relic to proactively detect issues As a cloud-native core banking platform, 10x Banking wants engineering teams to make informed decisions based on real-time production insights. New Relic helps 10x collect telemetry data in one place so that teams can have ownership of the services they run and identify problems before they impact customers.
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Announcing the winners of the 2024 Remote Excellence Awards, product updates at Remote, Gusto Global's expansion to India, and more!
Announcing the winners of the 2024 Remote Excellence Awards, product updates at Remote, Gusto Global's expansion to India, and more!
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🏆 The results are in! We’re pleased to announce the winners of the 2024 Remote Excellence Awards 🎉
The Remote Excellence Awards recognize companies that have demonstrated exceptional commitment, innovation, and enthusiasm in navigating the challenges and opportunities presented by remote work.
🥁 And the winners are…
🏆 Excellence in Remote Work Culture: TheyDo - Journey Management
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🏆 Excellence in Talent Strategy: Doist
🏆 Remote for Good Award: Peek Vision
🏆 Liftoff Award for Startups: TheyDo - Journey Management
🏆 Small and Mighty Award for SMEs: MUI
🏆 Trailblazer Award for Large Businesses: Superside
🏆 Global Icon Award Winners: Camunda, Loop Earplugs, Airbase, SuperAnnotate and Tymit
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Do you know how to adopt generative AI quickly and safely?
On Point
Brought to you by Liz Hilton Segel, chief client officer and managing partner, global industry practices, & Homayoun Hatami, managing partner, global client capabilities
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Safely seizing gen AI’s value. Gen AI presents a once-in-a-generation opportunity for companies. The technology could add up to $4.4 trillion in economic value to the global economy, McKinsey research suggests. While many corporate leaders are determined to capture this value, recognition is growing that gen AI opportunities come with significant risks. By adapting proven risk management strategies, it’s possible to move on gen AI responsibly and with good pace, McKinsey Technology Council chair Lareina Yee and coauthors explain.
•
Steps to address risks. Many business leaders are focusing on deciding how to respond to the “inbound” risks related to adopting gen AI, such as IP infringement, malicious use, security threats, and third-party risk. Most organizations will benefit from a focused sprint to learn how gen AI is changing their external environment. Consider four steps enterprises can take to benefit from gen AI while minimizing risk, and visit McKinsey Digital to explore highlights from case studies.
—Edited by Belinda Yu, editor, Atlanta
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by "Only McKinsey" <publishing@email.mckinsey.com> - 01:23 - 28 Mar 2024 -
🇺🇸 Simplify your US expansion with Remote, introducing the US Expansion package.
🇺🇸 Simplify your US expansion with Remote, introducing the US Expansion package.
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Hi MD,
Are you expanding your US-based team this year?
Navigating the complex landscape of US employment laws, running multi-state payroll, and ensuring compliance can often seem daunting, but they don't need to be.
We're excited to introduce the Remote US Expansion package, designed specifically to assist companies like yours to grow your footprint in the US without unnecessary stress, whether you're registered in the US or not.
Everything you need
Streamlined multi-state payroll:
We handle everything from tax calculations to filings, making payroll hassle-free for your entire team.
Regulatory state compliance:
We manage automated state registrations and ongoing compliance, ensuring you stay in line with regulations.
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We have hand-picked benefit providers, allowing you to offer competitive packages and scale with confidence.
Integrated with Remote:
Whether you're creating an entity and looking for payroll or PEO services, or want to test the market with contractors or EOR employees, you can manage your US team in Remote.
We want to transform the complex world of US employment admin into a simplified, manageable process so you can focus on what matters most – your business.
Are you ready to simplify your expansion?
Learn how Remote can make your US expansion smooth and compliant, then book a demo today to take the first step towards a hassle-free expansion.
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Wide Range of GPS tracking software products that are easy to white-label and customize for your business needs
Wide Range of GPS tracking software products that are easy to white-label and customize for your business needs
Telematics Solutions We Offer
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Maximizing gen AI’s potential for US state services
On Point
Brought to you by Liz Hilton Segel, chief client officer and managing partner, global industry practices, & Homayoun Hatami, managing partner, global client capabilities
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Gen AI in US states. US states that capture gen AI’s value have the opportunity to enhance residents’ experiences with services that state governments provide. Gen AI can also help states implement operational efficiencies, improve productivity, and modernize legacy IT platforms. However, this new technology also comes with a unique set of unknowns and risks. State leaders thus need to adopt innovative approaches to establish and develop capabilities, say McKinsey senior partners Gayatri Shenai and Tim Ward and their coauthors.
—Edited by Querida Anderson, senior editor, New York
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by "Only McKinsey" <publishing@email.mckinsey.com> - 01:36 - 27 Mar 2024 -
Is a net-zero transition still possible?
Intersection
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Progress has been made to reduce global carbon emissions—but not enough. Under the current trajectory, the world won’t achieve net-zero emissions even during this century, according to the authors of a recent McKinsey report. To learn more about what opportunities remain for accelerating decarbonization efforts, check out the latest edition of the Five Fifty.
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by "McKinsey Quarterly Five Fifty" <publishing@email.mckinsey.com> - 04:16 - 26 Mar 2024
