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EP76: Netflix's Tech Stack
EP76: Netflix's Tech Stack
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System Design: Apache Kafka In 3 Minutes (Youtube video)
Netflix's Tech Stack
How Do C++, Java, Python Work?
Top 5 Kafka use cases
How is data transmitted between applications?
An Unusual Request: Combating International Book Piracy on Amazon
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System Design: Apache Kafka In 3 Minutes
Netflix's Tech Stack
This post is based on research from many Netflix engineering blogs and open-source projects. If you come across any inaccuracies, please feel free to inform us.
Mobile and web: Netflix has adopted Swift and Kotlin to build native mobile apps. For its web application, it uses React.
Frontend/server communication: GraphQL.
Backend services: Netflix relies on ZUUL, Eureka, the Spring Boot framework, and other technologies.
Databases: Netflix utilizes EV cache, Cassandra, CockroachDB, and other databases.
Messaging/streaming: Netflix employs Apache Kafka and Fink for messaging and streaming purposes.
Video storage: Netflix uses S3 and Open Connect for video storage.
Data processing: Netflix utilizes Flink and Spark for data processing, which is then visualized using Tableau. Redshift is used for processing structured data warehouse information.
CI/CD: Netflix employs various tools such as JIRA, Confluence, PagerDuty, Jenkins, Gradle, Chaos Monkey, Spinnaker, Altas, and more for CI/CD processes.Latest articles
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How Do C++, Java, Python Work?
The diagram shows how the compilation and execution work.
Compiled languages are compiled into machine code by the compiler. The machine code can later be executed directly by the CPU. Examples: C, C++, Go.
A bytecode language like Java, compiles the source code into bytecode first, then the JVM executes the program. Sometimes JIT (Just-In-Time) compiler compiles the source code into machine code to speed up the execution. Examples: Java, C#
Interpreted languages are not compiled. They are interpreted by the interpreter during runtime. Examples: Python, Javascript, Ruby
Compiled languages in general run faster than interpreted languages.
Over to you: which type of language do you prefer?Top 5 Kafka use cases
Kafka was originally built for massive log processing. It retains messages until expiration and lets consumers pull messages at their own pace.
Unlike its predecessors, Kafka is more than a message queue, it is an open-source event streaming platform for various cases.
Let’s review the popular Kafka use cases.Log processing and analysis
The diagram below shows a typical ELK (Elastic-Logstash-Kibana) stack. Kafka efficiently collects log streams from each instance. ElasticSearch consumes the logs from Kafka and indexes them. Kibana provides a search and visualization UI on top of ElasticSearch.Data streaming in recommendations
E-commerce sites like Amazon use past behaviors and similar users to calculate product recommendations. The diagram below shows how the recommendation system works. Kafka streams the raw clickstream data, Flink processes it, and model training consumes the aggregated data from the data lake. This allows continuous improvement of the relevance of recommendations for each user.System monitoring and alerting
Similar to the log analysis system, we need to collect system metrics for monitoring and troubleshooting. The difference is that metrics are structured data while logs are unstructured text. Metrics data is sent to Kafka and aggregated in Flink. The aggregated data is consumed by a real-time monitoring dashboard and alerting system (for example, PagerDuty).CDC (Change data capture)
Change Data Capture (CDC) streams database changes to other systems for replication or cache/index updates. For example, in the diagram below, the transaction log is sent to Kafka and ingested by ElasticSearch, Redis, and secondary databases.System migration
Upgrading legacy services is challenging - old languages, complex logic, and lack of tests. We can mitigate the risk by leveraging a messaging middleware. In the diagram below, to upgrade the order service in the diagram below, we update the legacy order service to consume input from Kafka and write the result to ORDER topic. The new order service consumes the same input and writes the result to ORDERNEW topic. A reconciliation service compares ORDER and ORDERNEW. If they are identical, the new service passes testing.
Over to you: Do you have any other Kafka use cases to share?
How is data transmitted between applications?
The diagram below shows how a server sends data to another server.
Assume a chat application running in the user space sends out a chat message. The message is sent to the send buffer in the kernel space. The data then goes through the network stack and is wrapped with a TCP header, an IP header, and a MAC header. The data also goes through qdisc (Queueing Disciplines) for flow control. Then the data is sent to the NIC (Network Interface Card) via a ring buffer.
The data is sent to the internet via NIC. After many hops among routers and switches, the data arrives at the NIC of the receiving server.
The NIC of the receiving server puts the data in the ring buffer and sends a hard interrupt to the CPU. The CPU sends a soft interrupt so that ksoftirqd receives data from the ring buffer. Then the data is unwrapped through the data link layer, network layer and transport layer. Eventually, the data (chat message) is copied to the user space and reaches the chat application on the receiving side.
Over to you: What happens when the ring buffer is full? Will it lose packets?An Unusual Request: Combating International Book Piracy on Amazon
As many of you know, I publish my books on Amazon.
It is a great platform to do so. Amazon is where I direct people to find and buy my books. Unfortunately, there is an increasingly problematic piracy issue on the site for my books internationally, especially in India, which I am no longer able to solve by myself. The provided links direct to Amazon India, and ALL the books sold through those links are pirated.
More and more customers are getting low-quality, pirated books shipped to them. The smaller problem is that pirates get paid, and not me. The larger problem is that people get books that are unusable and unacceptable in quality, and leave 1-start reviews.
If you work at Amazon, can you please reply to this email, and help escalate this issue? I would like to keep promoting Amazon as a trusted source to purchase my books. But this issue needs to be resolved, and I'd need help from within the company. Thanks a lot in advance!
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by "ByteByteGo" <bytebytego@substack.com> - 11:36 - 9 Sep 2023 -
What's on the agenda at the G20 Summit?
by "McKinsey & Company" <publishing@email.mckinsey.com> - 10:27 - 9 Sep 2023 -
2023 es el año clave de la IA generativa
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Según una encuesta reciente de McKinsey, un tercio de los encuestados dijeron que sus organizaciones utilizan la IA generativa (IAG) de forma habitual en al menos una función comercial, y el 40 por ciento señaló que sus organizaciones aumentarán su inversión en IAG. Sin duda, 2023 está demostrando ser un año decisivo para esta tecnología. A pesar de su incipiente disponibilidad pública, la IAG ya se está adoptando en todos los sectores, zonas geográficas y niveles jerárquicos en el mundo empresarial. En el artículo destacado de este mes, Michael Chui, Lareina Yee, Bryce Hall, Alex Singla y Alexander Sukharevsky, de McKinsey, comentan el crecimiento explosivo de la IAG, su potencial para transformar industrias y las conclusiones clave de la encuesta de McKinsey. Otros temas destacados de la edición de este mes son los siguientes:
•
El papel del consejo de administración en la gestión del riesgo geopolítico
•
Cómo los nuevos CEOs pueden aprovechar al máximo su primer año en el puesto
•
Cómo las empresas con mejores resultados logran un crecimiento consistente y rentable
•
Lo que depara el futuro a los líderes de estrategia en medio de la volatilidad actual y los mandatos cambiantes
La selección de nuestros editores
LOS DESTACADOS DE ESTE MES
Resiliencia geopolítica: El nuevo imperativo del consejo de administración
El riesgo geopolítico ocupa un lugar destacado en la agenda del CEO. Los miembros del consejo de administración pueden ayudar mejorando su comprensión del contexto siguiendo la evolución de la situación y supervisando los controles para mitigar estos riesgos.
Gestione las crisis futuras
Cómo tener un buen comienzo como CEO
Aproveche el primer año en el cargo como una oportunidad de renovación tanto personal como institucional.
Saque el máximo partido a su primer año
El triple play: Crecimiento, beneficio y sostenibilidad
El crecimiento de los ingresos es bueno. El crecimiento rentable es mejor. Pero un crecimiento rentable que promueva las prioridades ASG es aún superior. He aquí cómo las empresas con mejores resultados que optan activamente por el crecimiento consiguen la tripleta del crecimiento.
Invierta en crecimiento sostenible e inclusivo
La evolución del mandato del líder de estrategia
Los líderes de estrategia han asumido responsabilidades adicionales durante la última década en respuesta a la creciente volatilidad y los mandatos cambiantes.
Impulse el impacto
La habilitación de energía renovable con sistemas de almacenamiento de energía en baterías
El mercado de los sistemas de almacenamiento de energía en baterías está creciendo rápidamente. Estas son las preguntas clave para quienes quieren liderar el camino.
Abra camino
Por qué el camino hacia la riqueza y el crecimiento globales es importante para la estrategia
Hay cuatro escenarios plausibles sobre cómo podría desarrollarse la economía mundial en la próxima década. He aquí cómo las empresas pueden trazar un rumbo.
Conozca los 4 escenariosEsperamos que disfrute de los artículos en español que seleccionamos este mes y lo invitamos a explorar también los siguientes artículos en inglés.
McKinsey Explainers
Find direct answers to complex questions, backed by McKinsey’s expert insights.
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McKinsey Classics
In the age of automation and AI, how can finance leaders ensure success? Read our 2018 classic “Bots, algorithms, and the future of the finance function” to learn more.
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by "Destacados de McKinsey" <publishing@email.mckinsey.com> - 08:38 - 9 Sep 2023 -
Forward Thinking on funding a clean world with Ann Mettler
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Forward Thinking on funding a clean world with Ann Mettler
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From poverty to empowerment: Raising the bar for sustainable and inclusive growth
The net-zero transition: What it would cost, what it could bring
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by "McKinsey Global Institute" <publishing@email.mckinsey.com> - 02:39 - 8 Sep 2023 -
The future of gen AI in 15 charts
The CEO Shortlist
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Curated by Liz Hilton Segel, chief client officer and managing partner, global industry practices, & Homayoun Hatami, managing partner, global client capabilities
The CEO role has never been easy: the boss is ultimately in charge of forming the company’s new strategies, then marshaling the resources to deliver on them. But what we’re hearing now from the world’s CEOs is that their role is harder than ever. Accordingly, we’re doubling down on our commitment to support them. Our CEO Excellence research is generating a steady stream of insights on how the best CEOs consistently deliver results. And other colleagues continue to surface the issues that matter most to CEOs and their teams in the C-suite. In line with that, we’ve changed the focus (and the name) of this newsletter to signal our commitment to helping CEOs—both present and future—do the best jobs they can. Rest assured, we will continue to deliver, twice monthly, four articles and reports that are must-reads for people across the workforce—from C-level execs to the front line. In this edition, we look at the future of generative AI, software developer productivity, and more. We hope you enjoy the read.
—Liz and Homayoun
All gen AI, all the time. It might feel like overload, but gen AI is just getting started. With so many current use cases—and hundreds, if not thousands, more on the horizon—knowing how to apply the technology to your business can seem daunting. To help, we’ve pulled together 15 of our most insightful charts, not only to offer ideas about where gen AI is headed, but also to help business leaders in a wide variety of industries put this tool to work, creating efficiencies and value.
Peer with us into the crystal ball with What’s the future of generative AI? An early view in 15 charts, a new visual McKinsey Explainer.Are you familiar with DORA and SPACE? If not, maybe you should be: they’re essential metrics that software developers use to measure productivity—something companies have historically struggled with. Our new approach combines these tools and others to shine a light on what can sometimes seem like a black box. As every company becomes a software company, shouldn’t you know what’s going on?
It’s true: Yes, you can measure software developer productivity, by Chandra Gnanasambandam, Martin Harrysson, Alharith Hussin, Jason Keovichit, and Shivam Srivastava. What do you call it when carmakers sell insurance, bankers sell furniture, accountants sell HR services, and a few superapps sell all the above and more? We call it the ecosystem economy. Senior partners Venkat Atluri and Miklós Dietz have documented a massive shift from industry sectors to customer-focused ecosystems and make the case that this might be the biggest economic reorganization in history. What will it mean for your company?
Read or listen to the latest episode of our Inside the Strategy Room podcast, Strategies to win in the new ecosystem economy, and order the book if you’d like to go deeper.Growing the top line is good. Growing the bottom line is better. And best of all is growth that accrues to the benefit of all stakeholders. Our new research finds that companies that are “triple outperformers”—meaning they grow faster and are more profitable than peers while also improving sustainability and ESG efforts—exceed their peers in shareholder returns.
Hit the trifecta with The triple play: Growth, profit, and sustainability, by Rebecca Doherty, Claudia Kampel, Anna Koivuniemi, Lucy Pérez, and Werner Rehm.We hope you find our new focus on CEOs inspiring and helpful. See you in two weeks with four more McKinsey ideas for the CEO and others in the C-suite.
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by "McKinsey CEO Shortlist" <publishing@email.mckinsey.com> - 02:42 - 8 Sep 2023 -
We knew her when: Unilever’s past CHRO (Chanel’s new CEO) on reimagining work
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
•
Break with tradition. The COVID-19 pandemic broke traditional models of employment, says Leena Nair, former CHRO of Unilever, in an interview with McKinsey alum Mary Meaney. Creating personalized solutions for employees in 190 countries has been a huge challenge, Nair explains. To help, Unilever developed a platform called COVID Awareness and Situation Intelligence that can predict infection and hospitalization rates. Local leaders were able to use the platform’s data to decide when to open an office.
•
Working dynamically. Even before the pandemic, Unilever was investing in digital tools that enable people to work fluidly, Nair says. One digital tool matches people who have capacity in particular areas with those who are looking for those skills. In 2020, that enabled Unilever to move resources from the hard-hit parts of the business to those that were growing. About 10,000 employees have been redeployed or have used the platform, Nair adds. See five lessons Unilever’s past CHRO says she’s learned since the COVID-19 pandemic began.
— Edited by Belinda Yu, editor, Atlanta
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Don't Miss Out! "Accelerate development of vision enabled self-checkout pipelines with OpenVINO™ Model Server"
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How to Choose a Replication Strategy
How to Choose a Replication Strategy
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In the last issue, we kicked off a 2-part series exploring common data replication strategies. We learned about the leader-follower model - its synchronous and asynchronous variations, consistency considerations, failure handling, and more.
In this issue, we'll examine two alternative approaches - multi-leader and leaderless replication. We'll contrast their designs, dive into how they work, and see the types of use cases where they excel.
By the end, you'll understand the core replication models and how to select the right strategy based on your system needs and constraints. Let's jump back in where we left off last week.
Multi-Leader Replication
Multi-leader replication, sometimes called leader-leader replication, involves the use of multiple primary nodes, also known as leaders, each capable of receiving and processing write requests. These leaders replicate data between each other to stay up to date. Each leader may also have follower replicas for read scaling.
The primary advantage of this model is increased write availability. With multiple active leaders, failure of one node doesn't disrupt writes - other leaders continue handling write requests. This improves upon leader-follower designs where a failed leader halts writes until a new leader is available.
However, multi-leader replication comes with its own set of challenges. For instance, with multiple leaders handling write requests, conflicting changes may occur when leaders modify the same data concurrently.
Managing Conflict
Conflicts are a natural outcome in multi-leader replication models given that multiple leaders can perform write operations simultaneously. Effective conflict management is a complex task, but it is crucial for ensuring data consistency and integrity.
Here are some commonly employed conflict resolution strategies.
Last Write Wins
This is a straightforward method where the most recent change takes precedence. While easy to implement, it risks discarding important updates.
Conflict-free Replicated Data Types (CRDTs)
CRDTs allow for seamless reconciliation of conflicting changes by merging them. CRDTs come in various types for different kinds of data like counters, sets, and lists, and automatically resolve conflicts without requiring a separate conflict resolution process.
Operational Transformation
Operational transformation is often used in real-time collaborative applications. It takes the operation itself into account, not just the state of the data. This method is complex to implement but offers fine-grained control.
Application-specific Resolution
In some cases, conflict resolution logic can be pushed to the application level. The application can employ domain-specific rules or even involve human intervention for resolving conflicts.
Data Partitioning
Another alternative is to partition data across multiple leaders to minimize conflicting changes. However, implementing cross-partition transactions requires careful coordination, and potential hot spots on busy data partitions need to be managed effectively. It’s worth noting that this strategy can reduce the overall write throughput across the cluster.
Replication Lag and Inconsistent Reads
As with leader-follower replication, multi-leader systems are susceptible to replication lag and inconsistent reads. They cause temporary inconsistencies between leaders until updates fully propagate. Applications must be designed with this in mind.
Use Cases
What are some use cases for multi-leader replication? For applications that have users globally, multi-leader replication can reduce the latency for end-users by allowing them to interact with a nearby leader node.
Systems that cannot afford downtime, such as financial transaction platforms, can benefit from having multiple leaders. Even if one goes down, operations continue.
For applications with heavy write loads, distributing the write operations across multiple leaders can prevent any single node from becoming a bottleneck.
Tradeoffs and Challenges
In essence, multi-leader replication is particularly useful for applications that prioritize high write availability, fault tolerance, and globally-distributed data accessibility. Many modern databases can leverage this replication strategy, either natively, or with an extension, with varying degrees of success.
Multi-leader replication provides high availability but requires careful design around consensus, conflict detection, and resolution mechanisms. When implemented well, it can be a powerful approach for maximizing write throughput and availability.
In the next section, we’ll explore the leaderless replication model which takes a different approach.
Leaderless Replication
Leaderless replication takes a quorum-based approach. This concept may sound a bit strange, especially when we've just spent some time discussing models that operate under a clear hierarchy. In a leaderless system, any node in the network has the authority to accept write operations. The absence of a single leader fundamentally changes the dynamics of our system.
Quorum Writes and Reads
Now, let's start with a key concept that underpins leaderless replication: 'quorum writes and reads'. In a system without a leader, we don't rely on any single node to validate a read or write operation. Instead, we aim for consensus among a certain number of nodes. This number is called the 'quorum'. Using a quorum approach balances high availability with data accuracy, since we no longer require full consensus across all nodes.
In this system, we use three important values.
'n' is the total number of nodes in our system.
'W', the write quorum, is the minimum number of nodes that need to agree for a write to be considered successful.
'r', the read quorum, is the minimum number of nodes that need to agree for a read to be valid.
For strong consistency, a general guideline is to have w + r > n. It ensures that any read overlaps with any write and returns the most recent value.
For example, imagine a system with 3 nodes (n=3). If we configure w to 2, that means we need two out of three nodes to acknowledge a write request before it is deemed successful. If one of the nodes went down, the write operations could still continue. This idea works similarly for reads. If r is set to 2, the read operation would query 2 nodes and return the most recent data between the two.
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by "ByteByteGo" <bytebytego@substack.com> - 11:39 - 7 Sep 2023 -
Corporate boards have a new mandate: Help companies build geopolitical resilience
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
•
Rerouting supply chains with AI. Multinational companies with complex supply chains now have a new tool at their disposal: generative AI. In the face of ongoing geopolitical tensions and uneven economic recovery from the COVID-19 pandemic, companies are using generative AI to identify vulnerabilities and help them quickly connect with suppliers. Some countries now have regulations requiring monitoring of environmental and human rights issues, which can be identified through technology. While only about 14% of supply chain professionals currently use AI, a new survey shows that more than 90% plan to start. [FT]
•
Managing geopolitical risks. Recent McKinsey Global Institute research shows that global flows of data, exports, and talent remain strong; however, the world is also becoming more fragmented. While senior leaders know it’s important to navigate geopolitical risks, the role of corporate boards in doing so is not always clear. McKinsey senior partner Chris Leech and colleagues suggest steps directors can take to help them deal with larger-scale forces such as macroeconomic shocks and climate change. Reassessing a board’s composition to include diverse domain expertise and relevant experience and holding meetings in a range of markets to deepen a board’s understanding are first steps.
•
Building boards for today’s global order. A board composed of subject matter experts with clearly defined roles (for example, through a set of key committees) can help companies build resilience in supply chains and other areas. Dashboards that regularly review relevant markets can help boards gain clarity on critical developments and their effects. Learn how boards can adapt their monitoring and mitigation strategies for the fast-changing geopolitical landscape.
— Edited by Gwyn Herbein, editor, Atlanta
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by "McKinsey On Point" <publishing@email.mckinsey.com> - 12:45 - 7 Sep 2023 -
Securing Freight Drivers and Transportation Vehicles with Video Telematics
Securing Freight Drivers and Transportation Vehicles with Video Telematics
Discover how video telematics changed freight transportation. Witness how it boosted safety and productivity on the road.
Challenges
Solutions
Reduce accidents with
real-time risk alerts for
drivers.
Prevent tiredness and distraction-related accidents, ensuring driver well-being.
Access historical journey data easily for incident analysis and optimization.
Real-time cargo visibility ensures security and efficient logistics management.
Results
Uffizio Technologies Pvt. Ltd., 4th Floor, Metropolis, Opp. S.T Workshop, Valsad, Gujarat, 396001, India
by "Sunny Thakur" <sunny.thakur@uffizio.com> - 08:00 - 6 Sep 2023 -
Delivery by drone may be landing on a porch near you
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ON DRONE DELIVERIES
Drone deliveries are developing, but challenges remain
Robin RiedelYou might be startled if you looked out your window and saw a drone hovering near your door, about to release a package onto your front steps. But such a sight could become more common as companies ramp up the use of drones in making deliveries. In 2021, there were close to half a million commercial-drone-delivery flights globally, and that number grew to about 875,000 in 2022 (an average of almost 2,400 drone deliveries per day). In 2023, we expect drone deliveries to exceed the one-million mark.
The benefits of such trips go beyond quickly providing a lunch order or birthday gift. Delivery drones fly at an average speed of 30 to 60 miles per hour, which allows them to rush critical supplies to people in disaster zones and remote, inaccessible areas. In crowded urban areas, deliveries via air routes could ease traffic congestion. The environmental advantages are also clear: delivering a one-pound burrito with a drone that usually weighs between five to 25 pounds generates far less emissions than using an average car, which weighs about 4,100 pounds.
If the scale-up continues, as we expect, there could be many winners. Some skeptics might question our current growth projections, however, since companies thus far have made limited progress on their long-standing plans to increase drone delivery flights. So what recent developments are encouraging more optimism? And what challenges remain?
First, the positives. Investor interest in drone delivery opportunities is at an all-time high: funding reached $101 million in 2022 but has hit $770 million in just the first half of 2023. The technology has also advanced considerably; for example, drones can now accurately navigate during subpar conditions, such as rainstorms.
In another major shift, the time-consuming process of defining regulations has recently borne fruit. As of March 2023, at least seven major regulatory bodies had issued rules about commercial-drone operations, focusing on aircraft certification, operator certification, airspace and operating rules, and infrastructure. (Aerial platform drones—those used for inspections or other types of observation—have lower certification requirements, so they are already in more widespread use.) In the United States, the Federal Aviation Administration’s Beyond Visual Line-of-Sight Aviation Rulemaking Committee released a report in March 2022 that included some recommendations, still under review, that could facilitate multiple aspects of delivery drone operations, including pilot certification and repair and maintenance.“In 2023, we expect drone deliveries to exceed the one-million mark.”
Public opinion of drone deliveries has also warmed. In a McKinsey survey of over 4,600 consumers, 56 percent of respondents said that they would opt for drone delivery if it was faster than the alternatives and did not cost more. Further, in a recent survey of drone industry executives, respondents reported that they expected 60 percent of their end customers to return after the first use of drone services.
Now let’s look at the challenges ahead. Despite the uptick in consumer acceptance, many people still worry that delivery drones may generate too much noise, invade privacy, or simply interfere with their enjoyment of a scenic sunset by crisscrossing the sky. Publicizing the benefits of delivery drones, such as lower emissions, may win over some new adherents. Consumers may also become more supportive if they see how longer-range drones can increase equity by improving people’s access to critical products and services. For example, there is a start-up that delivers vaccines and medicines to over 2,000 hospitals in Ghana, Rwanda, and the United States. Once consumers become more aware of such services, they may become more tolerant of a drone’s buzzing.
Beyond winning over consumers, the drone industry must address some remaining regulatory and technological barriers. Currently, many countries allow operators to control only a single drone, and some also require visual observers for some parts of the flight. The resulting high labor costs make it challenging to scale flights. On the technology side, the industry could benefit from further improvements in batteries—to support longer flights—and in the detect-and-avoid systems that help drones navigate crowded areas.
Of course, drones have uses that extend far beyond delivery, and these applications are also advancing, maybe even at a faster rate. Many companies, for example, including a large furniture retailer, use drones in warehouses to take photographs of inventory, which they then analyze using artificial intelligence. Others monitor remote assets using aerial surveillance drones that can check for damage, eliminating the need for costly on-site visits. Outside the corporate sphere, drones have been incorporated into aerial firefighting, agricultural seeding, and wildlife management. Eventually, passenger drones may play a big role in transportation. Even though it’s still early in the game, the possibilities are endless within this exciting sector.ABOUT THE AUTHOR
Robin Riedel is a partner in McKinsey’s Bay Area office.
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