Operations | Monitoring | ITSM | DevOps | Cloud

The telecommunications industry is undergoing its most significant transformation in decades. The move from vertically integrated, proprietary systems to disaggregated, cloud-native infrastructure has unlocked enormous potential for agility and innovation. Yet, for many operators, the challenge has been how to realize that potential while meeting the stringent performance, security, and interoperability requirements that telecom networks demand.

This blog was authored by Jason Bloomberg, Managing Director, Intellyx BV ‍ Observability depends upon telemetry – the data streaming from various applications, services, and systems that indicate their internal state in real-time. Various tools consume such telemetry to enable both operational and cybersecurity tasks.

Database latency rarely starts in your app layer because it’s almost always a query doing more work than it should. Metrics tell you when that happens, but slow-query logging tells you which statement did it and how. That’s gold for tracking down missing indexes, inefficient filters, or accidental full scans. Pair the logging with a some lightweight counter metrics, and you get both an early warning and a clear path to a fix.

Not all software is the product of rigid planning, extensive documentation, and carefully designed test pipelines. Some of it emerges in bursts of intuition, created by small teams or individuals who prioritize momentum over process. This is what many engineers call vibe coding: development driven by flow and creativity, where the goal is to get something working quickly rather than ensuring every edge case is accounted for.

Landing pages are the lifeblood of modern marketing campaigns. They’re not the homepage, not the product catalog, not the blog—they’re the sharp end of the funnel where traffic from ads, emails, and social clicks is supposed to turn into revenue. A landing page is where a $50,000 media buy either pays off or evaporates.

A year ago, we hit a wall. Our Grafana OSS releases were excruciating to execute. The process was confusing and hard to follow, security patches were non-trivial, and many engineering hours were lost to an overly manual process. We needed to move fast, cut through ambiguity, and pull in just the right people without waiting on roadmaps or org charts.

Data Build Tool (dbt) is an open source analytics engineering framework that enables teams to transform raw data that has been loaded into a warehouse like Snowflake, BigQuery, Redshift, or Databricks using SQL-based workflows. dbt is available in two main forms: dbt Core, the free and open source CLI tool, and dbt Cloud, a managed platform that adds scheduling, UI support, collaboration tools, and native integrations.

A Kubernetes cluster can generate more than 1,400 metrics out of the box. That’s a lot of numbers to sift through, especially when you’re troubleshooting a production slowdown in the middle of the night. The key is knowing which metrics tell you the most, with the least noise. These are the signals worth paying attention to when you need answers fast.

Amazon Athena is heralded for its simplicity, pay-per-query pricing, and speed. Others say Athena has its fair share of limitations, which could affect your overall analytics experience and quality of analyses. So, what is what? In this post, we’ll share what AWS Athena does, compare it to Amazon Redshift, and share how to understand and control your Athena costs in AWS (with just one tool).