Operations | Monitoring | ITSM | DevOps | Cloud

A few weeks ago, a lead DevOps engineer at a fast-growing SaaS company hit an unexpected wall. “It used to just work… until we scaled,” the lead noted after their Terraform setup began buckling under the weight of a growing cloud footprint. Another chimed in: “We’re spending thousands on infrastructure every week, but we can’t trace it back to who deployed what, or why.” Sound familiar? You’re not alone.

Kibana gives you a structured way to explore log data indexed in Elasticsearch. With the right queries and visualizations, you can identify anomalies, debug issues more quickly, and track trends across services. This blog covers practical ways to query logs using Kibana’s Lucene and KQL syntax, build visualizations that surface meaningful signals, and set up dashboards for ongoing log-based monitoring.

Kong Gateway is a popular API gateway that sits at the edge of your infrastructure, routing and shaping traffic across microservices. It’s fast, pluggable, and battle-tested, but for many teams, it remains a black box. You might have OpenTelemetry set up across your application stack. Traces flow from your app servers, databases, and third-party APIs. But the moment a request enters through Kong, observability drops off.

Manual log investigation is one of those engineering tasks that quietly drains hours without offering much real value. You're debugging an incident. Monitoring shows elevated error rates. Now begins the familiar drill: It’s a tedious cycle, and it doesn’t scale. The whole process breaks down when you’re trying to automate incident response, run continuous security monitoring, or generate compliance reports.

In growing organizations, network requests pile up and so does the risk of delays, miscommunication, or misconfigurations. Whether a developer needs a static IP for a staging server or a project team is scaling infrastructure, manual processes don’t scale with you. LightMesh Requestor Workflow gives your users a secure, controlled way to request static IP addresses — without granting access to your entire IP address management (IPAM) platform. Admins stay in control. IT team stays productive.

You're monitoring a microservices-based system. Alerts trigger when response times exceed 2 seconds. But when you open Jaeger, you're faced with thousands of traces. Identifying which service or operation is responsible becomes time-consuming. Jaeger metrics help reduce this friction by exposing aggregated telemetry. Instead of scanning individual traces, you get service-level and operation-level performance metrics, latency, throughput, and error rates that highlight where the issue lies.

A DIY project to turn alerts into real-world signals using FireHydrant’s Hacker Mode.

Fixtures may be one of Playwright’s most powerful yet under-used features. Playwright fixtures can be used to simplify repetitive setup or teardown in your tests, manage test data ,and test state better. Fixtures are key if your objective is to write cleaner, maintainable and manageable Playwright tests. This tutorial is aimed at helping you master using Playwright fixtures, understand their purpose, and showing how you can use them most effectively in your tests.