Log Monitoring Software Resources

Articles, Glossary Terms, Discussions, and Reports to expand your knowledge on Log Monitoring Software

Resource pages are designed to give you a cross-section of information we have on specific categories. You'll find articles from our experts, feature definitions, discussions from users like you, and reports from industry data.

Contents

Log Monitoring Software Articles

Serverless Architecture: What It Is, Benefits, and Limitations

Shipping faster, building momentum, and growing market share is the dream of any enterprise leader.

by Sudipto Paul

Log Monitoring Software Glossary Terms

Log Management

Businesses leverage log management to collect and analyze data from systems, applications, and devices. Know the best practices for log management.

by Alyssa Towns

Logs

What are logs and why is it important as a software feature? Our G2 guide can help you understand logs and popular software with logging features.

by Tian Lin

Log Monitoring Software Discussions

What are the most trusted log monitoring platforms among software engineers and DevOps teams based on user reviews?

Hi G2, I'm trying to work out which log monitoring platforms software engineers and DevOps teams actually trust, using G2 ratings and review themes. From the log monitoring category, with ratings:

Dynatrace (4.5, 1,366 reviews): trusted for Davis AI that explains root cause instead of firing a hundred alerts.
Sentry (4.5, 226 reviews): trusted by developers for real-time error tracking and detailed stack traces.
Grafana Labs (4.5, 179 reviews): trusted as a single pane across metrics, logs, and traces.
Datadog (4.4, 726 reviews): trusted for unifying logs, metrics, and traces to see the whole stack.
New Relic (4.4, 586 reviews): trusted for real-time observability and distributed tracing across services.

For engineers and DevOps, which platform earned your trust in production? And did trust come from detection speed, root-cause clarity, or how it held up during an incident?

Trust usually gets earned on the worst incident of the quarter, not during normal monitoring. I’d be interested in which of these still gave engineers a clear trail when five services started failing at once. That’s where Dynatrace’s root-cause approach or Datadog’s cross-signal view should prove whether they actually reduce investigation time.

Answered: Barkha Bali on September 3, 2026

Your answer

Question on: Sentry

Does Sentry support distributed tracing?

We're running a microservices architecture and tracing requests across services has been a pain point. Does Sentry handle distributed tracing well? We're also already using OpenTelemetry, wondering if we'd have to re-instrument everything or if it works with our existing setup.

Yes, and the OpenTelemetry question is probably the more useful one to answer first: No, you don't need to re-instrument. Sentry supports OTLP, so you can point your existing OTel setup at Sentry and your traces will show up without touching your instrumentation. Docs here: https://docs.sentry.io/concepts/otlp/ On distributed tracing: it follows requests across services end-to-end, so you can see exactly where a transaction slowed down or broke and which service caused it. In a microservices setup the useful part is that errors don't show up in isolation, you get the full request path that led to them. And if you're already using Sentry for errors, that context lives in the same place. Same issue, same trace.

Answered: Anton Bjorkman on March 30, 2026

Your answer

Question on: Sentry

Is Sentry good for observability?

We're looking at consolidating our observability stack and Sentry has come up as an option. Curious how it compares to something like Datadog or New Relic, is it a full observability platform or more of a debugging tool?

Sentry covers errors, performance, traces, logs, metrics, session replay, and profiling. But what sets it apart is the debugging-first approach. Instead of staring at dashboards, Sentry connects a slow endpoint or spike in errors directly to the code, stack trace, and release that caused it. Seer, Sentry's AI agent, goes a step further by analyzing errors automatically, identifying root causes, and suggesting fixes before you even start debugging. The recently launched metrics product lets you track application metrics alongside your error and performance data, so you get the full picture without switching tools. For developers looking to consolidate, it replaces separate error tracking, APM, and metrics tools with one platform built around finding and fixing issues faster.

Log Monitoring Software Resources

Articles, Glossary Terms, Discussions, and Reports to expand your knowledge on Log Monitoring Software

Log Monitoring Software Articles

Serverless Architecture: What It Is, Benefits, and Limitations

Log Monitoring Software Glossary Terms

Log Monitoring Software Discussions

Log Monitoring Software Reports