That turn releasing software into a routine, low-risk event.
We build the delivery pipeline and day-2 operations that let your team ship often and sleep at night — CI/CD from commit to production, environments as code, and observability that catches problems early.
On AWS, Azure, or Google Cloud, inside your own accounts, with every pipeline definition and runbook assigned to you. Steady state in 4–8 weeks.
Because the path from a finished commit to live production is held together by manual steps, tribal knowledge, and hope. Releases get batched into a big, dreaded event because each one is risky — so they happen rarely, which makes every release bigger and riskier still.
When something breaks at 2 a.m., nobody can tell what changed or how to roll it back, and recovery takes hours the business can’t afford.
This isn’t a tooling problem you fix by buying a CI server. It’s an engineering discipline: an automated pipeline that builds, tests, and releases the same way every time; environments you can rebuild from code; monitoring that turns a silent failure into an early alert; and a rollback you’ve actually rehearsed.
Closing the gap between a team that ships daily without drama and one that fears every deploy is exactly what DevOps services are for.
DevOps isn’t one tool — it’s a set of capabilities, each removing a specific source of release risk or operational toil. For each: what it does, the benefit, and a one-line illustration.
Builds, tests, and packages every commit automatically, then promotes it through staging to production along one defined path. Benefit — releases get smaller, more frequent, and far less risky, because the pipeline does the same safe thing every time instead of relying on whoever ran the last deploy.
Example: a fix that used to wait two weeks for the next batched release ships the same afternoon, with a blast radius small enough that any problem is obvious.
Ships a change to a slice of traffic first — canary or blue-green — watches the metrics, and rolls back automatically if they degrade. Benefit — a bad release affects 1% of users for 90 seconds instead of everyone for an hour, turning deployment into a controlled, reversible step.
Example: a new checkout build goes to 5% of traffic, error rates tick up, and the pipeline rolls it back before most customers ever see it.
Defines build, staging, and production environments in version-controlled code so they’re identical and reproducible. Benefit — environment drift and “it passed in staging” failures disappear, and a rebuilt environment is a pipeline run, not a multi-day scramble.
Example: a bug that only appeared in production is reproduced in an identical environment spun up from the same code in minutes — not a week guessing at config differences.
Instruments the system with metrics, logs, and traces, and wires alerts to the signals that predict user pain. Benefit — problems surface as an alert the team acts on, not a customer complaint, so mean-time-to-detection drops from hours to minutes.
Example: a memory leak that would have crashed the service at peak is caught on a trend line hours early, and the fix ships before a user is affected.
Sets up on-call, runbooks, error budgets, and post-incident review so failures are handled fast and don’t recur. Benefit — recovery goes from a frantic scramble to a rehearsed procedure, cutting mean-time-to-recovery and the revenue an outage burns.
Example: a database failover that once meant an hour of downtime and a war room becomes a ten-minute runbook any on-call engineer can execute.
Runs the pipeline and platform after launch — patching, scaling, capacity, backups, reliability — as an ongoing operation, not a one-time setup. Benefit — the platform stays healthy and fast without a fire drill, so the team ships features instead of babysitting infrastructure.
Example: a traffic surge triggers automatic scale-out and an alert, instead of a degraded site and a midnight call to add servers by hand.
This is the delivery-and-operations layer: the pipeline that carries code to production and the practices that keep it healthy there. It runs on the cloud foundation we architect and build and pairs with the security controls we embed in the same pipeline — distinct jobs we scope honestly rather than bundle.
We map how code moves from commit to production today, find the manual steps and bottlenecks, and design the pipeline that fits your stack and cadence — run as an AI readiness assessment scoped to delivery, with the honest “automate this, leave that alone” call included.
We build the automated build–test–release pipeline — quality gates, artifact management, and progressive delivery (canary or blue-green) — on your existing CI/CD platform, so every change takes the same safe, repeatable path to production.
We define your environments in version-controlled IaC (Terraform or the platform-native tool) so build, staging, and production are identical and reproducible, and a new environment is a pipeline run instead of a manual rebuild.
Where it fits, we containerize workloads and run them on Kubernetes with sane defaults — autoscaling, rolling and canary deployments, health checks — so releases and recovery are orchestrated, not hand-driven.
We instrument the system with metrics, logs, and traces, wire alerting to the signals that predict user pain, and set up on-call, runbooks, and post-incident review — with human-in-the-loop judgment kept where a call genuinely needs one.
We run the pipeline as an ongoing day-2 operation — or train your team to: read the dashboards, run a deploy, execute a rollback, recover an environment from code — so you own the capability when we step back, not a black box only we can touch.
What you get when you hire us for DevOps services — all assigned to you
The same delivery model behind all our engineering work, tuned for the pipeline — one accountable lead, fixed scope, no handoffs.
Map how code reaches production today, baseline the four delivery metrics, and find the manual steps and risk.
Output: a target pipeline & the metrics we’ll be judged on
Build the CI/CD pipeline with quality gates and progressive delivery, and codify your environments as infrastructure-as-code.
Output: a working automated path from commit to production
Add observability, alerting, and a rehearsed rollback and incident path, then prove it under real conditions.
Output: early problem detection & a recovery procedure that works
Run it in production — or train your team to — with the four metrics reported weekly against the kickoff targets.
Output: a reliable delivery operation & a team that owns it
Steady state in 4–8 weeks, full IP assignment signed at kickoff, payment tied to the ROI we agree — faster, safer releases, not hours billed.
We won’t claim a DevOps case study we don’t have — so here is the one that fits this page most exactly, told straight.
BJ’s Restaurants is a 200+ location restaurant chain whose operations are software-critical, and for 4+ years we’ve run its software delivery. When we started, production releases went out roughly every two weeks — heavy, batched, and cautious, exactly the doom loop above.
By restructuring how work flows through their pipeline — smaller units of work, automated pre-release quality checks, regression prevention, and continuous production monitoring — release cadence moved to twice a week with zero critical defects sustained across those years. A traditional, multi-location, non-tech enterprise now ships at the cadence and stability of a frontier software company, and the cost of maintaining its web apps and operations went down, not up.
That is the outcome these DevOps services exist to produce: not a faster CI server, but the engineering discipline — automated quality gates, staged rollout, monitoring, and a delivery process the team trusts — that lets an enterprise ship often and safely at once. It’s the same discipline behind the security-embedded pipeline and the cloud foundation those releases run on.
Silicon Prime is a Stanford-rooted Responsible AI lab, founded in 2011, run by founder Kelvin Tran — 20+ years of production engineering, personally accountable for every engagement. We’ll tell you plainly when your release problem is three fixes, not a year-long platform rebuild — which a firm billing by the managed seat won’t.
What sets our DevOps services apart is that you end up with a delivery capability your own team operates, not a pipeline you depend on us to touch.
Proven release cadence, not a promise. A multi-year production record of taking a non-tech enterprise from every-two-weeks to twice-a-week releases with zero critical defects — the exact outcome this work exists to produce, sustained, not pitched.
Faster and safer, by design. We engineer for throughput and stability at once — progressive delivery, quality gates, rehearsed rollback — because the research and our own record agree that real DevOps gives you both, not a trade.
Tool- and cloud-neutral. We build on your existing CI/CD platform across AWS, Azure, or GCP, never a tool we resell. The pipeline serves your workload, not a partner quota.
Founder-led, built to transfer. No account managers, no handoffs — and the pipeline, IaC, runbooks, and trained team are assigned to you, so the dependency on us is optional when we step back.
Where point-of-sale, ordering, and operations software is business-critical and a bad release means lost revenue across every location — the exact setting where we sustained twice-a-week releases with zero critical defects.
Payments and decisioning systems where every release needs progressive rollout, instant rollback, and an auditable change trail. Fintech software →
Storefronts that must ship constantly yet absorb peak traffic without a degraded checkout, where deployment frequency and reliability have to rise together.
Multi-tenant products shipping continuously, where the delivery pipeline is product velocity and downtime is churn.
What teams want to know before they trust a pipeline with their releases.
Three distinct jobs, and we’ll scope which one your problem calls for. DevOps is delivery velocity and operations — the CI/CD pipeline, infrastructure-as-code, observability, and the day-2 practices that let you ship fast and reliably. DevSecOps is the security evolution of that pipeline — SAST, dependency and secrets scanning, and policy gates in the same flow, so you ship fast without shipping vulnerabilities. Cloud engineering architects and builds the cloud foundation the pipeline runs on. Often a team has a decent cloud but a release process that’s still manual and scary — that gap is squarely DevOps work.
The opposite, when it’s engineered right — and that’s the most important thing the data shows. In the 2024 State of DevOps research, elite performers ship far more often than low performers and run a change failure rate of about 5% versus 64%, recovering in under an hour. Frequent, small, reversible releases are safer than rare, big, manual ones: each change is tiny, the path is automated and identical every time, and a bad deploy rolls back in seconds.
A CI server is a tool; DevOps is the engineering discipline around it. Most teams that “have CI” still deploy manually, can’t rebuild an environment from code, hear about failures from customers, and have never rehearsed a rollback. The pipeline that makes releasing routine is the automated build-test-release path plus progressive delivery, infrastructure-as-code, observability, and a working incident process — the discipline that actually moves the four delivery metrics, built on whatever tooling you already run.
The four DORA metrics, baselined at the start and reported weekly: deployment frequency, lead time for changes, change failure rate, and time to restore service. We agree the targets at kickoff, and payment is tied to the ROI they represent — faster, safer, more frequent releases — not to billable hours. You watch the trend lines every week, so the value is a number, not a claim you take on faith.
Both are on the table; the choice is yours. We can run the pipeline as an ongoing managed DevOps operation, or build it and train your team to operate it — dashboards, deploys, rollbacks, environment recovery from code. The engagement is built around the handover either way: keep us on a reduced retainer, or take the keys. There’s no black-box pipeline only we can touch.
At the delivery layer we build the pipeline with sane access controls, scoped credentials, and an NDA and security review at the start of every engagement. Embedding active security testing — SAST, dependency and secrets scanning, DAST, signed-artifact policy gates — is its own discipline, which we cover under DevSecOps services. If shipping fast without shipping vulnerabilities is the real goal, we scope the two together so security accelerates delivery instead of gating it.
You do — completely. The CI/CD pipeline, the infrastructure-as-code for your environments, the runbooks, the dashboards, and the incident process all transfer under full work-for-hire IP assignment signed at kickoff, and your team is trained to operate and extend them. There’s no proprietary tooling locked to us — just your own platform, automated and owned by you.
Most DevOps services engagements reach steady state in 4–8 weeks under a fixed-scope arrangement with one accountable lead, and payment is tied to the delivery outcomes we agreed to. Build cost depends on the state of your pipeline and the size of your estate — our AI development cost guide covers how we scope and price engineering work — and we weigh it against a documented downside: a single hour of downtime now exceeds $300,000 for most mid-size and large enterprises (ITIC, 2024).
Thirty minutes · No pitch deck
Tell us how you deploy today and we’ll assess the gaps, name the highest-leverage fixes, and give you a costed path to faster, safer, more frequent releases — whether that’s a focused project or ongoing DevOps services.