Trust TechAhead for Your Serverless Needs

Serverless is a cloud execution model where the provider handles provisioning, scaling, and patching of infrastructure. You deploy functions or event‑driven services, which scale automatically, and you only pay for actual execution time.

You pay only for compute when your code runs (per‑request, per‑ms billing), avoiding idle capacity costs, OS licenses, and patching. Auto‑scaling prevents over‑provisioning, and managed services reduce operations effort, lowering overall TCO.

Great fit for event‑driven APIs, backends, data processing, and bursty workloads. Less ideal for long‑running tasks, heavy stateful services, or low‑latency trading systems. We assess SLAs, runtime limits, and workload patterns before recommending.

Auto-scaling handles sudden traffic spikes with fine-grained concurrency. Cold-start latency is mitigated with warmers, provisioned concurrency, or minimum instance strategies to maintain low tail latency.

Yes. We analyze the monolith, identify candidate domains, and incrementally carve out functions/services. Blue-green or canary releases with feature flags minimize downtime during refactoring.

We enforce least-privilege IAM, secrets management, VPC/private networking, input validation, and WAF/API Gateway policies. Managed platforms provide patching, isolation, and audit logging by default.

Compute: AWS Lambda, Azure Functions, Google Cloud Functions/Run. APIs: API Gateway/Azure API Management/GCP API Gateway. Data: DynamoDB, Aurora Serverless, Firestore/BigQuery, or SQL. IaC/CI-CD: SAM/CDK/Terraform + GitHub Actions/Azure DevOps.

Traditional hosting requires you to manage servers, capacity, and patching. Serverless offloads infrastructure management to the provider, letting you focus on code. Billing shifts from per-instance hours to per-request compute duration with automatic scaling.

No. You retain full control over code, APIs, data models, and security policies. The platform simply manages infrastructure so your team can focus on features.

Simple backends or automation can be delivered in weeks; complex, integrated systems may take a few months. Discovery, pilot, MVP, and phased scale-out milestones define the plan.

Yes. Event-driven functions work well with SaaS APIs, queues, and webhooks. We implement retries, dead-letter queues, and idempotency for reliability.

We minimize cold starts with provisioned concurrency (Lambda), minimum instances (Cloud Run), and warmers. Package size optimization and VPC configurations also reduce initialization time.

We implement centralized logs, metrics, and traces (e.g., CloudWatch/Cloud Logging + OpenTelemetry). Alerts on error rates/latency, structured logs with correlation IDs, and dashboards provide full observability.

We use IaC (Terraform, AWS SAM/CDK, Azure Bicep) and pipelines (GitHub Actions, Azure DevOps) for repeatable deployments, environment parity, and automated testing/security checks.

We use IaC (Terraform, AWS SAM/CDK, Azure Bicep) and pipelines (GitHub Actions, Azure DevOps) for repeatable deployments, environment parity, and automated testing/security checks.

Yes. We use open standards (OpenAPI), abstraction layers, and portable patterns (e.g., Knative/Cloud Run). Provider-specific code is isolated behind adapters to ease future migration.

Managed secret stores (AWS Secrets Manager, Azure Key Vault), KMS-backed encryption, short-lived credentials, and least-privilege roles, combined with automated rotation and audit logs, enforce governance.