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#Kinesis Data Reel by @datastreakofficial (verified account) - This video walks through an event-driven microservices architecture where Kafka acts as the central event backbone. Incoming client traffic is load-ba
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@datastreakofficial
This video walks through an event-driven microservices architecture where Kafka acts as the central event backbone. Incoming client traffic is load-balanced across API services, which publish business events such as ORDER_PLACED to Kafka instead of making synchronous downstream calls. Independent microservices consume these events asynchronously, enabling horizontal scaling, fault isolation, and reliable processing. Transactional data is stored in the database, while Redis caching provides fast access to frequently requested data. This architecture is ideal for high-traffic e-commerce platforms requiring scalability, resilience, and high availability. #Kafka #SystemDesign #Microservices #EventDrivenArchitecture #BackendEngineering
#Kinesis Data Reel by @_securebysuhana_ - ๐—š๐—ถ๐˜ƒ๐—ฒ ๐—บ๐—ฒ ๐Ÿฎ ๐—บ๐—ถ๐—ป๐˜‚๐˜๐—ฒ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—œ'๐—น๐—น ๐˜๐—ฒ๐—ฎ๐—ฐ๐—ต ๐˜†๐—ผ๐˜‚ ๐—ต๐—ผ๐˜„ ๐˜๐—ต๐—ฒ ๐—ข๐—ฆ๐—œ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น ๐˜„๐—ผ๐—ฟ๐—ธ๐˜€

The ๐—ข๐—ฆ๐—œ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น (๐—ข๐—ฝ๐—ฒ๐—ป ๐—ฆ๐˜†๐˜€๐˜๏ฟฝ
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@_securebysuhana_
๐—š๐—ถ๐˜ƒ๐—ฒ ๐—บ๐—ฒ ๐Ÿฎ ๐—บ๐—ถ๐—ป๐˜‚๐˜๐—ฒ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—œโ€™๐—น๐—น ๐˜๐—ฒ๐—ฎ๐—ฐ๐—ต ๐˜†๐—ผ๐˜‚ ๐—ต๐—ผ๐˜„ ๐˜๐—ต๐—ฒ ๐—ข๐—ฆ๐—œ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น ๐˜„๐—ผ๐—ฟ๐—ธ๐˜€ The ๐—ข๐—ฆ๐—œ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น (๐—ข๐—ฝ๐—ฒ๐—ป ๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ๐˜€ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ฐ๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป) is a ๐Ÿณ-๐—น๐—ฎ๐˜†๐—ฒ๐—ฟ ๐—ฐ๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜‚๐—ฎ๐—น ๐—ณ๐—ฟ๐—ฎ๐—บ๐—ฒ๐˜„๐—ผ๐—ฟ๐—ธ that explains how data moves across a network. It helps engineers ๐—ฑ๐—ฒ๐˜€๐—ถ๐—ด๐—ป, ๐˜‚๐—ป๐—ฑ๐—ฒ๐—ฟ๐˜€๐˜๐—ฎ๐—ป๐—ฑ, ๐—ฎ๐—ป๐—ฑ ๐˜๐—ฟ๐—ผ๐˜‚๐—ฏ๐—น๐—ฒ๐˜€๐—ต๐—ผ๐—ผ๐˜ ๐—ป๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ ๐—ฐ๐—ผ๐—บ๐—บ๐˜‚๐—ป๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป. Letโ€™s break it down ๐Ÿ‘‡ 7๏ธโƒฃ ๐—”๐—ฝ๐—ฝ๐—น๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—Ÿ๐—ฎ๐˜†๐—ฒ๐—ฟ โ€ข The layer closest to the user. โ€ข Handles communication for applications like browsers, email clients, and APIs. โ€ข Common protocols: ๐—›๐—ง๐—ง๐—ฃ, ๐—›๐—ง๐—ง๐—ฃ๐—ฆ, ๐—ฆ๐— ๐—ง๐—ฃ, ๐—™๐—ง๐—ฃ 6๏ธโƒฃ ๐—ฃ๐—ฟ๐—ฒ๐˜€๐—ฒ๐—ป๐˜๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—Ÿ๐—ฎ๐˜†๐—ฒ๐—ฟ โ€ข Prepares data for the application layer. โ€ข Responsible for ๐—ฑ๐—ฎ๐˜๐—ฎ ๐˜๐—ฟ๐—ฎ๐—ป๐˜€๐—น๐—ฎ๐˜๐—ถ๐—ผ๐—ป, ๐—ฒ๐—ป๐—ฐ๐—ฟ๐˜†๐—ฝ๐˜๐—ถ๐—ผ๐—ป, ๐—ฎ๐—ป๐—ฑ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฟ๐—ฒ๐˜€๐˜€๐—ถ๐—ผ๐—ป. โ€ข Ensures data is readable between systems. 5๏ธโƒฃ ๐—ฆ๐—ฒ๐˜€๐˜€๐—ถ๐—ผ๐—ป ๐—Ÿ๐—ฎ๐˜†๐—ฒ๐—ฟ โ€ข Manages ๐˜€๐—ฒ๐˜€๐˜€๐—ถ๐—ผ๐—ป๐˜€ ๐—ฏ๐—ฒ๐˜๐˜„๐—ฒ๐—ฒ๐—ป ๐—ฑ๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ๐˜€. โ€ข Opens, maintains, and closes communication sessions. โ€ข Adds checkpoints so connections can recover after interruptions. 4๏ธโƒฃ ๐—ง๐—ฟ๐—ฎ๐—ป๐˜€๐—ฝ๐—ผ๐—ฟ๐˜ ๐—Ÿ๐—ฎ๐˜†๐—ฒ๐—ฟ โ€ข Ensures ๐—ฟ๐—ฒ๐—น๐—ถ๐—ฎ๐—ฏ๐—น๐—ฒ ๐—ฒ๐—ป๐—ฑ-๐˜๐—ผ-๐—ฒ๐—ป๐—ฑ ๐—ฐ๐—ผ๐—บ๐—บ๐˜‚๐—ป๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป. โ€ข Breaks data into segments and reassembles them. โ€ข Handles ๐—ฒ๐—ฟ๐—ฟ๐—ผ๐—ฟ ๐—ฑ๐—ฒ๐˜๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ป๐—ฑ ๐—ณ๐—น๐—ผ๐˜„ ๐—ฐ๐—ผ๐—ป๐˜๐—ฟ๐—ผ๐—น. โ€ข Protocols: TCP, UDP 3๏ธโƒฃ ๐—ก๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ ๐—Ÿ๐—ฎ๐˜†๐—ฒ๐—ฟ โ€ข Responsible for ๐—ฟ๐—ผ๐˜‚๐˜๐—ถ๐—ป๐—ด ๐—ฎ๐—ป๐—ฑ ๐—น๐—ผ๐—ด๐—ถ๐—ฐ๐—ฎ๐—น ๐—ฎ๐—ฑ๐—ฑ๐—ฟ๐—ฒ๐˜€๐˜€๐—ถ๐—ป๐—ด. โ€ข Determines the best path for data to travel. โ€ข Protocols: ๐—œ๐—ฃ, ๐—œ๐—–๐— ๐—ฃ, ๐—œ๐—ฃ๐˜€๐—ฒ๐—ฐ 2๏ธโƒฃ ๐——๐—ฎ๐˜๐—ฎ ๐—Ÿ๐—ถ๐—ป๐—ธ ๐—Ÿ๐—ฎ๐˜†๐—ฒ๐—ฟ โ€ข Handles communication ๐˜„๐—ถ๐˜๐—ต๐—ถ๐—ป ๐˜๐—ต๐—ฒ ๐˜€๐—ฎ๐—บ๐—ฒ ๐—ป๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ. โ€ข Converts packets into frames. โ€ข Uses ๐— ๐—”๐—– ๐—ฎ๐—ฑ๐—ฑ๐—ฟ๐—ฒ๐˜€๐˜€๐—ฒ๐˜€ to deliver data to the correct device. 1๏ธโƒฃ Physical Layer โ€ข The hardware layer of the network. โ€ข Includes cables, switches, electrical signals, and transmission media. โ€ข Converts data into binary bits (0s and 1s). โœ… Quick way to remember the OSI Model: Please Do Not Throw Sausage Pizza Away The ๐—ข๐—ฆ๐—œ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น ๐—ฒ๐—ป๐˜€๐˜‚๐—ฟ๐—ฒ๐˜€ ๐˜€๐˜๐—ฟ๐˜‚๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ๐—ฑ, ๐—ฟ๐—ฒ๐—น๐—ถ๐—ฎ๐—ฏ๐—น๐—ฒ, ๐—ฎ๐—ป๐—ฑ ๐˜€๐˜๐—ฎ๐—ป๐—ฑ๐—ฎ๐—ฟ๐—ฑ๐—ถ๐˜‡๐—ฒ๐—ฑ communication across networks. #cybersecurity @_securebysuhana_
#Kinesis Data Reel by @datastreakofficial (verified account) - How do microservices dynamically find each other without hardcoded IP addresses?

In this video, I explain the Service Discovery Pattern using a real-
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@datastreakofficial
How do microservices dynamically find each other without hardcoded IP addresses? In this video, I explain the Service Discovery Pattern using a real-world architecture example with API Gateway, Service Registry, and Kubernetes pods. Youโ€™ll learn: How services register themselves How API Gateway discovers healthy instances How load balancing works dynamically What happens when a service crashes How Kubernetes handles service discovery internally If you're preparing for system design interviews, working on microservices architecture, or exploring DevOps & cloud-native systems, this concept is essential. Drop your questions in the comments ๐Ÿ‘‡ Iโ€™ll reply for sure! #microservices #systemdesign #kubernetes #devops #softwarearchitecture
#Kinesis Data Reel by @an.engineers.quest - Is your system lagging because of slow queries or blocking calls? โšก๏ธ
Choosing between Synchronous and Asynchronous communication is one of the most cr
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@an.engineers.quest
Is your system lagging because of slow queries or blocking calls? โšก๏ธ Choosing between Synchronous and Asynchronous communication is one of the most critical decisions in system design. While Sync offers simplicity and immediate feedback, Async unlocks the scalability needed for high-traffic microservices. The Breakdown: ๐Ÿ”น Sync: Best for real-time operations where โ€œnowโ€ is the only option. Think logins and payments. ๐Ÿ”น Async: The hero of high-throughput. Use it for background jobs, notifications, and decoupling services to prevent โ€œthe waiting game.โ€ Stop guessing why your latency is spiking and start looking at how your services talk to each other. Hashtags #systemdesign #microservices #backenddevelopment #softwarearchitecture #scalability
#Kinesis Data Reel by @cloudlaunchpad_official - ๐—”๐—บ๐—ฎ๐˜‡๐—ผ๐—ป ๐—˜๐—ž๐—ฆ ๐—ถ๐˜€ ๐—ฝ๐—ผ๐˜„๐—ฒ๐—ฟ๐—ณ๐˜‚๐—น.
๐—•๐˜‚๐˜ ๐—บ๐—ฎ๐—ป๐—ฎ๐—ด๐—ถ๐—ป๐—ด ๐—ž๐˜‚๐—ฏ๐—ฒ๐—ฟ๐—ป๐—ฒ๐˜๐—ฒ๐˜€ ๐—ฐ๐—น๐˜‚๐˜€๐˜๐—ฒ๐—ฟ๐˜€ ๐—ถ๐˜€ ๐—ป๐—ผ๐˜ ๐—ฎ๐—น๐˜„๐—ฎ๐˜†๐˜€ ๐˜€๐—ถ๐—บ๐—ฝ๐—น๐—ฒ.

 โ€ข Ne
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@cloudlaunchpad_official
๐—”๐—บ๐—ฎ๐˜‡๐—ผ๐—ป ๐—˜๐—ž๐—ฆ ๐—ถ๐˜€ ๐—ฝ๐—ผ๐˜„๐—ฒ๐—ฟ๐—ณ๐˜‚๐—น. ๐—•๐˜‚๐˜ ๐—บ๐—ฎ๐—ป๐—ฎ๐—ด๐—ถ๐—ป๐—ด ๐—ž๐˜‚๐—ฏ๐—ฒ๐—ฟ๐—ป๐—ฒ๐˜๐—ฒ๐˜€ ๐—ฐ๐—น๐˜‚๐˜€๐˜๐—ฒ๐—ฟ๐˜€ ๐—ถ๐˜€ ๐—ป๐—ผ๐˜ ๐—ฎ๐—น๐˜„๐—ฎ๐˜†๐˜€ ๐˜€๐—ถ๐—บ๐—ฝ๐—น๐—ฒ. โ€ข Networking. โ€ข IAM policies. โ€ข Node groups. โ€ข Security configurations. ๐—ช๐—ต๐—ฒ๐—ป ๐—ฒ๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐˜๐—ฒ๐—ฎ๐—บ ๐˜€๐—ฒ๐˜๐˜€ ๐˜๐—ต๐—ถ๐˜€ ๐˜‚๐—ฝ ๐—ฑ๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜๐—น๐˜†, ๐—ฐ๐—ผ๐—บ๐—ฝ๐—น๐—ฒ๐˜…๐—ถ๐˜๐˜† ๐—ด๐—ฟ๐—ผ๐˜„๐˜€ ๐—ณ๐—ฎ๐˜€๐˜. So the real question is not โ€œCan you run Kubernetes?โ€ Itโ€™s โ€œCan you run it consistently at scale?โ€ ๐—ช๐—ฎ๐˜๐—ฐ๐—ต ๐—ต๐—ผ๐˜„ ๐—–๐—น๐—ผ๐˜‚๐—ฑ๐—Ÿ๐—ฎ๐˜‚๐—ป๐—ฐ๐—ต๐—ฃ๐—ฎ๐—ฑ ๐˜€๐˜๐—ฎ๐—ป๐—ฑ๐—ฎ๐—ฟ๐—ฑ๐—ถ๐˜‡๐—ฒ๐˜€ ๐—˜๐—ž๐—ฆ ๐—ฑ๐—ฒ๐—ฝ๐—น๐—ผ๐˜†๐—บ๐—ฒ๐—ป๐˜๐˜€. #Kubernetes #AWSEKS #DevOps #PlatformEngineering
#Kinesis Data Reel by @clystron.tech - Strict health checks can cause restart loops in production. If your health endpoint depends on databases or external APIs, a slowdown can make your se
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@clystron.tech
Strict health checks can cause restart loops in production. If your health endpoint depends on databases or external APIs, a slowdown can make your service look unhealthy. #devops #systemdesign #architecture #backenddeveloper #cloud #sre #microservices #programming
#Kinesis Data Reel by @datastreakofficial (verified account) - In this video, we break down how a Spotify-style streaming platform works in production using AWS.

We cover:

โ€ข CDN-based global audio delivery using
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@datastreakofficial
In this video, we break down how a Spotify-style streaming platform works in production using AWS. We cover: โ€ข CDN-based global audio delivery using S3 and CloudFront โ€ข Microservices running inside Kubernetes โ€ข DynamoDB for scalable metadata storage โ€ข Redis for ultra-low-latency caching โ€ข Event streaming using Kafka โ€ข Real-time processing with Apache Flink โ€ข Analytics powered by Redshift This is a real-world system design architecture used by modern streaming platforms handling millions of users and billions of events. Whether youโ€™re preparing for a System Design interview, building a scalable platform, or learning cloud architecture, this breakdown will help you understand production-grade design patterns. Subscribe to DataStreak for more real-world system design deep dives. #systemdesign #awsarchitecture #microservices #kubernetes #distributedsystems
#Kinesis Data Reel by @techbridgelatam - Observability is no longer optional for modern systems. In cloud-native and distributed architectures, understanding what is happening inside your app
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@techbridgelatam
Observability is no longer optional for modern systems. In cloud-native and distributed architectures, understanding what is happening inside your applications in real time is critical. By combining metrics, logs, and traces, observability helps IT leaders and engineering teams move beyond basic monitoring to quickly identify root causes, improve system reliability, and optimize performance at scale. As microservices, Kubernetes, and hybrid cloud environments grow in complexity, observability has become a key pillar of DevOps, SRE, and platform engineering strategies. Stay ahead of the curve and build systems that are resilient, scalable, and transparent. Follow for technical leadership content: ... #Observability #DevOps #SRE #CloudNative #Kubernetes #SoftwareArchitecture #DistributedSystems #ITLeadership #TechTrends #SystemReliability
#Kinesis Data Reel by @siddharthsah_ - Day 23: Nginx, Istio, and Unplanned Traffic ๐Ÿง โš™๏ธ

A busy on-call morning. Had to debug why an Nginx config failed in a new environment-it came down to
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@siddharthsah_
Day 23: Nginx, Istio, and Unplanned Traffic ๐Ÿง โš™๏ธ A busy on-call morning. Had to debug why an Nginx config failed in a new environmentโ€”it came down to an Istio template not creating the necessary DNS records. Later, we chased down 502 errors in staging caused by a gateway restart. THE INTERVIEW QUESTION: โ€œHow do you troubleshoot 502 Bad Gateway errors in a Kubernetes environment using Istio?โ€ THE ANSWER: 1๏ธโƒฃ Isolate the Layer: Check if the error is coming from the Ingress Gateway, the Sidecar, or the Application itself using kubectl logs and istioctl analyze. 2๏ธโƒฃ Verify Connectivity: Ensure the Upstream Service is healthy and that Service Entries/Virtual Services are correctly configured. 3๏ธโƒฃ Check the Lifecycle: In our case, an Istio Gateway restart caused a temporary disconnect. Always check for recent pod restarts or config deployments in Splunk/K8s. THE LIFE SIDE: Still snowing in Dallas. Fed four kids, played 8 games of ping pong, and hit a solid back day. Finally seeing some wins at the table! Drop a โ€œLOGโ€ if youโ€™ve ever spent 3 hours in Splunk for a 5-minute fix! ๐Ÿ‘‡ #softwareengineering #oncall #systemdesign #dadlife #consistency
#Kinesis Data Reel by @arjay_the_dev (verified account) - How does Kubernetes work? 

K8s is a super popular orchestration system for containerized applications. #devops #k8s #coding #programming
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@arjay_the_dev
How does Kubernetes work? K8s is a super popular orchestration system for containerized applications. #devops #k8s #coding #programming
#Kinesis Data Reel by @kodekloud (verified account) - The OSI model explained like never before! ๐Ÿš€
Think of network packets like Russian nesting dolls, each of the 7 layers wrap around the previous one a
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@kodekloud
The OSI model explained like never before! ๐Ÿš€ Think of network packets like Russian nesting dolls, each of the 7 layers wrap around the previous one as your HTTP request travels from browser to server. Here's the journey: โœ… Layer 7: Your HTTP request โœ… Layer 6: Encryption & formatting โœ… Layer 5: Session management โœ… Layer 4: TCP ports & sequences โœ… Layer 3: IP routing โœ… Layer 2: MAC addressing โœ… Layer 1: Physical signals Save this for later & follow for more networking content ๐Ÿ’ก hashtag#osimodel hashtag#networking hashtag#systemdesign hashtag#computerscience
#Kinesis Data Reel by @devopscube (verified account) - Running out of IPs on EKS?

With the default VPC CNI, every pod gets an IP from the VPC.

When scaling workloads, the IP pool can run out quickly.

Pl
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@devopscube
Running out of IPs on EKS? With the default VPC CNI, every pod gets an IP from the VPC. When scaling workloads, the IP pool can run out quickly. Plan CIDR ranges early, add secondary CIDR blocks, and choose nodes with higher ENI limits. #kubernetes #eks #aws #devops

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The massive #Kinesis Data collection on Instagram features today's most engaging videos. Content from @arjay_the_dev, @datastreakofficial and @kodekloud and other creative producers has reached thousands of posts globally. Filter and watch the freshest #Kinesis Data reels instantly.

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Content Creation Tips & Strategy

๐Ÿ”ฅ #Kinesis Data shows high engagement potential - post strategically at peak times

๐Ÿ“น High-quality vertical videos (9:16) perform best for #Kinesis Data - use good lighting and clear audio

โœจ Many verified creators are active (50%) - study their content style for inspiration

โœ๏ธ Detailed captions with story work well - average caption length is 763 characters

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