DevOps Engineering Services
Modernize your delivery pipelines with CI/CD automation, infrastructure-as-code, SRE practices, cloud-native deployments, and observability that drives engineering velocity. From manual deployments to fully automated pipelines, on-premise to multi-cloud, we build DevOps capabilities that enable continuous delivery at scale.
Years of Service
Client Renewal Rate
Global Clients
Ave. Onboarding
When to Choose DevOps Engineering Services
Choose Scrums.com DevOps Engineering Services When:
- Manual deployments cause frequent failures and you need automated CI/CD pipelines that test, build, and deploy reliably (reduce deployment time by 10x)
- Production incidents consume engineering time with firefighting instead of building features (reduce incidents by 60% through observability and automation)
- Infrastructure provisioning takes days or weeks and you need infrastructure-as-code enabling environment creation in minutes
- Your DevOps team can't scale with developer growth, they're overwhelmed with tickets and manual operations blocking delivery velocity
- Cloud costs are escalating without visibility into resource utilization, optimization opportunities, or cost allocation across teams
- You lack deployment confidence with no rollback capabilities, insufficient testing, or unclear production health visibility
- Kubernetes adoption is stalled due to complexity, lack of internal expertise, or unclear orchestration strategy
- You need 24/7 reliability but don't have SRE capabilities, on-call practices, or incident response frameworks
Consider Alternative Scrums.com Solutions:
- Need comprehensive cloud infrastructure management? → Cloud Hub Services
- Want AI-powered deployment automation? → AI & Automation Services
- Modernizing infrastructure as part of platform transformation? → Platform Modernization
- Need ongoing infrastructure operations and support? → Software Maintenance & Support
- Building cloud-native applications from scratch? → Custom Software Development
What's Included in DevOps Engineering Services
Our comprehensive DevOps engineering services cover the entire platform lifecycle, from CI/CD pipeline design and infrastructure automation to production monitoring and incident response. We build DevOps capabilities that enable teams to deploy faster, operate reliably, and scale confidently.
CI/CD Pipeline Engineering & Automation
Design and implement automated CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, Azure Pipelines, or CircleCI. We build pipelines that automatically test code, scan for security vulnerabilities, build containers, deploy to multiple environments, and rollback on failures, reducing deployment time from hours to minutes while improving reliability through consistent, repeatable processes.
Infrastructure-as-Code (IaC) & Configuration Management
Implement infrastructure-as-code using Terraform, CloudFormation, Pulumi, or Ansible to version, test, and deploy infrastructure like application code. We eliminate manual configuration, prevent infrastructure drift, enable environment reproducibility, and accelerate provisioning from days to minutes, ensuring consistent, auditable infrastructure across development, staging, and production environments.
Container Orchestration & Kubernetes
Deploy and manage containerized applications using Docker and Kubernetes (EKS, AKS, GKE, self-managed). We design container architectures, implement orchestration platforms, configure auto-scaling, establish service mesh patterns, and optimize resource utilization, enabling microservices deployment, efficient scaling, and simplified operations for cloud-native applications.
Cloud Infrastructure & Multi-Cloud Architecture
Design, deploy, and operate cloud infrastructure across AWS, Azure, GCP, or hybrid environments. We architect for high availability, implement disaster recovery, optimize cloud costs, configure networking and security, and establish cloud governance, leveraging cloud-native services (Lambda, ECS, CloudFront, S3, etc.) to build scalable, resilient, cost-effective infrastructure.
Monitoring, Observability & Incident Response
Implement comprehensive monitoring and observability using Prometheus, Grafana, DataDog, New Relic, or CloudWatch. We establish metrics, logs, and distributed tracing, create alerting rules and dashboards, implement on-call rotations, and build incident response workflows, providing visibility into system health, enabling proactive problem detection, and reducing mean time to recovery (MTTR) by 70%.
Site Reliability Engineering (SRE) Practices
Adopt SRE methodologies including SLO/SLI/error budget frameworks, chaos engineering, capacity planning, and toil reduction. We establish reliability targets, automate operational tasks, implement progressive deployment strategies (canary, blue-green), conduct failure mode analysis, and build cultures balancing velocity with stability, achieving 99.9%+ uptime while maintaining rapid release cadence.
Our DevOps Engineering Approach
We don't just build pipelines, we build DevOps cultures. Our approach combines automation engineering, SRE principles, and organizational change management to transform how teams build, deploy, and operate software at scale.
Platform Engineering Mindset
We build internal developer platforms that abstract infrastructure complexity, enabling developers to self-service provision environments, deploy applications, and access resources without DevOps bottlenecks. This platform engineering approach reduces cognitive load, accelerates development velocity, and allows DevOps teams to scale their impact, supporting hundreds of developers without proportionally increasing DevOps headcount.
Everything-as-Code Philosophy
Infrastructure, configuration, policies, monitoring, and even documentation exist as version-controlled code. This everything-as-code approach enables automated testing before production, peer review of infrastructure changes, rollback capabilities for any failure, and compliance-as-code enforcement, treating operations with the same rigor as application development and eliminating manual toil that causes incidents.
AI-Augmented Operations
Our AI agents enhance DevOps capabilities through automated incident detection, intelligent log analysis, predictive scaling recommendations, security vulnerability scanning, and automated remediation of common issues. AI doesn't replace DevOps engineers, it handles repetitive operational tasks (log analysis, alert correlation, capacity monitoring) while engineers focus on architecture, automation improvement, and strategic platform evolution.
DevOps Engineering Implementation Process
Our structured DevOps implementation builds automation maturity progressively, delivering immediate operational improvements while establishing long-term platform capabilities.
DevOps Assessment & Strategy
We begin by understanding your current delivery practices, identifying automation opportunities, and designing a DevOps roadmap aligned with your velocity and reliability goals. Our team assesses CI/CD maturity, evaluates infrastructure, analyzes deployment pain points, and creates a prioritized transformation plan.
Key Activities:
- Current DevOps maturity assessment (CI/CD, IaC, monitoring, incident response)
- Deployment process analysis and bottleneck identification
- Infrastructure architecture review and optimization opportunities
- Cloud cost analysis and optimization recommendations
- Team skills assessment and training needs identification
- DevOps strategy development with phased milestones
- Success metrics definition (deployment frequency, lead time, MTTR, change failure rate)
- Tool selection and architecture design
Deliverable: DevOps assessment report, transformation roadmap, architecture diagrams, cost-benefit analysis
Foundation & Tooling Setup
Establish DevOps foundations including CI/CD platforms, infrastructure-as-code frameworks, monitoring systems, and container orchestration. We configure tools, integrate with existing systems, implement initial automation, and prepare environments for progressive capability rollout.
Key Activities:
- CI/CD platform setup (Jenkins, GitLab CI, GitHub Actions, Azure Pipelines)
- Infrastructure-as-code implementation (Terraform, CloudFormation)
- Container platform deployment (Docker, Kubernetes/EKS/AKS/GKE)
- Monitoring and observability platform configuration (Prometheus, Grafana, DataDog)
- Secret management and security tooling (Vault, AWS Secrets Manager)
- Repository structure and branching strategy establishment
- Initial pipeline creation for priority applications
- Team access provisioning and training kickoff
Deliverable: Configured DevOps platforms, initial CI/CD pipelines, monitoring dashboards, IaC frameworks
Automation & Pipeline Rollout
Progressively automate deployments, infrastructure provisioning, testing, and monitoring across teams and applications. We implement CI/CD for additional services, expand infrastructure automation, establish observability practices, and build self-service capabilities for development teams.
Key Activities:
- CI/CD pipeline expansion across applications and microservices
- Infrastructure-as-code coverage for all environments (dev, staging, prod)
- Automated testing integration (unit, integration, E2E, security scans)
- Container orchestration for microservices deployments
- Auto-scaling configuration and optimization
- Monitoring instrumentation and alerting rule creation
- Incident response workflow automation
- Developer self-service platform capabilities
- Progressive deployment strategies (blue-green, canary releases)
- Security automation (vulnerability scanning, policy-as-code)
Deliverable: Automated CI/CD for all services, IaC managing all infrastructure, comprehensive monitoring, self-service platforms
SRE Practices & Continuous Optimization
Adopt SRE methodologies, optimize platform performance, reduce operational toil, and continuously improve reliability and velocity. We establish SLOs, implement chaos engineering, automate incident response, and ensure DevOps practices evolve with organizational growth.
Key Activities:
- SLO/SLI definition and error budget implementation
- Chaos engineering and failure testing
- Capacity planning and cost optimization
- Performance monitoring and optimization
- Toil identification and automation
- Incident postmortem and prevention
- Platform scalability improvements
- Team training and knowledge sharing
- DevOps metrics analysis and continuous improvement
- Quarterly platform reviews and roadmap updates
Deliverable: SRE practices established, optimized platforms, reduced toil, continuous reliability improvements
Ready for Automated, Reliable Deployments?
Our DevOps engineering services combine CI/CD automation, infrastructure-as-code, and SRE practices to enable 10x faster deployments, 99.9% uptime, and 60% fewer incidents, transforming operations from bottleneck to competitive advantage through platform engineering that scales.
DevOps Engineering Technologies We Use
Our DevOps engineers have deep expertise across cloud platforms, CI/CD tools, container orchestration, infrastructure-as-code frameworks, and monitoring platforms. From AWS and Kubernetes to Terraform and GitLab CI, we deploy the right DevOps technology stack for your infrastructure needs, all orchestrated through SEOP for unified visibility.
What Our Clients Say
DevOps Engineering Services Pricing
What Impacts DevOps Engineering Costs?
Infrastructure Complexity & Scale
Managing simple single-region deployments costs less than multi-region, multi-cloud, or hybrid infrastructure with complex networking, security requirements, and compliance constraints. More environments, regions, and technologies = more DevOps engineering effort.
Automation Maturity Level
Building DevOps from scratch (no CI/CD, manual deployments, no IaC) requires more initial investment than enhancing existing automation with improved pipelines, monitoring, and practices. Lower starting maturity = more foundational work.
Team Size & Application Count
Supporting 10 developers deploying 5 applications requires different DevOps capacity than supporting 100+ developers with 50+ microservices. More teams and services = more pipeline maintenance, incident response, and platform scaling.
Technology Stack Diversity
Standardized technology stacks (all applications use same languages, frameworks, databases) simplify DevOps compared to heterogeneous environments mixing .NET, Java, Node.js, Python, legacy systems, and various databases. More diversity = more tooling and expertise required.
Reliability & Compliance Requirements
Business-critical systems requiring 99.9%+ uptime, 24/7 on-call support, and comprehensive observability cost more than development systems with relaxed availability requirements. Regulated industries (FinTech, Healthcare) add compliance automation overhead (audit trails, policy-as-code, security scanning).
Cloud Optimization & FinOps
Basic cloud infrastructure management costs less than comprehensive FinOps including cost optimization, resource tagging, showback/chargeback, reserved instance management, and continuous rightsizing. Active cost management requires dedicated effort but delivers 30-50% cloud savings.
Industry Benchmarks: What DevOps Engineering Typically Costs
These are general industry ranges to help you budget:
Basic DevOps Services (Small Teams, Limited Automation)
CI/CD for limited applications, basic infrastructure management, business-hours support
Industry range: $10K - $25K/month
Standard DevOps Services (Mid-Sized Teams, Growing Automation)
Comprehensive CI/CD, IaC for all infrastructure, Kubernetes, monitoring, on-call support
Industry range: $25K - $60K/month
Enterprise DevOps Services (Large Teams, Full SRE)
Multi-cloud platforms, extensive automation, 24/7 SRE, advanced observability, platform engineering
Industry range: $60K - $150K+/month
DevOps Transformation Projects
Initial setup, migration, platform engineering, comprehensive automation buildout
Industry range: $75K - $300K per project
The Scrums.com Advantage: Enterprise DevOps at Predictable Costs
Unlike cloud consultancies focused solely on infrastructure, we deliver comprehensive DevOps engineering combining automation, observability, and cultural transformation at 40-60% cost savings compared to US/UK DevOps agencies—while achieving higher reliability and faster delivery through platform engineering approaches.
What Makes Our DevOps Services Different:
Platform Engineering Focus – Build self-service developer platforms that scale DevOps impact across hundreds of engineers without proportional headcount growth
Everything-as-Code – Infrastructure, monitoring, security policies, and documentation version-controlled, tested, and automated like application code
AI-Augmented Operations – AI agents handle log analysis, alert correlation, capacity monitoring, and common incident remediation—freeing engineers for strategic work
SRE Methodology – Establish reliability culture with SLOs, error budgets, chaos engineering, and toil reduction—balancing velocity with stability
Proven Frameworks – Pre-built CI/CD patterns, IaC modules, monitoring templates accelerating implementation 3-5x faster than building from scratch
Multi-Cloud Expertise – Deep experience across AWS, Azure, GCP enabling informed architecture decisions and avoiding vendor lock-in
94% Client Renewal Rate – Clients stay because DevOps delivers promised outcomes: faster deployments, fewer incidents, lower costs
Three Ways to Structure DevOps Engineering
Dedicated DevOps Team
Full-time DevOps engineers, SREs, and platform engineers working exclusively on your infrastructure and automation.
Best for: Organizations needing comprehensive DevOps capabilities and continuous platform improvement
Part-Time DevOps Specialists
Dedicated DevOps engineers working part-time (20hrs/week) on CI/CD, infrastructure, and monitoring improvements.
Best for: Growing teams scaling DevOps without full-time headcount
Augmented DevOps Engineers
Add individual DevOps specialists, SREs, or cloud architects to your existing infrastructure team.
Best for: Teams with DevOps foundation needing specialized expertise (Kubernetes, multi-cloud, SRE practices)
Ready to See What DevOps Services Would Cost?
Pricing depends on infrastructure complexity, team size, and reliability requirements. View our transparent pricing models or get a custom DevOps quote after a consultation.
Industries We Serve with DevOps Engineering
From FinTech platforms requiring zero-downtime deployments and PCI compliance to healthcare systems needing HIPAA-compliant infrastructure automation, our DevOps engineering services deliver reliability and velocity tailored to industry-specific operational requirements.
Fintech
Banking & Financial Services
Logistics & Supply Chain
Technology & SaaS
Telecommunications
Insurance
Retail & Ecommerce
Healthcare & Telemedecine
DevOps Engineering Success Stories
DevOps Engineering Services FAQs
What's the difference between DevOps and Platform Engineering?
DevOps focuses on practices, culture, and automation enabling collaboration between development and operations teams—typically including CI/CD, IaC, monitoring, and incident response. Platform Engineering builds internal developer platforms (self-service tools, environments, workflows) that abstract infrastructure complexity, enabling developers to deploy and operate applications without DevOps team bottlenecks. Platform Engineering is the evolution of DevOps—scaling DevOps impact across hundreds of engineers by building platforms instead of handling individual requests. We deliver both: foundational DevOps automation plus platform engineering for self-service scale.
How long does DevOps implementation take?
Timeline varies by starting maturity and scope. Basic CI/CD setup (initial pipelines, automated testing, deployment automation) takes 2-4 weeks. Comprehensive DevOps (CI/CD for all services, IaC managing all infrastructure, monitoring, containerization) takes 2-3 months. Full platform engineering transformation (self-service platforms, multi-cloud, advanced SRE) requires 6-12 months. Using phased approach, you see value immediately—first automated pipeline deploys within 2-3 weeks, with progressive capability rollout based on prioritization.
Do we need to migrate to cloud for DevOps?
No. DevOps principles (automation, CI/CD, IaC, monitoring) apply to on-premise infrastructure, cloud, or hybrid environments. We implement DevOps practices wherever your infrastructure exists—using tools like Jenkins, Ansible, and Prometheus that work across environments. However, cloud platforms (AWS, Azure, GCP) provide native services (managed Kubernetes, serverless, managed databases) that accelerate DevOps adoption and reduce operational overhead. Most organizations find cloud migration beneficial but not required for DevOps transformation.
Can DevOps improve our cloud costs?
Yes. DevOps automation enables cost optimization impossible with manual processes: Right-sizing resources based on actual usage patterns, Auto-scaling matching capacity to demand (scale down during low traffic), Reserved instances and savings plans for predictable workloads, Spot instances for fault-tolerant batch jobs, Resource tagging enabling cost allocation and showback, Automated cleanup of unused resources (old snapshots, detached volumes, zombie instances). Most organizations achieve 30-50% cloud cost reduction through DevOps-enabled FinOps practices within 6 months.
What if our team lacks DevOps expertise?
That's expected—most development teams lack specialized DevOps skills in Kubernetes, Terraform, monitoring platforms, or SRE practices. Our DevOps engineers bring required expertise while progressively training your team through hands-on collaboration, documentation, runbook creation, and knowledge transfer sessions. By engagement end, your engineers have practical DevOps experience gained through real implementation—not just theory. This approach builds internal capability for long-term platform ownership without external dependency.
How do you handle incident response and on-call?
We offer flexible on-call coverage models: Dedicated SRE team providing 24/7 incident response, triaging alerts, coordinating resolution, and conducting postmortems. Shared on-call where our DevOps engineers participate in your on-call rotation, supporting your team during incidents. Training & handoff where we establish on-call practices, create runbooks, implement alerting, and train your team for self-sufficiency. Most clients start with dedicated coverage during initial DevOps implementation, transitioning to shared or self-managed on-call as team capability grows.
Can you work with our existing tools and infrastructure?
Yes. We adapt to your current tooling (Jenkins, GitLab, Azure DevOps, existing cloud accounts) rather than forcing tool changes. If your tools are adequate, we enhance and automate within existing platforms. When tools limit capabilities (outdated Jenkins, insufficient monitoring), we recommend upgrades and migration paths—but always considering integration complexity, team familiarity, and business disruption. Most engagements involve 70% working with existing tools plus 30% introducing complementary tools addressing specific gaps.
What's included in infrastructure-as-code implementation?
Comprehensive IaC coverage includes: Cloud infrastructure (VPCs, subnets, security groups, load balancers, compute instances), Kubernetes configuration (namespaces, deployments, services, ingress rules), Databases and data stores (RDS, DynamoDB, managed databases with automated backups), Monitoring and alerting (CloudWatch, Prometheus setup, alert configurations), Security policies (IAM roles, security groups, secrets management), Network architecture (multi-AZ, multi-region, VPN/Direct Connect), Application configurations (environment variables, feature flags, service discovery). Everything provisioned, version-controlled, and tested as code—enabling environment reproduction, disaster recovery, and compliance auditing.
How do you measure DevOps success?
We track DORA (DevOps Research and Assessment) metrics through SEOP dashboards: Deployment Frequency (how often code reaches production—daily/weekly/monthly), Lead Time for Changes (time from commit to production deployment), Mean Time to Recovery (MTTR) (how quickly systems recover from failures), Change Failure Rate (percentage of deployments causing incidents). Additional metrics include: infrastructure provisioning time, incident count and severity, toil percentage (manual operational work vs. automation), cloud cost per customer/transaction. Quarterly reviews compare current metrics against baselines, demonstrating velocity and reliability improvements.
What happens after initial DevOps implementation?
Post-implementation options include: Ongoing platform engineering where our team continues improving automation, optimizing performance, and scaling platform capabilities as organization grows. Managed operations providing 24/7 monitoring, incident response, and infrastructure management. Advisory services with part-time DevOps architect providing strategic guidance, quarterly reviews, and architecture decisions. Knowledge transfer and handoff where we train your team for complete platform ownership and self-sufficiency. Most clients choose ongoing support (managed ops or advisory) to maintain DevOps momentum and prevent capability regression.
