Kong consulting and hands-on support

Kong is an open-source API gateway and service mesh used to route, secure, and observe traffic between clients, APIs, and microservices. It is commonly adopted by platform, DevOps, and application teams to standardize API access, enforce consistent policies, and reduce operational overhead in distributed systems.

Kong is frequently deployed on Kubernetes and supports cloud, on-premises, and hybrid environments, making it a practical fit for multi-team API governance and shared platform patterns. It often complements broader Platform Engineering initiatives focused on reliable, self-service delivery.

• Request routing and load balancing for north-south and east-west traffic
• Authentication, authorization, and policy enforcement through plugins
• Rate limiting, quotas, and traffic shaping to protect upstream services
• Observability integrations for logs, metrics, and distributed tracing
• Centralized management of API standards and lifecycle controls

Kong is an open-source API gateway and service mesh used to route, secure, and observe traffic between clients and microservices. It is commonly used to standardize ingress and API policy enforcement across Kubernetes, cloud, and hybrid environments.

• Centralizes north-south traffic control with consistent routing, host and path matching, and request and response transformations across services.
• Improves API security with established auth patterns such as JWT, OAuth2, API keys, and mutual TLS at the gateway layer.
• Limits abuse and reduces noisy-neighbor risk using rate limiting, request size limits, and IP allow and deny lists close to the edge.
• Increases resilience with configurable timeouts, retries, circuit breaking patterns, and upstream load balancing behavior.
• Supports progressive delivery through weighted traffic splitting and controlled rollouts for new API versions and service revisions.
• Extends behavior through a mature plugin ecosystem, enabling policies and integrations without requiring application code changes.
• Fits Kubernetes and GitOps workflows via declarative configuration and the Kong Ingress Controller for reviewable, repeatable changes.
• Enables multi-team governance using reusable policy templates and consistent controls across routes, services, and workspaces.
• Strengthens observability by integrating with metrics, logs, and tracing backends to isolate latency, error rates, and dependency bottlenecks.
• Scales to high throughput with a lightweight data plane and deployment patterns that support multi-zone and multi-region architectures.

Kong is a strong fit when teams need a shared control point for API traffic, consistent security and reliability controls, and a clear path to operational standardization as microservices scale. Common trade-offs include managing plugin and policy sprawl across many routes, aligning ownership between platform and application teams, and avoiding duplicated controls when combining gateway and mesh policies.

Common alternatives include NGINX, Apigee, AWS API Gateway, and Istio, depending on whether the priority is edge performance, full API management, managed cloud integration, or deeper service mesh features. For background, see Kong in the CNCF ecosystem.

Our experience with Kong helped us turn API gateway and service mesh work into repeatable delivery patterns—declarative configuration, security baselines, and operational runbooks—so teams could govern and scale API traffic across microservices and Kubernetes with reliable day-2 operations.

Some of the things we did include:

• Deployed Kong Gateway on Kubernetes using GitOps workflows, standardizing how services, routes, consumers, and plugins were promoted across environments.
• Designed gateway and mesh architectures for hybrid environments, including north-south and east-west traffic separation and clear ownership boundaries between platform and application teams.
• Implemented authentication and authorization with OIDC/JWT against enterprise identity providers, enforcing least-privilege access, tenant isolation, and auditable policy changes.
• Hardened edge security with mTLS, rate limiting, IP allow/deny policies, request validation, and WAF-style controls where required.
• Established CI/CD guardrails to lint and test Kong configuration, validate plugin compatibility, and automate progressive rollouts with safe rollback strategies.
• Built end-to-end observability by exporting metrics to Prometheus, standardizing structured logs, and enabling distributed tracing to shorten latency and error investigations.
• Migrated legacy gateways and NGINX-based routing into Kong, rationalizing routes and policies while minimizing breaking changes for client applications.
• Implemented traffic management patterns such as canary releases, header-based routing, request/response transformations, and circuit-breaking behaviors to support safer microservice releases.
• Designed high-availability patterns (multi-zone scheduling, autoscaling, health probes, graceful draining) and documented upgrade/rollback steps to reduce change risk.
• Optimized performance and cost by tuning worker/concurrency settings, connection pooling, caching behavior, and plugin usage based on real request profiles and SLOs.

This experience helped us accumulate significant knowledge across multiple Kong use-cases—from platform standardization and security to observability and production operations—and enables us to deliver high-quality Kong setups that are maintainable, scalable, and aligned with how teams ship and run microservices.

Some of the things we can help you do with Kong include:

• Assess your current Kong Gateway/service mesh posture and deliver a prioritized report covering security, reliability, and operability gaps.
• Define an adoption roadmap for consistent API governance across teams, environments, and Kubernetes/hybrid deployments.
• Design and implement Kong Gateway architecture (services, routes, plugins, consumers) aligned to platform standards and SDLC workflows.
• Harden ingress and service-to-service traffic with authN/authZ, mTLS, rate limiting, request validation, and policy guardrails for compliance.
• Automate configuration and releases using Infrastructure as Code, GitOps, and CI/CD so changes are repeatable, reviewable, and auditable.
• Implement observability for API traffic with metrics, logs, tracing, dashboards, and SLOs to improve detection and reduce MTTR.
• Optimize performance and cost with caching strategies, timeout/connection tuning, autoscaling patterns, and capacity planning.
• Troubleshoot production issues (latency, 5xx spikes, plugin conflicts, upstream instability) and codify fixes into operational runbooks.
• Operationalize upgrades and change management with safe rollout patterns, reliability reviews, and incident response playbooks.
• Enable teams through hands-on training and reference patterns for secure API publishing, versioning, and lifecycle management.

For related delivery patterns, see our platform engineering services.