we have launched @event_parlour on @ProductHunt check us out 👇 producthunt.com/products/eve…

15 years of software engineering, condensed to help you build and scale. 💻🚀 Here are 3 ways I can help you leverage tech today: 1️⃣ Build & Ship Software: Turn your ideas into robust, production-ready apps. 2️⃣ Websites & E-commerce: Establish a high-converting digital storefront. 3️⃣ Automation & AI Agents: Put your business on autopilot and save hours of manual work. Whether you want to learn the skill or need it built for your business - let’s talk. 📱 Call/WhatsApp: 0727206415 🌐 Let’s build the future together. #BuildInPublic #TechKe

storefronts links are supported bring your domain is coming to @event_parlour my storefront example - olive.eventparlour.com

Host with us - eventparlour.com

Guys I’m open to collaboration (paid) BTW. I’m not sure how this open schedule will last so HMU fast.

I am looking for an opportunity as a software engineer: My tech stack is : Node.js/Nestjs Python Javascript TypeScript tools: docker git/github Backend: Express FastAPI Ruby on Rails Database: PostgreSQL MongoDB Mysql Other technologies: Redis, TypeORM, Prisma, Next.js, React and Tailwind CSS So If you are looking for a software engineer please DM me. 📞 254727206415 Thank you for your attention !!

Betting backends are usually a mess—so I built a better one. A multi-tenant engine in Go 1.26. 100k users | <200ms latency K-Sorted IDs & Atomic Wallets M-Pesa/Tax Engine integrated Sovereign Minimalism Clean. Fast. Production-ready. github.com/nutcas3/lets-bet

I am looking for someone with good frontend skills for a TW React Next.js for an opensource project. You will work on wiring it with a rust backend. This is a good chance for someone who is junior but meticulous and willing to accept something small on the side. No vibe coders.

Not only are MCPs awesome, but ours has access to comprehensive query insights data. Super powerful for investigating query performance. Just ask it "what are the slowest queries in my database" and get ripping!

B-tree database lookups are way slower without a memory cache in place a good replacement policy for OLTP. MySQL uses a segmented LRU whereas Postgres uses a clock-sweep algorithm. Both good choices for different reasons.

In Kafka, we have topics. Producers send data to a topic, and consumers pull data from it. Each topic has multiple partitions. You might have heard your team lead say that we can simply increase the partition count to make our cluster more scalable. There is no ordering guarantee across partitions for a topic, but messages within a partition are ordered. This can be confusing initially, but think of consumer groups as subscribers: each group has multiple consumers pulling data from a topic, and the group maintains its own offset for that topic. Check out the pinned post on my profile to understand this in detail!

As a Backend Engineer in 2026 aiming for Staff, please learn: 1. One language deeply (Go/Rust/Java) Not “I can write APIs”, but runtime model, memory, concurrency, profiling, GC behavior (if any), and how to read stack traces like a native. 2. Data modeling and storage fundamentals Relational modeling, constraints, isolation levels, indexes, query plans, locks, deadlocks, migrations, backup/restore, partitioning. Most “scaling” problems are schema query shape problems. 3. Distributed systems basics that actually show up in prod Consistency vs availability, timeouts, retries, idempotency, backpressure, message ordering, leader election, clock skew, eventual consistency, and what happens during partial failures. 4. API design and contracts Versioning, pagination, filtering, error models, idempotency keys, rate limits, backwards compatibility, and how to avoid breaking mobile clients for months. 5. Performance and capacity engineering Latency budgets (p50/p95/p99), tail latency causes, load testing, queueing theory intuition, connection pools, CPU vs IO bound, and capacity planning with real numbers. 6. Reliability engineering SLOs/SLIs, incident response, postmortems, alerting that does not spam, error budgets, graceful degradation, feature flags, circuit breakers, bulkheads. 7. Observability like a pro Structured logs, metrics, tracing, correlation ids, RED/USE metrics, sampling strategies, and how to debug “it is slow sometimes” without just guessing. 8. Security fundamentals AuthN/AuthZ, least privilege, secrets management, token expiry, OWASP basics, SSRF, injection, secure defaults, audit logs, threat modeling for your own services. 9. Messaging and async systems Kafka/Rabbit/SQS semantics, at-least-once vs exactly-once (and why “exactly once” is mostly a marketing term), consumer groups, retries, DLQs, replay, dedupe. 10. Caching with correctness Cache invalidation strategies, TTLs, stampede protection, read-through/write-through, negative caching, and when caching makes bugs harder than latency. 11. Infrastructure literacy Linux basics, networking (DNS, TCP, TLS), containers, k8s concepts, autoscaling, deployment strategies (blue/green, canary), and what your cloud bill is really paying for. 12. System design, but with tradeoffs Designing is picking pain. Learn to write down constraints, failure modes, data growth, and operational cost. Staff is judged on tradeoffs, not diagrams. 13. Codebase leadership Design docs, RFCs, review quality, mentorship, aligning teams, reducing complexity, owning a subsystem end-to-end, making boring systems that do not wake people at 2am. 14. Pick ONE domain to go deep Payments, search, streaming, identity, infra, data platform, etc. Staff engineers are “the person for a hard area”, not generic API writers. Stop hopping stacks every month. Pick a lane, build proof of reliability, and become the person people call when prod is on fire. That is Staff.

You're probably sick of me saying "B-tree" but these impact SO MUCH of database performance. They're used all over the place in Postgres, MySQL, and SQLite. This week I broke down B-tree lookups and how the page cache makes lookups faster.

- Go backend - SQLite or Postgres database - vanilla JS frontend - Claude Code Everything else is just a distraction that keeps you from shipping.

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One question that I constantly ask myself is: How can I quickly learn skills?

You can't avoid learning Linux if you want to grow your cloud and DevOps career.

Working as a backend engineer gave me a smooth transition into Cloud and DevOps engineering. Having visibility on deployment pipelines, configuring the AWS servers, working with Nginx all made it easier.

If you are thinking of being a DevOps engineer, first invest your time in learning Linux. Not just the basic stuff, but you really need to understand how it works beyond the "ls" command.

Kubernetes is the most interesting technology I have ever worked with at scale. Fully immersed in Cloud Native development.