Cloud & DevOps ServicesShipping should be boring.
We build the pipelines, infrastructure, and observability that make a deploy routine and an incident diagnosable — so releasing on a Friday stops being a decision anyone has to make.
Why does shipping still feel risky?
Infrastructure only becomes visible when it fails, which is exactly why it tends to get attention one incident too late.
- 01Deploying is a person, not a pipeline
- One engineer knows the sequence, so releases wait for them and batch up while they do. Each batch is larger than the last, which makes every release riskier, which makes everyone batch more.
- 02The bill went up and nobody can say which thing did it
- Nothing is tagged, so spend cannot be attributed to a service, a team, or an environment. There are instances nobody will switch off because nobody can prove what they do.
- 03An incident is guesswork
- No traces, no structured logs, no alerts that fire before a customer emails. Recovery time is really the time it takes for someone to remember which box to check first.
All three are the same missing thing: infrastructure that cannot describe itself, to you or to anyone you hire next.
Infrastructure you can read.
Anything configured by clicking through a console cannot be reviewed, reproduced, or rolled back, and it exists only in the memory of whoever did it. Everything we build is defined in code and lives in your repository.
Instrumentation comes first, because performance and cost work done without measurement is guessing with extra steps. You should be able to answer "what changed?" from a dashboard, not from a hypothesis.
Real savings come from right-sizing, lifecycle policies, and architecture changes — not from a report telling you that you spend a lot on compute. We start by making spend attributable, then fix what the attribution exposes.
Documentation is written for whoever is on call, not for the person who built the system. If a procedure only works when its author is awake and reachable, it is not a procedure.
What cloud and DevOps services does Devarithm offer?
Most engagements take two or three of these first, in the order the audit says will help soonest. If the application layer is the real constraint rather than the infrastructure, backend engineering is the page you want.
CI/CD Pipeline Engineering
One reviewed path from a merged commit to production, running the same way every time. This is the single change that most reliably makes releases smaller, more frequent, and less frightening.
- Build, test, and deploy pipeline per environment
- Automated checks, linting, and test gates
- Staged rollout and automated rollback
- Preview environments for pull requests
Infrastructure as Code
Your entire environment defined in version-controlled code, so it can be reviewed, reproduced, and recreated. The test of it is simple: could you rebuild production from an empty account?
- Terraform modules for the full estate
- Reproducible environments with no drift
- Secrets management and rotation
- Change review and plan-based deployment
Containerisation & Orchestration
Packaging and runtime chosen to match the size of your team, including the recommendation to stay on a managed platform when orchestration would cost more to run than it saves.
- Dockerised services with optimised build layers
- Orchestration on ECS, Kubernetes, or a managed platform
- Autoscaling and resource limits
- Health checks and graceful shutdown
Observability, Logging & Alerting
The layer that turns an outage from a mystery into a timeline. Metrics, structured logs, and traces that connect, plus alerts tuned to what users actually feel.
- Metrics, dashboards, and service-level indicators
- Structured logging and distributed tracing
- Alerting on user-facing symptoms, not noise
- Incident runbooks for known failure modes
Cloud Cost Optimisation
Attribution first, then reduction. Once spend can be traced to a service and an environment, the decisions about what to resize, schedule, or switch off stop being arguments.
- Tagging and cost attribution by service and environment
- Right-sizing and reserved or spot capacity planning
- Storage lifecycle and data transfer review
- Budget alerts and ongoing cost reporting
Security, Backup & Disaster Recovery
The things nobody tests until they need them. Least-privilege access, encrypted state, and a restore procedure that has actually been run rather than merely documented.
- IAM review and least-privilege access model
- Network, encryption, and secrets hardening
- Automated backups with tested restores
- Disaster recovery plan with defined RTO and RPO
Want to know what your infrastructure actually costs you?
In engineering time, in release risk, or on the invoice. The audit measures all three and tells you what to fix first.
No commitment required. No pitch deck. Just a focused 30-minute conversation.
How does Devarithm set up cloud infrastructure?
Five stages, sequenced so the riskiest thing you do today gets safer first. Nothing here requires a freeze on feature work.
- 01Week 1–2
Infrastructure & Cost Audit
We inventory what is running, how it is deployed, what it costs, and where it is undefended. We also measure your current deploy frequency and recovery time, because you cannot show improvement without a baseline.
You getEstate inventory, cost attribution, and a measured baseline
- 02Week 2–3
Pipeline & Infrastructure Design
The target state: environment topology, the deployment path, the rollback strategy, and what gets defined in code first. Sequenced so each stage is shippable on its own.
You getTarget architecture and a staged migration plan
- 03Week 3–7
Implement & Migrate
Pipelines built, infrastructure codified, and workloads moved environment by environment — staging before production, always with a path back. Your team keeps shipping throughout.
You getPipelines live and infrastructure defined in code
- 04Week 7–8
Observe & Verify
Dashboards, tracing, and alerting go in, then we verify the things everyone assumes: that a restore works, that a rollback rolls back, and that an alert reaches a human.
You getMonitoring live, restores and rollbacks tested
- 05Week 8+
Handover & Support
Runbooks, architecture documentation, and a walkthrough with the people who will operate it. We stay on as the long-term partner rather than handing over a system nobody else has run.
You getRunbooks, documentation, and ongoing support
What tech stack do we use for cloud and DevOps?
Defaults, not dogma. Almost all of this work happens inside a cloud account you already have, and we build on what is sound rather than migrating you for its own sake.
- Cloud
- AWSGoogle CloudCloudflareVercel
- Infrastructure as Code
- TerraformAWS CDKPulumi
- Containers & Runtime
- DockerKubernetesAmazon ECSAWS Lambda
- CI/CD
- GitHub ActionsGitLab CIArgo CD
- Observability
- GrafanaPrometheusOpenTelemetrySentry
Kubernetes is excellent and it is also a full-time system to operate. Most teams under about twenty engineers get more from a managed platform and spend the saved attention on their product.
Staging and production should be reached by the same code path with different variables. Environments that are deployed differently will eventually behave differently, usually at the worst moment.
Page a human for what a user can feel — errors, latency, failed jobs. Alerting on every cause produces noise, and noisy alerts get muted, which is worse than having none.
Who is this service built for?
This is also a filter. If none of these describe you, the discovery call will be short and free, and we will tell you honestly.
- Teams Shipping Too Slowly
- Releases are batched because each one is an event, and the person who knows the deploy steps is a dependency for everyone else.
- One reviewed pipeline, smaller releases, and a rollback that works
- Companies After an Incident
- Something broke, diagnosis took hours, and the post-mortem concluded that nobody could see what was happening.
- Tracing, structured logs, alerting on symptoms, and tested runbooks
- Startups Whose Cloud Bill Outgrew Them
- Spend climbed faster than usage and nothing is tagged, so no one can say which service or environment is responsible.
- Cost attribution first, then right-sizing and lifecycle work against real data
- Teams With No Dedicated DevOps
- Infrastructure is owned part-time by whichever engineer touched it last, and it shows in the drift between environments.
- Everything defined in code, plus documentation your team can operate from
Every engagement starts with a baseline.
We measure your current deploy frequency, recovery time, and spend before changing anything, because improvement you cannot show is indistinguishable from activity.
Thirty minutes to scope it, no obligation.
How can you engage Devarithm for infrastructure work?
Indicative ranges for cloud and DevOps work. We give you a scoped figure after the audit, not before it — but you should not have to book a call to find out the order of magnitude.
A defined piece of work with a clear end state — a pipeline build, an infrastructure-as-code migration, or an observability rollout.
- Fixed deliverables and fixed timeline
- Everything delivered as code in your repository
- Runbooks and documentation included
- Best for: pipelines, IaC migrations, observability
Ongoing infrastructure ownership for teams without a dedicated platform engineer.
- Continuous infrastructure and pipeline work
- Monitoring, cost review, and capacity planning
- Incident support and post-incident follow-up
- Best for: teams with no dedicated DevOps
A fixed two-to-four week burst with a defined output, and no commitment past it.
- Fixed sprint window, fixed output
- No long-term commitment
- Best for: one pipeline, a cost-reduction pass, an audit
What actually moves your number: the size of the existing estate, how many environments and services are involved, compliance requirements, and whether workloads are being migrated as part of the work.
Make the next deploy boring.
Tell us how you deploy today and what it costs you — in time, in risk, or on the invoice. We will tell you what to fix first and what it takes.
No commitment. No 50-slide deck. A focused 30-minute call.
Frequently Asked Questions
What is DevOps?
DevOps is the practice of building and running software with one set of tools and one set of owners, rather than handing finished code to a separate operations team. In practice it means automated deployment pipelines, infrastructure defined in code, and monitoring that tells the people who wrote a service how it is behaving in production.
What is infrastructure as code?
Infrastructure as code means your servers, networks, databases, and permissions are defined in version-controlled files rather than configured by hand in a web console. It makes infrastructure reviewable, reproducible, and recoverable — you can rebuild an environment from the repository instead of from memory.
Do we need Kubernetes?
Probably not. Kubernetes is powerful and it is also a full-time system to operate. Teams under roughly twenty engineers usually get more from a managed platform such as ECS, App Runner, or Vercel, and we will say so rather than selling you the more complex option.
How much do cloud and DevOps services cost?
Project-based infrastructure work typically runs ₹3L–₹12L (roughly $3,500–$14,000), and ongoing infrastructure ownership runs ₹1.5L–₹5L per month. Estate size, environment count, and compliance requirements are the main cost drivers.
Can you reduce our cloud bill?
Usually, though we do not quote a percentage before an audit — anyone who does is guessing at your architecture. The first step is making spend attributable by service and environment, because most of the saving comes from decisions that attribution makes obvious.
Will this lock us into one cloud provider?
We use managed services where they are clearly worth it and keep the rest portable, and we tell you which is which. Everything is defined in code in your repository, so the decisions stay visible and reversible rather than buried in a console.
Can you work with our existing AWS setup?
Yes, and that is the usual case. We start by codifying what already exists rather than rebuilding it, then improve in place. A migration only gets proposed when the current setup genuinely cannot carry where you are going.
Do you provide incident and on-call support?
On retainer, yes — incident support, post-incident follow-up, and the runbook updates that come out of it. On project engagements we hand over tested runbooks so your team can respond without us.
How long does a DevOps engagement take?
Most run eight to ten weeks from audit to handover, with the pipeline typically live by week four. Estate size and how many workloads have to migrate are what move that most.
Do you support the infrastructure after handover?
Yes. Lifetime support is the default engagement here rather than an upsell — ongoing maintenance, monitoring, cost review, and infrastructure work as the system grows.
You might also need
Backend Engineering
When the constraint turns out to be the application layer rather than the infrastructure it runs on.
System Architecture
A short review before a migration, when the question is what the target should be rather than how to get there.
SaaS Product Development
Product builds that arrive with pipelines, monitoring, and infrastructure as code already in place.