EP151: 24 Good Resources to Learn Software Architecture in 2025

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This week’s system design refresher:

• 24 Good Resources to Learn Software Architecture in 2025

• SOAP vs REST vs GraphQL vs RPC

• SQS vs SNS vs EventBridge vs Kinesis

• Top 5 common ways to improve API performance

• xAI’s Grok-3 One-Pager

• SPONSOR US

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24 Good Resources to Learn Software Architecture in 2025

The resources can be divided into different types such as:

1. Software Design Books
   Some books that can help are DDIA, System Design Volume 1 & 2, Clean Architecture, Domain-Driven Design, and Software Architecture: the Hard Parts

2. Tech Blogs and Newsletters
   Read technical blogs by companies like Netflix, Uber, Meta, and Airbnb. Also, the ByteByteGo newsletter provides insights into software design every week.

3. YouTube Channels and Architectural Resources
   YouTube channels like MIT Distributed Systems, Goto Conferences, and ByteByteGo can help with software architecture and system design. Azure Architecture Center and AWS Architecture Blog are other important resources.

4. WhitePapers
   For deeper insights, read whitepapers like Facebook Memcache Scaling, Cassandra, Amazon DynamoDB, Kafka, and Google File System.

5. Software Career Books
   A Software Architect also needs to develop holistic skills. Books about software career aspects such as Pragmatic Programmer, The Software Architect Elevator, The Software Engineer's Guidebook, and Philosophy of Software Design can help.

Over to you: Which other resources will you add to the list?

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SOAP vs REST vs GraphQL vs RPC

The diagram below illustrates the API timeline and API styles comparison.

Over time, different API architectural styles are released. Each of them has its own patterns of standardizing data exchange.

You can check out the use cases of each style in the diagram.

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SQS vs SNS vs EventBridge vs Kinesis

1. AWS SQS: It is a fully managed message queuing service that helps decouple communication between distributed components.

2. AWS SNS: A fully managed publish/subscribe messaging service using topics to send messages to multiple subscribers or endpoints (such as email, Lambda, SQS, and so on).

3. AWS EventBridge: It is a serverless event bus that facilitates the routing of events between AWS services, and applications based on specific routing rules and filters.

4. AWS Kinesis Data Streams: A real-time data streaming service that captures, processes, and analyzes data in near real-time.

How can you choose which service to use?

Here are some basic tips and examples:

• For massive amounts of events like a clickstream from an application use Kinesis Data Stream

• For events processed by a single consumer like an image processing job, SQS is a better choice.

• For sending messages and notifications, SNS is a great choice.

• For system events such as a new user registration that multiple services must receive and react to, use EventBridge.

Over to you: Have you used SQS, SNS, EventBridge, or Kinesis?

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Top 5 common ways to improve API performance

Result Pagination:
This method is used to optimize large result sets by streaming them back to the client, enhancing service responsiveness and user experience.

Asynchronous Logging:
This approach involves sending logs to a lock-free buffer and returning immediately, rather than dealing with the disk on every call. Logs are periodically flushed to the disk, significantly reducing I/O overhead.

Data Caching:
Frequently accessed data can be stored in a cache to speed up retrieval. Clients check the cache before querying the database, with data storage solutions like Redis offering faster access due to in-memory storage.

Payload Compression:
To reduce data transmission time, requests and responses can be compressed (e.g., using gzip), making the upload and download processes quicker.

Connection Pooling:
This technique involves using a pool of open connections to manage database interaction, which reduces the overhead associated with opening and closing connections each time data needs to be loaded. The pool manages the lifecycle of connections for efficient resource use.

Over to you: What other ways do you use to improve API performance?

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xAI’s Grok-3 One-Pager

Grok 3 was unveiled on February 17. According to Elon Musk, it is “the smartest AI on Earth.”

But what makes it so powerful?

Grok 3 has been trained on the Colossus supercomputer with 100K Nvidia H100 GPUs. According to one stat, it has been trained for 200 million GPU hours. The key capabilities of Grok 3 are coding, science research, problem-solving, creating marketing campaigns, personalized assistance, and API integration.

Some special features of Grok 3 are:

1. DeepSearch: Allows Grok to search the web and X posts for real-time data and information.

2. Think Mode: Decompose complex queries into steps just like human problem-solving.

3. Big Brain Mode: A heavy-duty mode for intensive tasks like simulations, data analysis, or reasoning.

Here’s how Grok 3 possibly works:

1. Grok 3 supports multi-modal inputs. The user can ask questions as text, upload images, or talk to Grok. The inputs are tokenized to initiate processing.

2. Synthetic data training enhances the query interpretation.

3. This is fed to the core transformer model that analyzes the input.

4. The core transformer issues a search directive to DeepSearch to retrieve necessary information from the web or real-time X data.

5. Next, a self-correct process ensures accuracy through an internal feedback loop.

6. Depending on the user’s input, the Think Mode or Big Brain Mode refines the responses as required. It might again use DeepSearch to find more information.

7. The answers are delivered to the user in a multimodal manner.

Note that these details are based on piecing together information from xAI blogs about Grok and new feature announcements. More details may be revealed in the coming days.

Over to you: Have you used xAI’s Grok 3?

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