Top 9 System Integrations
Top 9 Architectural Patterns for Data and Communication Flow
Peer-to-Peer
The Peer-to-Peer pattern involves direct communication between two components without the need for a central coordinator.
API Gateway
An API Gateway acts as a single entry point for all client requests to the backend services of an application.
Pub-Sub
The Pub-Sub pattern decouples the producers of messages (publishers) from the consumers of messages (subscribers) through a message broker.
Request-Response
This is one of the most fundamental integration patterns, where a client sends a request to a server and waits for a response.
Event Sourcing
Event Sourcing involves storing the state changes of an application as a sequence of events.
ETL
ETL is a data integration pattern used to gather data from multiple sources, transform it into a structured format, and load it into a destination database.
Batching
Batching involves accumulating data over a period or until a certain threshold is met before processing it as a single group.
Streaming Processing
Streaming Processing allows for the continuous ingestion, processing, and analysis of data streams in real-time.
Orchestration
Orchestration involves a central coordinator (an orchestrator) managing the interactions between distributed components or services to achieve a workflow or business process.
#SystemIntegrations #APIGateway #PubSub #Batching #ETL #RequestResponse
Concurrency vs Parallelism
Things Every Developer Should Know:
Concurrency is ๐๐๐ parallelism.
In system design, it is important to understand the difference between concurrency and parallelism.
As Rob Pyke(one of the creators of GoLang) stated:โ Concurrency is about ๐๐๐๐ฅ๐ข๐ง๐ ๐ฐ๐ข๐ญ๐ก lots of things at once. Parallelism is about ๐๐จ๐ข๐ง๐ lots of things at once.โ This distinction emphasizes that concurrency is more about the ๐๐๐ฌ๐ข๐ ๐ง of a program, while parallelism is about the ๐๐ฑ๐๐๐ฎ๐ญ๐ข๐จ๐ง.
Concurrency is about dealing with multiple things at once. It involves structuring a program to handle multiple tasks simultaneously, where the tasks can start, run, and complete in overlapping time periods, but not necessarily at the same instant.
Concurrency is about the composition of independently executing processes and describes a program's ability to manage multiple tasks by making progress on them without necessarily completing one before it starts another.
Parallelism, on the other hand, refers to the simultaneous execution of multiple computations. It is the technique of running two or more tasks or computations at the same time, utilizing multiple processors or cores within a computer to perform several operations concurrently. Parallelism requires hardware with multiple processing units, and its primary goal is to increase the throughput and computational speed of a system.
In practical terms, concurrency enables a program to remain responsive to input, perform background tasks, and handle multiple operations in a seemingly simultaneous manner, even on a single-core processor. It's particularly useful in I/O-bound and high-latency operations where programs need to wait for external events, such as file, network, or user interactions.
Parallelism, with its ability to perform multiple operations at the same time, is crucial in CPU-bound tasks where computational speed and throughput are the bottlenecks. Applications that require heavy mathematical computations, data analysis, image processing, and real-time processing can significantly benefit from parallel execution.
What is DevSecOps?
What is DevSecOps?
DevSecOps emerged as a natural evolution of DevOps practices with a focus on integrating security into the software development and deployment process. The term โDevSecOpsโ represents the convergence of Development (Dev), Security (Sec), and Operations (Ops) practices, emphasizing the importance of security throughout the software development lifecycle. The diagram below shows the important concepts in DevSecOps.
1 . Automated Security Checks
2 . Continuous Monitoring
3 . CI/CD Automation
4 . Infrastructure as Code (IaC)
5 . Container Security
6 . Secret Management
7 . Threat Modeling
8. Quality Assurance (QA) Integration
9 . Collaboration and Communication
10 . Vulnerability Management
Linux Boot Process
Linux Performance Observability Tools
Popular interview question: how to diagnose a mysterious process thatโs taking too much CPU, memory, IO, etc?
The diagram above illustrates helpful tools in a Linux system.
โvmstatโ โ reports information about processes, memory, paging, block IO, traps, and CPU activity.
โiostatโ โ reports CPU and input/output statistics of the system.
โnetstatโ โ displays statistical data related to IP, TCP, UDP, and ICMP protocols.
โlsofโ โ lists open files of the current system.
โpidstatโ โ monitors the utilization of system resources by all or specified processes, including CPU, memory, device IO, task switching, threads, etc.
