DevOps & SRE
DevOps and site reliability engineering is the practice of making software delivery boring in the best sense - every merge is a candidate release, every failure is observable before a customer reports it, and every incident produces a fix instead of a repeat.
About DevOps & SRE
We build CI/CD pipelines, observability stacks, and on-call practices so your team deploys confidently without living in incident channels. That means automated builds and tests on GitHub Actions or GitLab CI, infrastructure defined as code, and dashboards tuned to the handful of metrics that actually predict an outage rather than a wall of noisy alerts nobody reads.
Founders and engineering leads bring us in for two different reasons: either they are shipping fast but breaking production too often, or they have inherited a manually deployed stack and need pipeline discipline before the next hire joins. Our DevOps work pairs naturally with the Laravel, Node.js, and Next.js applications we build, but we also embed with existing teams who just need the pipeline and reliability layer upgraded around code we did not write.
What's included
Everything we deliver on this engagement
CI/CD pipeline design and build automation
We design pipelines on GitHub Actions, GitLab CI, or Jenkins so every merge triggers tests, builds, and a deploy candidate automatically. Manual SSH-and-pull deploys are replaced with promotion workflows between staging and production that anyone on the team can trigger safely. Build caching and parallelization keep pipelines fast enough that developers actually wait for green before merging.
Infrastructure-as-code and environment parity
Terraform or Pulumi configs put your servers, databases, and networking under version control instead of tribal knowledge and console clicks. Staging and production are built from the same definitions so "it worked in staging" stops being a warning sign. New environments spin up in hours instead of days when you need a hotfix branch or a load-test replica.
Observability - logging, metrics, and tracing
We wire up Datadog, Grafana, Sentry, or open-source equivalents so you can see latency, error rates, and resource usage across services in one place, not scattered across server logs. Traces connect a slow page load to the specific query or API call causing it. Dashboards are built around the metrics that predict incidents, not vanity graphs nobody checks.
SLOs, error budgets, and incident response playbooks
We help define what "reliable enough" means for your product in concrete numbers - uptime targets, latency budgets, acceptable error rates - then set alerts against those thresholds instead of arbitrary CPU spikes. Incident playbooks document who gets paged, what to check first, and how to communicate status, so a 2am outage does not depend on one engineer's memory.
Security scanning, dependency updates, and secrets rotation
Automated dependency scanning and update PRs keep known vulnerabilities from sitting unpatched for months. Secrets move out of `.env` files committed to git and into proper vault or secrets-manager storage with rotation policies. Container images are scanned for CVEs before they reach production, not after a security questionnaire asks about it.
On-call setup, runbooks, and post-incident reviews
We set up rotation schedules and paging (PagerDuty, Opsgenie, or lighter-weight alternatives) sized to your actual team, plus runbooks for the failure modes you have already seen. After incidents, we run blameless postmortems focused on process gaps and monitoring blind spots rather than who pushed the bad commit.
Our process
How we deliver devops & sre
- 01
Baseline reliability (week 1)
We measure current deploy frequency, failure rate, and mean time to recovery, and audit existing pipelines and infrastructure before proposing changes or targets.
- 02
Pipeline first (weeks 1–2)
Automated builds, tests, and deploy promotion go live first, since every later improvement depends on releases being repeatable and low-risk.
- 03
Observe everything (weeks 2–4)
Logging, metrics, and alerting are wired to the handful of signals that predict outages, with dashboards your team will actually open during an incident.
- 04
Improve continuously (week 4+)
Blameless postmortems, quarterly reliability reviews, and - if you want it - an ongoing retainer so toil keeps trending down instead of creeping back.
Tech stack
Tools we use for devops & sre
Docker
Consistent build artifacts and runtime environments across local, staging, and production without "works on my machine" surprises.
GitHub Actions / GitLab CI
The pipeline backbone for most teams we work with; version-controlled workflows that run tests and deploys on every push.
Terraform
Infrastructure defined as reviewable code so environment changes go through the same PR process as application code.
AWS & GCP
The two cloud platforms we deploy to most often, chosen based on your existing footprint, budget, and compliance needs.
Grafana, Datadog & Sentry
Metrics, dashboards, and error tracking - we pick based on budget and whether you need a managed SaaS or a self-hosted stack.
Linux
The base layer for nearly every production environment we operate; scripting and systemd fluency matters more than any single vendor tool.
Who this is for
Use cases that commonly need devops & sre
Startups whose releases keep breaking production
Deploys happen by SSHing into a server and running a script, and every third release takes down something unrelated. We introduce a tested, automated pipeline so shipping stops being a source of anxiety for the whole team.
Teams about to hit a compliance or enterprise sales review
A prospective enterprise customer wants uptime numbers, incident history, and access control evidence you do not currently track. We put SLOs, logging, and audit-friendly deploy history in place before the security questionnaire lands.
Engineering teams drowning in noisy on-call pages
Alerts fire on CPU blips no one acts on, and the team has stopped trusting PagerDuty. We rebuild alerting around actionable thresholds and add runbooks so being on-call stops meaning constant, useless interruptions.
Companies migrating off a single point-of-failure server
One VPS running the database, app, and cron jobs has become the whole business's risk profile. We move infrastructure to reproducible, code-defined environments with backups and a real disaster-recovery plan.
Common mistakes
What teams get wrong about devops & sre
"We need Kubernetes to be a serious engineering org"
Kubernetes solves orchestration problems most small and mid-size teams do not have yet, at a real operational cost. We right-size infrastructure - Docker Compose, managed PaaS, or ECS often outperform a Kubernetes cluster nobody has time to operate well.
"DevOps means hiring one person to click deploy"
DevOps is a set of practices - automation, observability, shared ownership - not a job title that absorbs all operational risk. We build systems the whole engineering team can operate, not a single bottlenecked hero.
"More logging automatically means better observability"
Unstructured logs nobody queries are not observability, they are a bill. We design for the specific questions you will need to answer during an incident, then instrument toward those answers deliberately.
"CI/CD is a one-time setup we can ignore after launch"
Pipelines rot as dependencies, test suites, and team size change. We treat pipeline health as an ongoing metric - build time, flake rate - not a project that ends the day it first goes green.
Pricing & timeline
What to expect on budget and schedule
Pipeline and observability setup projects for an existing application typically range from $6k–$18k, depending on how much infrastructure needs to move to code and how many environments you run.
A basic CI/CD pipeline for an existing Laravel or Next.js app can be live in 1–2 weeks. Full GitOps with staging, canary-style deploys, and production monitoring typically takes 4–6 weeks end to end.
Beyond initial setup, embedded SRE support is available as a monthly retainer scoped to your stack and incident volume - useful for teams who want reliability improvements to keep compounding rather than stalling once the consultant leaves.
FAQ
Common questions about devops & sre
How much do DevOps and SRE services cost?
- Pipeline and observability setup projects often range from $6k–$18k depending on infrastructure complexity and environment count. Embedded SRE support beyond that is available as a monthly retainer scoped to your stack and incident volume.
How long does it take to set up CI/CD for an existing app?
- A basic pipeline for an existing Laravel or Next.js app can be live in 1–2 weeks. Full GitOps with staging, canary deploys, and monitoring typically takes 4–6 weeks.
Can you help during an active production outage?
- Yes. We offer incident response support and can stabilize deployments, roll back bad releases, and document root causes while the fire is still going, not just afterward.
Do you require we adopt Kubernetes to work with you?
- No. We right-size orchestration to your actual scale - many of our clients run happily on Docker Compose, a managed PaaS, or Vercel without Kubernetes overhead they would have to staff for.
Can you take over DevOps for a stack you did not build?
- Yes, this is a large share of our DevOps engagements. We start with an infrastructure and pipeline audit, then stabilize the highest-risk gaps first before touching anything that is already working well.
What do you need from us to start a DevOps engagement?
- Access to your current repos, cloud accounts, and deploy process, plus a sense of your worst recent incident. Most of the real information surfaces in the baseline audit rather than a pre-written brief.
Related
Related services and work
Related services
Ready to scope devops & sre?
Tell us about your product, timeline, and constraints. We reply within one business day with next steps - no generic pitch deck.