IBM Feature Trails

Feature trailActive

AI Agent Orchestration Platform

The AI Agent Orchestration Platform continues to evolve with a focus on practical implementation and integration. Recent developments include exposing MCP tools via ContextForge MCP Gateway for centralized management and security, enabling AgentOps with Langfuse and IBM Telemetry for production-grade observability, and building AI agents using Langflow with Granite 4.0 models. The platform also emphasizes agentic workflows, with tutorials on CrewAI integration and reimaging financial decision-making. OpenRAG on watsonx.data is now available as a managed RAG service built on the OpenRAG open-source project, integrating Docling for document processing, OpenSearch for retrieval, and Langflow for agent orchestration. It offers advanced RAG capabilities beyond traditional methods, including adaptive retrieval, hybrid search, structure-aware content processing, reduced integration effort, and an enterprise foundation with robust security and governance.

3 posts · 2020–2026

Timeline

20202026

Feature trailActive

Data Prep Kit for LLM Workloads

The Data Prep Kit (DPK) is an open-source toolkit with 20+ modules for pre-processing data for code and language. It supports ingestion, document annotation, filtering, and redaction of private information, enabling developers to build end-to-end data pipelines from ingestion to tokenization. DPK modules can scale from laptop to datacenter and integrate with frameworks like Ray and Spark, offering APIs for Python, Ray, Spark, and Kubeflow Pipelines. It has been used to produce pre-training data. This post highlights the integration of DPK with watsonx.data for unstructured data processing and the creation of scalable, repeatable, and maintainable data pipelines.

5 posts · 2020–2026

Timeline

20202026

Feature trailActive

Secure LLM Inference Access Control

secure-llm-inference-access-control: Introduces adapter-based access control for LLM inference, enabling fine-grained, per-query authorization by attaching lightweight, domain-specific model extensions (adapters) to a single shared base model. This approach addresses the challenge of preventing LLMs from leaking confidential information by enforcing access policies at inference time, rather than relying on post-hoc filtering or costly private silos. The secure-inference project integrates with the llm-d framework, utilizing LoRA adapters for each domain with policy-enforced routing. This post details the training and inference phases, including user authentication via JWT/SSO, authorization via Open Policy Agent, semantic matching for adapter selection, and routing to inference pools with appropriate adapters loaded. It provides an example of per-role inference routing for a software engineer.

1 post · 2026

Timeline

Feature trailActive

AI-Assisted Vulnerability Discovery and Response

AI is accelerating vulnerability discovery and exploitation, compressing the window between a defect's existence and its operationalization. This necessitates faster response times and proactive security measures. The post highlights the increasing effectiveness of AI in identifying and assessing vulnerabilities, leading to a shrinking response gap for CVEs. It also emphasizes the importance of maintaining dependency inventories, identifying unsupported frameworks, and considering extended support.

1 post · 2026

Timeline

Feature trailActive

Terraform Modules for IBM Cloud Infrastructure

The terraform-ibm-modules project provides production-tested, IBM-supported Terraform modules for building and managing IBM Cloud infrastructure. These modules encapsulate best practices for service configuration, security, compliance, and scalability, enabling faster and more reliable infrastructure deployments. The project integrates with AI assistants via the Model Context Protocol (MCP) server to facilitate AI-assisted infrastructure composition. The latest iteration emphasizes AI-ready building blocks and the integration of financial services compliance controls via `fscloud` submodules.

1 post · 2026

Timeline

Feature trailActive

Cassandra for AI Data Storage

Cassandra is evolving to meet the demands of AI-driven applications, offering native vector types for Approximate Nearest Neighbor (ANN) searches, ACID transactions for reliable data updates, and an improved Unified Compaction Strategy (UCS) for enhanced performance and resource efficiency. These advancements position Cassandra as a robust solution for large-scale AI data storage and retrieval.

1 post · 2026

Timeline

Feature trailActive

ContextForge MCP Gateway

ContextForge MCP Gateway provides a secure, governed bridge between AI agents and enterprise systems, simplifying MCP server management. It offers centralized management of MCP servers, integration with identity infrastructure, automatic REST API updates, over 30 safety guardrails, and observability dashboards. The 1.0.0 Beta release introduces multi-tenant workspaces, 35+ security plugins, protocol translation, built-in observability, a high-performance architecture, and flexible deployment options.

2 posts · 2025

Timeline

20252026

Feature trailCooling

IBM MQ Debugging and Observability

IBM MQ debugging and observability capabilities are enhanced through integration with OpenTelemetry (OTel) for tracing, providing developers with better visibility into message flow. This complements existing console-based debugging and performance tooling, offering a more comprehensive approach to troubleshooting messaging applications. The integration extends to various platforms including z/OS, Appliances, and containerized environments, with a focus on shift-left observability from the IDE.

5 posts · 2020–2025

Timeline

20202026

Feature trailCooling

SysML V2 Modeling Language

SysML V2 is a new, ground-up redesign of the Systems Modeling Language, offering a more precise, expressive, and flexible textual and graphical notation for designing complex systems. It enhances interoperability, automation, and integration with tools (including AI), and provides improved capabilities for modeling system structure, data, behavior, and requirements. It aims to streamline systems engineering processes, boost coordination across domains, and enable real-time consistency.

1 post · 2025

Timeline

20252026

Feature trailCooling

IBM Granite Models

IBM Granite models are IBM's family of open, performant, and trusted LLMs. This release includes Granite 3.0 language models for agentic workflows, RAG, text summarization, analytics, classification, and content generation. Granite for code models are trained on 116 programming languages for code-related tasks. Granite for time series models are for multivariate time-series forecasting. Granite Guardian models provide input-output guardrail capabilities. Models are available on Hugging Face, Ollama, and Replicate. The IBM Granite Community provides cookbooks and notebooks for data preparation, fine-tuning, RAG, tool use, and agentic workflows. The Granite Playground offers an interactive environment. A workshop guides users through common use cases. Integration with watsonx.ai Prompt Lab and watsonx Developer Hub is available.

3 posts · 2022–2025

Timeline

20222026

Feature trailCooling

Multimodal Reasoning and Vision Models

This post introduces the Granite 3.2 models, which include new reasoning capabilities for language models and the first vision model. These models enable developers to build applications that can process and reason over multiple data types, such as text and images. Examples include turning PDFs into FAQs using multimodal RAG, debugging code from screenshots, building personal stylists, creating AI research agents for image analysis, and managing budgets from images of spending history. The post also points to tutorials and a cookbook for further exploration.

1 post · 2025

Timeline

20252026

Feature trailCooling

Envizi Supply Chain Intelligence and Catena-X Integration

IBM Envizi Suite's Supply Chain Intelligence Scope 3.1 module and Product Carbon Footprint (PCF) 3.1 module have achieved full certification within the Catena-X ecosystem. This integration enables seamless data exchange and compliance with Catena-X principles, including data sovereignty and interoperability, for automotive manufacturers. The solution provides capabilities for tracking product carbon footprints, optimizing supply chains, and enhancing data-driven decision-making through advanced analytics, artificial intelligence, and IoT technologies. Key data types mapped include compliance, product, and organizational data.

1 post · 2024

Timeline

20242026

Feature trailCooling

Live Kernel Updates with IPsec Tunnels

Live kernel updates for IBM AIX now support active IPsec tunnels through the `ipsec_auto_migrate` option, automating the disabling and re-enabling of the IPsec subsystem during updates to maintain data-in-flight protection. This feature is available for AIX 7.3 TL3 and later versions, supporting IKEv2, but introduces a brief window where traffic may be unencrypted and does not preserve tunnel states.

1 post · 2024

Timeline

20242026

Feature trailCooling

IBM Cloud Deployable Architecture Builder VS Code Extension

The IBM Cloud Deployable Architecture Builder extension for VS Code allows developers to manage projects, create and manage private catalogs, validate and deploy Deployable Architecture (DA) products using modifiable templates, and set DA inputs and outputs directly within the VS Code environment. This streamlines the DA workflow from product creation to deployment.

1 post · 2024

Timeline

20242026

Feature trailCooling

Kubernetes Node Resource Management

This post details troubleshooting and resolving Kubernetes node resource issues, specifically high memory usage. It outlines steps to identify resource-hungry pods using `kubectl top nodes` and `kubectl describe node`, and provides methods to adjust pod resource configurations (`limits`, `requests`) and assign pods to appropriate node groups using `nodeSelector`. It also covers the cleanup of related Kubernetes resources.

2 posts · 2019–2024

Timeline

20192026

Feature trailQuiet since 2024

Unified Data Management with watsonx.data and Cloudera

This post details the integration of IBM watsonx.data with Cloudera, focusing on unified data management, analytics, and AI-driven innovation. It highlights how the combined platforms enable seamless data access across hybrid and multicloud environments, support unified analytics and AI workloads, ensure interoperability with open data formats, enhance data governance through integration with Apache Atlas, optimize performance for diverse workloads, and leverage low-cost object storage. Use cases for telecom and financial services are presented, emphasizing cost optimization, revenue growth, fraud detection, and risk simulation. The architecture emphasizes a unified metadata repository and the use of open data formats like Apache Iceberg.

1 post · 2024

Timeline

20242026

Feature trailQuiet since 2024

Automated Guardium Collector Deployment

IBM Security Guardium collectors can now be deployed and configured automatically using Ansible, improving operational efficiency, ensuring consistent configurations, and enabling rapid scaling of Guardium deployments for enhanced data protection.

1 post · 2024

Timeline

20242026

Feature trailQuiet since 2024

IBM Granite.Code AI Coding Companion

IBM Granite.Code is an AI coding companion integrated with VS Code, powered by the Granite LLM for code. It offers features like code generation, explanation, documentation, translation, and unit test generation. It supports numerous programming languages and offers a self-hosting option via Ollama. Recent enhancements include improved context window size (128K) and training on 116 languages, with specific support for Go, C, C++, Python, Java, JavaScript, and TypeScript. The tool provides real-time code assistance with its integrated chat interface and intelligent code completions in the code editor.

1 post · 2024

Timeline

20242026

Feature trailQuiet since 2024

IBM Wazi as a Service for z/OS Development

IBM Wazi as a Service provides on-demand access to z/OS virtual server instances in the IBM Cloud for development and testing. It integrates with the Wazi family of editors and DevOps tools, offering a cloud-native development experience. Users can spin up pre-configured z/OS development systems, customize them using Ansible playbooks for tasks like code compilation and debugging, and build custom Wazi images with the Wazi Image Builder. The service aims to streamline z/OS development workflows.

1 post · 2024

Timeline

20242026

Feature trailQuiet since 2024

Semantic Search and Generative AI Integration

watsonx.ai is an IBM cloud-based generative AI platform that uses NLP and machine learning to analyze and understand text-based data, such as contracts. In the context of contract analysis, you can use watsonx.ai to automate the process of extracting and classifying various types of clauses, comparing them with guidance, and generating recommendations for alignment. This includes redlining contracts and suggesting rewording or reorganization. The platform leverages semantic analysis for a more elaborate view of the clauses, going beyond traditional AI or contract template-based processing.

1 post · 2023–2024

Timeline

20232026

Feature trailQuiet since 2024

Spark Performance Optimization

This post details how to use the Spark `explain` API and Spark UI to analyze and debug Spark SQL query execution plans. It covers understanding physical plans, logical plans, and the impact of configurations like `spark.sql.codegen.wholeStage`. The post also explains how to interpret the output of `explain` and `explain(true)` and how to use the Spark UI's SQL tab for visualization and debugging of completed jobs. This complements existing content on Spark performance optimization by providing specific guidance on reducing network I/O, disk I/O, optimizing CPU utilization, and leveraging in-memory computation. It also covers file formats, parallelism, reducing shuffle, filtering data, caching, join optimization, tuning cluster resources, avoiding expensive operations, handling data skew, and using UDFs effectively.

3 posts · 2018–2024

Timeline

20182026

Feature trailQuiet since 2024

IBM Cloud Projects Resource Management

IBM Cloud Projects offers features for managing infrastructure, providing insights into account billing, security, and compliance. It integrates with tools like Event Streams for reliability engineering alerts and helps identify and remove unused resources. The system allows users to bring existing resources into a project by providing credentials (API key or Trusted Profile) from the relevant account, selecting resources to tag, and applying changes. This streamlines account management and cleanup processes.

1 post · 2024

Timeline

20242026

Feature trailQuiet since 2024

Local Container and Kubernetes Development Environment

This post details the customization of Rancher Desktop for IBM Edge Application Manager (IEAM) edge agent installation on macOS. It outlines specific configuration changes to the `override.yaml` file and Volume settings within Rancher Desktop to ensure successful deployment of the IEAM agent, which runs as a Docker container on macOS. This builds upon the general availability of Rancher Desktop as an open-source alternative to Docker Desktop for local container and Kubernetes development on Mac.

1 post · 2024

Timeline

20242026

Feature trailQuiet since 2024

Local Container and Kubernetes Development Environment

This post details the installation of Red Hat OpenShift 4 on a laptop using Red Hat CodeReady Containers (CRC), an open-source alternative to Minishift and Minikube. It covers prerequisites, hardware requirements, installation steps, configuration options (memory, pull secret), starting and stopping the cluster, accessing the cluster via CLI and web console, and notes on certificate expiration. It also mentions a sample project, Cloud Native Starter, for testing deployments on CRC.

2 posts · 2020–2024

Timeline

20202026

Feature trailQuiet since 2023

IBM Business Automation Manager Open Edition Migration

IBM Business Automation Manager Open Edition (IBM BAMOE) v9 is a cloud-native business automation solution integrating BPMN and DMN with open-source tools for hybrid clouds. It offers enhanced collaboration via wider Git repository support, rapid coding with Quarkus and Kogito for hot-reloading and auto-generated APIs, cost-efficient serverless decisions, seamless event-driven capabilities with Kafka integration, and cloud-centric design with Red Hat OpenShift support. The process engine supports straight-through process scenarios and integration with external services within decision flows.

1 post · 2023

Timeline

20232026

Feature trailQuiet since 2023

Kubeflow Pipelines Tekton Backend Optimizations

Kubeflow Pipelines V2.0 introduces a platform-neutral Intermediate Representation (IR) for ML workflows, improving portability and metadata richness. Optimizations for the Tekton backend include a dedicated custom task controller to reduce latency and throughput for drivers and publishers, and integration of driver and task construction logic into a single reconciliation cycle to decrease the number of queued tasks. The `finally` clause in Tekton Pipelines allows for guaranteed execution of tasks. This post details adding Python support to Tekton Pipelines, enabling OpenWhisk Python Actions to run on Knative by creating a CI/CD pipeline that packages Python applications and their dependencies into Docker images.

3 posts · 2020–2023

Timeline

20202026

Feature trailQuiet since 2023

SFTP Integration for Containerized Applications

This post introduces a method to enable SFTP integration for containerized applications, allowing legacy applications that rely on SFTP to be migrated to cloud-native environments like Kubernetes. It explores three solutions for managing SSH private keys: external vaults (AWS Secrets Manager), Kubernetes Secrets, and packaging keys within the container image, recommending the external vault approach for better security and key rotation management. The solution is demonstrated using Amazon EKS and Red Hat OpenShift on AWS (ROSA).

1 post · 2023

Timeline

20232026

Feature trailQuiet since 2023

COBOL Unit Testing Framework

COBOL Check is a unit testing framework for COBOL that enables testing of individual code sections. It supports test-driven development (TDD) and test-driven learning (TDL), allowing developers to refactor code, create test scenarios, and learn through testing. The framework can be integrated into CI/CD pipelines using tools like Bitbucket and Jenkins for automated testing and quality gates. It is available for z/OS systems and can be downloaded from its GitHub repository.

1 post · 2023

Timeline

20232026

Feature trailQuiet since 2022

Java Application Modernization

IBM Z and Cloud Modernization Stack on AWS enables mainframe application modernization by providing capabilities for API creation (z/OS Connect), cloud-native development for z/OS applications (Python, Node.JS, GoLang, COBOL, PL1, Java, Assembler with IDEs, AWS CodeCommit, CodeBuild, Wazi sandbox, Wazi Analyze), and enterprise automation across z/OS and AWS (Ansible cookbooks, GitOps, IaC on Red Hat OpenShift Cloud Platform on AWS). It aims to accelerate modernization, enable new business models, and integrate mainframe applications and data with AWS services.

2 posts · 2022

Timeline

20222026

Feature trailQuiet since 2022

Serverless Computing Challenges and Optimizations

Serverless computing, as realized in the case of Kubernetes by Knative, is the natural evolution of cloud computing. Knative automates resource scaling to match demand, reducing waste and energy consumption. Further energy savings can be achieved by suspending worker nodes when data center capacity is high enough to meet demand.

2 posts · 2022

Timeline

20222026

Feature trailQuiet since 2022

AI Inferencing on IBM Power10 with MMA

This post introduces the capability of running AI inferencing on IBM Power10 systems leveraging the new Matrix Math Accelerator (MMA) units. It details the developer setup using Anaconda and Conda packages from the RocketCE channel, and outlines a container-based demo framework for showcasing performance gains. Six real-world scenarios are presented, demonstrating up to 3x performance improvements with MMA for various AI workloads like image detection, action recognition, and fraud detection.

1 post · 2022

Timeline

20222026

Feature trailQuiet since 2022

Monorepo Build System Migration

This post details the migration of a Python monorepo from Bazel to Pants, focusing on improving CI times, developer experience, and reducing build metadata. The migration was phased, starting with formatters and linters, then tests, then binary rules, and finally Docker images. Key technical achievements include dependency inference, changed file detection, and the reduction of Bazel metadata from 19,000 lines to 2,400 lines of Pants metadata, resulting in CI times dropping from 10-12 minutes to under 4 minutes.

1 post · 2022

Timeline

20222026

Feature trailQuiet since 2022

IBM z16 Hardware Architecture and AI Acceleration

The IBM z16 mainframe system features the new IBM Telum processor with integrated AI acceleration, supporting up to 40TB of memory and 200 processors. It includes a Crypto Express8S adapter for quantum-safe cryptography and can fit in a 19" rack space.

2 posts · 2019–2022

Timeline

20192026

Feature trailQuiet since 2022

AI Data Minimization Toolkit

The AI Privacy toolkit provides a method to reduce the amount of personal data needed for machine learning model predictions by removing or generalizing input features without significantly impacting accuracy. This helps adhere to data minimization regulations like GDPR and reduces security risks associated with large datasets. The toolkit can determine the minimal set of features and their required detail level for a given trained model. It has been applied to classification models and research.

1 post · 2022

Timeline

20222026

Feature trailQuiet since 2021

GitOps for Cloud Infrastructure Management

This post introduces GitOps as an operational model for managing cloud infrastructure and applications. It outlines the core principles of GitOps, including declarative system definitions in Git, automated pull-based deployments, and continuous reconciliation. The post discusses how GitOps can be applied to various resources beyond containers, such as VMs and network devices, and addresses challenges like handling destructive changes and managing multiple environments. It also proposes a reference architecture for IBM Cloud, separating CaaS and IaaS layers and recommending tools like Argo CD and IBM Cloud Schematics for implementation.

1 post · 2021

Timeline

20212026

Feature trailQuiet since 2021

Model Serving on Kubernetes

ModelMesh, a model serving management layer for Watson products, is being contributed to the open-source community as ModelMesh Serving. It is designed for high-scale, high-density, and frequently changing model use cases, intelligently loading and unloading AI models to balance responsiveness and computational footprint. ModelMesh integrates with KServe, becoming the backend for Multi-Model Serving. It features distributed LRU cache management, intelligent placement and loading of models, resilient retries and rerouting, and seamless rolling updates. It supports hundreds of thousands of models in a single production deployment.

1 post · 2021

Timeline

20212026

Feature trailQuiet since 2021

Application Hierarchy of Needs for SREs and IT Operators

This post introduces the Application Hierarchy of Needs, a framework for SREs and IT Operators to measure and manage application health. It categorizes needs into Availability, Correctness, Responsiveness, and User Experience, and discusses how to measure these using KPIs, OKRs, SLOs, SLIs, and metrics like NPS and adoption funnels. It also introduces the Failed Customer Interaction (FCI) metric for business impact and discusses SRE/ITOps measurements like MTTR. The post highlights the integration of IBM Observability by Instana APM and IBM Cloud Pak for AIOps to address these needs.

1 post · 2021

Timeline

20212026

Feature trailQuiet since 2020

Node.js Rejection Handling and N-API Enhancements

Node.js 15 introduced significant changes to unhandled promise rejection handling, defaulting to process termination for better debugging. It also included npm 7 with default peer dependency installation, N-API Version 7 with new array buffer manipulation methods, and refinements to experimental Async Local Storage APIs. Node.js 14.x became the next LTS version, featuring stable Diagnostic Reports and full ICU data.

2 posts · 2019–2020

Timeline

20192026

Feature trailQuiet since 2020

IBM MQ on Raspberry Pi

IBM MQ is now available as a developer edition for Raspberry Pi OS, enabling developers to run and test MQ applications on small, credit-card sized computers. This expands the platform support for MQ, making it accessible for DIY projects and educational purposes. The offering includes features like multi-instance queue managers and clustering, with TLS authentication available on Raspberry Pi 3 and up. Installation instructions and configuration for the MQ Console are provided.

1 post · 2020

Timeline

20202026

Feature trailQuiet since 2020

Certificate Transparency Implementation

Certificate Transparency (CT) is a security mechanism that logs issued certificates to detect mis-issued or compromised certificates. Modern browsers enforce CT, and mobile developers can implement client-side checks using libraries or platform defaults. Server-side, ensuring certificates have valid Server Certificate Timestamps (SCTs) is crucial. Third-party tools can monitor CT logs, or individual applications can perform client-side validation.

1 post · 2020

Timeline

20202026

Feature trailQuiet since 2020

OpenAPI Specification Generation from Code Comments

The OpenAPI Comment Parser provides a tool to generate OpenAPI specifications from code comments, simplifying API documentation and ensuring it stays up-to-date with code changes. This reduces manual effort and allows developers to use the generated documentation for API testing. The tool is built for Node.js but can work with any language using a similar comment style.

1 post · 2020

Timeline

20202026

Feature trailQuiet since 2020

Log Template Mining for Network Outage Detection

The Drain3 log-template mining project, an open-source streaming log template miner, has been refactored for Python 3 and enhanced for production use. It now includes improved streaming support, resiliency through Kafka-based state persistence, and masking for improved accuracy. The project is available as a PyPI package and on GitHub. Log templates can be used for analytics, detecting anomalies in message frequencies and parameter values to identify network outages and other issues.

1 post · 2020

Timeline

20202026

Feature trailQuiet since 2020

AI-Assisted Image Labeling

The Cloud Annotations project introduces an AI-assisted autolabeling feature. This capability leverages a user-trained model to automatically label new images, significantly reducing manual effort in data preparation for object detection models. The process involves users labeling a subset of images, training a model, and then using the 'Auto label' button in the GUI to apply labels to the remaining dataset, followed by a review step. The tool is integrated with IBM Cloud Object Storage for data management.

1 post · 2020

Timeline

20202026

Feature trailQuiet since 2019

Helm Kubernetes Package Management

Helm 3 represents a significant architectural shift from Helm 2, moving to a client-only model by removing the Tiller component. This enhances security by delegating access control to Kubernetes user permissions and simplifies deployment by eliminating the need for Tiller initialization. Release storage has been updated to use Secrets within the release's namespace, with a new naming convention. Chart dependency management has been consolidated into `Chart.yaml`, and library charts are now supported. Helm 3 also introduces improved release upgrade strategies, simplified CRD support, and updates to the test framework.

1 post · 2019

Timeline

20192026

Feature trailQuiet since 2019

SSH Two-Factor Authentication

SSH access is secured with two-factor authentication, requiring both a public key and a time-based one-time password (TOTP) generated by an authenticator app. This enhances security by adding an extra layer of verification beyond traditional password or key-based authentication, mitigating risks from compromised credentials or brute-force attacks. The implementation involves configuring PAM modules and SSH server settings to prompt for the TOTP during login.

1 post · 2019

Timeline

20192026

Feature trailQuiet since 2019

Kubernetes Container Runtime Interface (CRI)

The Kubernetes Container Runtime Interface (CRI) standardizes the interaction between kubelet and container runtimes, enabling Kubernetes to support multiple runtimes beyond Docker. Compliance with OCI specifications and passing CRI validation tests are key requirements. Popular CRI implementations include containerd and cri-o.

1 post · 2019

Timeline

20192026

Feature trailQuiet since 2019

TLS 1.3 Support in Node.js

This post marks the initial introduction of TLS 1.3 support in Node.js, detailing the technical challenges and benefits of integrating this major protocol update. Future posts will likely cover its broader adoption, performance implications, and best practices for migration.

1 post · 2019

Timeline

20192026

Feature trailQuiet since 2019

YAML Templating Tool (ytt)

ytt is a YAML templating tool that understands YAML structure, using comments for annotation. It supports declarative and imperative operations via Starlark, modularization of configurations, data injection, and data validation. It offers syntactic sugar for conditionals, loops, and functions, and provides an 'overlay' feature for configuration management. ytt aims to simplify configuration and deployment on Kubernetes and other platforms.

2 posts · 2019

Timeline

20192026

Feature trailQuiet since 2019

MQTT Messaging Protocol

MQTT is a publish-subscribe messaging protocol built on TCP/IP, designed for efficient communication between IoT devices. It utilizes brokers to route messages from publishers to subscribers. Initially developed for SCADA systems, it has become a de facto standard for IoT communication. MQTT v3.1.1 became an OASIS standard in 2014 and an ISO standard in 2016. MQTT v5 was published in late 2018, introducing new features while maintaining its core principles of being compact, easy to understand, and easy to implement.

1 post · 2019

Timeline

20192026