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TRANSMISSIONS LIVE
// INSIGHTS

Field notes from
the deployment.

Deep technical write-ups, architecture breakdowns, and lessons from real engagements.

// FILTERED: RELIABILITY
3 MIN

OpenTelemetry: One Standard to Trace, Meter, and Log Everything

For years, observability meant three disconnected silos and a different agent for each vendor. OpenTelemetry (OTel) is the industry-wide answer: a single set of APIs, SDKs, and a wire protocol (OTLP)…

2 MIN

Chaos Engineering: Break It on Purpose Before It Breaks You

Every system has failure modes you have not met yet. Chaos engineering is the discipline of meeting them on your schedule, in daylight, with a rollback ready, instead of at 3am during a real outage.…

2 MIN

Runtime Security with Falco and Tetragon: Catching Attacks in the Act

Scanning images at build time tells you about known bad code. It says nothing about the compromised process spawning a shell in your payments pod at 2am. Runtime security watches actual behavior and…

2 MIN

Incident Response That Doesn't Burn People Out

Incidents are inevitable; trauma is optional. The difference between a team that learns from outages and one that quietly rage-quits is process, clear roles, blameless review, and a hard line on…

2 MIN

Kubernetes FinOps: Cutting Cloud Spend Without Cutting Reliability

Most Kubernetes bills are not expensive because of traffic, they are expensive because of slack . Over-provisioned requests, idle nodes, and forgotten volumes quietly compound. FinOps is engineering…

2 MIN

eBPF for Observability: Seeing Your Cluster Without Sidecars

For years, getting deep visibility meant injecting sidecars, patching binaries, or bolting agents onto everything. eBPF flips that: you attach safe programs to the kernel and watch every syscall,…

2 MIN

Progressive Delivery with Argo Rollouts: Canaries That Roll Themselves Back

A deploy that needs a human watching Grafana is not a deploy strategy, it is a hostage situation. Progressive delivery makes the release measure itself and roll back automatically when the numbers…

3 MIN

Kubernetes Autoscaling in Production: HPA, KEDA, and Karpenter

Autoscaling looks simple in a demo and gets subtle fast in production. Three controllers operate on different axes, and the failure modes only show up under real traffic. This is the mental model we…

1 MIN

Scaling Data Platforms, Part 3: Observability You'll Actually Use

Dashboards nobody opens are just expensive wallpaper. Part 3 is about signals that change behavior. Instrument the four questions Is the data fresh? Is the data complete? Is the data correct? Who is…

1 MIN

Scaling Data Platforms, Part 2: Streaming Ingestion with Kafka

Batch gets you correctness; streaming gets you freshness . In Part 2 we wire up a Kafka ingestion path that is safe to operate at 3am. Create a topic with sane defaults Set partitions and retention…

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