Kubernetes Programming Tutorials & Engineering Articles

How customer needs shaped Oxide's Kubernetes integrations.

iFood rebuilt its in-house security platform on ClickHouse Cloud, getting 9-16x faster queries at 40-50% of the cost and unlocking agentic threat hunts that cut a week of analyst work down to two hours.

Explore ClickStack’s latest upgrades, from richer trace navigation and Prometheus connectivity to smarter dashboards, quieter alerts, faster filtering and support for exponential histogram metrics.

How we rebuilt ClickHouse Cloud's autoscaling orchestration on Kubernetes' controller-runtime and a ClickHouse-powered signals table, adding a reactive fast path that scales services up in seconds instead of waiting for the next scheduled pass.

The 2026-07-28 Model Context Protocol (MCP) specification replaces legacy stateful constraints with a fully stateless core, enabling cloud-native horizontal scaling, serverless deployments, and standard round-robin load balancing. This architectural shift introduces standardized HTTP headers for efficient routing without deep packet inspection, caching controls, and Multi Round-Trip Requests (MRTR) to handle interactive and long-running tasks without blocking connections. Developers can immediately begin migrating their agentic applications to this highly scalable infrastructure using the newly available beta SDKs for Python, TypeScript, Go, and C#.

You can choose any of these hundred database systems and run queries. You can create tables and databases, insert data, drop tables, etc. Every database comes with a preloaded dataset of 100 million records, so you can test example queries. It has not onl

Running a dedicated Kubernetes cluster per team often results in more isolation than an organization requires. While one cluster can be successfully shared…

Treating a Gaggia espresso machine like a distributed system: instrumenting an ESP32 with OpenTelemetry, streaming shots and whole-house sensors into ClickHouse Cloud, and putting ClickStack (plus an LLM agent) on top to turn every pull into a queryable,

Stripe's Knowledge AI Platform is our versatile AI agent platform built to handle diverse non-coding knowledge work, from quick queries to complex, multi-day projects. By connecting employees to over 1,000 internal tools and skills, it enables secure, enterprise-scale productivity across the organization.

Every byte moved has a cost. As model checkpoints grow to hundreds of gigabytes or even a terabyte, that cost adds up quickly. To make things even worse…

This second installment explores how Ray’s higher-level libraries—Serve, Data, and Train—abstract the complexities of running AI workloads on Google's TPU slices. Ray Serve uses a simple topology configuration to correctly gang-schedule large multi-host models, while Ray Data eliminates data-loading bottlenecks by feeding accelerators directly with native JAX batches. Finally, JaxTrainer streamlines distributed training across TPUs by automatically handling cross-slice coordination, checkpointing, and fault tolerance.

Recent improvements to the OpenTelemetry Collector's Datadog receiver let teams reroute telemetry from their existing Datadog agents and SDKs to ClickStack. or any OTel destination making migrations and evaluations simpler than ever.

Ray 2.55 introduces official, first-class support for Google Cloud TPUs, enabling developers to run distributed Python workloads on Google's accelerators using the familiar Ray task-and-actor APIs. To handle the strict networking requirement of keeping multi-host TPU "slices" together over their Inter-Chip Interconnect (ICI), the KubeRay Operator on GKE automatically provisions and labels the underlying hardware layout. Ray Core utilizes these labels via its slice_placement_group() primitive to atomically reserve complete slices, allowing developers to deploy jobs through KubeRay, Ray Train, or Ray Serve simply by declaring a hardware topology (like "4x4") without writing custom placement code.

Februarys' ClickStack update brings major improvements to both Cloud and open source, including new query workflows, enhanced metrics exploration, performance optimizations, and expanded alerting options.

ClickHouse is fast by design, but raw database speed isn't enough. This post explores how ClickStack tightly integrates with ClickHouse to generate optimized queries — from progressive time window pagination and chunked charts to automatic use of materi

Learn how to send structured .NET logs directly to ClickHouse using Serilog — with full schema control, full-text search, and SQL queries over your log data.

ClickStack gets a literary upgrade with "AI Summarize", transforming raw logs into vivid, story-driven narratives that finally explain what's really happening in your systems.

How to remain competitive in the AI era of software engineering