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60 articles in Cloud & Infrastructure.
P.01Chaos engineering means deliberately injecting failure into a running system to find weaknesses before an outage does. Here's what it actually involves, what tools make it practical, and when a smaller team should and shouldn't bother.
P.02Most teams reach for cache-aside by default and never ask if it's actually the right pattern. Here's how the three main caching strategies behave under real traffic, the consistency gap each one leaves open, and how to pick between them.
P.03CAP theorem gets summarized as 'pick two of three' so often that the summary has replaced the theorem. Here's what it actually says, why the real constraint only bites during a network partition, and how to pick a consistency model for a system you're actually building.
P.04In under three months, one developer rebuilt Postgres from scratch in Rust using AI coding agents, and pgrust now matches Postgres 18.3's output across more than 46,000 regression queries. Here's what it actually is, and isn't, and why it matters.
P.05A distributed lock keeps two processes on different machines from touching the same resource at once, but the naive Redis implementation has a gap that lets it fail silently. Here's how the pattern actually works, and the fencing token that closes the gap.
P.06Round robin isn't wrong, but it's the wrong default more often than teams realize. Here's how the main load balancing algorithms actually behave under uneven traffic, when each one earns its complexity, and a working consistent hashing implementation.
P.07A naive retry loop can turn a brief blip into a full outage by hammering a recovering service the instant it comes back. Here's how exponential backoff and jitter actually prevent that, with working code, not just the formula.
P.08Sharding splits one database across many machines when a single server can't hold or serve your data anymore. The strategy you pick determines whether you get hot spots, painful resharding, or a system that actually scales. Here's how each one works.
P.09Writing to your database and publishing an event are two separate operations, and a crash between them silently loses data. The transactional outbox pattern closes that gap. Here's how it works and how to implement it.
P.10Adding read replicas is the standard fix for a database under read load, but it introduces a gap between when data is written and when it's readable everywhere. Here's what replication lag actually does to your application and how to design around it.
P.11When a business transaction spans multiple services, you can't wrap it in one database transaction anymore. The saga pattern solves this with a chain of local transactions and compensating actions. Here's how it works and when it earns its complexity.
P.12PostgreSQL 19 Beta 1 shipped with a REPACK command that finally makes VACUUM FULL and CLUSTER safe to run without a maintenance window, plus parallel autovacuum and smarter async I/O. Here's what changed and what to test now.
P.13A circuit breaker stops your application from hammering a failing dependency until it recovers. Here's how the pattern works, the three states that make it up, and how to implement one without over-engineering a simple retry.
P.14Firebase's complexity and Supabase's Postgres assumptions do not fit every project. PocketBase, Appwrite, and Convex each solve the backend problem differently. Here is when each one makes sense.
P.15Three tools, three different bets on where complexity belongs. Here's how to choose between BullMQ, Inngest, and Temporal based on what your system actually needs — not what sounds most impressive.
P.16Durable Objects solve the coordination problem that makes edge computing hard: how do you maintain consistent state across distributed nodes? Here's how they work and when to use them.
P.17Kafka is the default answer for message queuing at scale. But for teams running fewer than a million messages per day, NATS JetStream offers persistence, delivery guarantees, and a dramatically simpler operational footprint.
P.18A practical guide to setting up metrics collection with Prometheus and visualization with Grafana for backend services — what to instrument, what to skip, and what the dashboards should actually show.
P.19Dev Containers let you define your entire development environment in a JSON file. New team members are productive in minutes, not days. Here's how to set them up properly.
P.20A bloated Docker image costs you in pull times, storage fees, and attack surface. Here's how to build images that are small, fast to rebuild, and genuinely production-ready.
P.21R2's zero-egress pricing looks compelling on paper. Here's when it actually saves money, when S3's ecosystem still wins, and how to migrate if you decide to switch.
P.22Logs tell you what happened. Error tracking tells you what broke, in what context, for which users. Here's how to set up Sentry properly and avoid the alert fatigue that makes it useless.
P.23The fear of vendor lock-in leads to over-engineering. Here's a practical framework for deciding when to abstract cloud dependencies and when accepting lock-in is the right call.
P.24ClickHouse is a columnar database designed for analytical workloads. It answers queries over billions of rows in seconds that would take minutes in Postgres. Here's what application developers need to know.
P.25dbt turns SQL SELECT statements into a tested, documented, version-controlled data pipeline. Here's how it works and when you should add it to your data stack.
P.26Vercel dominates frontend hosting. AWS dominates enterprise infrastructure. Between those two extremes, Fly.io and Railway are the most practical choices for backend-heavy full-stack apps in 2026.
P.27Workers AI gives you access to a catalog of open-weight models — Llama, Mistral, Whisper, embedding models — running in Cloudflare's network. Here's what's actually useful, what the limitations are, and when it makes sense.
P.28SQLite runs in every phone and browser. Turso extends it to the server and edge with replication, branching, and a network protocol. Here's when it makes sense.
P.29Blue-green and canary deployments give you a way to release software without taking down your service or discovering a bug when it's already affecting everyone. Here's how they work and when to use each.
P.30eBPF lets you attach programs to any kernel hook — network packets, system calls, function calls — without patching the kernel or rebooting. Here's what application developers actually need to know.
P.31Tailscale creates a private mesh network across any combination of cloud servers, developer laptops, and office machines — without port forwarding, firewall rules, or dedicated VPN hardware.
P.32Multi-cloud gets pitched as the default choice for serious companies. The reality is more nuanced — and for most teams, the complexity cost is higher than the lock-in risk it's supposed to prevent.
P.33OpenTelemetry is the observability standard now. Most tutorials show you how to install the SDK and emit traces. Fewer explain which signals actually matter for web applications and which add noise without helping you debug anything.
P.34Password resets, invoices, and notification emails are infrastructure. Most developers treat them as an afterthought until a client asks why their welcome emails are disappearing. Here is the full picture.
P.35HPA scales on CPU and memory. But most production workloads don't scale well on those signals. KEDA, VPA, and Goldilocks fill the gaps that HPA leaves open.
P.36The queries that destroy production Postgres databases share a small set of root causes. Here is how to find them, understand what EXPLAIN ANALYZE is telling you, and fix them without guessing.
P.37Neon separates storage from compute to make Postgres behave like a serverless resource. The branching feature is what actually changes the development workflow — here's how it works and when it's worth the migration.
P.38Connection exhaustion is one of the most common production failures for apps that scale. Here's how pooling works, which tool fits which setup, and the configuration decisions that matter.
P.39From .env files to Vault to AWS Secrets Manager: a practical guide to storing credentials, API keys, and certificates without waking up to a breach notification.
P.40Site reliability engineering was designed for teams of hundreds. Most of its principles translate directly to teams of 5. Here is what a practical incident response process looks like when nobody has 'SRE' in their title.
P.41Service meshes promise secure, observable microservice communication. But most teams that adopt one do so before they need it. Here is how to decide, and what each option actually costs you.
P.42Message queues and event streams solve different problems. Kafka is not always the right answer. Here's how to think through event-driven patterns and choose the right tool for your production workload.
P.43Every SaaS team eventually faces the multi-tenancy decision. The wrong choice creates migration pain later. Here's how to think through database-per-tenant, schema-per-tenant, and row-level security based on what your product actually needs.
P.44Background jobs that crash mid-execution lose all their state. Temporal solves this by making workflows durable state machines that survive process restarts, deploys, and outages. Here's what it looks like in TypeScript and Python.
P.45Most teams treat their CI pipeline as a black box that occasionally fails. A few hours of optimization can cut your CI time by 40-60% and your GitHub Actions bill by a similar margin. Here's exactly how to do it.
P.46HashiCorp moved Terraform to a Business Source License in August 2023. OpenTofu forked it under the MPL. Pulumi took a different path entirely. Two and a half years on, the dust has settled enough to make a clear-headed choice.
P.47In March 2024, Redis Ltd. relicensed Redis under a source-available license. Within weeks, the Linux Foundation forked it as Valkey. Two years on, here's how the split played out and what it means for teams choosing an in-memory data store today.
P.48LLM calls are slow and expensive. Caching them is the obvious move. But caching the wrong responses breaks the user experience in ways that are subtle and hard to debug. Here's a practical guide to doing it right.
P.49ALTER TABLE locks your database. Your migration takes longer than expected. Users get errors. Here's how to handle schema changes that don't interrupt production traffic.
P.50Traditional monitoring tells you a request took 800ms. It doesn't tell you the LLM spent 600ms on a bad prompt, returned a hallucinated answer, and burned $0.04 in tokens. Here's how to actually instrument AI applications with OpenTelemetry.
P.51Explore the financial impact of the AI storage tax and the sharp rise in NAND and RAM costs, affecting enterprise IT budgets and cloud infrastructure strategies.
P.52Explore the shift towards serverless edge computing in the post-cloud era, focusing on performance improvements, cost savings, and real-world case studies of enterprises leveraging this technology.
P.53Analyzing the February 2026 Cloudflare edge network outage: cascading failures, bypassed canary deployments, R2 and Workers impact. Real architecture lessons for building resilient distributed systems.
P.54Data-driven analysis of platform engineering adoption in 2026. Compare Backstage, Port, and Cortex IDPs, golden paths, self-service infrastructure, and how to measure platform success with DORA metrics.
P.55Learn how to deploy WebAssembly applications on Kubernetes using SpinKube and containerd-wasm-shim. Step-by-step tutorial covering cluster setup, Spin app deployment, monitoring, and production readiness.
P.56EditorPickEveryone said WebAssembly would kill Docker. Two years later, they coexist — and the teams using both are shipping faster. A reality check on Wasm, containers, and the containerd shim approach.
P.57Everyone says go cloud-native. But what does that actually mean in 2026? We break down microservices, serverless, and containers — and why most teams should start simpler than they think.
P.58We benchmarked Supabase Edge Functions, Vercel Serverless, and Fly.io containers head-to-head. Here are the real cold start times, throughput, and costs.
P.59AWS and Google Cloud announced cross-cloud interconnect integration with encrypted-by-default networking. After years of vendor lock-in wars, competitors are collaborating. We break down what it means and what it does not.
P.60GitOps adoption hit 64% in 2025, and the next evolution is integrating real-time cost visibility into every infrastructure pull request. We break down why GitOps plus FinOps is the operational model serious teams are adopting in 2026.