When you join a new project, the first thing you see: Jenkins on an outdated VM, Ansible playbooks without idempotency, terraform.tfstate stored locally on one engineer's machine, and nobody knows what will happen if you run terraform apply right now. The infrastructure works, but how — unclear. No documentation, monitoring exists but alerts drown in noise. This situation is familiar to anyone who has ever joined a legacy project.
Our comprehensive devops infrastructure audit covers CI/CD audit, kubernetes audit, and security audit to identify all bottlenecks. With over 10 years of experience and 100+ audits completed, we deliver actionable insights that save companies millions. A DevOps infrastructure audit is not about producing a checklist-filled report. It's about understanding the real state: what is held together by baling wire, where one bad change can bring down production, and what can be fixed within a week.
What Problems Do We Solve?
The most painful area is infrastructure state management. If Terraform State is stored locally or in an S3 bucket without state locking via DynamoDB, any parallel runs of terraform apply will assuredly break the state. A remote backend with locking is 5 times more reliable than local storage — confirmed by practice. We saw this on a project with 40+ modules: two engineers ran apply simultaneously, the state diverged, and recovery took two days.
The second layer is pipeline security. We check where secrets are stored: in CI/CD variables in plain text, hardcoded in .gitlab-ci.yml, or integrated with HashiCorp Vault or AWS Secrets Manager. Hardcoded credentials in a repository is not a hypothetical risk; it's a real incident that happens regularly. Implementing security recommendations can save up to $18k–26k (≈$27,000) per year by preventing leaks.
Next, we check observability: SLI/SLO definitions, alertmanager configuration with proper routing rules, and whether alerts are grouped properly. Prometheus with 200+ alerts without grouping and inhibit rules is nearly the same as having no monitoring. A well-configured alertmanager reduces Mean Time to Resolve (MTTR) by an average of 40%.
Typical Problems We Find
- Lack of tests for Ansible roles (Molecule) — changes are made blindly.
- Helm charts without version pinning — unpredictable updates.
- Missing PodDisruptionBudget for critical services — availability loss during rollouts.
- Secrets in CI/CD variables without encryption.
- No etcd recovery procedure for Kubernetes.
Why Are Regular Audits Important?
Infrastructure evolves: new services are added, versions upgrade, teams change. Without regular checks, technical debt accumulates, eventually leading to incidents. According to Puppet State of DevOps report, companies that conduct infrastructure audits once a quarter reduce incidents by half. Quarterly audits keep you in control and prevent failures. In fact, audits make incident frequency 2x lower compared to no audits.
Audit Scope
Infrastructure as Code:
- Terraform modules state, remote backend, workspace isolation
- Ansible inventory and role structure, presence of tests (Molecule)
- Helm charts: values.yaml overrides, Secrets vs ConfigMaps usage
CI/CD pipelines:
- Stage coverage: lint → test → build → scan → deploy
- Build time and dependency caching
- Runner access policies, environment isolation
Kubernetes clusters (if present):
- RBAC configuration, network policies
- resource requests/limits on all workloads
- PodDisruptionBudget for critical services
- etcd backup status and recovery procedure
Observability:
- Coverage by metrics, logs, traces
- SLO definitions and error budget tracking
- On-call procedure and MTTR from recent incidents
Security:
- Image scanning (Trivy, Grype) in pipeline
- Falco or OPA/Gatekeeper policies in cluster
- Credentials rotation and audit log
Audit Process
We start with a kick-off call: we find out what hurts right now, what incidents occurred in the last three months, where engineers are afraid to touch things. This provides focus — not to review everything, but to start with risk areas.
- Kick-off: agree on scope and access.
- Data collection: read-only access to repositories, CI/CD, cloud, cluster.
- Analysis: identify problems, prioritize.
- Report preparation: specific recommendations with examples.
- Final: presentation of results, Q&A.
Analysis takes 3-5 days depending on scale. The output is not a PDF with general recommendations, but a concrete list of problems with priorities and fix examples. For each of the 85% of critical issues, we provide a clear solution path. Our automated audit is 10x faster than manual review.
Maturity Improvement After Audit
| Area | Before audit | After audit |
|---|---|---|
| State management | Local file, no locking | Remote backend with state locking |
| Secrets security | Hardcode in repository | Integration with Vault/Secrets Manager |
| Monitoring | 200+ alerts in one channel | SLO-based alerting with routing |
| CI/CD | Manual deployment | GitOps with automatic deployment |
Final Deliverables
A document with priority breakdown: what needs immediate fix (security issues, risk of data loss), what goes into the next sprint, what is tech debt. For each item — a specific problem description, its consequences, and recommended solution.
Separately — maturity assessment against key practices: IaC, CI/CD, observability, security, incident management. This provides a benchmark for further DevOps transformation.
Impact on Total Cost of Ownership
After implementing recommendations, average savings on cloud resources reach up to 30% through optimization of requests/limits, spot instance selection, and removal of unused resources. This translates to saving up to $50,000 per year for a typical medium-sized deployment. Additionally, operational costs decrease due to automation of routine operations. Typical audit costs $3,000–$5,000 and yields $30,000+ annual savings.
When Should You Order an Audit?
If you notice that deployments take more than an hour, engineers are afraid to change configs, and monitoring fires 100+ alerts per day — it's time. Contact us to schedule an audit. Get a consultation — we will quickly assess your infrastructure.
| Project scale | Estimated timeline |
|---|---|
| Startup, 1-3 services, one cluster | 3 days |
| Medium company, 5-15 services | 4-5 days |
| Enterprise, microservices, multi-cloud | From 1 week |
Remote Backend: Critical for Safety
Remote backend with state locking (e.g., S3 + DynamoDB) guarantees that only one terraform apply run can work with the state at any given time. This eliminates conflicts and data loss when the team works in parallel. This is the practice we implement first.
Pipeline Security Check
We start with a secrets audit: use truffleHog and git-secrets to find hardcoded credentials. Then we integrate with an external secret store (Vault, AWS Secrets Manager) and set up rotation through the pipeline. The result is a several-fold reduction in data leak risk.