Most engineering teams have scripts where a platform should be. Perimattic’s DevOps and platform engineering services build the missing layer — GitOps pipelines, Kubernetes platforms, managed DevOps, and cloud cost programs designed for production from the first sprint. If you’re comparing DevOps and platform engineering services because deployments are slow, incidents are expensive, or your cloud bill keeps climbing without explanation, this is the engagement that fixes the infrastructure, not just the symptoms.
Stack We Build On — Kubernetes, Terraform, ArgoCD, AWS, GitHub Actions, Prometheus, Grafana, Docker
Platform engineering is the discipline of designing, building, and operating the internal tooling, infrastructure, and workflows that let development teams ship software safely and quickly — without needing to become infrastructure experts themselves. It sits alongside DevOps consulting and managed DevOps services as one of the fastest-growing categories in enterprise engineering, because the old model — a handful of bash scripts, a shared Jenkins box, and a runbook nobody has read since 2021 — does not scale past a certain team size.
The challenge for most growing engineering organizations is not a lack of tools. It is the absence of a coherent platform: a paved road that developers can follow to provision infrastructure, deploy code, roll back safely, and understand what something costs before it costs it. A generic CI/CD template copied from a blog post will not understand your compliance requirements, your multi-account AWS structure, or the reason your last three incidents happened at 2am on a Friday. The gap between ad-hoc DevOps and a properly engineered platform becomes very expensive at scale — in engineering hours, in incident frequency, and in cloud bills that nobody can fully explain.
Perimattic builds custom DevOps and platform engineering solutions from the ground up: GitOps pipelines tuned to your branching model, Kubernetes platforms calibrated to your workload patterns, and cloud cost management practices grounded in your actual usage data. Every engagement is designed for production reliability and built with the observability, security, and self-service tooling needed to keep your platform maintainable as your team grows.
Delivery Model
Scripts and tribal knowledge held by one or two engineers
Delivery Model
Documented, versioned pipelines any engineer can operate
Infrastructure Changes
Manual, applied directly in the console or over SSH
Infrastructure Changes
Codified in Terraform, reviewed and applied through GitOps
Deployment Process
Manual builds triggered by whoever is free
Deployment Process
Automated CI/CD with approval gates and rollback built in
Cloud Spend
Discovered at the end of the month, on the invoice
Cloud Spend
Tracked continuously with cloud cost optimisation baked into architecture
Incident Response
Reactive, dependent on whoever is on call knowing the system
Incident Response
Runbooks, alerting, and observability designed before go-live
Scaling the Team
Every new hire needs months of tribal knowledge transfer
Scaling the Team
Self-service platform lets new engineers ship on day one
“A well-architected Kubernetes platform can cut deployment failures by more than half and shrink incident response time by days, not hours — but only if observability and rollback paths are designed in from the start, not bolted on after the first outage.”
Six specialist service lines covering every layer of enterprise infrastructure, from strategy and cost governance to GitOps, container platforms, and ongoing operations.
Strategy-first DevOps advisory: infrastructure audits, tooling assessments, and a prioritized roadmap before we touch a single pipeline. We identify where manual toil costs the most time, where reliability risk is highest, and which changes will move the needle fastest. The output is a written assessment your team can act on regardless of what you decide next.
Design and build of internal developer platforms that give your engineers self-service access to infrastructure, environments, and deployment tooling. We build golden-path templates, internal developer portals, and standardized service scaffolding — including container platform engineering on Kubernetes covering cluster architecture, autoscaling, namespace isolation, and security hardening.
End-to-end GitOps pipelines using ArgoCD and Flux, where your Git repository becomes the single source of truth for production. We design branching strategies, environment promotion workflows, and drift detection. This covers the full CI/CD pipeline build using GitHub Actions, GitLab CI, Jenkins, or CircleCI, with progressive delivery patterns like canary and blue-green deployments.
Ongoing, subscription-based DevOps support for teams who need senior infrastructure expertise without hiring a full platform team. Our managed DevOps services take on pipeline maintenance, infrastructure changes, incident response, observability, and continuous improvement as an extension of your engineering organization, scaling involvement up or down as your needs change.
Structured cloud cost optimization programs that reduce spend without sacrificing performance or reliability. We audit your AWS, Azure, or GCP usage, identify rightsizing and reserved capacity opportunities, implement tagging and cost allocation, and build dashboards that give finance and engineering a shared, real-time view of cloud spend across every account.
Specialist AWS DevOps services covering account structure, IAM design, CI/CD with CodePipeline or GitHub Actions, and infrastructure as code with Terraform or CDK. We design multi-account AWS landing zones that separate production from staging by default and bake cost optimization into the architecture from day one, rather than retrofitting it after the first surprising invoice.
A structured six-stage process from free platform assessment to live deployment and ongoing improvement.
We audit your current infrastructure, deployment process, cloud spend, and incident history to identify the changes that will deliver the fastest measurable return. This includes interviews with the engineers who operate the system day to day. This session is free and carries no obligation.
We evaluate your compliance constraints, team structure, and target reliability metrics, then design a platform architecture and prioritized roadmap that maps to your actual constraints. The roadmap is sequenced so that the highest-risk or highest-cost problems get addressed first.
We build a working pipeline or platform slice against one real service or team, validating the approach and surfacing any integration or organizational challenges before the full rollout begins. This stage exists to catch assumptions that only become visible once real workloads are using the system.
We build the CI/CD pipelines, infrastructure as code modules, and platform tooling, and migrate workloads incrementally so nothing breaks mid-transition. Every change is peer-reviewed and tested against staging before touching production, with a clear rollback path at every stage.
We run load testing, failure injection, and security review against the new platform, then document runbooks and train your team so they can operate the system confidently without us in the room. Handover includes recorded walkthroughs and written documentation.
We deploy to production with full observability in place, remain available for the first weeks of operation to resolve any issues, and plan the next iteration based on real usage data and cost trends. Many engagements continue into an ongoing DevOps as a service arrangement at this stage.
We audit your current infrastructure, deployment process, cloud spend, and incident history to identify the changes that will deliver the fastest measurable return. This includes interviews with the engineers who operate the system day to day. This session is free and carries no obligation.
We evaluate your compliance constraints, team structure, and target reliability metrics, then design a platform architecture and prioritized roadmap that maps to your actual constraints. The roadmap is sequenced so that the highest-risk or highest-cost problems get addressed first.
We build a working pipeline or platform slice against one real service or team, validating the approach and surfacing any integration or organizational challenges before the full rollout begins. This stage exists to catch assumptions that only become visible once real workloads are using the system.
We build the CI/CD pipelines, infrastructure as code modules, and platform tooling, and migrate workloads incrementally so nothing breaks mid-transition. Every change is peer-reviewed and tested against staging before touching production, with a clear rollback path at every stage.
We run load testing, failure injection, and security review against the new platform, then document runbooks and train your team so they can operate the system confidently without us in the room. Handover includes recorded walkthroughs and written documentation.
We deploy to production with full observability in place, remain available for the first weeks of operation to resolve any issues, and plan the next iteration based on real usage data and cost trends. Many engagements continue into an ongoing DevOps as a service arrangement at this stage.
Select an industry to see how a properly engineered platform outperforms ad-hoc DevOps in that domain.
DevOps in financial services has to satisfy strict audit trails, segregated environments, and change control processes that general-purpose CI/CD templates were never built for.
DevOps in financial services has to satisfy strict audit trails, segregated environments, and change control processes that general-purpose CI/CD templates were never built for.
Healthcare infrastructure has to handle HIPAA-regulated data and strict access controls, in change processes that satisfy compliance review without slowing releases to a crawl.
SaaS platforms need multi-tenant architectures and self-service deployment tooling, so product teams can ship independently without a central release manager as a bottleneck.
Retail infrastructure must absorb extreme seasonal traffic spikes, while keeping baseline cloud spend under control during quiet periods.
Manufacturing and logistics platforms often bridge hybrid cloud and on-premises systems that were never designed with modern observability in mind.
Booking platforms in travel and hospitality see extreme seasonal and event-driven demand swings that make static infrastructure sizing expensive and risky.
Perimattic's work resulted in stable production systems. The team was helpful, easily accessible, and communicative through email. Their professionalism was impressive.
Quality
4.5
Schedule
5.0
Cost
5.0
Willing to Refer
4.5
DevOps Managed Services · Oct 2023 - Aug 2024
24/7 monitoring and support for production environments plus Linux server administration for a leasing automation company.
The new architecture is scalable and highly efficient, saving a lot of money in fees. Perimattic provides high-quality IT consulting and cloud development work promptly and at great value. The team remains involved from the planning stage to providing support, showing diligence and proactiveness.
Quality
5.0
Schedule
5.0
Cost
4.5
Willing to Refer
5.0
AWS Migration (Legacy → Microservices) · Nov 2018 - Ongoing
Transitioned a travel systems company's legacy server system to an AWS-based microservices architecture with ongoing maintenance.
Four structural advantages that separate production-grade platform engineering from ad-hoc DevOps scripting.
Every platform we build includes monitoring, alerting, rollback paths, and security review from the first sprint. We do not build prototypes that need to be re-engineered before they can carry real production traffic.
We build infrastructure as code and GitOps pipelines, not one-off console changes that nobody can reproduce. You get a platform that is documented, versioned, and reviewable — not a system that depends on one engineer's memory.
Our team covers the full stack: infrastructure, CI/CD, observability, security, and cost governance. You get a single team responsible for everything from Terraform module to production incident response, rather than juggling separate vendors for each piece.
The team that designs your platform architecture also builds, tests, and hands it off. You get continuity from the scoping call to go-live, with no loss of context between advisory and engineering functions.
“Unlike boutique dev shops that build to spec without strategic context, or large consultancies that advise without shipping, Perimattic brings both capabilities to every DevOps engagement.”
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Read articleDevOps and platform engineering services deliver the pipelines, self-service tooling, and internal infrastructure that let your development teams ship software reliably — without needing to become infrastructure specialists themselves. DevOps is a set of practices and culture around collaboration between development and operations teams. Platform engineering is the discipline of building the actual internal product — tooling, self-service portals, golden-path templates — that makes those DevOps practices usable at scale. Most organizations start with DevOps consulting to fix immediate pipeline and reliability problems, then move toward platform engineering once the team is large enough that manual, ad-hoc processes stop scaling.
Managed DevOps services give you senior infrastructure expertise on demand, without the time and cost of recruiting, onboarding, and retaining a full internal platform team. Most clients use managed services to get production-grade infrastructure in place quickly, then decide later whether to build an internal team, keep the engagement ongoing, or run a hybrid model where Perimattic supports specialist areas like cloud cost optimization or Kubernetes while an internal team handles day-to-day operations.
GitOps means your Git repository is the single source of truth for what should be running in your infrastructure. Instead of engineers making manual changes in a cloud console, changes are proposed as pull requests, reviewed, merged, and then automatically applied by tools like ArgoCD or Flux. This gives you a full audit trail, easy rollback by reverting a commit, and drift detection that flags when the live environment stops matching what is in Git.
A focused proof of concept — such as one pipeline or one service migrated to the new platform — typically takes 2 to 4 weeks. A full platform build or migration across multiple services and environments usually runs 6 to 12 weeks, depending on the complexity of your existing infrastructure, compliance requirements, and how many teams need to be onboarded to the new tooling.
Savings vary significantly by starting point, but most organizations we work with are overpaying by 20 to 40 percent before a structured review — usually from oversized instances, unused reserved capacity, orphaned resources, and a lack of tagging that makes cost allocation impossible. We typically identify the highest-impact changes in the first two weeks of an engagement, with many savings realized within the first billing cycle after implementation.
We work across AWS, Azure, and Google Cloud Platform, and our AWS DevOps services practice is our deepest area of expertise given how much of our client base runs on AWS. We do not require a migration to a different provider to start an engagement. Our default approach is to work within your existing cloud environment and improve it, rather than force a costly and risky platform migration unless there is a clear business case for one.
In most cases, no switch is required. We can work within Jenkins, GitLab CI, CircleCI, or GitHub Actions — whichever your team already uses — and focus on improving pipeline reliability, speed, and security rather than forcing a tooling migration. Where a switch does make sense, such as adopting GitOps patterns that a legacy CI tool cannot support well, we will explain the tradeoffs clearly before recommending it.
We have delivered infrastructure for clients working under PCI DSS, HIPAA, SOC 2, and general enterprise security review requirements. This typically means segregated environments, encrypted data at rest and in transit, detailed audit logging, least-privilege IAM design, and documentation that satisfies your compliance and security teams during review.
Yes — our DevOps and platform engineering services include both one-time build engagements and ongoing managed DevOps support. Many clients move from an initial build engagement into an ongoing DevOps as a service arrangement, where we continue to operate, monitor, and improve the platform. Others prefer a defined build-and-handover engagement, where we train your internal team fully and step away, remaining available for a defined support window afterward.
Pricing depends on scope: a fixed-scope proof of concept is quoted as a flat project fee, a full platform build is typically quoted as a milestone-based project, and ongoing managed DevOps or DevOps as a service arrangements are priced monthly based on the level of coverage and response time your team needs. We provide a detailed quote after the free discovery session, once we understand the actual size and complexity of your environment.
We work alongside your existing team in almost every engagement. Most clients do not want to outsource their entire infrastructure function, and we do not encourage that either. Instead, we typically pair our engineers with yours during the build phase, so knowledge transfers naturally rather than through a single handover document at the end. Your team ends up more capable of operating and extending the platform than before we started.
Every engagement includes a defined support window after handover — typically several weeks — during which we remain available to resolve any issues that surface under real production load. Beyond that window, clients can choose a retainer-based support arrangement, move to a full DevOps as a service relationship, or rely entirely on their internal team using the documentation and runbooks we leave behind.
Tell us what is slowing your releases down, costing you unexplained cloud spend, or keeping your team up at night during incidents. We will show you exactly how a properly engineered platform can reduce manual toil, cut cloud costs, and deliver a measurable return in the first quarter.