Less DevOps overhead. More engineering impact.
Your team should not spend its time connecting tools, chasing alerts, and figuring out where the issue is or where the cost went. That work is real, it is constant, and none of it reaches a customer.
Free tier available. Paid suites from $20 per user per month.
What is DevOps overhead?
DevOps overhead is the engineering time that goes into running the toolchain rather than the product: wiring tools together, switching between consoles, chasing an alert back to the change that caused it, and working out where the cloud bill went. It is paid by the same engineers you hired to build things, and it grows with every tool added to the stack.
Six places the overhead hides, and what replaces each one
These are not features. They are the six things a team stops paying for once delivery, operations, security and cost read from the same model.
- 1Reduce tool sprawl
One platform. Less complexity. Build, deploy, monitor, secure and account for cost against a single model of the estate, instead of paying a tax in glue code and integration projects for every tool you add.
- 2Save engineering time
Less context switching. More building. The context an engineer needs is in one place rather than spread across ten consoles that each hold a fraction of the answer and none of the whole.
- 3Deploy faster
From code to production with less friction. Build, containerize, roll out progressively and roll back automatically from a described pipeline anybody on the team can read and run.
- 4Resolve incidents faster
Less time finding the problem. The failing workload arrives with the deployment that preceded it, the logs around the failure and the owner attached, so the call starts at diagnosis instead of at evidence gathering.
- 5See where your cloud money goes
Cloud cost visibility. Spend is attributed to clusters, namespaces, services and teams from the same inventory, which turns the monthly conversation from a total into a specific workload somebody owns.
- 6Automate the work that should not need you
Let intelligent agents handle the repetitive. Ark investigates, correlates and proposes a scoped plan with the trace behind it. You approve it, or let vetted playbooks run inside bounds you declared.
Overhead is not untidiness. It is engineering capacity.
Every hour spent operating the toolchain is an hour not spent on the product, and it is charged at the rate of your most experienced people.
Integration work nobody asked for
The tax on the tenth tool. Every tool added to the stack brings an integration, a credential to rotate, a dashboard to maintain and a runbook that assumes it. None of that work reaches a customer.
Context switching during incidents
The most expensive minutes you spend. The estate holds the answer, but it is split across the system that fired the alert, the one that recorded the deployment and the one that names the owner. Assembling it by hand is the outage.
Waiting on the person who knows
Knowledge that lives in one head. When only one engineer can read the pipeline or interpret the dashboard, everything else queues behind them, and their week goes on questions rather than on building.
A bill nobody can explain
Spend without an owner. Cost that cannot be attributed to a team or a service cannot be acted on, so it is either ignored until it is a problem or cut with a blunt instrument that takes capacity with it.
The common thread is that no single tool holds enough context to answer an operational question on its own, so a person becomes the integration layer. That person is usually the one you would rather have building something.
One model underneath, rather than a tenth console on top
Nothing is ripped out. The tools stay where they are, and the context stops being trapped inside them.
- Connect read-only first: clusters, cloud accounts and server fleets with scoped, revocable credentials, and nothing installed on your workloads.
- One inventory across every architecture: cloud, on-premises, hybrid, Kubernetes, virtual machines, containers and serverless.
- One lifecycle: build, deploy, monitor, alert, secure and attribute cost against the same services and owners.
- Agents that investigate before they act, and act only inside a scope somebody approved.
The moment it stops feeling like another tool is the first question that crosses two of them and still has an answer: which commit produced this container, which deployment caused this alert, what does this team actually cost. Those questions are cheap on a shared model and expensive on ten separate ones.
The same model, seen from six angles
Questions people ask at the stand
DevOps overhead is the engineering time that goes into running the toolchain rather than the product: wiring tools together, switching between consoles, chasing an alert back to the change that caused it, and working out where the cloud bill went. It is paid by the same engineers you hired to build things, and it grows with every tool added to the stack.
DevOpsArk connects to what you already run: clouds, clusters, CI systems, registries, monitoring and ticketing. The tools stay where they are. What changes is that they stop being the only place their context lives, so the number of integrations your team maintains by hand stops growing with the stack.
In three places, in our experience: the evidence-gathering phase of an incident, which shortens because the correlation is already done; the delivery path, which stops needing a specialist to operate; and the recurring manual work that agents take over under approval. None of them is glamorous, and all three are paid weekly.
No. Kubernetes is one of the environments it manages. Cloud accounts, on-premises and hybrid servers, virtual machines, containers and serverless functions are covered by the same model, and so is the whole lifecycle from build and delivery through operations, security and cost.
Connect clusters and cloud accounts with read-only credentials and the inventory, monitoring view, security posture and cost attribution appear within minutes, because nothing is installed on your workloads. Delivery and remediation are switched on later, when you want them.
They gather the evidence an engineer would gather, correlate it against your own estate, and report a conclusion together with the execution trace behind it. They propose actions as scoped plans that a person approves. Nothing runs unattended unless you have promoted it to a vetted playbook with declared bounds.
There is a free tier with a small allowance on every suite, and paid suites start at $20 per user per month. Licensing is per user rather than per node, per account or per gigabyte, so the bill follows the size of your team rather than the size of the estate.
Give the week back to the engineering
Bring one cluster or one cloud account and see what the connected view says about it. Half an hour, no installation on your workloads.