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The complete guide to distributed tracing
This guide will help you understand how distributed tracing provides unrivaled visibility and analysis in systems that can have dozens, hundreds, or thousands of services working together. You'll also learn: - How to establish true observability with distributed tracing - How your service affects — and is affected by — dependencies - How to decide when to take action by focusing on symptoms that directly impact users
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Performance is a shape – not a number
If you’re adopting microservices, you know that faster root cause analysis and the ability to confidently measure and explain performance are key to improving efficiency and saving developer time. Read this report to understand why: - Countless disconnected time-series statistics aren’t enough to explain the behavior of modern applications. - Tools must identify, triage, and explain latency issues, as organizations adopt microservices. - It’s critical to evolve our thinking about latency measurements and how they play a part in diagnostic workflows.
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How to reduce your logging bill by 90%
When trying to solve performance problems, you need a tool that analyzes the system as a whole. Logs are useful to understand point-in-time behavior and capture rich information about single actors in your environment, but they also require developers to piece together each part of a request lifecycle in order to understand dependencies. Learn how to: - Massively reduce your logging bill — and MTTR - Embed application logs in traces at no cost - More effectively surface the root cause in a complex system
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Observability won't replace monitoring (because it shouldn't)
If observability won't replace monitoring, if "the three pillars" aren't really pillars, and a single shiny datastore will never be sufficient, how should we model observability?
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Lightstep sounds like a lovely idea
Monitoring and observability for the world’s most reliable systems
