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by "McKinsey Week in Charts" <publishing@email.mckinsey.com> - 02:53 - 26 Oct 2024 -
EP135: Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
EP135: Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
Forwarded this email? Subscribe here for moreThe Enterprise Ready Conference for engineering leaders (Sponsored)
The Enterprise Ready Conference is a one-day event in SF, bringing together product and engineering leaders shaping the future of enterprise SaaS.
The event features a curated list of speakers with direct experience building for the enterprise, including OpenAI, Vanta, Checkr, Dropbox, and Canva.
Topics include advanced identity management, compliance, encryption, and logging — essential yet complex features that most enterprise customers require.
If you are a founder, exec, PM, or engineer tasked with the enterprise roadmap, this conference is for you. You’ll get detailed insights from industry leaders that have years of experience navigating the same challenges you face today. And best of all, it’s completely free since it’s hosted by WorkOS.This week’s system design interview:
Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
A Cheatsheet on Comparing API Architectural Styles
10 Key Data Structures We Use Every Day
A Cheatsheet to Build Secure APIs
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Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
Each platform offers a comprehensive suite of services that cover the entire lifecycle:
Ingestion: Collecting data from various sources
Data Lake: Storing raw data
Computation: Processing and analyzing data
Data Warehouse: Storing structured data
Presentation: Visualizing and reporting insights
AWS uses services like Kinesis for data streaming, S3 for storage, EMR for processing, RedShift for warehousing, and QuickSight for visualization.
Azure’s pipeline includes Event Hubs for ingestion, Data Lake Store for storage, Databricks for processing, Cosmos DB for warehousing, and Power BI for presentation.
GCP offers PubSub for data streaming, Cloud Storage for data lakes, DataProc and DataFlow for processing, BigQuery for warehousing, and Data Studio for visualization.
Over to you: What else would you add to the pipeline?A Cheatsheet on Comparing API Architectural Styles
It covers the 6 most popular API architectural styles:
SOAP
REST
GraphQL
gRPC
WebSocket
Webhook
Over to you: Which other architectural style have you used?
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10 Key Data Structures We Use Every Day
list: keep your Twitter feeds
stack: support undo/redo of the word editor
queue: keep printer jobs, or send user actions in-game
hash table: cashing systems
Array: math operations
heap: task scheduling
tree: keep the HTML document, or for AI decision
suffix tree: for searching string in a document
graph: for tracking friendship, or path finding
r-tree: for finding the nearest neighbor
vertex buffer: for sending data to GPU for rendering
Over to you: Which additional data structures have we overlooked?
A Cheatsheet to Build Secure APIs
An insecure API can compromise your entire application. Follow these strategies to mitigate the risk:
Using HTTPS
Encrypts data in transit and protects against man-in-the-middle attacks.
This ensures that data hasn’t been tampered with during transmission.Rate Limiting and Throttling
Rate limiting prevents DoS attacks by limiting requests from a single IP or user.
The goal is to ensure fairness and prevent abuse.Validation of Inputs
Defends against injection attacks and unexpected data format.
Validate headers, inputs, and payloadAuthentication and Authorization
Don’t use basic auth for authentication. Instead, use a standard authentication approach like JWTs
Use a random key that is hard to guess as the JWT secret
Make token expiration short
For authorization, use OAuthUsing Role-based Access Control
RBAC simplifies access management for APIs and reduces the risk of unauthorized actions.
Granular control over user permission based on roles.Monitoring
Monitoring the APIs is the key to detecting issues and threats early.
Use tools like Kibana, Cloudwatch, Datadog, and Slack for monitoring
Don’t log sensitive data like credit card info, passwords, credentials, etc.
Over to you: What else would you do to build a secure API?
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Your Strapi demo is over, what's next? 🙂
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The art of 21st-century leadership, corporate venture building, arenas of competition, and more highlights
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by "McKinsey Weekend Read" <publishing@email.mckinsey.com> - 11:52 - 24 Oct 2024 -
Why is introspection a critical part of leadership?
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Introspective leadership. The CEO role has never been more demanding, according to McKinsey senior partners Dana Maor, Kurt Strovink, and Ramesh Srinivasan and senior partner emeritus Hans-Werner Kaas. In their new book, The Journey of Leadership: How CEOs Learn to Lead from the Inside Out, the authors say the best CEOs can meet the moment by leading from the “inside out”—that is, achieving personal growth through introspection before inspiring others to change.
•
Boosting the bottom line. Human-centered leadership, which gives people a sense of purpose and nurtures their ambitions, can empower workers and also boost a company’s bottom line. A McKinsey Global Institute study of 1,800 large companies in 15 countries finds that businesses that focus on both human capital and financial performance are about 1.5 times more likely than the average company to remain high performers over time. Visit our latest McKinsey Quarterly Five Fifty to discover five mindset shifts that can help leaders focus more on the human element of their roles.
—Edited by Belinda Yu, editor, Atlanta
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by "Only McKinsey Perspectives" <publishing@email.mckinsey.com> - 10:08 - 24 Oct 2024 -
Your Strapi demo is almost over! ⏰
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by "Maxime Castres" <demo@strapi.io> - 05:33 - 24 Oct 2024 -
Event-Driven Architectural Patterns
Event-Driven Architectural Patterns
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Event-driven architecture (EDA) is a software design approach emphasizing the production, detection, consumption, and reaction to events. In this architecture, events are state changes or updates within a system.
EDA is particularly beneficial in modern software development because it can decouple services, enhance scalability, and improve responsiveness.
By allowing systems to react to events asynchronously, EDA supports real-time processing and enables systems to handle high volumes of data efficiently. This approach is useful in distributed systems and microservices architectures, where different components must operate independently yet cohesively.
The importance of EDA in today's software landscape cannot be overstated. It offers significant advantages such as:
Improved fault tolerance because systems can continue operating even if some components fail.
Better resource utilization by enabling services to scale independently based on demand.
Supports dynamic and flexible workflows, allowing businesses to adapt quickly to changing requirements and market conditions.
In this article, we’ll explore various patterns used in event-driven architecture. By examining these patterns, the aim is to gather insights into how they can be applied to build robust, scalable, and responsive systems.
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by "ByteByteGo" <bytebytego@substack.com> - 10:37 - 24 Oct 2024 -
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by "Maxime Castres" <demo@strapi.io> - 05:32 - 24 Oct 2024 -
How much value could digital and AI generate for consumer goods firms?
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Welcome to the latest edition of Only McKinsey Perspectives. We hope you find our insights useful. Let us know what you think at Alex_Panas@McKinsey.com and Axel_Karlsson@McKinsey.com.
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Six innovation zones. Amid all the hype around generative AI’s (gen AI’s) promise to reinvent how businesses run—and even though many consumer-packaged-goods (CPG) leaders say they use it regularly—no CPG company has truly scaled its gen AI and traditional AI capabilities. According to analysis by McKinsey senior partner Jessica Moulton and coauthors, the industry’s most significant sources of value from digital and AI transformations fall into six “innovation zones,” including product and innovation, as well as manufacturing and operations.
—Edited by Belinda Yu, editor, Atlanta
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2024 Observability Forecast Report is here!
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The 2024 Observability Forecast reveals the state of observability, identifying key areas of growth and opportunity, while uncovering what’s driving adoption and investment strategies.
Key findings from the forecast include:- AI adoption is currently at 29% globally, but is expected to surge, with 41% of companies planning to implement AI monitoring, and 39% adopting AIOps capabilities over the next year.
- 37% of organizations manage siloed telemetry data while continuing to grapple with tool sprawl, compared to 38% that have more unified data.
- 46% said observability improved their operations most by enabling real-time data insights from a single dashboard.
Discover insights from 1,700 technology professionals to help shape your strategic decisions for the coming year.Read Report
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