[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.] #  @Kaperskyguru Solomon Eseme Solomon Eseme posts on X about python, redis, token, $newr the most. They currently have XXXXXX followers and XXX posts still getting attention that total XXXXXX engagements in the last XX hours. ### Engagements: XXXXXX [#](/creator/twitter::306896648/interactions)  - X Week XXXXXXX +619% - X Month XXXXXXX -XX% - X Months XXXXXXXXX +108% - X Year XXXXXXXXX +78% ### Mentions: XX [#](/creator/twitter::306896648/posts_active)  - X Week XX +50% - X Month XXX -XXXX% - X Months XXX +332% - X Year XXX +96% ### Followers: XXXXXX [#](/creator/twitter::306896648/followers)  - X Week XXXXXX +0.63% - X Month XXXXXX +1.70% - X Months XXXXXX +12% - X Year XXXXXX +20% ### CreatorRank: XXXXXXX [#](/creator/twitter::306896648/influencer_rank)  ### Social Influence [#](/creator/twitter::306896648/influence) --- **Social category influence** [stocks](/list/stocks) [technology brands](/list/technology-brands) [social networks](/list/social-networks) **Social topic influence** [python](/topic/python) #268, [redis](/topic/redis) #5, [token](/topic/token), [$newr](/topic/$newr) #3, [safely](/topic/safely) #623, [cloudflare](/topic/cloudflare) #107, [i remember](/topic/i-remember), [hahaha](/topic/hahaha), [mindset](/topic/mindset), [loops](/topic/loops) **Top assets mentioned** [New Relic, Inc. (NEWR)](/topic/$newr) [Cloudflare, Inc. (NET)](/topic/cloudflare) ### Top Social Posts [#](/creator/twitter::306896648/posts) --- Top posts by engagements in the last XX hours "Youre in a backend interview. They ask: How would you design a rate-limiting system for APIs at scale Heres how to approach it:" [X Link](https://x.com/Kaperskyguru/status/1979097774764572844) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-17T08:10Z 35.8K followers, 32.2K engagements "Scheduling logic: - Jobs stored in DB with metadata (interval next_run owner). - Scheduler polls due jobs periodically. - Pushes tasks to queue (Kafka RabbitMQ SQS). - Workers consume and execute" [X Link](https://x.com/Kaperskyguru/status/1980182276240801912) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T08:00Z 35.8K followers, 2210 engagements "@rob_stemp Oh yeah. I remember those days of data grid with JQuery. Hahaha good old days" [X Link](https://x.com/Kaperskyguru/status/1979657051606561110) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-18T21:13Z 35.8K followers, XX engagements "Tools you should know: - Prometheus & Grafana for metrics - OpenTelemetry for tracing - ELK or Loki for logs - Datadog New Relic or Honeycomb if youre going managed But tools are secondary mindset first" [X Link](https://x.com/Kaperskyguru/status/1980303093708587289) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T16:00Z 35.8K followers, XXX engagements "You've been learning Python for a while now. Youve done loops classes functions and even built a few small scripts. But when someone says Build a backend for this app you freeze. Here's why this happens to so many Python devs and how to fix it" [X Link](https://x.com/Kaperskyguru/status/1980573793237250239) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T09:56Z 35.8K followers, 1403 engagements "Youre in a backend interview. They ask: How would you design a distributed job scheduling system like Cron but at scale Heres how to approach it:" [X Link](https://x.com/Kaperskyguru/status/1980182229109416070) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T08:00Z 35.8K followers, 29.4K engagements "The challenge: no duplicate runs. Solutions: - Use distributed locks (Redis Redlock or DB row locks). - Assign job ownership using consistent hashing. - Store last executed at timestamps to avoid re-runs" [X Link](https://x.com/Kaperskyguru/status/1980182287905169476) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T08:00Z 35.8K followers, 2021 engagements "Optimizations: - Use a priority queue for high-urgency tasks. - Cache active jobs in Redis to reduce DB load. - Group small periodic jobs into batch jobs" [X Link](https://x.com/Kaperskyguru/status/1980182334730276991) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T08:00Z 35.8K followers, 1315 engagements "How to say it in the interview: Id design a distributed job scheduler using a central job DB horizontally scaled schedulers Redis locks for deduplication a distributed queue for dispatch and stateless workers for execution fault-tolerant observable and elastic" [X Link](https://x.com/Kaperskyguru/status/1980182346465960433) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T08:00Z 35.8K followers, 1202 engagements "Or take databases. You can write SELECT * FROM users sure. But backend engineers: - Design efficient schemas - Add constraints and indexes - Handle transactions safely - Think about scaling and caching This is the invisible work that makes apps reliable" [X Link](https://x.com/Kaperskyguru/status/1980573829383762263) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T09:56Z 35.8K followers, XX engagements "Message flow: - User sends a message through WebSocket. - Chat service validates and publishes to a queue (e.g. Kafka). - Consumers persist messages in DB and push to recipients. - Notifications trigger for offline users" [X Link](https://x.com/Kaperskyguru/status/1978008676666671216) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-14T08:03Z 35.8K followers, 5050 engagements "Data storage: - Primary store: NoSQL (Cassandra DynamoDB) for fast writes. - Search index: ElasticSearch for message queries. - Cache: Redis for active conversations and user sessions" [X Link](https://x.com/Kaperskyguru/status/1978008688352010699) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-14T08:03Z 35.8K followers, 4417 engagements "Scaling strategy: - Partition users by chat room or region. - Use consistent hashing for message routing. - Replicate WebSocket gateways across regions. - Store connection states in Redis or an in-memory grid" [X Link](https://x.com/Kaperskyguru/status/1978008699978535052) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-14T08:03Z 35.8K followers, 3823 engagements "Additional features: - Typing indicators via lightweight WebSocket events. - Message edits/deletes handled with event versioning. - End-to-end encryption for privacy. - Push notifications for offline clients" [X Link](https://x.com/Kaperskyguru/status/1978008723370201215) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-14T08:03Z 35.8K followers, 3055 engagements "How to say it in the interview: Id design a real-time chat system with WebSockets for communication Kafka for decoupling Redis for session caching and a NoSQL DB for persistence all orchestrated for horizontal scalability and fault tolerance" [X Link](https://x.com/Kaperskyguru/status/1978008735428771869) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-14T08:03Z 35.8K followers, 2736 engagements "Common strategies: - Fixed Window simple but can burst near boundaries. - Sliding Window smoother control more accurate. - Token Bucket / Leaky Bucket allows bursts controls average rate" [X Link](https://x.com/Kaperskyguru/status/1979097809782739136) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-17T08:11Z 35.7K followers, 2667 engagements "Now architecture for scale: - API Gateway intercepts every request. - Rate Limiter Service checks users usage. - Cache Layer (Redis) stores counters and timestamps. - Backend only processes allowed requests" [X Link](https://x.com/Kaperskyguru/status/1979097821719695640) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-17T08:11Z 35.8K followers, 2537 engagements "Redis is perfect here its fast atomic and supports Lua scripts for operations like: - INCR + EXPIRE - Atomic token updates - Distributed locks (if needed)" [X Link](https://x.com/Kaperskyguru/status/1979097833329561852) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-17T08:11Z 35.8K followers, 2319 engagements "Handling scale & distribution: - Use consistent hashing to distribute users across Redis shards. - Sync metrics asynchronously to a database for long-term analytics. - Keep the limiter stateless just rely on Redis or an in-memory store" [X Link](https://x.com/Kaperskyguru/status/1979097845031669777) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-17T08:11Z 35.8K followers, 2073 engagements "For even larger systems push limits closer to the edge: - CDN-level rate limiting (Cloudflare Fastly). - API Gateway plugins (Kong Envoy). - Hybrid setup with global + local limits" [X Link](https://x.com/Kaperskyguru/status/1979097879961833578) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-17T08:11Z 35.8K followers, 1488 engagements "Here's how to say it in the interview: Id design a distributed rate limiting system with Redis as a centralized store token bucket algorithm for fairness consistent hashing for scale and strong observability for tracking abuse ensuring API stability under any load" [X Link](https://x.com/Kaperskyguru/status/1979097891693375971) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-17T08:11Z 35.8K followers, 1343 engagements "For example: If your API feels slow most engineers jump straight into optimizing code. But often the culprit isnt code its I/O. A single SELECT * or missing index can waste more time than XXX lines of inefficient logic" [X Link](https://x.com/Kaperskyguru/status/1980226520804364526) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T10:56Z 35.8K followers, XX engagements "Thats why profiling matters more than guessing. Use tools like: - EXPLAIN ANALYZE for SQL queries - APMs like New Relic or Datadog - Built-in profilers (Nodes inspect Pythons cProfile Gos pprof) Dont optimize blindly. Measure then tune" [X Link](https://x.com/Kaperskyguru/status/1980226532728783219) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T10:56Z 35.8K followers, XXX engagements "Why this matters: At scale small issues multiply fast. A single missing index or retry loop can cause cascading failures. Observability lets you spot issues before users do and prove you actually fixed them" [X Link](https://x.com/Kaperskyguru/status/1980303081486348320) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T16:00Z 35.8K followers, XX engagements "Youre in a backend interview. They ask: How would you design a real-time chat system like Slack or WhatsApp Heres how to approach it:" [X Link](https://x.com/Kaperskyguru/status/1978008629690437819) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-14T08:03Z 35.8K followers, 69.9K engagements "Fault tolerance: - If a worker dies unacked messages go back to the queue. - Scheduler nodes are stateless can restart safely. - Store job state transitions in DB for audit and replay" [X Link](https://x.com/Kaperskyguru/status/1980182311342838189) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T08:00Z 35.8K followers, 1538 engagements "Visibility & management: - Expose APIs/UI for job status next runs logs. - Emit metrics: job latency success/failure rate queue depth. - Add retries with exponential backoff for failed tasks" [X Link](https://x.com/Kaperskyguru/status/1980182323057635493) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-20T08:00Z 35.8K followers, 1328 engagements "The purpose of caching isnt speed its efficiency. Caching reduces the need to do expensive operations repeatedly. That might be a DB query an API call or a computation. But every cache has a tradeoff: freshness vs. performance" [X Link](https://x.com/Kaperskyguru/status/1980551767776768167) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T08:28Z 35.8K followers, XXX engagements "Where to cache: Database queries: Redis or Memcached - Static assets: CDN like Cloudflare - API responses: Edge caching or local memory - Computed results: background jobs Choose based on whats expensive and whats stable" [X Link](https://x.com/Kaperskyguru/status/1980551779474723283) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T08:28Z 35.8K followers, XXX engagements "Example: You know how to make HTTP requests. But do you know how to: - Design REST endpoints - Handle authentication tokens - Manage rate limiting and errors - Version your API Thats what real backend work looks like" [X Link](https://x.com/Kaperskyguru/status/1980573817501282392) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T09:56Z 35.8K followers, XX engagements "Every backend developer faces this question at some point: Should I learn Java Node.js Go or Python Each has strengths. But lets look at what really makes Java stand out especially for building systems that last" [X Link](https://x.com/Kaperskyguru/status/1980664636711338039) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T15:57Z 35.8K followers, 2331 engagements "Go is modern clean and great for microservices. But it still lacks the vast ecosystem Java has built over XX years. In Java almost every problem has a stable mature library or framework waiting for you" [X Link](https://x.com/Kaperskyguru/status/1980664660488777805) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T15:57Z 35.8K followers, XXX engagements "Python wins on simplicity but at scale performance becomes a bottleneck. Thats why most machine learning pipelines are served by Java backends even if theyre trained in Python" [X Link](https://x.com/Kaperskyguru/status/1980664672274825392) [@Kaperskyguru](/creator/x/Kaperskyguru) 2025-10-21T15:57Z 35.8K followers, XXX engagements
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
@Kaperskyguru Solomon Eseme
Solomon Eseme posts on X about python, redis, token, $newr the most. They currently have XXXXXX followers and XXX posts still getting attention that total XXXXXX engagements in the last XX hours.
Engagements: XXXXXX #
- X Week XXXXXXX +619%
- X Month XXXXXXX -XX%
- X Months XXXXXXXXX +108%
- X Year XXXXXXXXX +78%
Mentions: XX #
- X Week XX +50%
- X Month XXX -XXXX%
- X Months XXX +332%
- X Year XXX +96%
Followers: XXXXXX #
- X Week XXXXXX +0.63%
- X Month XXXXXX +1.70%
- X Months XXXXXX +12%
- X Year XXXXXX +20%
CreatorRank: XXXXXXX #
Social Influence #
Social category influence stocks technology brands social networks
Social topic influence python #268, redis #5, token, $newr #3, safely #623, cloudflare #107, i remember, hahaha, mindset, loops
Top assets mentioned New Relic, Inc. (NEWR) Cloudflare, Inc. (NET)
Top Social Posts #
Top posts by engagements in the last XX hours
"Youre in a backend interview. They ask: How would you design a rate-limiting system for APIs at scale Heres how to approach it:"
X Link @Kaperskyguru 2025-10-17T08:10Z 35.8K followers, 32.2K engagements
"Scheduling logic: - Jobs stored in DB with metadata (interval next_run owner). - Scheduler polls due jobs periodically. - Pushes tasks to queue (Kafka RabbitMQ SQS). - Workers consume and execute"
X Link @Kaperskyguru 2025-10-20T08:00Z 35.8K followers, 2210 engagements
"@rob_stemp Oh yeah. I remember those days of data grid with JQuery. Hahaha good old days"
X Link @Kaperskyguru 2025-10-18T21:13Z 35.8K followers, XX engagements
"Tools you should know: - Prometheus & Grafana for metrics - OpenTelemetry for tracing - ELK or Loki for logs - Datadog New Relic or Honeycomb if youre going managed But tools are secondary mindset first"
X Link @Kaperskyguru 2025-10-20T16:00Z 35.8K followers, XXX engagements
"You've been learning Python for a while now. Youve done loops classes functions and even built a few small scripts. But when someone says Build a backend for this app you freeze. Here's why this happens to so many Python devs and how to fix it"
X Link @Kaperskyguru 2025-10-21T09:56Z 35.8K followers, 1403 engagements
"Youre in a backend interview. They ask: How would you design a distributed job scheduling system like Cron but at scale Heres how to approach it:"
X Link @Kaperskyguru 2025-10-20T08:00Z 35.8K followers, 29.4K engagements
"The challenge: no duplicate runs. Solutions: - Use distributed locks (Redis Redlock or DB row locks). - Assign job ownership using consistent hashing. - Store last executed at timestamps to avoid re-runs"
X Link @Kaperskyguru 2025-10-20T08:00Z 35.8K followers, 2021 engagements
"Optimizations: - Use a priority queue for high-urgency tasks. - Cache active jobs in Redis to reduce DB load. - Group small periodic jobs into batch jobs"
X Link @Kaperskyguru 2025-10-20T08:00Z 35.8K followers, 1315 engagements
"How to say it in the interview: Id design a distributed job scheduler using a central job DB horizontally scaled schedulers Redis locks for deduplication a distributed queue for dispatch and stateless workers for execution fault-tolerant observable and elastic"
X Link @Kaperskyguru 2025-10-20T08:00Z 35.8K followers, 1202 engagements
"Or take databases. You can write SELECT * FROM users sure. But backend engineers: - Design efficient schemas - Add constraints and indexes - Handle transactions safely - Think about scaling and caching This is the invisible work that makes apps reliable"
X Link @Kaperskyguru 2025-10-21T09:56Z 35.8K followers, XX engagements
"Message flow: - User sends a message through WebSocket. - Chat service validates and publishes to a queue (e.g. Kafka). - Consumers persist messages in DB and push to recipients. - Notifications trigger for offline users"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.8K followers, 5050 engagements
"Data storage: - Primary store: NoSQL (Cassandra DynamoDB) for fast writes. - Search index: ElasticSearch for message queries. - Cache: Redis for active conversations and user sessions"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.8K followers, 4417 engagements
"Scaling strategy: - Partition users by chat room or region. - Use consistent hashing for message routing. - Replicate WebSocket gateways across regions. - Store connection states in Redis or an in-memory grid"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.8K followers, 3823 engagements
"Additional features: - Typing indicators via lightweight WebSocket events. - Message edits/deletes handled with event versioning. - End-to-end encryption for privacy. - Push notifications for offline clients"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.8K followers, 3055 engagements
"How to say it in the interview: Id design a real-time chat system with WebSockets for communication Kafka for decoupling Redis for session caching and a NoSQL DB for persistence all orchestrated for horizontal scalability and fault tolerance"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.8K followers, 2736 engagements
"Common strategies: - Fixed Window simple but can burst near boundaries. - Sliding Window smoother control more accurate. - Token Bucket / Leaky Bucket allows bursts controls average rate"
X Link @Kaperskyguru 2025-10-17T08:11Z 35.7K followers, 2667 engagements
"Now architecture for scale: - API Gateway intercepts every request. - Rate Limiter Service checks users usage. - Cache Layer (Redis) stores counters and timestamps. - Backend only processes allowed requests"
X Link @Kaperskyguru 2025-10-17T08:11Z 35.8K followers, 2537 engagements
"Redis is perfect here its fast atomic and supports Lua scripts for operations like: - INCR + EXPIRE - Atomic token updates - Distributed locks (if needed)"
X Link @Kaperskyguru 2025-10-17T08:11Z 35.8K followers, 2319 engagements
"Handling scale & distribution: - Use consistent hashing to distribute users across Redis shards. - Sync metrics asynchronously to a database for long-term analytics. - Keep the limiter stateless just rely on Redis or an in-memory store"
X Link @Kaperskyguru 2025-10-17T08:11Z 35.8K followers, 2073 engagements
"For even larger systems push limits closer to the edge: - CDN-level rate limiting (Cloudflare Fastly). - API Gateway plugins (Kong Envoy). - Hybrid setup with global + local limits"
X Link @Kaperskyguru 2025-10-17T08:11Z 35.8K followers, 1488 engagements
"Here's how to say it in the interview: Id design a distributed rate limiting system with Redis as a centralized store token bucket algorithm for fairness consistent hashing for scale and strong observability for tracking abuse ensuring API stability under any load"
X Link @Kaperskyguru 2025-10-17T08:11Z 35.8K followers, 1343 engagements
"For example: If your API feels slow most engineers jump straight into optimizing code. But often the culprit isnt code its I/O. A single SELECT * or missing index can waste more time than XXX lines of inefficient logic"
X Link @Kaperskyguru 2025-10-20T10:56Z 35.8K followers, XX engagements
"Thats why profiling matters more than guessing. Use tools like: - EXPLAIN ANALYZE for SQL queries - APMs like New Relic or Datadog - Built-in profilers (Nodes inspect Pythons cProfile Gos pprof) Dont optimize blindly. Measure then tune"
X Link @Kaperskyguru 2025-10-20T10:56Z 35.8K followers, XXX engagements
"Why this matters: At scale small issues multiply fast. A single missing index or retry loop can cause cascading failures. Observability lets you spot issues before users do and prove you actually fixed them"
X Link @Kaperskyguru 2025-10-20T16:00Z 35.8K followers, XX engagements
"Youre in a backend interview. They ask: How would you design a real-time chat system like Slack or WhatsApp Heres how to approach it:"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.8K followers, 69.9K engagements
"Fault tolerance: - If a worker dies unacked messages go back to the queue. - Scheduler nodes are stateless can restart safely. - Store job state transitions in DB for audit and replay"
X Link @Kaperskyguru 2025-10-20T08:00Z 35.8K followers, 1538 engagements
"Visibility & management: - Expose APIs/UI for job status next runs logs. - Emit metrics: job latency success/failure rate queue depth. - Add retries with exponential backoff for failed tasks"
X Link @Kaperskyguru 2025-10-20T08:00Z 35.8K followers, 1328 engagements
"The purpose of caching isnt speed its efficiency. Caching reduces the need to do expensive operations repeatedly. That might be a DB query an API call or a computation. But every cache has a tradeoff: freshness vs. performance"
X Link @Kaperskyguru 2025-10-21T08:28Z 35.8K followers, XXX engagements
"Where to cache: Database queries: Redis or Memcached - Static assets: CDN like Cloudflare - API responses: Edge caching or local memory - Computed results: background jobs Choose based on whats expensive and whats stable"
X Link @Kaperskyguru 2025-10-21T08:28Z 35.8K followers, XXX engagements
"Example: You know how to make HTTP requests. But do you know how to: - Design REST endpoints - Handle authentication tokens - Manage rate limiting and errors - Version your API Thats what real backend work looks like"
X Link @Kaperskyguru 2025-10-21T09:56Z 35.8K followers, XX engagements
"Every backend developer faces this question at some point: Should I learn Java Node.js Go or Python Each has strengths. But lets look at what really makes Java stand out especially for building systems that last"
X Link @Kaperskyguru 2025-10-21T15:57Z 35.8K followers, 2331 engagements
"Go is modern clean and great for microservices. But it still lacks the vast ecosystem Java has built over XX years. In Java almost every problem has a stable mature library or framework waiting for you"
X Link @Kaperskyguru 2025-10-21T15:57Z 35.8K followers, XXX engagements
"Python wins on simplicity but at scale performance becomes a bottleneck. Thats why most machine learning pipelines are served by Java backends even if theyre trained in Python"
X Link @Kaperskyguru 2025-10-21T15:57Z 35.8K followers, XXX engagements