Practical insights on Kubernetes, cloud infrastructure, and DevOps from the team that manages it every day.
A default Kubernetes installation is convenient, not safe. Here are the 12 controls we apply to every production cluster — pod security, secrets, network policies, image signing, runtime threat detection, and more.
Most on-call rotations are just "whoever is awake." Here's how to fix alert noise, write runbooks people actually use, and build a rotation sustainable enough that your engineers stop leaving over it.
Most incident reviews are blame sessions or document theater. Here's what a genuinely useful postmortem looks like — how to run it, what to write, and how to make sure the actions actually get closed.
Platform Engineering is the hottest term in infrastructure right now — and most companies misapply it. Here's what it actually means, where DevOps ends and Platform Engineering begins, and the inflection point (hint: it's around 80–150 engineers) where one becomes the other.
A stage-by-stage framework for when K8s earns its operational overhead — and what to run instead at seed, Series A, and early scale. We manage Kubernetes every day; this is our honest take.
Rolling updates are not enough. A Kubernetes rolling update with a backward-incompatible schema change produces errors for every user mid-rollout. Here's when to use each strategy — and the database migration problem nobody warns you about.
Metrics, logs, traces, and alerting — the exact Prometheus + Loki + Tempo stack we implement for production Kubernetes environments, and the reasoning behind each choice.
Most startups run PostgreSQL with no verified backups, no read replica, and a failover plan that's never been tested. Here's the minimum setup for a production database you can trust — WAL archiving, weekly restore tests, streaming replication, PgBouncer, and a tested failover runbook.
Most startups treat on-call as an ops problem. It's actually a retention problem. Here's how bad on-call setups drive out your best engineers — and what to do instead.
40+ pages a week, no runbooks, no postmortems. Here's the exact process we use to audit alerting, build runbook culture, and cut meaningless pages by 80% — without touching the infrastructure.
A Series A SaaS company was paying $34k/month on AWS. They assumed it was the cost of growth. We found $21k/month they weren't actually using.
A 200GB Postgres monolith, a schema change that couldn't wait, and zero tolerance for downtime. Here's the expand-contract pattern that gets you there.
The pricing jumped, the free tier is gone, and you're evaluating alternatives. An honest account of what a Heroku migration involves — which platform to target, how to containerize, how to cut over the database, and what teams consistently underestimate.
Your on-call engineer isn't burnt out because they lack resilience — they're burnt out because the alert stack was never designed. A three-tier alert taxonomy, the runbook requirement, and how to reset from scratch.
A team getting 80+ pages per week, half of them noise, MTTR pushing 47 minutes. Here's how we rebuilt their alerting around SLOs, moved to a self-hosted Prometheus/Grafana/Loki/Tempo stack, and wrote 87 runbooks — cutting pages by 86% and MTTR to 9 minutes.
A B2B SaaS with 12 engineers was spending $380K/year on AWS. Ninety days later they were at $200K — without touching a single feature. Here's the exact breakdown of where the money was going.
A Series B SaaS company was spending $28K/month on AWS. Six weeks later: $9,200/month. No application changes — pure infrastructure work on EC2 right-sizing, RDS, EBS snapshots, data transfer, orphaned resources, and S3 storage tiering.
Every new client we onboard has CloudWatch dashboards nobody reads, logs that vanish when pods restart, or no alerting until customers complain. Here's how we fix it.
One engineer on permanent on-call is a $200K hire on an 18-month clock. Here's the rotation structure, escalation design, and coverage model that doesn't burn people out.
A marketplace startup handed us admin access on day one. No resource limits on 60% of pods, secrets in ConfigMaps, two minor versions behind with unpatched CVEs. The full week-one audit and how we prioritized the remediation.
Most startups solve on-call by putting the wrong person on rotation, burning out the right one, or hoping nothing breaks at 3am. There's a better way.
After 60+ startup infrastructure audits, the same five gaps appear every time: untested backups, secrets in git, no cost alerts, on-call of one, and infrastructure only one person understands. Here's what they are and what actually fixes them.
A Series B SaaS company's CFO flagged cloud costs as a top-three burn concern heading into Q3. Two weeks of auditing and four weeks of changes later, the bill dropped 63%. Here's every line item — oversized instances, NAT gateway waste, orphaned resources, missing Savings Plans, and S3 storage class misuse.
Manual SSH deploys, secrets in Slack, a database backup that didn't match the live schema, and former contractors with active credentials. A candid account of a real infrastructure audit — and the eight weeks it took to fix.
We see the same five patterns before a startup has a major production incident. None of them look dangerous until they combine. Here's how to spot them.
An e-commerce SaaS was spending $82K/month on AWS with no clear trend. Eight weeks later, they were at $31K. Here's every cut we made and why.
A B2B SaaS startup's lead engineer was being paged 11 times a night. He had two months left before quitting. Here's how we fixed their incident management in 6 weeks.
A 60-engineer SaaS team was finding out about outages from support tickets — 21 minutes after users started experiencing failures. Here's the OpenTelemetry, Prometheus, Grafana, Loki, and PagerDuty stack we built, and what changed in three months.
A structured audit of whether your system holds up under real conditions — not just normal ones. Six categories, what we typically find, and why untested backup restores are the most common critical gap.
A SaaS startup was spending $31k/month on AWS. Their board noticed. We brought it to $17k in six weeks — without changing the architecture or accepting risk to reliability.
A B2B SaaS company was spending $47K/month on AWS with no clear understanding of why. Six weeks later, the bill was $18K. Here's exactly what we changed — and why the NAT gateway line surprised them most.
NAT gateway tax, oversized RDS, zombie snapshots, idle load balancers — the line items that don't make it onto the dashboard but show up on the invoice every month.
We audited a SaaS startup's GKE bill and found $8,400/month in waste. The fixes took two weeks. Here's every line item and how we addressed it.
Most teams discover their monitoring gaps during an incident. Here's how to build observability that tells you something is wrong before your users do.
The average Kubernetes cluster overspends by 45–65%. Here's what we find in every audit — misconfigured resource requests, always-on staging, no HPA — and the exact fix order by impact.
From the 48-hour setup checklist to the week-one assessment to the first quick wins — what actually happens when you bring on a fractional DevOps team.
Your senior DevOps engineer just gave notice. Three years of infrastructure knowledge is about to walk out the door. Here's what to do in the next 48 hours — and the weeks after.
A B2B SaaS startup was spending $42K/month on AWS with no one tracking where it went. Here's exactly what we found and how we cut the bill nearly in half.
A Series A company was spending $68k/month on AWS and didn't know where most of it was going. Six findings, six weeks, $336k annualized savings.
When to hire your first DevOps engineer, what to outsource, and how to structure your ops team as you scale from seed to Series B. The real cost comparison.
The pipeline patterns that matter — fast feedback, safe deploys, rollback in under 5 minutes, and the antipatterns that slow teams down without anyone noticing.
How to structure Terraform for teams — remote state, module design, CI/CD integration, and the patterns that prevent drift before it takes down production.
What actually breaks Kubernetes at 2am — resource limits, RBAC, network policies, GitOps pipelines, and the upgrade strategy no one documents.
The architecture decisions that actually matter when you're building for scale — IaC, autoscaling, observability, cost controls, and security from day one.
A HealthTech startup went from no security controls to SOC 2 Type II certified in 14 weeks. Here's how we handled every implementation challenge — secrets sprawl, RBAC rollout, policy writing — and what the outcome meant for the business.
A monolithic 2-hour deploy process, zero rollback capability, and a team afraid to ship on Fridays. Here's how we fixed it with GitOps, ArgoCD, and Helm.
A fully loaded DevOps engineer costs $150K–$200K+. But the real cost isn't the salary — it's the single point of failure, ramp-up time, and expertise gaps.
Cloud GPU instances are expensive at scale. Here's how we set up on-premise GPU clusters with Kubernetes for ML training workloads — and when it makes sense.
SOC 2 audits don't have to be painful. Here's the infrastructure checklist we use to get clients audit-ready in 6 weeks.
We migrated a SaaS company from AWS to GCP with zero downtime. Here's the playbook: DNS cutover strategy, data sync, and rollback plan.
By default, every pod in Kubernetes can talk to every other pod. Here's why that's a security risk and how to fix it.
We use both across client engagements. Here's an honest comparison and when to pick each one.
What does it actually look like when a fractional DevOps team embeds in your company? Here's a real day from one of our engagements.
Book a free audit and we'll show you exactly where your quick wins are.