February 22, 2026
An on-call engineer paged at 3 AM has limited cognitive capacity. They may not be familiar with the specific service that is failing. They may have joined the team two weeks ago. A runbook bridges the gap between the alert firing and the correct human response. Without runbooks, incident response depends on tribal knowledge – the engineer who built the service and knows its failure modes. That engineer is on vacation when the incident hits.
February 21, 2026
Cardinality is the number of unique time series Prometheus tracks. Every unique combination of metric name and label key-value pairs creates a separate series. A metric with 3 labels, each having 100 possible values, generates up to 1,000,000 series. In practice, cardinality explosions are the single most common way to kill a Prometheus instance.
The usual culprits are labels containing user IDs, request paths with embedded IDs (like /api/users/a]3f7b2c1), session tokens, trace IDs, or any unbounded value set. A seemingly innocent label like path on an HTTP metric becomes catastrophic when your API has RESTful routes with UUIDs in the path.
February 21, 2026
Most Kubernetes clusters run at 15-30% actual CPU utilization but are billed for the full provisioned capacity. The gap between what you reserve and what you use is pure waste. This article covers the practical workflow for finding and eliminating that waste.
Kubernetes resource requests are the foundation of cost. When a pod requests 4 CPUs, the scheduler reserves 4 CPUs on a node regardless of whether the pod ever uses more than 0.1 CPU. The node is sized (and billed) based on what is reserved, not what is consumed.
February 21, 2026
Prometheus stores metrics on local disk with a default retention of 15 days. Most production teams extend this to 30 or 90 days, but local storage has hard limits. A single Prometheus instance cannot scale disk beyond the node it runs on. It provides no high availability – if the instance goes down, you lose scraping and query access. And each Prometheus instance only sees its own targets, so there is no unified view across clusters or regions.
February 21, 2026
If Prometheus runs out of memory and crashes, you lose all alerting. If its disk fills up, it stops ingesting and you have a blind spot that may last hours before anyone notices. If scrapes start timing out, metrics go stale and alerts based on rate() produce no data (which means they silently stop firing rather than triggering). Prometheus must be the most reliably monitored component in your stack.
February 21, 2026
In Prometheus, cardinality is the number of unique time series. Every unique combination of metric name and label key-value pairs constitutes one series. The metric http_requests_total{method="GET", path="/api/users", status="200"} is one series. Change any label value and you get a different series. http_requests_total{method="POST", path="/api/users", status="201"} is a second series.
A single metric name can produce thousands or millions of series depending on its labels. A metric with no labels is exactly one series. A metric with one label that has 10 possible values is 10 series. A metric with three labels, each having 100 possible values, is up to 1,000,000 series (100 x 100 x 100), though in practice not every combination occurs.
February 21, 2026
An SLI (Service Level Indicator) is a quantitative measurement of service quality – a number computed from your metrics. Examples: the proportion of successful HTTP requests, the proportion of requests faster than 500ms, the proportion of jobs completing within their deadline.
An SLO (Service Level Objective) is a target value for an SLI. It is an internal engineering commitment: “99.9% of requests will succeed over a 30-day rolling window.”
February 21, 2026
Synthetic monitoring means actively probing your services on a schedule rather than waiting for users to report problems. Instead of relying on internal health checks or real user traffic to detect issues, you send controlled requests and measure the results. The fundamental question it answers is: “Is my service reachable and responding correctly right now?”
This is distinct from real user monitoring (RUM), which observes actual user interactions. Synthetic probes run 24/7 regardless of traffic volume, so they catch outages at 3 AM when no users are active. They provide consistent, repeatable measurements that are easy to alert on. The tradeoff is that synthetic probes test a narrow, predefined path – they do not capture the full range of user experience.
February 21, 2026
The Prometheus ecosystem has exporters for most infrastructure components: node_exporter for Linux hosts, kube-state-metrics for Kubernetes objects, mysqld_exporter for MySQL, and hundreds more. You write a custom exporter when your application or service does not have a Prometheus endpoint, you need business metrics that no generic exporter can provide (revenue, signups, queue depth), or you need to adapt a non-Prometheus system that exposes metrics in a proprietary format.