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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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Incident management handbook: How to deal with being on-call
Responding to an alert can be daunting – for managers, developers, and anyone who is paged in the middle of the night. This step-by-step guide shows how to ask the right questions and stay organized along the entire journey from getting paged to resolving an incident. You'll also learn: - Where to start when your pager goes off - How to work through the On-Call Stages of Grief - How to use the process of elimination as a debugging strategy - How to mitigate the impact on users as quickly as possible
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How deep systems broke observability
Organizations move to microservices so that developers can deploy faster, without having to plan or coordinate their activities with other teams. But if microservices were supposed to be about release velocity, why has "pushing new code" become such a stressful experience? Join Ben Sigelman, LightStep CEO and co-creator of OpenTracing and OpenTelemetry, in an on-demand webinar to learn: - Why developers are responsible for more than they can control - How microservices become deep systems - Best practices for observability - How to reduce MTTR and improve system performance
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OpenTelemetry 101
This technical guide provides an overview of key concepts of observability and distributed tracing, and details the underlying relationship between core concepts in the OpenTelemetry project, including spans, metrics, and exporters. OpenTelemetry provides a single set of APIs, libraries, agents, and collector services to capture distributed traces and metrics from your application. OpenTelemetry is a Cloud Native Computing Foundation (CNCF) project. This is a great reference guide for those who are just getting started with distributed tracing, as well as for veterans who are using (or plan to use) open source instrumentation, including OpenTelemetry or its predecessors, OpenTracing and OpenCensus.
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The power of platform teams
Platform teams are force multipliers — they reduce cognitive load for developers and make it easier to ship new features. Every investment in platform is an investment in making the rest of the development organization more efficient and effective. This ebook will help you understand how to build successful platform teams, and how to set them up for future growth. You'll also learn: - How to build a modern platform team - How to release more features with less risk - How to connect your platform team with key stakeholders in development, incident response, management, and product
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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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Ensuring success with Kubernetes
Containerized applications like Kubernetes allow teams to build and release software faster, but at the cost of increased complexity. This guide will help you navigate that complexity, avoid common pitfalls, and take advantage of the highly active user community. You'll also learn how to: - Roll out Kubernetes at scale - Build an effective observability strategy - Ensure a better customer experience
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Putting services first: A new scorecard for observability
Microservices allow us to achieve higher velocity and team independence, but at the cost of limited visibility into service health and dependencies. When things break — and they will — we can't expect to find a solution by guessing-and-checking across the entire system. Or rely on raw telemetry data (metrics, logs, and traces) to guide our hypotheses and investigations. Enter: A New Scorecard for Observability In this guide, you'll learn: - Why the “Three Pillars of Observability” fail to address the observability needs of modern systems - How APM broke microservices - What you can do to better develop, understand, and operate your distributed system
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Distributed tracing at scale: Analyzing Google’s June 2nd outage
On Sunday June 2nd, Google Cloud Platform had an extended networking-based outage. There was significant disruption of commonly used services like YouTube and Gmail, as well as Google hosted applications like Snapchat. LightStep Research’s ongoing synthetic testing shows that the impact was longer than the advertised incident report, and provides an example of the type of evidence you can share with a cloud provider when discussing an outage. Read this brief to understand: - How to quickly understand the scope and impact of an outage - How to measure the performance of cloud service APIs - How to utilize distributed tracing at scale - How to fact check an incident report or status page
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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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Lightstep sounds like a lovely idea
Monitoring and observability for the world’s most reliable systems
