This content originally appeared on DEV Community and was authored by Stanislav Deviatov
Articles
A Conceptual Model for Storage Unification
Presents a practical conceptual model for storage unification that treats data virtualization as the core abstraction and enumerates seven design considerations: internal vs shared tiering, bidirectional format fidelity, client- vs server-side stitching, integrated vs external tiering jobs, direct vs API access, lifecycle ownership, and schema evolution. Emphasizes primary-system ownership for safe shared-tiering and maps specific trade-offs for Kafka, Iceberg/lakehouse and HTAP integrations.
Add Remote MCP Server with OAuth to Your Existing API
Practical, MCP-focused walkthrough: converts a Zuplo-hosted API into an OAuth-protected remote MCP server by adding an /mcp handler, enabling oAuthResourceMetadata for discovery, installing the OAuth Protected Resource plugin to populate .well-known metadata, configuring dynamic client registration, and validating with the MCP Inspector; includes production hardening guidance (rate limits, prompt-injection and secret-masking policies).
Building Aira, Postman’s Product Research Agent
Postman presents Aira, a production research agent that transforms issue tracker data into a Neo4j knowledge graph, upgrades from large-context LLMs to a reasoning-class model (o3) for iterative, cross-issue queries, and exposes reusable Flow modules (Slack auth, ack, response) so teams can embed structured, cited product insights into existing workflows; practical lessons on scaling retrieval, citation, and componentization are included.
Designing API Error Messages for AI Agents
Presents concrete patterns for making API errors machine-actionable for AI agents: use RFC 7807-style problem payloads augmented with explicit recovery instructions, HATEOAS links for remediation/status checks, semantic fields (trace_id, parameters, suggestions) and stable internal error codes. These patterns reduce agent hallucination, enable deterministic retry/escalation logic, and provide a clear path to integrate agentic consumers into enterprise APIs.
Examines the urgent problem of publicly exposed enterprise MCP servers (researchers found ~1,800) and gives architects actionable options: keep MCPs network-isolated where possible, implement OAuth following the MCP spec (noting current tooling gaps), or integrate SSO/SAML via identity providers; discusses gateway centralization trade-offs and recommends prototyping SAML on high-value servers to inform longer-term architecture decisions.
Goodbye Apiary.io, You’ll Be Missed
Apiary.io is being shut down; the article couples this industry event with a pragmatic migration workflow: a referenced apiblueprint2openapi repo, recommended generated/apispecconverter.31.yaml, and concrete openapi-format commands plus config to normalize operationIds and upgrade to OpenAPI 3.1—actionable guidance for teams migrating legacy API Blueprint docs to modern OpenAPI-driven portals.
How SPS Commerce built their internal developer portal
SPS Commerce describes how it built an enterprise internal developer portal using Port with IaC (Pulumi), Azure Pipelines, Docker, and a tooling-agnostic data model to unify repos, vulnerabilities, APIs and feature flags. Key takeaways: codify portal configs for repeatable releases, use generic scalable models to support acquisitions, scaffold self-service actions to drive adoption, and expose structured SDLC data (including for AI agents) to enable real-time migration and governance visibility.
How to Update API Deployments to Enable AI Agent Access
Explains how to prepare enterprise API deployments for AI agents by combining MCP/A2A protocols with OAuth 2.1: create dedicated MCP entry points at the gateway, issue opaque access tokens (translate to JWTs via phantom tokens), enforce audience/scopes, use token exchange for upstream calls, and emit dynamic claims for fine-grained resource authorization—practical patterns and a reference deployment to implement them.
JSON Streaming in OpenAPI v3.2.0
Explains OpenAPI v3.2 additions (itemSchema and itemEncoding) to model per-item schemas for JSON streams and event streams. Shows concrete patterns: content-types for JSONL/NDJSON and json-seq, YAML examples using itemSchema, SSE modeling with oneOf/contentSchema, and a Node/Express producer example—practical guidance for documenting and implementing streaming APIs in enterprise systems.
MCP and OAuth 2.0: A Match Made in Heaven
Demonstrates how MCP leverages OAuth 2.0 RFCs (RFC9728, 8414, 7591, 8707) to enable dynamic AS discovery, on-the-fly client registration, and resource-scoped tokens for transient LLM clients. Includes sequence flows, HTTP examples and an Auth0+MCP sample repo, providing actionable guidance to implement least-privilege, discoverable OAuth flows for LLM-driven integrations.
Orchestrating Complex Workflows With XState
Shows how to run XState as the orchestration layer for backend workflows with two production patterns—per-request interpreters in AWS Lambda and long-lived interpreters in ECS—providing code samples, state hydration/persistence advice, and JMeter benchmarks (latency, throughput, cost) that demonstrate ECS yields lower transition latency and higher throughput at higher idle cost while Lambda favors low-cost, single-shot use-cases.
Protecting MCP Servers from Prompt Injection Attacks
Provides a concrete, implementable pattern for preventing prompt injection via MCP servers: a Zuplo outbound policy with policy JSON and route wiring, local testing with Ollama, model recommendations, and strict/permissive operational modes—enabling architects to block or quarantine malicious outbound content before it reaches downstream LLMs and to tune detection for enterprise AI pipelines.
Tips To Monitor MCP Ecosystems
Provides an enterprise-focused monitoring framework for MCP/agent ecosystems: defines concrete metrics (context length/reuse, mutation rates, intent-to-action traces, token-economy ratios), highlights real incidents (Anthropic CVE, Asana exposure, Backslash scans) to justify higher observability, and outlines implementation patterns (instrumentation middleware, AI gateways, infra telemetry) to detect misuse, drift, and security lapses before production impact.
When Your App Talks Back: Securing Mobile App Backend Communication
Synthesizes mobile-specific protections for backend communication—certificate pinning, mTLS, application-layer encryption, RASP, and attestation—highlighting their limits and how to layer them. Recommends keeping secrets server-side or retrieving them dynamically, using attestation for strong device/app integrity and tying tokens to requests, and combining client and server controls (rate limits, anomaly detection) to mitigate tampering and bot farms.
Why Enterprise AI Integration Strategies Fail (And What Actually Works)
Presents a practical enterprise playbook: compares point-to-point, platform, and standardized-protocol (MCP) approaches with TCO estimates, documents costly production failures from missing test environments, and introduces the CSM governance stack (Enterprise/Project/Code/UX) as the control plane for auditability, risk management, and rapid, scalable AI integration.
Why Federated API Management Is Essential for Hybrid Cloud
Presents federated API management as the operational model for hybrid cloud: local gateways enforce runtime policies and observability while a central governance/control plane distributes policies, catalog metadata, and RBAC. The article focuses on how to reconcile autonomy and compliance—covering service discovery, policy propagation, identity federation, and aggregated telemetry—to reduce cross-cloud sprawl and maintain enterprise-grade API governance.
Why Internal Developer Platforms Need APIs
Expert interview: make IDPs API-first and keep consoles ‘dumb’ — expose controllers/APIs as the single source of truth so multiple clients (UIs, IDEs, agents) can consume consistent behavior; reframe MCP servers as intent-oriented tools (e.g., deploy_application) instead of one-to-one API reflections to enable reliable agent automation and centralized policy enforcement.
Apache Camel
Consolidated overview of Apache Camel 4 up to the 4.14 LTS: details unified telemetry (camel-telemetry/opentelemetry2), an opinionated observability service, a common management port (9876), extensive AI/langchain and vector DB components (Milvus/Pinecone/Qdrant/Weaviate), enhanced Camel JBang CLI migration/debug tooling and route/group management APIs—practical summary for architects planning upgrades or adoption.
Simplify local prototyping with Camel JBang infrastructure
Shows how to use camel jbang infra to launch Testcontainers-backed Artemis locally, configure an AMQP JMS connection factory and Camel YAML routes (HTTP
AMQPXJ), and validate end-to-end via Artemis UI and camel cmd; enables fast, realistic prototyping of integration flows and legacy-to-JSON facades without full infra setup.
The 5 Apache Camel Anti-Patterns That Silently Kill Integration Projects
Practical guide that maps five common Apache Camel anti-patterns to explicit fixes: break monolithic routes into direct/seda subroutes, extract business logic into testable beans, enable streamCaching and use .streaming() to avoid OOMs, configure deadLetterChannel and targeted onException redelivery policies, and convert payloads to DTOs to avoid header-based state. Useful, code-backed checklist for architects reducing technical debt in Camel-based integrations.
Apache Kafka
Building a Modern Real-Time Data Streaming Architecture: Two Paths from Kafka to Snowflake
Presents a practical comparison of S3-staging ETL versus Snowflake’s native Kafka connector for real-time Kafka→Snowflake pipelines, focusing on trade-offs (latency, operational complexity, schema handling) and a binary-payload case study that shows when the native connector can simplify architecture and eliminate staging layers.
Iceberg Topics for Apache Kafka®: Zero ETL, Zero Copy
Presents Iceberg Topics: an Apache-2.0 RSM plugin that makes a Kafka topic appear as an Apache Iceberg table by materializing Parquet at segment roll and using manifest-driven fetch to reconstruct batches. The approach is per-topic opt-in, preserves hot-path latency (local segments), eliminates duplicate PUTs and connector sprawl, and provides one durable copy for both replay and SQL analytics with practical operational guidance and repo/whitepaper links.
Kafka to Iceberg – Exploring the Options
Compares Flink SQL, Kafka Connect, and Confluent Tableflow for Kafka→Iceberg pipelines, focusing on schema management and evolution, exactly-once delivery, fan-in/fan-out patterns, upsert/overwrite semantics, processing requirements (stateful vs stateless), and long-term Iceberg housekeeping. Includes concrete DDL/config examples and highlights where managed Tableflow reduces operational burden versus self-managed Flink/Connect, giving architects actionable criteria for selection.
Migrating Apache Kafka Clusters from ZooKeeper to KRaft
Instaclustr presents a step-by-step, automated migration workflow for moving production Kafka clusters from ZooKeeper to KRaft: initial ZooKeeper backups, deploy KRaft controller quorum (co-located or new nodes), phased rack-by-rack broker migration with health checks and two restart phases, final controller reconfiguration, and decommissioning of ZooKeeper. Emphasis is on safety (pre/post backups), minimized human error, and maintaining availability during migration—practical operational controls for enterprise-managed Kafka transitions.
Multi-Region Kafka using Synchronous Replication for Disaster Recovery with Zero Data Loss (RPO=0)
Presents a practical RPO=0 architecture for Kafka applications: WarpStream’s BYOC model performs quorum writes to multi-region object stores plus replicated metadata (DynamoDB Global Tables/Spanner) and only acknowledges writes after both data and metadata are durably replicated, enabling automated cross-region failover; trade-offs include higher write latency, throughput impact, and increased cost.
Replacing KRaft controller nodes
Practical postmortem of replacing a KRaft controller node in production: backup meta.properties, provision replacement with same node/cluster IDs (cp-ansible), verify via kafka-metadata-quorum/kafka-metadata-shell and monitor raft fetch metrics. Diagnosed metadata snapshot fetch timeouts (logs shown) and remediated by raising controller.quorum.request.timeout.ms and controller.quorum.fetch.timeout.ms; proposes enabling metadata compression and references Kafka/Confluent version constraints and JIRA KAFKA-19541.
Test a Kafka Processor with Gatling
Presents a reproducible pattern for end-to-end performance testing of Kafka processors using Gatling and a community Kafka plugin: it composes request keys, sends messages via a Gatling simulation, listens for reply_ messages, uses a custom QueueMessage serde and a check that asserts isProcessed=true, and produces Gatling reports for throughput and latency—useful for integrating streaming load tests into CI pipelines._
The hidden pitfalls of Kafka tiered storage
Examines two non-obvious Kafka tiered-storage pitfalls—per-fetch sequential remote reads that multiply round trips and remote reads that can exceed fetch.max.bytes—shows concrete logs and config interactions (fetch.max.bytes, max.partition.fetch.bytes, remote.log.reader.threads, remote.fetch.max.wait.ms), and explains the Kafka 4.2.0 fixes plus interim tuning to avoid latency, OOMs, and throughput degradation in production.
Azure
Hybrid Logic Apps deployment on Rancher K3s Kubernetes cluster
Provides a hands-on deployment pattern for running Azure Logic Apps Standard on lightweight K3s (k3d) clusters: covers Docker Desktop/WSL2 setup, k3d cluster creation, Azure Arc connection, Container Apps extension, and configuring runtime storage with on‑prem SQL and SMB. Useful for architects needing a low-overhead hybrid runtime for Logic Apps at the edge.
New in Azure API Management: MCP in v2 SKUs + external MCP-compliant server support
Azure API Management now supports MCP in v2 SKUs (public preview) and can act as a governance/control plane for external MCP‑compliant tool servers: secure access via Microsoft Entra ID/OAuth and Credential Manager, policy-based routing and transformations, rate limiting and monitoring with Azure Monitor/Application Insights, and discovery via API Center—allowing enterprises to expose REST APIs as MCP tools or pass through existing runtimes without code rewrites.
Debezium
Outbox Pattern with Spring Boot and Debezium
Presents Spring Outbox, a Spring-native library that implements the transactional outbox pattern with auto-configuration, pre-built Debezium connectors (MySQL/Postgres/Mongo), and RabbitMQ/Kafka integrations. The article shows concrete project setup, domain modeling, and an S2P sample to demonstrate atomic persistence of events and commands, reducing CDC and plumbing overhead for enterprise event-driven systems.
Subatomic & Effortless Change Data Capture with Debezium Extensions for Quarkus
Debezium’s new Quarkus extension embeds the Debezium engine inside Quarkus apps (Postgres connector supported), exposing @Capturing handlers, configurable deserializers, and quarkus.debezium.* settings so services can receive CDC events in-process. The guide includes dev-service setup, offset storage choices, example code, and native build notes (Mandrel/GraalVM). Useful for lightweight/POC or low-footprint CDC deployments—not a drop-in replacement for production Kafka Connect architectures.
MuleSoft
DataWeave Generative Transformation Deep Dive: AI Innovation for Rapid Data Transformation
MuleSoft details a production pipeline that uses LLMs to generate DataWeave scripts from metadata or sample I/O: intent reasoning distills transformation goals, a retrieval-augmented augmentor brings back relevant DataWeave functions/examples, LLMs (including a fine-tuned Mistral‑Nemo 12B with QLoRA) synthesize scripts, and an execution validator plus error-correction loop ensures syntactic validity and behavioral correctness — enabling automated, auditable transformation generation for enterprise integration teams.
From Idea to Production: Building an AI-Powered MCP Server for MuleSoft in 30 Minutes
Practical walkthrough converting a generated MuleSoft project into an MCP server so Claude (through CurieTech AI) can produce RAML specs, manage OAuth2 tokens, and publish APIs to Anypoint Exchange. The post includes endpoint-level cURL calls, project layout, Claude Desktop MCP config, and a Git repo — enabling rapid, reproducible automation of MuleSoft API lifecycle at enterprise scale (note: lacks performance benchmarks and formal security hardening).
From Prompts to Production: Building MuleSoft Apps with MCP Server
Hands-on walkthrough of MuleSoft MCP Server (Model Context Protocol) that turns VS Code into an AI copilot for end-to-end Mule development: scaffolding Maven projects, generating RAML/OAS, publishing to Exchange, and deploying to CloudHub 2.0/Runtime Fabric. Contains concrete config (mcp.json), connected-app scope guidance, CLI commands and examples of saga/circuit-breaker patterns—useful for teams automating enterprise integration pipelines.
How to Build a Real-Time API Status Portal in MuleSoft
Provides a MuleSoft-specific blueprint and open-source implementation for exposing sanitized, real-time API health to external consumers. Uses Anypoint Monitoring APIs (or a sidecar middleware) to aggregate metrics into a time-series store, serves a sanitized status API, and drives a React dashboard with multi-channel notifications—practical code, security guidance, and deployment notes enable enterprise adoption.
Running Anypoint Flex Gateway Serverless on Azure Container Apps
Provides a hands-on deployment recipe for running Anypoint Flex Gateway on Azure Container Apps, including Azure CLI examples, merged YAML/FLEX_CONFIG injection and escaping, readiness-probe configuration, and a workaround for Azure CLI/portal transformation of env var values. Useful for architects operationalizing MuleSoft gateway in Azure serverless environments.
Simplifying MuleSoft Builds with a Parent POM Structure
Provides a MuleSoft‑specific parent POM pattern that centralizes dependencies, plugin configuration (exchange-mule-maven-plugin, mule-maven-plugin, munit-maven-plugin), and environment profiles to enforce consistency across apps. Includes concrete pom snippets, CloudHub deployment settings, MUnit coverage rules, and GitHub examples to quickly adopt in enterprise CI/CD pipelines.
Oracle
#1079 OIC Activity Stream Tracing Levels and OCI Logging
Provides a concrete, platform-specific mapping of OIC activity-stream trace levels to OCI Logging outputs: shows what fields are present at Debug vs Audit vs Production, how to enable and name logs, sort and filter logContent (including examples using integrationFlowIdentifier and opcRequestId), use Logger action to push additional fields, and build OCI Dashboard widgets—practical guidance for debugging, compliance and operational dashboards.
#1081 OCI Log Analytics – Leveraging the new AI feature
Demonstrates OCI Log Analytics’ new ‘LoganAI’ conversational interface for interrogating OIC activity-stream logs without hand-written MQL: the author shows concrete NL queries and saved Log Explorer queries to identify failed flows, duplicate order numbers, validation/shipping states, and average execution time, providing a repeatable observability workflow for Oracle iPaaS teams.
Solace
Event Brokers as Event API Gateways – Bridging the Asynchronous Gap
Presents an enterprise pattern for using event brokers (with Solace Event Portal) as event-API gateways: brokers perform protocol mediation (REST/WebSocket/AMQP/MQTT/JMS) while preserving at-least-once delivery, enforce runtime policies (ACLs, quotas, flow control) at edge gateway brokers in a DMR-based event mesh, and integrate legacy systems (Kafka/IBM MQ) via bridging to expose governed event APIs.
From Spec to Simulation: Solace Event Feeds Bring AsyncAPI to Life
Solace extends AsyncAPI into live, shareable event simulations: community-contributed AsyncAPI-based feeds plus data-generation rules and publishing patterns are runnable via feeds.solace.dev or the stm CLI. The approach provides domain-realistic streams, broker connectivity, and automation hooks for CI/testing, reducing friction in EDA validation and demos.
Solace Schema Registry: Ushering in a New Era of Event-Driven Data Governance
Solace’s GA Schema Registry adds broker-level, centralized schema management and compatibility enforcement to the Solace Event Mesh: supports Avro/JSON Schema (Protobuf planned), deploys HA nodes co-located with brokers with automatic replication across regions, and includes versioning, compatibility checks and SERDES/codelabs—making schema governance and runtime validation first-class for enterprise EDA.
WSO2
Modern Software Delivery: Enabling CI/CD for API Management
Step-by-step WSO2-specific CI/CD pattern: Jenkins orchestrates pipeline runs that restore a persisted vcs_config.yaml and invoke apictl vcs to calculate Git-diffed APIs, deploying only changed artifacts to the gateway. Article includes a runnable Git repo, Jenkinsfile, docker-compose, and guidance for webhook triggers, artifact persistence and selective promotion to deliver auditable, faster API rollouts.
Releases
Apache Camel 4.14 LTS (GA) delivers operational and developer productivity advances: grouped route control and JSON dumps for management, JBang improvements (Spring Boot-attached debugging, route/group commands, test plugin), Groovy shared-source hot-reload, Java 25 preparatory changes, performance/resiliency tweaks, and new components (ISO-8583, LangChain4J agent) enabling LLM-agent integrations and modern enterprise use cases.
Kroxylicious 0.15.0 (GA) fixes a critical bootstrap resilience issue by switching the default bootstrapServers selection to round-robin (configurable to random), spreading client bootstrapping load and mitigating single-point-of-failure scenarios; it also adds a Kubernetes record-encryption quickstart that demonstrates in-cluster encryption-at-rest without external services, providing immediate operational value for enterprise Kafka proxy deployments.
MuleSoft Inference Connector v1.0
Announces MuleSoft Inference Connector v1.0: a unified Anypoint connector that abstracts multiple LLM/ML providers into Mule operations. Includes config and Anypoint Studio flow XML plus Postman examples for agent prompt templates, chat/completions, image generation, vision, moderation and tools-native templates—enabling architects to embed secure, scalable LLM inference into enterprise integration patterns without bespoke HTTP glue.
This content originally appeared on DEV Community and was authored by Stanislav Deviatov