How is data sent over the network? Why do we need so many layers in the OSI model?
The diagram below shows how data is encapsulated and de-encapsulated when transmitting over the network.
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🔹 Step 1: When Device A sends data to Device B over the network via the HTTP protocol, it is first added an HTTP header at the application layer.
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🔹 Step 2: Then a TCP or a UDP header is added to the data. It is encapsulated into TCP segments at the transport layer. The header contains the source port, destination port, and sequence number.
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🔹 Step 3: The segments are then encapsulated with an IP header at the network layer. The IP header contains the source/destination IP addresses.
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🔹 Step 4: The IP datagram is added a MAC header at the data link layer, with source/destination MAC addresses.
🔹 Step 5: The encapsulated frames are sent to the physical layer and sent over the network in binary bits.
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🔹 Steps 6-10: When Device B receives the bits from the network, it performs the de-encapsulation process, which is a reverse processing of the encapsulation process. The headers are removed layer by layer, and eventually, Device B can read the data.
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We need layers in the network model because each layer focuses on its own responsibilities. Each layer can rely on the headers for processing instructions and does not need to know the meaning of the data from the last layer.
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👉 Over to you: Do you know which layer is responsible for resending lost data?
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Model Context Protocol (MCP) is a new system introduced by Anthropic to make AI models more powerful.
It is an open standard (also being run as an open-source project) that allows AI models (like Claude) to connect to databases, APIs, file systems, and other tools without needing custom code for each new integration.
MCP follows a client-server model with 3 key components:
1 - Host: AI applications like Claude that provide the environment for AI interactions so that different tools and data sources can be accessed. The host runs the MCP Client.
Kubernetes (K8S) is an open-source container orchestration platform originally developed by Google and now maintained by CNCF.
Here’s how developers interact with Kubernetes:
1 - Developers create manifest files describing the application.
2 - Kubernetes takes these manifest files, validates them, and deploys the applications across its cluster of worker nodes.
3 - Kubernetes manages the entire lifecycle of the application.
Kubernetes is made up of two main components:
1 - Control Plane: It is like the brain of Kubernetes and consists of the following parts:
- API Server: It receives all incoming requests from users or CLI.
1 - Collaboration Tools
Software development is a social activity. Learn to use collaboration tools like Jira, Confluence, Slack, MS Teams, Zoom, etc.
2 - Programming Languages
Pick and master one or two programming languages. Choose from options like Java, Python, JavaScript, C#, Go, etc.
3 - API Development
Learn the ins and outs of API Development approaches such as REST, GraphQL, and gRPC.
4 - Web Servers and Hosting
Know about web servers as well as cloud platforms like AWS, Azure, GCP, and Kubernetes
5 - Authentication and Testing
Learn how to secure your applications with authentication techniques such as JWTs, OAuth2, etc. Also, master testing techniques like TDD, E2E Testing, and Performance Testing
6 - Databases
Learn to work with relational (Postgres, MySQL, and SQLite) and non-relational databases (MongoDB, Cassandra, and Redis).
Twitter has enforced very strict rate limiting. Some people cannot even see their own tweets.
Rate limiting is a very important yet often overlooked topic. Let's use this opportunity to take a look at what it is and the most popular algorithms.
A thread.
#RateLimitExceeded
What is rate limiting? Rate limiting controls the rate at which users or services can access a resource. Here are some examples:
- A user can send a message no more than 2 per second
- One can create a maximum of 10 accounts per day from the same IP address
Fixed Window Counter
The algorithm divides the timeline into fixed-size time windows and assigns a counter for each window. Each request increments the counter by some value. Once the counter reaches the threshold, subsequent requests are blocked until the new time window begins