# Performance Monitoring Published articles for Performance Monitoring. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Linux Server Health Checks: 10 Metrics Every Sysadmin Should Monitor DevFeed: [Linux Server Health Checks: 10 Metrics Every Sysadmin Should Monitor]() Original publisher: [Read original article]() Author: Sujitha Paduchuri, ManageEngine Published: 2026-07-06T12:13:41Z Content type: tutorial Language: en Sources: [Hayden James]() Topics: [Linux](), [Monitoring](), [Linux performance](), [health checks]() Tags: [blog](), [cpu](), [disk-space](), [guests](), [health-checks](), [linux](), [linux-performance](), [load](), [memory](), [metrics](), [monitoring](), [observability](), [performance](), [performance-monitoring](), [server](), [sysadmins]() ### AI overview A practical guide to monitoring Linux server health through metrics that can reveal resource problems earlier than broad CPU, memory, or disk-usage figures. It discusses iowait, load average, active swap activity, and inode exhaustion, along with warning signs and follow-up investigations. ### Source excerpt Servers give you warnings before they fail. Most sysadmins performing Linux server monitoring miss them because they're watching the wrong numbers. The metrics that actually matter are one level deeper: iowait instead of CPU percentage, active swap paging instead of memory usage, inode counts instead of just disk space. Continue reading... ## The 10 Most Popular Postgres Extensions on Neon DevFeed: [The 10 Most Popular Postgres Extensions on Neon]() Original publisher: [Read original article]() Author: Ben Hagan Published: 2025-08-21T16:04:10Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [Database](), [dashboards](), [datasets](), [Embeddings](), [Query (disambiguation)](), [observability](), [Monitoring](), [Latency](), [real-time](), [SQL](), [Code]() Tags: [data](), [database](), [embeddings](), [extensions](), [full-text-search](), [geospatial](), [insights](), [latency](), [monitoring](), [observability](), [performance](), [performance-monitoring](), [popular](), [postgres](), [real-time](), [search](), [sql]() ### AI overview The article presents the ten most popular Postgres extensions on Neon, using platform-wide installation and usage statistics. It explains how extensions can add full-text search, geospatial capabilities, vector storage for embeddings, database functions, query-performance monitoring, and UUID generation, and highlights an interactive real-time dashboard for exploring the data. ### Source excerpt Postgres is loved not just for what it is, but for what it can become: its extension system lets you transform your database into a full-text search engine, a geospatial powerhouse, or a vector store for embeddings - all without switching tools. With many thousands of active data... ## Understanding SLAs, SLOs, and SLIs in Service Reliability DevFeed: [Understanding SLAs, SLOs, and SLIs in Service Reliability]() Original publisher: [Read original article]() Author: Abhimanyu Saharan Published: 2025-07-02T00:00:00Z Content type: tutorial Language: en Sources: [Abhimanyu Saharan]() Topics: [site-reliability-engineering](), [Monitoring](), [Latency]() Tags: [examples](), [metrics](), [monitoring](), [performance](), [performance-monitoring](), [software-engineering](), [uptime]() ### AI overview This article explains the differences between SLAs, SLOs, and SLIs using real-world examples, with emphasis on service reliability metrics for uptime, latency, and performance monitoring. ### Source excerpt Learn the difference between SLA, SLO, and SLI with real-world examples. Master key service reliability metrics for uptime, latency, and performance monitoring. ## Firebase at I/O Connect 2024 DevFeed: [Firebase at I/O Connect 2024]() Original publisher: [Read original article]() Author: Andrea Wu Published: 2024-09-27T06:00:00Z Content type: news Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Genkit](), [observability](), [telemetry](), [Testing](), [Generative AI](), [Google]() Tags: [ai](), [app-distribution](), [community](), [firebase](), [generative-ai](), [genkit](), [google-i-o](), [launch](), [news](), [observability](), [performance-monitoring](), [telemetry](), [testing](), [updates]() ### AI overview The Firebase team reports on its participation in regional I/O Connect events in Berlin, Bengaluru, and Beijing. The article announces Firebase AI Monitoring in private preview, an AI Testing Agent in early access preview through Firebase App Distribution, and the I/O Crossword project. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Firebase updates announced at Google I/O 2023 include PaLM API Extensions and full-stack development improvements DevFeed: [Firebase updates announced at Google I/O 2023 include PaLM API Extensions and full-stack development improvements]() Original publisher: [Read original article]() Author: Dmitry Lyalin Published: 2023-05-10T00:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Google](), [Extension](), [Generative AI](), [PaLM API](), [Firestore](), [Development](), [Serverless]() Tags: [ai](), [android](), [app-check](), [app-distribution](), [astro](), [cloud-functions](), [crashlytics](), [extension](), [extensions](), [firebase](), [firestore](), [flutter](), [full-stack-development](), [generative-ai](), [google](), [google-i-o](), [ios](), [launch](), [palm](), [palm-api](), [performance-monitoring](), [python](), [remote-config](), [serverless](), [svelte](), [terraform](), [updates](), [vue](), [web]() ### AI overview Firebase announces Google I/O 2023 updates including new generative AI Extensions powered by the PaLM API, a preview of the Chatbot with PaLM API extension, and improvements intended to simplify full-stack development. ### Source excerpt Everything we shipped! From AI Extensions to launches that simplify full stack development ## Transforming home buying in Latin America using Firebase DevFeed: [Transforming home buying in Latin America using Firebase]() Original publisher: [Read original article]() Author: Akua Prempeh Published: 2022-11-09T00:00:00Z Content type: article Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [App](), [Development](), [Mobile](), [Website]() Tags: [app-development](), [crashlytics](), [developers](), [development](), [firebase](), [firebase-stories](), [mobile](), [performance-monitoring](), [platform]() ### AI overview La Haus co-founder and CTO Santiago GarcΓ­a and Tech Lead Daniel Gomez Rico discuss their app development journey and how La Haus uses Firebase tools to help prospective homeowners in Latin America research homes, make reservations, and submit secure down payments. ### Source excerpt A conversation with the Santiago GarcΓ­a (co-founder and CTO) and Daniel Gomez Rico (Tech Lead) of La Haus talk about their app development journey and how La Haus uses Firebase tools to help prospective homeowners in Latin America buy their first home. ## Adding Firebase Performance Monitoring to a Jetpack Compose app DevFeed: [Adding Firebase Performance Monitoring to a Jetpack Compose app]() Original publisher: [Read original article]() Author: Marina Coelho Published: 2022-11-03T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Compose](), [Firebase](), [Monitoring](), [Android](), [data]() Tags: [android](), [compose](), [firebase](), [how-to](), [jetpack-compose](), [monitoring](), [performance-monitoring]() ### AI overview This tutorial explains how to add Firebase Performance Monitoring to an Android app built with Jetpack Compose. It describes automatically collected performance data, including app lifecycle, screen rendering, and HTTP/S network request data, and introduces custom traces for monitoring specific parts of the code. ### Source excerpt Learn how to add Firebase Performance Monitoring to an Android app built with Jetpack Compose. ## What's new at Firebase Summit 2022 DevFeed: [What's new at Firebase Summit 2022]() Original publisher: [Read original article]() Author: Kara Yu Published: 2022-10-18T00:00:00Z Content type: news Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Angular](), [Next.js](), [Deployment]() Tags: [android](), [app-check](), [authentication](), [c-plus-plus](), [c-sharp](), [cloud-functions](), [cloud-messaging](), [cloud-storage](), [crashlytics](), [deployment](), [extensions](), [firebase](), [firebase-summit](), [firestore](), [flutter](), [games](), [google-analytics](), [in-app-messaging](), [machine-learning](), [news](), [performance-monitoring](), [personalization](), [realtime-database](), [remote-config](), [unity](), [updates](), [web]() ### AI overview Firebase's 2022 Summit article announces platform updates, including preview support in Firebase Hosting for deploying dynamic web frameworks such as Next.js and Angular Universal through the Firebase CLI. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Adding Crashlytics to a Jetpack Compose app DevFeed: [Adding Crashlytics to a Jetpack Compose app]() Original publisher: [Read original article]() Author: Marina Coelho Published: 2022-06-23T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Crashlytics](), [Firebase](), [Android](), [Jetpack Compose](), [Gradle]() Tags: [android](), [crashlytics](), [firebase](), [gradle-plugin](), [jetpack](), [jetpack-compose](), [performance-monitoring]() ### AI overview A tutorial on adding Firebase Crashlytics to an Android application built with Jetpack Compose. It explains how Crashlytics captures crash data, uploads reports to a Firebase project, groups crashes, and guides the required Gradle configuration. ### Source excerpt Learn how to add Firebase Crashlytics to an Android app built with Jetpack Compose. ## Building Firebase Quickdraw Multiplayer DevFeed: [Building Firebase Quickdraw Multiplayer]() Original publisher: [Read original article]() Author: Tri Cao; Scott Shipman Published: 2022-06-14T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Web app](), [Cloud Functions](), [Realtime Database](), [Artificial Intelligence]() Tags: [ai](), [cloud-functions](), [firebase](), [games](), [google-analytics](), [hosting](), [multiplayer](), [performance-monitoring](), [realtime-database](), [web-app]() ### AI overview This tutorial explains how Firebase Quickdraw, a web game with an AI guessing bot, was extended with multiplayer functionality. It covers shareable rooms for up to four players, Realtime Database, Cloud Functions, Firebase Hosting, Google Analytics, and Firebase Performance Monitoring. ### Source excerpt Build a multiplayer game with Firebase! ## What's new from Firebase at Google I/O 2022 DevFeed: [What's new from Firebase at Google I/O 2022]() Original publisher: [Read original article]() Author: Tyler Crowe Published: 2022-05-11T00:00:00Z Content type: news Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Extension](), [Google](), [App](), [Development]() Tags: [android](), [app-check](), [app-development](), [app-distribution](), [apps](), [crashlytics](), [emulator-suite](), [extension](), [extensions](), [firebase](), [flutter](), [google](), [google-i-o](), [hosting](), [ios](), [news](), [performance-monitoring](), [swift](), [updates](), [web]() ### AI overview Firebase announces updates presented at Google I/O 2022, including Extension events, third-party extensions, and integrations intended to support app development and customization. ### Source excerpt News, tutorials, and updates from the Firebase team. ## How Firebase Performance Monitoring optimized app startup time DevFeed: [How Firebase Performance Monitoring optimized app startup time]() Original publisher: [Read original article]() Author: Viswanathan Munisamy Published: 2022-03-09T00:00:00Z Content type: article Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Android](), [Mobile](), [App](), [Code](), [configuration]() Tags: [android](), [app-quality](), [app-startup](), [article](), [code](), [configuration](), [cpu](), [dependencies](), [firebase](), [measurement](), [metrics](), [mobile](), [network](), [optimization](), [performance](), [performance-monitoring](), [tool]() ### AI overview This article explains how Firebase Performance Monitoring measures Android application cold-start performance, including startup time, initial display, CPU and memory impact, and network requests. It describes the library's startup tasks and suggests comparing app versions with and without the library to measure its effect. ### Source excerpt Mobile users expect their apps to be fast and responsive, and apps with a slow startup time, especially during coldstart, can leave them feeling... ## What's new at Firebase Summit 2021 DevFeed: [What's new at Firebase Summit 2021]() Original publisher: [Read original article]() Author: Kristen Richards Published: 2021-11-10T00:00:00Z Content type: news Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Extension](), [stripe](), [Firestore](), [Google](), [GitHub]() Tags: [android](), [app-check](), [authentication](), [c-plus-plus](), [c-sharp](), [cloud-functions](), [cloud-messaging](), [cloud-storage](), [crashlytics](), [development](), [extension](), [extensions](), [firebase](), [firebase-summit](), [firestore](), [flutter](), [games](), [github](), [google-analytics](), [in-app-messaging](), [machine-learning](), [news](), [performance-monitoring](), [personalization](), [platform](), [realtime-database](), [remote-config](), [sendgrid](), [stripe](), [unity](), [updates](), [web]() ### AI overview Firebase Summit 2021 introduced platform updates focused on accelerating app development, operating apps with confidence, and scaling them. The article highlights new Firebase Extensions for e-commerce, payments, messaging, merchandise, and Cloud Firestore search. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Pinpointing API performance issues with Custom URL Patterns DevFeed: [Pinpointing API performance issues with Custom URL Patterns]() Original publisher: [Read original article]() Author: Ibrahim Ulukaya Published: 2021-10-20T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [API](), [Monitoring](), [dashboards](), [Traces]() Tags: [api](), [app-quality](), [best-practices](), [firebase](), [monitoring](), [patterns](), [performance](), [performance-monitoring](), [traces](), [tutorials]() ### AI overview This tutorial explains how Firebase Performance Monitoring analyzes network request performance using automatically aggregated and custom URL patterns. It shows how developers can identify slow requests, review response times, success rates, and payload sizes, and investigate performance trends while URL aggregation removes personally identifiable information. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Unlocking your app's best experience with Firebase Performance Monitoring DevFeed: [Unlocking your app's best experience with Firebase Performance Monitoring]() Original publisher: [Read original article]() Author: Nitin Kaushik Published: 2021-08-02T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Monitoring](), [Mobile](), [Development]() Tags: [app-performance](), [app-quality](), [best-practices](), [crashlytics](), [firebase](), [monitoring](), [performance-metrics](), [performance-monitoring](), [releases](), [test-lab]() ### AI overview This article explains how Firebase Performance Monitoring helps developers understand app performance from users' perspectives. It covers real-time performance metrics, monitoring releases during development and after launch, and analyzing screen-rendering and network-request data across user segments. ### Source excerpt News, tutorials, and updates from the Firebase team. ## What's new from Firebase at Google I/O 2021 DevFeed: [What's new from Firebase at Google I/O 2021]() Original publisher: [Read original article]() Author: Kristen Richards Published: 2021-05-18T00:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Emulator](), [Google](), [Command-line interface](), [Cloud Functions](), [Authentication](), [Android]() Tags: [a-b-testing](), [android](), [app-check](), [app-distribution](), [cli](), [cloud](), [cloud-functions](), [crashlytics](), [emulator-suite](), [extensions](), [firebase](), [firebase-cli](), [games](), [google](), [google-i-o](), [google-i-o-2021](), [launch](), [news](), [performance-monitoring](), [personalization](), [pre-release](), [remote-config](), [testing](), [tutorials](), [updates](), [web]() ### AI overview Firebase announces updates presented at Google I/O 2021, including a Storage Emulator for the Emulator Suite and Android App Bundle support in Firebase App Distribution. The updates target app development, testing, backend emulation, and user experience. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Measuring Realtime Database performance with Firebase Performance Monitoring DevFeed: [Measuring Realtime Database performance with Firebase Performance Monitoring]() Original publisher: [Read original article]() Author: Sam Stern Published: 2021-03-12T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Realtime Database](), [Monitoring](), [real user monitoring](), [Latency](), [SDK](), [WebSocket](), [React]() Tags: [backend](), [database-performance](), [firebase](), [javascript](), [latency](), [monitoring](), [performance](), [performance-monitoring](), [react](), [real-user-monitoring](), [realtime](), [realtime-database](), [tutorials](), [web](), [websocket]() ### AI overview This tutorial explains how to measure Realtime Database performance with Firebase Performance Monitoring. It uses custom traces to measure database operations over the long-running WebSocket connection and examines how latency varies by user geography. ### Source excerpt News, tutorials, and updates from the Firebase team. ## How GameNexa Studios used Firebase to grow and diversify their monetization strategy DevFeed: [How GameNexa Studios used Firebase to grow and diversify their monetization strategy]() Original publisher: [Read original article]() Author: Firebase Team Published: 2020-12-17T00:00:00Z Content type: article Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [data](), [A/B Testing](), [personalization](), [Google Analytics](), [Crashlytics](), [Monitoring]() Tags: [a-b-testing](), [admob](), [analytics](), [case-study](), [crashlytics](), [firebase](), [google-analytics](), [monetization](), [performance-monitoring](), [personalization](), [revenue](), [user-experience]() ### AI overview This Firebase case study describes how GameNexa Studios used Google Analytics and Firebase Predictions to segment users, then applied Remote Config and A/B Testing to tailor ads and in-app promotions. The company reported increased in-app purchase revenue, restored ad revenue to pre-pandemic levels, and higher conversions. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Helpful product updates from Firebase Summit 2020 DevFeed: [Helpful product updates from Firebase Summit 2020]() Original publisher: [Read original article]() Author: Francis Ma Published: 2020-10-27T00:00:00Z Content type: news Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Authentication](), [Cloud Functions](), [Emulator](), [Realtime Database](), [App](), [Cloud](), [Development]() Tags: [authentication](), [bigquery](), [cloud](), [cloud-functions](), [cloud-messaging](), [community](), [crashlytics](), [emulator-suite](), [extensions](), [firebase](), [firebase-summit](), [firestore](), [google-analytics](), [hosting](), [in-app-messaging](), [ios](), [performance-monitoring](), [product-updates](), [realtime-database](), [remote-config](), [tutorials](), [unity](), [web]() ### AI overview Firebase Summit 2020 introduced product updates including a Firebase Authentication emulator for rapid local iteration and development, alongside continued investment in tools for app development and operation. The article also highlights Firebase usage growth and the role of Firebase and Google Cloud in supporting apps such as Classkick. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Android Vitals - First draw time πŸ‘©πŸŽ¨ DevFeed: [Android Vitals - First draw time πŸ‘©πŸŽ¨]() Original publisher: [Read original article]() Author: Py βš” Published: 2020-08-29T11:51:28Z Content type: tutorial Language: en Sources: [Py βš”]() Topics: [Android](), [Monitoring](), [App]() Tags: [android](), [bug](), [callback](), [coding](), [community](), [development](), [engineering](), [extension-function](), [function](), [inclusive](), [monitoring](), [performance](), [performance-monitoring](), [software](), [vitals]() ### AI overview This article explains how Android app startup time is tied to the first completely loaded frame and focuses on measuring when cold start ends. It compares Choreographer.postFrameCallback() with ViewTreeObserver.addOnDrawListener(), describing timing behavior, an API 25 issue, and an API 26 listener-merging bug workaround. ### Source excerpt Header image: Light Field by Romain Guy. This blog series is focused on stability and performance monitoring of Android apps in production. Last week, I wrote about how to best determine the app start time. Today, we focus on determining the time at which cold start ends. According to the Play Console documentation: Startup times are tracked when the app's first frame completely loads. We learn a bit more from the App startup cold time documentation: Once the app process has completed the first draw, the system process swaps out the currently displayed background window, replacing it with the main activity. At this point, the user can start using the app. In Android Vitals - Rising to the first drawn surface πŸ€½β™‚, we learnt that: ActivityThread.handleResumeActivity() schedules the first frame. On the first frame Choreographer.doFrame() calls ViewRootImpl.doTraversal() which performs a measure pass, a layout pass, and finally the first draw pass on the view hierarchy. First frame Since API level 16, Android provides a simple API to schedule a callback when the next frame happens: Choreographer.postFrameCallback(). class MyApp : Application() { var firstFrameDoneMs: Long = 0 override fun onCreate() { super.onCreate() Choreographer.getInstance().postFrameCallback { firstFrameDoneMs = SystemClock.uptimeMillis() } } } Unfortunately, calling Choreographer.postFrameCallback() has the side effect of scheduling a frame that runs before the first traversal is scheduled. So the time reported here is before the time of the frame that runs the first draw. I was able to reproduce this on API 25 but also noticed it doesn't happen in API 30, so this bug was probably fixed. First draw ViewTreeObserver On Android, each view hierarchy has a ViewTreeObserver which can hold callbacks for global events such as layout or draw. ViewTreeObserver.addOnDrawListener() We can call ViewTreeObserver.addOnDrawListener() to register a draw listener: view.viewTreeObserver.addOnDrawListener { // repo ## Android Vitals - When did my app start? ⏱ DevFeed: [Android Vitals - When did my app start? ⏱]() Original publisher: [Read original article]() Author: Py βš” Published: 2020-08-21T21:01:05Z Content type: tutorial Language: en Sources: [Py βš”]() Topics: [Android](), [Monitoring](), [Processes]() Tags: [android](), [coding](), [community](), [development](), [engineering](), [inclusive](), [monitoring](), [performance](), [performance-monitoring](), [process](), [software](), [vitals]() ### AI overview This Android Vitals article evaluates several ways to determine when an Android app starts, including Application.onCreate(), ContentProvider.onCreate(), class loading, and Linux process start time. It explains why process fork time may precede the meaningful beginning of app cold-start monitoring. ### Source excerpt Header image: Ressence Type 5 Tilt by Romain Guy. This blog series is focused on stability and performance monitoring of Android apps in production. Last week, I wrote about using process importance to determine why an app was started. To track cold start time, we need to know when the app started. There are many ways to do that and this blog evaluates different approaches. As a reminder, I already established in Android Vitals - What time is it? that I would use SystemClock.uptimeMillis() to measure time intervals. Application.onCreate() The simplest approach is to capture the time at which Application.onCreate() is called. class MyApp : Application() { var applicationOnCreateMs: Long = 0 override fun onCreate() { super.onCreate() applicationOnCreateMs = SystemClock.uptimeMillis() } } ContentProvider.onCreate() In How does Firebase initialize on Android? we learn that a safe early initialization hook for library developers is ContentProvider.onCreate(): class StartTimeProvider : ContentProvider() { var providerOnCreateMs: Long = 0 override fun onCreate(): Boolean { providerOnCreateMs = SystemClock.uptimeMillis() return false } } ContentProvider.onCreate() also works for app developers and it's called earlier in the app lifecycle than Application.onCreate(). Class load time Before any class can be used, it has to be loaded. We can rely on static initializers to store the time at which specific classes are loaded. We could track the time at which the Application class is loaded: class MyApp : Application() { companion object { val applicationClassLoadMs = SystemClock.uptimeMillis() } } In Android Vitals - Diving into cold start waters πŸ₯Ά, we learnt that on Android P+ the first class loaded is the AppComponentFactory: @RequiresApi(Build.VERSION_CODES.P) class StartTimeFactory : androidx.core.app.AppComponentFactory() { companion object { val factoryClassLoadMs = SystemClock.uptimeMillis() } } ) Original publisher: [Read original article]() Author: Francis Ma Published: 2019-05-07T00:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [ML Kit](), [API](), [Google](), [object-detection](), [Mobile]() Tags: [c-plus-plus](), [crashlytics](), [emulator-suite](), [fabric](), [firebase](), [firestore](), [google](), [google-analytics](), [google-i-o](), [launch](), [machine-learning](), [ml-kit](), [mobile](), [object-detection](), [on-device](), [performance-monitoring](), [test-lab](), [updates]() ### AI overview Firebase announces its biggest Google I/O 2019 updates, including new ML Kit beta capabilities for on-device translation, real-time object detection and tracking, and custom image classification with AutoML Vision Edge. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Fishing For Correlations DevFeed: [Fishing For Correlations]() Original publisher: [Read original article]() Author: GameChanger Published: 2019-02-12T19:51:49Z Content type: article Language: en Sources: [GameChanger]() Topics: [observability](), [Application Performance Management (APM)](), [Instrumentation](), [Koa](), [Monitoring](), [Node.js](), [PostgreSQL](), [Logging](), [async/await]() Tags: [back-end](), [instrumentation](), [logging](), [metrics](), [monitoring](), [node-js](), [observability](), [performance-monitoring](), [postgresql]() ### AI overview The article describes GameChanger's effort to improve observability during performance degradation in a new back-end system. It discusses instrumenting a Node.js and Koa application, using PostgreSQL, Datadog metrics and APM, and Loggly for centralized logging. The team can monitor system and request metrics but still faces challenges correlating logs, timelines, and behavioral trends. ### Source excerpt Have you ever participated in a firefight where the root cause seems unclear, then suddenly the symptoms self-resolve? Sometimes inadvertent action may cause it, other times it appears miraculous. If you find yourself in this situation, or excusing recovery with "it was a one-off blip," your system likely lacks sufficient observability. With development and operations increasingly converging, application instrumentation continues to concern many teams building new platforms and maintaining legacy ones. The general rule of thumb when introducing observability into a system is to instrument everything. However, this philosophy creates a user experience challenge. How do we deliver the salient system correlations to the people who can best leverage them? The platform team at GameChanger recently had the opportunity to tackle this question when we encountered performance degradation while scaling a new back-end system. We are not yet finished, but we have progressed meaningfully. Diving into the black box Modern Node.js, using async/await with Koa, powers GameChanger's nascent Team Manager product. PostgreSQL serves as the primary datastore and PgBouncer manages connection pooling to the database. We already use Datadog to monitor many of our legacy systems. Starting with Datadog for a new system made sense for a number of reasons: Vendor familiarity: engineers already understand the operational model and where to look for diagnostics Breadth of functionality: support for a wide variety of metrics, application performance monitoring (APM) and centralized logging, and mature monitor types, ensure our telemetry can scale alongside the codebase Low adoption cost: integrating new services with our existing Datadog configuration is trivial After building an MVP, our baseline instrumentation included typical system level metrics, such as load average, CPU utilization, and used memory, as well as custom metrics for all requests like duration and status code. Such metrics enabl [Next page]()