If you work in DevOps, there’s a good chance you already automate builds, test continuously, and ship frequently. Yet many incident reports, audit findings, and late-night pages trace back to one root misunderstanding: who is responsible for what in the cloud. On AWS, that answer is framed by the Shared Responsibility Model (SRM) a simple idea with far-reaching implications. AWS is responsible for the security of the cloud, and customers are responsible for security in the cloud. The nuance lies in the word in. DevOps teams define, provision, deploy, and operate the workloads that actually live inside AWS. That makes SRM a daily operational concern, not a theoretical one.
This guide explains the AWS Shared Responsibility Model in practical DevOps terms. You will learn how responsibilities split across IaaS, containers, and serverless; how SRM maps to CI/CD pipelines, Infrastructure as Code (IaC), policy enforcement, observability, and incident response; and how to codify it so your team can move fast without breaking governance.
AWS is responsible for the security of the cloud. That includes the global infrastructure (regions, availability zones, edge locations), the hardware, software, networking, and facilities that run AWS services. AWS maintains physical security, hypervisor integrity, foundational services, and many managed control planes.
You are responsible for security in the cloud. That includes how you configure services, how you secure identities and data, how you deploy and patch workloads, how you isolate networks, how you log, monitor, and respond, and whether your application meets regulatory obligations.
This split doesn’t remove your need for security; it changes where you exert effort. Instead of racking servers and installing hypervisor patches, you manage identities, configurations, encryption, app code, container images, Lambda functions, and pipelines.
DevOps teams often work across multiple compute models, sometimes within the same product. The Shared Responsibility Model flexes accordingly.
AWS: Physical facilities, hardware, networking, hypervisor, and foundational services reliability.
Customer (you): Guest OS security and patching, AMI hardening, network segmentation in VPC, security groups and NACLs, IAM roles and policies, data classification and encryption, key management policy, application security, runtime monitoring, backup/restore policies, vulnerability management.
AWS: Underlying infrastructure, managed control planes (EKS/ECS), Fargate runtime isolation and patching, cluster control plane availability.
Customer: Cluster configuration (if self-managed nodes), node image hardening (for EC2 worker nodes), pod security (admission policies, namespaces), container image security (scan, sign, provenance), IAM roles for service accounts, secrets management, network policies, registry governance, application code, observability, backup and DR drills.
AWS: Underlying servers, OS, runtime environments, scaling infrastructure, global platform security.
Customer : Function code, event permissions, IAM policies, input validation, secret handling, environment variable hygiene, data encryption configuration, least privilege on triggers and destinations, observability, and compliance evidence.
AWS: Service availability, patching of managed control planes, durability SLAs.
Customer: Bucket/table/cluster configuration, access policies and encryption settings, parameter and password policies, query and data lifecycle governance, backup/restore testing, data residency controls, monitoring and anomaly detection.
The pattern: the more managed the service, the more AWS handles undifferentiated heavy lifting, and the more your responsibility shifts to configuration, identity, data, and code.
Use this matrix to clarify ownership across your team. Adjust columns for your org (Platform, Security, Application, SRE, Data). “Primary” means accountable; “Partner” means collaborates closely.
|
Area |
AWS |
DevOps/Platform |
Security/GRC |
Application Team |
SRE/Operations |
|
Physical security |
Primary |
— |
— |
— |
— |
|
Hypervisor/Host patching |
Primary |
— |
— |
— |
— |
|
VPC design & segmentation |
— |
Primary |
Partner |
Partner |
Partner |
|
IAM architecture & roles |
— |
Primary |
Partner |
Partner |
Partner |
|
Key management policy (KMS) |
— |
Primary |
Partner |
Partner |
Partner |
|
Service configuration (S3, RDS, etc.) |
— |
Primary |
Partner |
Partner |
Partner |
|
OS patching (EC2) |
— |
Primary |
Partner |
— |
Partner |
|
Container base image standards |
— |
Primary |
Partner |
Partner |
Partner |
|
Pipeline security (scanning, signing) |
— |
Primary |
Partner |
Partner |
Partner |
|
App code security (SAST/DAST) |
— |
Partner |
Partner |
Primary |
Partner |
|
Secrets management |
— |
Primary |
Partner |
Partner |
Partner |
|
Logging/observability |
— |
Partner |
Partner |
Partner |
Primary |
|
Backup/DR drills |
— |
Partner |
Partner |
Partner |
Primary |
|
Incident response runbooks |
— |
Partner |
Primary |
Partner |
Primary |
|
Compliance evidence |
— |
Partner |
Primary |
Partner |
Partner |
Codify this table in your runbooks and onboarding docs. Disagreements resolved on paper now prevent finger-pointing during incidents.
Threat model early. Identify data flows, trust boundaries, and regulatory needs.
Select service models intentionally. If you cannot patch OS at scale, avoid EC2 for that tier.
Enforce secure coding standards.
Integrate SAST and dependency scanning in pull requests.
Sign artifacts to establish provenance.
Use ephemeral, hardened build environments (e.g., AWS CodeBuild).
Scan container images and IaC templates as part of CI.
Store artifacts in S3 with bucket policies blocking public access by default.
Run integration tests in isolated accounts or VPCs.
Add security tests (DAST) for exposed endpoints.
Validate IAM policies with automated checks (policy-as-code).
Require manual approval for production in regulated contexts.
Enforce change tracking and release notes for auditability.
Use blue/green or canary with automatic rollback.
Apply least-privilege roles to deployment agents and workloads.
Centralize logs in CloudWatch and route to analytics/long-term storage.
Define SLOs; alert on error budgets and key security indicators.
Conduct game days for incident and DR runbooks.
Post-incident reviews focus on controls, not blame.
Convert findings into automated guardrails.
SRM is not a one-time decision; it is a lens used in every lifecycle stage.
Use AWS CloudFormation or the AWS CDK to define VPCs, subnets, security groups, IAM roles, KMS keys, and service configs.
Version control your infrastructure in Git; changes require code review.
Build reusable, secure “golden modules” consumed by product teams.
Enforce rules automatically with:
Service Control Policies (SCPs) in AWS Organizations to prohibit risky actions globally.
AWS Config and conformance packs for continuous compliance checks.
Open Policy Agent (OPA)/Conftest to lint Terraform or Kubernetes manifests.
Guardrails in pipelines that fail builds on policy violations.
When IaC and policy as code are standard, SRM transforms from a slide deck into living guardrails.
IAM Design: Prefer roles over users. Grant least privilege. Use permission boundaries and session policies for fine control.
Cross-Account Access: Use AWS Organizations and role assumption rather than long-lived keys. Separate environments by accounts (dev, test, prod).
Secrets Management: Use AWS Secrets Manager or Parameter Store. Never commit secrets to repos or store in plaintext environment variables. Rotate keys.
MFA and Conditional Access: Enforce MFA for privileged operations. Use condition keys (e.g., aws:RequestedRegion) to restrict use where sensible.
At Rest: Enable SSE-S3 or SSE-KMS on S3. Use KMS CMKs for critical data. For RDS and DynamoDB, turn on encryption at rest.
In Transit: Enforce TLS everywhere. Use ACM for certificate management and automatic rotation.
Data Lifecycle: Define retention, archival, and deletion policies. Automate S3 lifecycle rules. Test restores periodically.
Data Residency and Classification: Tag data by sensitivity. Keep regulated data in approved regions/accounts. Restrict cross-region replication when necessary.
VPC Baseline: Private subnets for workloads; public only where necessary. Use NAT gateways for outbound traffic from private subnets.
Security Groups and NACLs: Default-deny posture. Keep rules specific and managed through IaC.
Service-to-Service Access: Consider AWS PrivateLink and VPC endpoints for private connectivity to AWS services. Use AWS WAF for edge filtering.
Zero Trust Mindset: Authenticate and authorize every call. Favor short-lived credentials and identity-aware proxies where applicable.
Logging: Centralize CloudTrail, VPC Flow Logs, ALB/NLB logs, and CloudWatch logs. Protect the log destination from tampering.
Metrics and Traces: Use CloudWatch metrics and X-Ray for tracing. Create dashboards per service and environment.
Alerting: Tie CloudWatch alarms to SNS and incident response tooling. Distinguish between security, reliability, and cost alerts.
Incident Response: Maintain runbooks covering triage, containment, communication, forensics, and recovery. Conduct periodic simulations.
AWS: Physical hardware, hypervisor, regional infrastructure availability.
You: Harden AMIs, patch OS and runtime, lock security groups, enforce TLS, use KMS-encrypted EBS volumes, configure ALB/WAF, scale with ASG, log to CloudWatch, rotate IAM roles, backup and test restore.
AWS: EKS control plane and availability, managed Kubernetes API.
You: Node group security (if EC2), PodSecurity admission, network policies, image scanning and signing, IRSA for least-privilege access, secrets via Secrets Manager, tracing with X-Ray/OpenTelemetry, autoscaling, backups of persistent volumes where used.
AWS: Servers, OS, runtime scaling, durability of managed services.
You: Function code, IAM permissions, resource policies on API, input validation, environment variable hygiene, DynamoDB table encryption and access patterns, alarms and DLQs, throttling, WAF on API if public.
Assuming managed means secured for your use case. Misconfigurations still expose data.
Over-entitled IAM roles granted for convenience.
Storing secrets in plaintext variables or code.
Treating logging as an afterthought, losing forensic visibility.
Skipping restore drills. Backups without tested restores are hope, not strategy.
Single-account sprawl. Use multi-account governance to contain blast radius.
Manual changes in the console. Prefer IaC and audit every drift.
Organization & Identity
Separate dev/test/stage/prod into distinct AWS accounts under AWS Organizations.
Use SSO with MFA. All privileged actions require MFA.
Enforce least privilege with permission boundaries and role assumption.
Network & Perimeter
Private subnets by default; restrict inbound with security groups and NACLs.
Use WAF on internet-facing endpoints. Prefer PrivateLink/VPC endpoints for AWS service access.
Data
Encrypt at rest with KMS everywhere feasible.
Classify data and tag resources accordingly.
Automate lifecycle and deletion policies.
Workloads
Maintain hardened base images or use Fargate/Serverless to reduce OS surface.
Scan images and dependencies pre-deploy. Sign artifacts.
Enforce runtime limits and least privilege (capabilities, FS permissions, timeouts)
Pipelines
Run builds in ephemeral runners.
SAST, SCA, IaC policy checks in PRs and CI.
Require approvals for production. Store artifacts in private S3 with deny-public-access.
Observability & IR
Aggregate logs; protect log buckets.
Create high-signal alarms with runbook links.
Run incident and DR game days quarterly.
Compliance
Use AWS Config rules and conformance packs.
Capture evidence automatically from pipelines and IaC repos.
Keep an auditable change history for infra and app releases.
Document your SRM matrix. Clarify who owns what across teams.
Baseline accounts and identity. Adopt AWS Organizations, SSO, MFA, and least-privilege roles.
Codify networks and IAM via IaC. Lock down VPC, subnets, security groups, and critical IAM in code.
Harden pipelines. Add SAST, SCA, IaC linting, image scans, and artifact signing.
Encrypt by default. Turn on KMS, enforce TLS, lock S3 buckets public access block.
Centralize logs and metrics. Build dashboards per service and environment.
Practice incidents and restores. Test your plan before production tests you.
Iterate with policy as code. Automate guardrails and make SRM self-enforcing.
1) What is the AWS Shared Responsibility Model in one sentence?
AWS secures the cloud infrastructure, and you secure everything you put in it identities, configurations, data, code, and operations.
2) How does responsibility change between EC2, containers, and serverless?
As you move from EC2 to containers to serverless, AWS handles progressively more of the underlying infrastructure; your responsibility focuses more on identity, configuration, code, and data.
3) If AWS is responsible for the cloud, why did my S3 bucket leak?
Because bucket access policies and data classification are your responsibility. Misconfiguration is a customer-side risk; use least privilege, block public access, and audit with AWS Config.
4) Do I still need to patch when I use managed services?
For serverless and many managed services, AWS patches underlying systems. You still must patch your application dependencies and keep runtimes and libraries current.
5) Is encryption AWS’s job or mine?
AWS provides encryption capabilities and key management services; you are responsible for enabling, configuring, and governing their use, including key rotation policies and access controls.
6) Who owns IAM?
You do. AWS provides IAM as a service, but you design roles, policies, and trust relationships. Poor IAM design is a leading cause of breaches.
7) How do I prove compliance in a DevOps world?
Automate evidence collection: keep infra in code, use signed artifacts, retain pipeline logs, centralize CloudTrail, and apply AWS Config with conformance packs. Your change history becomes your audit trail.
8) Does policy as code replace security teams?
No. It operationalizes agreed controls. Security partners with DevOps to define controls; DevOps encodes and maintains them; SRE enforces and monitors in runtime.
9) Are multi-account setups mandatory?
Not mandatory, but strongly recommended. Separate accounts reduce blast radius, clarify responsibilities, and simplify cost, access, and compliance boundaries.
10) What is the fastest way to start aligning with SRM today?
Block public S3 access, enforce MFA, move infra to IaC, centralize logs, and add scanning to CI. Then iteratively add guardrails like SCPs and AWS Config rules.
The AWS Shared Responsibility Model is not just a security slogan; it is the operating system of your DevOps practice. It delineates where AWS stops and where your accountability begins on identities, configurations, data protection, code quality, and operational excellence. When you embed SRM into your CI/CD pipelines, Infrastructure as Code, policy as code, observability, and incident response, you transform security from a gate at the end into an accelerator throughout. The payoff is real: fewer incidents, faster recovery, easier audits, and the confidence to ship faster on a secure foundation.
Treat this guide as your blueprint. Start by clarifying ownership, codifying your controls, and making your pipelines enforce the rules you agree to. With each iteration, the Shared Responsibility Model will move from documentation to daily habit freeing your teams to deliver at high velocity without compromising trust, compliance, or resilience
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