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Why are US doctors leaving their roles?
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How can companies help their employees embrace change?
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Commitment to change. What organization doesn’t want lasting performance improvements that establish a competitive advantage? For a company undergoing transformation, cultivating employee “will” to change the way it operates is critical for success, McKinsey senior partner John C. W. Parsons and coauthors explain. Organizations that focus on generating this will—along with building critical skills, executing with rigor, and setting a holistic aspiration—are far more likely to outperform peers.
—Edited by Belinda Yu, editor, Atlanta
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by "Only McKinsey Perspectives" <publishing@email.mckinsey.com> - 11:09 - 24 Sep 2024 -
Are you a human-centered leader?
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Human-centered leadership gives people a sense of purpose and recognizes their ambitions. That doesn’t just help leaders help their people—it can also boost a company’s bottom line, say Dana Maor, Hans-Werner Kaas, Kurt Strovink, and Ramesh Srinivasan. To learn how to lead from the inside out, check out the latest edition of the Five Fifty.
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by "McKinsey & Company" <publishing@email.mckinsey.com> - 02:15 - 24 Sep 2024 -
How Uber Scaled Cassandra for Tens of Millions of Queries Per Second?
How Uber Scaled Cassandra for Tens of Millions of Queries Per Second?
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Disclaimer: The details in this post have been derived from the Uber Engineering Blog. All credit for the technical details goes to the Uber engineering team. The links to the original articles are present in the references section at the end of the post. We’ve attempted to analyze the details and provide our input about them. If you find any inaccuracies or omissions, please leave a comment, and we will do our best to fix them.
Uber’s app is a wonderful piece of engineering, enabling the movement of millions of people around the world and tens of millions of food and grocery deliveries.
One common thing across each trip and delivery is the need for low-latency and highly reliable database interactions. Uber made this a reality with their Cassandra database as a service platform.
Supporting a multitude of Uber’s mission-critical OLTP workloads for more than six years, the Cassandra database as a service has achieved some amazing stats:
Tens of millions of queries per second
Petabytes of data
Tens of thousands of Cassandra nodes
Thousands of unique keyspaces
Hundreds of unique Cassandra clusters with over 400+ nodes per cluster
Multi-region support
However, this scale wasn’t achieved overnight. Over the years, the Uber engineering team faced numerous operational challenges.
In this post, we’ll pull back the curtains from the architecture of Uber’s Cassandra setup and the multiple problems they solved to reach the desired scale.
The Cassandra Team Responsibilities
As mentioned, Uber runs Cassandra as a managed service. A dedicated team takes care of the platform's day-to-day operations. Here are the responsibilities of the team:
Implement new features in Cassandra and contribute to the community. This also includes critical bug fixes.
Integrate Cassandra into Uber’s ecosystem. This involves changes to the control plane, configuration management tools, observability, and alert management platform at Uber.
Build the managed Cassandra solution as a one-stop shop for Uber’s application teams.
Ensure 4 nines of availability (99.99%) and 24/7 support for the application teams.
Guide on best practices and data modeling needs of the application teams.
Architecture of Uber’s Cassandra Setup
The diagram below shows the overall Cassandra ecosystem at Uber.
On a high level, the Cassandra cluster spans across regions with the data replicated between them.
Uber’s in-house stateful management system Odin handles the configuration and orchestration of thousands of clusters. Together this forms the Cassandra Managed Service that powers different types of workloads, ranging from read-skewed to mixed to write-skewed.
See the diagram below to understand Odin’s role:
Let’s now look at the major components of the Cassandra database as a service architecture:
Cassandra Framework
This is an in-house framework developed by Uber and is responsible for the lifecycle of running Cassandra in Uber’s production environment.
The framework is powered by Uber’s stateful control plane Odin. It adheres to Odin’s standards and abstracts the complexity of Cassandra’s various functionalities such as:
Node selection and replacement
Rolling restarts and capacity adjustments
Decommissioning nodes
Starting and stopping nodes
Cassandra Client
The Cassandra client is the interface between the applications and the Cassandra clusters.
Uber forked the Go and Java open-source Cassandra clients and adapted them to work in Uber’s ecosystem. These clients use the service discovery mechanism to find the initial nodes to connect. This way there’s no need to hardcode the Cassandra endpoints in the application layer.
Some of the enhancements made by Uber within these clients are around additional observability features such as:
Capturing query fingerprints
DDL/DML features mapping
Service Discovery
Service discovery is a critical piece of large-scale distributed systems. It helps discover service instances on the fly, preventing hard coding and unnecessary configurations.
See the diagram below that shows the concept of service discovery:
At Uber, each Cassandra cluster is uniquely identified and their nodes can be discovered in real time.
Whenever a Cassandra node changes its status (Up, Down, or Decommission), the framework notifies the service discovery about the change. Applications (or service consumers) use the service discovery as the first contact point to connect to a Cassandra node. As the nodes change their status, the service discovery adjusts the list.
Challenges of Scaling Uber’s Cassandra Service
Since the inception of Cassandra’s service at Uber, it has continued to grow every year and more critical use cases have been added.
The service was hit with significant reliability challenges. Let’s look at some of the most important ones in more detail.
1 - Unreliable Node Replacement
Node replacement is a critical part of any large-scale fleet. There are multiple reasons for node replacement:
Hardware failures
Fleet optimization
Changes to the deployment topology
Disaster recovery
Cassandra provides a graceful node replacement approach that decommissions the existing node and adds a new node. But there were a few hiccups such as:
Node decommissioning getting stuck
Failing node addition
Data inconsistency
Every node replacement does not face these issues, but even a small percentage has the potential to impact the entire fleet. It adds operational overhead to teams. For example, even a 95% success rate means 5 failures out of 100 node replacements. In case 500 nodes are replaced every day, 25 failures may easily engage 2 engineers just recovering from these failures.
It was important to fix the root problem and that was Cassandra not cleaning up hint files for orphan nodes.
Think of it like this: You have a big family message board at home. When a family member moves out, everyone keeps their old sticky notes about them on the board. When you decide to get a new message board, you carefully copy all these notes to the new board.
The same was the case with Cassandra. A legit node N1 may store hint files locally for its peer node that was part of the Cassandra ring. However, even when the peer node is not part of the ring, node N1 does not purge the hint files. When N1 decommissions, it transfers all the orphan hint files to its next successor. Over time, the hint files keep growing, resulting in terabytes of garbage hint files. Transferring such a big file could take multiple days.
The team made a few changes in Cassandra:
Proactively purge the hint files belonging to orphan nodes.
Dynamically adjust the hint transfer rate limiter so the transfer can finish in hours instead of days.
Another fix was related to the node decommission step erroring out due to parallel activity, such as rolling restart due to fleet upgrades. The control plane wasn’t able to probe Cassandra about the decommissioned state. To handle this, they improved Cassandra's bootstrap and decommission path by exposing the state so the control plane could get the current status and take necessary action.
See the snippet below that explains the approximate change:
public boolean isDecommissionFailed() { if (operationMode == Mode.LEAVING && hasDecommissionFailed) { return true; } return false; } public boolean isBootstrapFailed() { if (operationMode == Mode.JOINING && hasBootstrapFailed) { return true; } return false; }Source: Uber’s Engineering Blog
After these changes, the node replacement became 99.99% reliable.
2 - Cassandra’s Lightweight Transactions Error Rate
Few business use cases relied on Cassandra’s Lightweight Transactions at scale. However, these cases suffered higher error rates every other week.
It was a general belief that Cassandra’s Lightweight Transactions were unreliable. One of the errors was due to pending range due to multiple simultaneous node replacements. It’s similar to a mismanaged library where too many librarians are replaced at once and tracking books becomes quite difficult.
When a new node N2 replaces an old node N1, the Gossip code path on N2 continues pointing to N1’s IP address, resulting in a DNS resolution error. Ultimately, N2 could not function as expected, and restarting it was the only option.
Uber’s engineering team improved the error handling inside the Gossip protocol, making Cassandra Lightweight Transactions more robust.
3 - Data Inconsistency Issues
Another problem was related to data inconsistency due to sluggish Cassandra repairs.
Cassandra repairs are an important activity for every Cassandra cluster to fix data inconsistencies. While there are open-source solutions to trigger the repair, Uber did not want a control-plane-based solution. In their view, the repair should be an integral part of Cassandra similar to compaction.
With this goal, the Uber Cassandra team implemented the repair orchestration inside Cassandra itself. See the diagram below:
On a high level, they assigned a dedicated thread pool to the repair scheduler. The repair scheduler inside Cassandra maintains a new replicated table for the node status and repair history.
The scheduler picks the node that ran the repair first and continues orchestration to ensure each table and all ranges are repaired.
Since the implementation of a fully automated repair scheduler inside Cassandra, there has been no dependency on the control plane, which reduced the operational overhead significantly.
Conclusion
Uber’s Cassandra setup is a testament to the importance of incremental changes to build a large-scale fleet.
In this post, we’ve taken a deep look at the architecture of Uber’s Cassandra setup and the design of the managed service. We also looked at multiple challenges the engineering team overcame to make the Cassandra database service more reliable at scale.
Reference:
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What is a critical quality that successful CEOs have in common?
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A key trait. To deal with supply chain disruptions, technological change, generational differences at work, and other challenges, leaders will likely find that humility, confidence, selflessness, vulnerability, and resilience—while crucial qualities—are not enough. Leaders must also be versatile, McKinsey senior partners Dana Maor, Kurt Strovink, Ramesh Srinivasan, and senior partner emeritus Hans-Werner Kaas share in their new book, The Journey of Leadership: How CEOs Learn to Lead from the Inside Out (Portfolio, September 2024).
—Edited by Belinda Yu, editor, Atlanta
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Cybersecurity update: A leader’s guide
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Your organization may never have been the target of cybercrime—but all it takes is one data breach to damage its reputation and customer loyalty. New and more sophisticated cyberattacks occur almost daily, and generative AI (gen AI) tools have made it all but impossible to distinguish between real and fake content. In an environment of heightened vigilance, tech and cybersecurity leaders are moving into the spotlight. For more news and strategies, check out our latest article on cybersecurity—part of our McKinsey Explainers series—and the insights below.
Cyberattacks have become so damaging—the estimated annual cost of cybercrime could reach $10.5 trillion by 2025—that some organizations have invested in extensive defensive capabilities, including, in some cases, military-grade technology and cyber talent. While these can be effective safeguards, it’s also critical to consider the role that boards of directors could play in shoring up cyber defenses, according to McKinsey experts in a new article. Besides providing oversight and guidance, board members can evaluate the potential impact on business and “make sure the security team feels the mantle of accountability to deliver on what they promised,” observe the authors. “When it comes to cybersecurity, the ultimate compliment for an organization is that nothing happens—the enterprise keeps running uninterrupted. A board of directors can lead that charge.”
That’s the minimum number of dimensions that cybersecurity providers need to consider to offer a reliable security proposition. McKinsey partner Marc Sorel and colleagues note that business value is a critical dimension. “Organizations today struggle with understanding how to measure the return or value of a dollar spent on cybersecurity,” they say. “Providers should structure their output, reporting, and dashboards to speak to business audiences as well as technical audiences.”
That’s McKinsey experts in an article on what they call the “talent-to-value protection” approach to reducing cyber risk. Unlike traditional security talent management, where the most important roles depend on hierarchy, talent-to-value protection defines the most important roles as those that show a maximum reduction in risk or create the most security value. Given the current global shortage of skilled cybersecurity workers, this approach to hiring could be a game changer for organizations. “Leaders can progressively reduce risk in key areas rather than attempting to mitigate it all at once,” suggest the authors.
It’s often a challenge for companies to keep their cybersecurity protocols up to date—and generative AI (gen AI) has only made it more difficult. “Malicious use has been more headline-grabbing because of deepfakes and scams,” says McKinsey senior partner Ida Kristensen in an episode of the Inside the Strategy Room podcast. For example, in the past, most spam emails could be identified readily by their “bad grammar, bad language, and things that just didn’t quite make sense,” she says. “But now it is so much easier to create high-quality spam emails using gen AI.” While security controls and oversight can help, enhanced human awareness of risk may offer the most effective protection. “Risk management is everyone’s job,” says Kristensen. “You’ve got to make sure that you have people who say, ‘That’s a little weird. That guy never leaves me a voicemail.’”
Cyberattacks may not be colorful, but the language used to describe them can be. “Pig butchering” joins the lexicon of cyberthreat standards such as phishing, pharming, smurfing, and island hopping. Derived from the practice of fattening hogs before slaughter, the term pig butchering refers to swindles where the scammers gradually “fatten” victims by gaining their trust and eventually lure them into making financial investments. What precautions can businesses take against this and other types of online fraud? “Even today’s most sophisticated cybercontrols, no matter how effective, will soon be obsolete,” caution McKinsey partner Jim Boehm and colleagues, pointing to three cybersecurity trends that leaders may need to watch to understand and mitigate the disruptions of the future.
Lead by improving cybersecurity.
— Edited by Rama Ramaswami, senior editor, New York
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by "McKinsey Leading Off" <publishing@email.mckinsey.com> - 04:20 - 23 Sep 2024 -
What are the tech trends that matter most?
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‘Golden age of innovation.’ Despite market challenges and dips in investment, innovation and interest in the tech sector remain strong, McKinsey technology experts Lareina Yee and Roger Roberts share on a recent episode of The McKinsey Podcast. Although tech investment dropped between 30% and 40%, some trends, such as generative AI (gen AI) and robotics, are continuing to see increasing investments, Yee reveals.
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The influence of gen AI. Gen AI acts as a catalyst for many of the technology trends, such as analytical AI and machine learning, which have seen increasing interest and investment. The capabilities in gen AI are also very relevant for robotics, which is one of the featured trends in the McKinsey Technology Trends Outlook 2024 report. Listen to the full podcast episode on The McKinsey Podcast to learn more about two newer tech trends.
—Edited by Belinda Yu, editor, Atlanta
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by "Only McKinsey Perspectives" <publishing@email.mckinsey.com> - 01:48 - 23 Sep 2024 -
The quarter’s top themes
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In the third quarter of 2024, our top ten posts from McKinsey Themes highlight middle managers, saying ‘no’ at work, top technology trends, and more. At No. 1 is The executive’s reading list, which features books recommended by global leaders—like McKinsey’s Bob Sternfels—to consider adding to your library. Read on for our full top 10.
2. What to read next: books on AI
Literature on artificial intelligence (AI) is everywhere, and for good reason. McKinsey research estimates that generative AI could add between $2.6 trillion to $4.4 trillion annually to the economy while increasing the impact of all AI by 15 to 40 percent. Learn about the hot topic
3. Help yourself to these personal development books
You don’t need to wait for the new year to make positive changes in your life—you can start right now. Whether you’re taking steps to define your purpose, tackling big projects, or trying to curb overthinking, these personal development books just might give you the motivation you need to get started. Make resolutions now
What do companies comprising the Magnificent Seven and the Granolas have in common? They have captured investors’ fancy with a superpower, or an integrated set of people, processes, and technology that creates value by helping an organization do something better than its competitors. Fly above competitors
As India anticipates a century of independence in 2047, it is committing to sustainable and inclusive growth in its goal of becoming a developed economy. To understand how Indian enterprises can achieve the growth necessary to help propel the nation towards its centennial aspirations, McKinsey analyzed publicly traded companies over a 10-year period. 7 trends
Disagreeing at work about critical business problems can be constructive if done in a healthy manner. That’s according to McKinsey’s Chris Hartley and coauthors: “Contributory dissent allows individuals and groups to air their differences in a way that moves the discussion toward a positive outcome and doesn’t undermine leadership or group cohesion.” Flex your ‘no muscle’
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by "McKinsey Top Ten" <publishing@email.mckinsey.com> - 03:51 - 22 Sep 2024
