Operations | Monitoring | ITSM | DevOps | Cloud

Temporal lets you orchestrate complex, reliable workflows, but when something breaks or slows down, the built-in dashboards only give you a list of events and some basic filters. You can see what happened and filter by attributes like workflow type or namespace, but you can't drill deeper. There's no way to jump straight from a metric spike to the exact trace or log line you care about.

Fat bills from observability vendors and tons of not-so-insightful telemetry data have turned out to be a very common issue today. This often leaves teams having to explain the lack of clear ROI, despite the growing costs. If you’re using OpenTelemetry to record your observability data, there are some practical methods you can apply to keep those costs from piling up.

In today’s complex distributed systems, observability has evolved from a nice-to-have feature to a mission-critical engineering discipline. Engineering teams across organizations depend on robust observability to maintain system reliability and quickly diagnose issues when they inevitably arise. However, current observability tooling significantly lags behind user expectations by failing to support a critical capability: querying across different telemetry signals.

“A system is never the sum of its parts; it's the product of their interaction.” — Russell Ackoff, Systems Thinker Infrastructure monitoring is an attempt to capture and record the product of interactions between various systems. Infrastructure monitoring comes across as challenging and tedious, often spread across multiple tooling system.

One of the most common things we hear from our users, is how AWS costs keep increasing with CloudWatch often playing a big role. CloudWatch has long been the default observability solution for AWS users. While it’s great for some use-cases, it’s also important to check out and weigh other alternatives which could be better suited for modern observability demands. Let’s examine some areas where modern observability platforms outweigh CloudWatch. Note.

New Relic vs DataDog: Both tools are popular for application and infrastructure monitoring, offering a wide range of features. This post compares New Relic and DataDog on key aspects like APM, log management, infrastructure monitoring, and OpenTelemetry support. Info I instrumented a sample Spring Boot Application and sent data to Datadog and New Relic to evaluate my experience. Some takeaways are subjective and based on personal preference.

Open-source log management tools provide cost-effective, customizable approaches for collecting and analyzing log data. They help teams quickly identify patterns, spot anomalies, and resolve issues. With numerous options available, it's important to understand their strengths and limitations. This article examines the top open-source log management tools in 2025, focusing on their capabilities, performance, and best use cases.