★ ★ ★ ★ ★ 4.9 Client Rated
TRUSTED BY THE WORLD’S MOST ICONIC COMPANIES.
★ ★ ★ ★ ★ 4.9 Client Rated
The most consequential decisions in a serverless project happen before a single function is written — and they're the decisions that most development teams make too quickly. Our serverless architecture consulting service brings senior cloud architects into your planning process to design the right serverless solution for your specific workload characteristics, performance requirements, integration landscape, and cost model. We evaluate whether serverless is the right fit for your use case (and where it isn't), define the function decomposition strategy, design the event-driven communication patterns between services, select the appropriate managed services from AWS, Azure, or GCP to handle state, storage, queuing, and orchestration, and produce a documented architecture that your development team can execute against with confidence. Serverless done right starts with architecture done right.
AWS Lambda is the most widely adopted serverless compute platform in enterprise deployments — and getting the most from it requires more than wrapping business logic in a function handler. Our AWS Lambda development service covers the full spectrum of production-grade Lambda engineering: function design with appropriate scope and single-responsibility boundaries, cold start mitigation strategies (provisioned concurrency, runtime optimization, dependency minimization), IAM permission design following least-privilege principles, VPC configuration for functions that require private network access, dead letter queue configuration for reliable failure handling, and deployment automation through AWS SAM, CDK, or Serverless Framework. We build Lambda-based backends, event processors, data pipelines, and integration workflows that perform reliably and cost-efficiently at any scale.
Building APIs on serverless infrastructure — combining AWS API Gateway or Azure API Management with Lambda or Azure Functions — delivers the auto-scaling, zero-idle-cost, and reduced operational overhead advantages of serverless while exposing clean, versioned, and well-documented interfaces to your clients and internal consumers. Our serverless API development service covers REST and GraphQL API design, request validation and transformation, authentication and authorization integration (JWT, OAuth 2.0, API keys, Cognito, and custom authorizers), rate limiting and throttling configuration, CORS handling, API versioning strategy, and integration with backend data stores and downstream services. We build APIs that are performant under load, secure by design, and maintainable as your integration surface grows.
The architectural pattern that makes serverless most powerful — and most capable of handling enterprise-scale workloads — is event-driven design: services that communicate through events rather than direct calls, decoupled by message queues and event buses that allow each component to scale, fail, and evolve independently. We design and implement event-driven serverless architectures using AWS EventBridge, SQS, SNS, Kinesis, and Azure Service Bus — building pipelines for real-time data processing, asynchronous workflow orchestration, cross-service communication, and fan-out processing patterns that would be complex and costly to implement on conventional server infrastructure. Our event-driven architectures are designed for both correctness (guaranteed delivery, idempotent processing, dead letter handling) and operational visibility (structured logging, distributed tracing, alerting).
Moving workloads from conventional server-based or container-based infrastructure to serverless isn't a lift-and-shift operation — it requires rethinking how applications are decomposed, how state is managed, and how services communicate. Our serverless migration service assesses your existing application portfolio, identifies the workloads where serverless refactoring will deliver the highest return (in cost reduction, operational simplification, or scalability improvement), and executes the migration in a phased approach that keeps production systems running while the serverless equivalent is built, tested, and validated alongside them. We handle both the technical migration and the infrastructure-as-code transition — replacing manually provisioned servers and container clusters with reproducible, version-controlled serverless deployments that are fundamentally easier to operate at scale.
Serverless architecture is particularly well-suited to data workloads with variable or unpredictable volume — where the pay-per-execution model converts idle infrastructure cost into zero cost during low-activity periods and the auto-scaling behavior handles volume spikes without manual intervention. We build serverless data processing pipelines for ETL and ELT workflows, real-time stream processing with AWS Kinesis and Lambda or Azure Event Hubs and Functions, batch data transformation triggered by S3 object events or scheduled CloudWatch Events, and webhook and API data ingestion systems that process and route inbound data from external sources. Our serverless data engineering work integrates with downstream warehouses and lakes on Snowflake, Redshift, BigQuery, and Delta Lake.
Complex multi-step business processes — order fulfillment workflows, document processing pipelines, approval chains, data enrichment sequences — require reliable orchestration that handles retries, manages state across steps, and provides visibility into the status of in-flight workflow instances. We implement serverless workflow orchestration using AWS Step Functions and Azure Durable Functions, designing state machines that express your business process logic explicitly, handle partial failures gracefully, and produce the audit trail and monitoring visibility that compliance and operations teams require. Compared to implementing equivalent orchestration logic inside individual Lambda functions, Step Functions-based orchestration dramatically reduces the complexity of error handling, timeout management, and workflow state visibility in production.
The shared responsibility model in serverless shifts infrastructure security to the cloud provider but leaves application-layer security — IAM design, secrets management, data encryption, input validation, dependency security, and network controls — firmly in the hands of the development team. Our serverless security engineering service addresses the specific attack surface of serverless applications: over-permissioned Lambda execution roles (the most common serverless security gap in enterprise deployments), hardcoded secrets in function environment variables, injection vulnerabilities in event-triggered functions, insecure direct object references in API handlers, and unprotected function URLs. We design IAM policies with least-privilege precision, integrate AWS Secrets Manager and Parameter Store for secure secrets management, implement WAF rules for API endpoints, and conduct function-level security reviews as part of every serverless delivery engagement.
One of serverless architecture's most compelling promises — that you only pay for what you use — doesn't automatically translate into low bills. Poorly configured serverless applications can generate surprisingly high costs through memory over-provisioning, inefficient invocation patterns, unnecessary data transfer between services, underutilized provisioned concurrency, and unoptimized function durations. Our serverless cost optimization service conducts a detailed analysis of your existing serverless workloads — profiling function execution patterns, memory allocation efficiency, invocation frequency, and cross-service data flows — and implements targeted optimizations that reduce your serverless spend without compromising performance or reliability. We also design cost-aware architectures for new serverless projects, establishing the billing visibility and alerting that prevents cost surprises before they appear on an invoice.
Debugging and operating serverless applications requires a different observability approach than conventional server-based systems — because the ephemeral, distributed nature of function execution means that traditional monitoring tools designed around long-lived processes provide incomplete visibility. We implement serverless observability stacks using AWS CloudWatch with structured logging, AWS X-Ray for distributed tracing across function chains and downstream service calls, custom metrics and dashboards for business-level KPI monitoring, and alerting configurations that catch cold start degradation, error rate spikes, and cost anomalies before they become production incidents. For deployed serverless applications, we provide ongoing support retainers covering runtime version updates, dependency security patching, performance tuning, and incident response — ensuring that your serverless infrastructure remains secure, current, and cost-efficient over its operational lifetime.
The project involved implementing a data Warehouse architecture with a specialized team experienced in the relevant tools.
Burger King approached us to enhance the performance of their back-end processes, seeking a team of specialists to address their specific tech needs.
YellowPepper partnered with Coderio to bolster its development team across various projects associated with its FinTech solutions. This collaboration aimed to leverage our expertise and elite resources to enhance the efficiency and effectiveness of the YellowPepper team in evolving and developing their digital payments and transfer products.
The most important thing to understand about serverless development is that its benefits extend well beyond the compute layer. Yes, you no longer provision or manage servers — but the deeper value is the operational model shift that serverless enables: your engineering team stops spending time on infrastructure management, capacity planning, OS patching, and availability engineering for the compute layer, and redirects that capacity toward product development. For organizations where engineering bandwidth is the primary constraint on product velocity, serverless architecture is a force multiplier — not because it makes individual functions run faster, but because it removes entire categories of operational work from the engineering team's plate. Organizations that adopt serverless primarily to reduce server costs often underestimate its real value, which is the time-to-market and engineering focus advantage it creates.
The way you decompose business logic into individual functions has more impact on the long-term maintainability, testability, debuggability, and cost efficiency of a serverless application than any other design decision. Functions that are too coarse — containing large amounts of logic that could be independently deployed and scaled — lose most of the granularity and composability benefits of the serverless model. Functions that are too fine-grained — with individual functions handling trivial operations — create excessive invocation overhead, distributed tracing complexity, and IAM surface area that increases security governance cost. The right function scope is determined by the unit of independent scalability, independent deployability, and single-responsibility that makes sense for your specific business logic — and getting that decomposition right early prevents the expensive refactoring that coarse-grained serverless architectures typically require as they mature.
Cold start latency — the additional initialization time that occurs when a serverless function is invoked for the first time or after a period of inactivity — is one of the most frequently dismissed concerns in serverless architecture discussions, and one of the most commonly encountered production problems. For latency-sensitive workloads — user-facing APIs, real-time data processing, synchronous integration workflows — cold starts that add hundreds of milliseconds to function initialization are unacceptable, and they don't resolve themselves as traffic increases if the invocation pattern includes regular idle periods. The engineering solutions to cold start problems — provisioned concurrency, runtime selection (Node.js and Python have meaningfully lower cold start overhead than Java and .NET in most configurations), dependency minimization, and module lazy loading — need to be designed into the architecture from the start, not addressed as a production incident after go-live.
One of the most common misconceptions about serverless architecture is that its stateless execution model simplifies application state management. In reality, serverless relocates state management rather than eliminating it — from in-memory application state to external managed services that functions read from and write to. Session state moves to DynamoDB, ElastiCache, or a managed key-value store. Workflow state moves to Step Functions or Durable Functions. File state moves to S3 or Blob Storage. Database connections move from persistent pools to connection proxies like RDS Proxy that manage pooling on behalf of stateless functions. Designing these state management patterns correctly — choosing the right external service for each category of state, handling the consistency and concurrency implications of distributed state access, and managing the cost model of external state storage — is one of the more demanding architectural challenges in production serverless systems.
Serverless applications composed of dozens or hundreds of functions, event sources, IAM roles, API configurations, queue definitions, and managed service integrations are simply unmanageable at production scale without infrastructure as code. Manual configuration through cloud consoles does not reproduce reliably across environments, does not produce auditable change history, does not support rollback, and creates significant operational risk when the engineer who originally configured a resource is unavailable. AWS SAM, AWS CDK, Serverless Framework, and Terraform are the primary IaC tools for serverless infrastructure — and choosing between them based on your team's language familiarity, testing requirements, and multi-cloud strategy is an important early decision. Organizations that deploy serverless production systems without IaC consistently encounter configuration drift, environment inconsistencies, and compliance audit challenges that would not exist with disciplined infrastructure-as-code from the start.
Most serverless development guidance assumes a single-cloud deployment target — and for many applications, that assumption is valid. But enterprise organizations with existing multi-cloud commitments, data residency requirements across regions and providers, or vendor risk management policies that limit concentration on a single cloud provider need serverless architectures designed with provider abstraction in mind. The concrete challenge is that AWS Lambda, Azure Functions, and Google Cloud Functions differ in their event source ecosystems, IAM models, VPC integration approaches, and toolchain support — meaning that logic written against one provider's native services doesn't transfer cleanly to another. Building a provider abstraction layer that allows core business logic to be deployed across multiple serverless platforms is more expensive upfront and delivers significant optionality in organizations where multi-cloud is a genuine requirement rather than an aspiration.
One of the more persistent false choices in cloud architecture discussions is the framing of serverless versus containers as competing approaches where organizations must pick one. In practice, the most well-designed enterprise cloud architectures use both — with serverless handling event-driven, variable-load, and highly granular workloads where its auto-scaling and pay-per-execution economics create clear value, and containers handling long-running processes, stateful workloads, CPU-intensive tasks, and latency-sensitive services where serverless cold start and execution duration limits create constraints. AWS explicitly supports this hybrid model through services like App Runner, Fargate, and Lambda container images — and Azure and GCP offer equivalent hybrid deployment patterns. Organizations that force all workloads into a single execution model typically end up with either serverless applications that would perform and cost less on containers, or containerized workloads that would operate better and more cheaply as functions.
The identity and access management (IAM) configuration of serverless applications is where the most consequential and most commonly neglected security decisions live. In a serverless architecture, every function has an execution role — a set of IAM permissions that determines what AWS resources and actions that function can access. The path of least resistance is to assign overly broad permissions (AdministratorAccess or broad service-level policies) to avoid permission errors during development. The consequence is a production security posture where a compromised function — through a code vulnerability, a malicious dependency, or an injection attack via an untrusted event source — can access far more of your AWS account than the function's legitimate business logic requires. Least-privilege IAM design for serverless functions requires defining the exact resources and actions each function needs, scoped to the specific ARNs it legitimately operates on — and it requires the discipline to maintain that specificity as functions evolve and new permissions are added.
The monitoring and observability approaches that work well for long-lived server processes — CPU and memory utilization dashboards, process-level log aggregation, uptime monitoring — provide inadequate visibility into serverless applications. A Lambda function that succeeds 99.9% of the time and fails 0.1% of the time with a specific error type is invisible to health-check monitoring but may be silently corrupting a significant fraction of your data. Effective serverless observability requires distributed tracing that follows a request through its complete function chain and downstream service calls (AWS X-Ray, Honeycomb, Datadog APM), structured logging with correlation IDs that allow individual invocations to be reconstructed across log streams, custom metrics that track business-level outcomes alongside technical metrics, and anomaly detection on invocation error rates, duration distributions, and throttling events that surface problems before they accumulate into incidents. Organizations that apply traditional monitoring approaches to serverless architectures consistently have poor visibility into the actual behavior of their production systems.
We build high-performance software engineering teams better than everyone else.
Coderio specializes in Serverless Development, delivering scalable and secure solutions for businesses of all sizes. Our skilled developers have extensive experience building modern applications, integrating complex systems, and migrating legacy platforms. We stay up to date with the latest technology advancements to ensure your project's success.
We have a dedicated team of Serverless Development with deep expertise in creating custom, scalable applications across a range of industries. Our team is experienced in both backend and frontend development, enabling us to build solutions that are not only functional but also visually appealing and user-friendly.
No matter what you want to build, our tailored services provide the expertise to elevate your projects. We customize our approach to meet your needs, ensuring better collaboration and a higher-quality final product.
Our engineering practices were forged in the highest standards of our many Fortune 500 clients.
We can assemble your Serverless Development team within 7 days from the 10k pre-vetted engineers in our community. Our experienced, on-demand, ready talent will significantly accelerate your time to value.
We are big enough to solve your problems but small enough to really care for your success.
Our Guilds and Chapters ensure a shared knowledge base and systemic cross-pollination of ideas amongst all our engineers. Beyond their specific expertise, the knowledge and experience of the whole engineering team is always available to any individual developer.
We believe in transparency and close collaboration with our clients. From the initial planning stages through development and deployment, we keep you informed at every step. Your feedback is always welcome, and we ensure that the final product meets your specific business needs.
Beyond the specific software developers working on your project, our COO, CTO, Subject Matter Expert, and the Service Delivery Manager will also actively participate in adding expertise, oversight, ingenuity, and value.
Smooth. Swift. Simple.
We are eager to learn about your business objectives, understand your tech requirements, and specific Serverless Development needs.
We can assemble your team of experienced, timezone-aligned, expert Serverless Development developers within 7 days.
Our [tech] developers can quickly onboard, integrate with your team, and add value from the first moment.
Whether you’re looking to leverage the latest technologies, improve your infrastructure, or build high-performance applications, our team is here to guide you.
Accelerate your software development with our on-demand nearshore engineering teams.
