what-full-stack-observability-requires-today.pptx

Newrelic stack observability overview

1. New Relic Observability Platform How to have a single source of truth with the core elements of full-stack observability

2. What Full-Stack Observability Requires Today Introduction Observability has become an important practice for modern digital enterprises. No other strategy so effectively enables engineers to deliver excellent customer experiences with software, despite the complexities and distributed nature of their application and infrastructure landscape. 1 3 Delivering more perfect software is a constant challenge, but the companies that do it well often see three main outcomes: • Improved uptime and performance. Delivering an exceptional digital customer experience that drives engagement, conversion, and brand affinity requires your development and operations teams to have the visibility and tools needed to identify, diagnose, and repair issues quickly. • Greater scale and efficiency. As your company grows, you must maintain a firm handle on your environments as you migrate workloads to the cloud to gain scale, re-architect applications and infrastructure, and adopt architectures such as microservices and serverless. You must also rationalize disparate tools to eliminate data silos, enable holistic visibility, and reduce costs. Our research indicates that the average respondent collects telemetry data from less than half of their systems. • Accelerated time to market. Today’s consumers are more demanding than ever. You must equip your development teams with data and tools to support faster feature delivery, rapid recovery, and more experimentation to drive competitive business advantages. You also must gain agility with continuous delivery practices such as configuration management, continuous integration, and automated testing. Successful DevOps teams foster a culture of collaboration and visibility, so engineers across organizational boundaries can share learnings, coordinate better, and know exactly where to focus.

3. 1 Solving Modern Systems’ Challenges with Observability 05

4. What Full-Stack Observability Requires Today The reality is that change—in infrastructure, code, and end-user behavior—is the hallmark of modern systems. And this change doesn’t inherently need to be risky. You need technology partners that can help you effectively balance system reliability with speed. You need to see how all of your applications and their underlying services and systems relate, so you can understand dependencies across organizational boundaries, and troubleshoot and solve problems faster. And the holy grail: You need to be able to ask ad hoc questions of your data in real time, even if—especially if—you didn’t initially anticipate needing to ask those questions. When you do that, you get observability. 06 New Relic One: Observability Made Simple . Full-Stack Observability Analyze and troubleshoot problems easily across your entire software stack Applied Intelligence Automatically detect anomalies, correlate issues, and reduce alert noise Telemetry Data Platform Ingest, visualize, and alert on all of your telemetry data in one place

5. 2 A Single (Open) Source of Truth 5 For full-stack observability, you need to collect data from both open and proprietary sources and combine it in one place. You need to automatically apply instrumentation wherever it makes sense, and add instrumentation where you need visibility the most. Full-Stack Observability lets you easily visualize, analyze, and troubleshoot your entire software stack in one con nected experience. You can stop switching between dispa rate tools and trying to stitch together scattered data to figure out what went wrong. With rich analytics and a curated user experience, Full-Stack Observability surfaces the context your teams need to pinpoint and resolve problems within your infrastructure, applications, and end-user experience faster.   Applied Intelligence gives you the ability to detect, understand, and resolve incidents faster. By harnessing the power of artificial intelligence and machine learn - ing , Applied Intelligence offers AIOps capabilities that reduce alert noise, helping you find insights in the data that would otherwise go unnoticed. Telemetry Data Platform lets you ingest, visualize, and alert on all your metrics, events, logs, and traces from any source—all in one place. The world’s most powerful, managed, open, and unified telemetry data - base now comes with out-of-the-box integrations for popular open source tools to enable easy setup and eliminate the cost and complexities of hosting, opeating , and managing additional monitoring systems or data stores. With all of your telemetry data in one place, you can investigate your unknown unknowns with confidence.

6. What Full-Stack Observability Requires Today Traces Logs Third-Party Data Metrics Integrations SDKs APIs METRICS EVENTS LOGS TRACES Applications and Microservices Infrastructure and Services 6

7. What Full-Stack Observability Requires Today M.E.L.T: A quick breakdown At New Relic, we believe that metrics, events, logs, and traces (or MELT ) are the essential data types of observability. Here’s a brief overview of each. 7 METRICS Metrics are the starting point for full-stack observability. They are low overhead to collect, inexpensive to store, dimensional for quick analysis, and a great way to measure overall health. Because of that, many tools have emerged for metric collection, such as Prometheus, Telegraf, StatsD, Dropwizard, and Micrometer. An “open” full-stack observ- ability solution needs to be able to consume metrics from any of these sources that diverse teams have adopted in the modern digital enterprise. EVENTS Events are a critical (and often overlooked) telemetry type that must be part of any full-stack observability solution. Although events and logs share some similarities, the two are often mistakenly conflated. Events are discrete, detailed records of significant points of analysis. But they contain a higher level of abstraction than the level of detail provided by logs. Logs are comprehensive and discrete records of everything that happened within a system; events are records of selected significant things that happened with metadata attached to the record to sharpen its context. For example, when New Relic collects transaction events— individual instances of the execution of a method or a code block in a process—data is automatically added to show the number of database calls executed and the duration of those calls.

8. What Full-Stack Observability Requires Today LOGS Logs are important when an engineer is in “deep” debug- ging mode, trying to understand a problem. Logs provide high-fidelity data and detailed context around an event, so engineers can re-create what happened millisecond by millisecond. Just as with metrics and traces, tools have emerged to reduce the toil and effort of collecting, filter - ing, and exporting logs. Common solutions include Fluentd, Fluent Bit, Logstash, and AWS CloudWatch, as well as many other emerging standards. 8 TRACES Traces are valuable for showing the end- to- end latency of individual calls in a distributed architecture. These calls give specific insight into the myriad customer journeys through a system. Traces enable engineers to under- stand those journeys, find bottlenecks, and identify errors so they can be fixed and optimized. Like with met - rics, different tools ( Jaeger, Zipkin, AWS X- ray, etc.) and standards ( W3C Trace Context and OpenTelemetry project , for example) have emerged, allowing sophisticated organizations to create custom solutions.

9. Thank You To learn about how New Relic provides these essential components of full-stack observability, visit newrelic.com/platform/explorer.