New feature: PostgreSQL Magic Dashboard in AppSignal for Node
Today, we’ve added a magic dashboard to the Node integration that shows you the performance and volume of your PostgreSQL queries.
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Node.js Logging Guide-Best Tips and Tools to Use in 2020
When applications experience performance issues, developers may rely on heuristics and find the root cause of issues by directly looking into their code. However, in modern application environments, several services, third-party APIs, and cloud-based components can make it difficult to pinpoint the root cause of an issue. Application logs can help developers detect and resolve issues faster.
Serverless Most Popular Programming Languages
About 90% of all Lambda functions monitored by Dashbird on AWS Lambda are running Nodejs and Python runtimes. Is this purely a reflection of the general popularity of these programming languages?
New Integration: PostgreSQL Instrumented for Node.js
Today’s release of Node.js integration supports PostgreSQL as well as all the consumers of the pg library.
Avoiding Memory Leaks in NodeJS: Best Practices for Performance
Memory leaks are something every developer has to eventually face. They are common in most languages, even if the language automatically manages memory for you. Memory leaks can result in problems such as application slowdowns, crashes, high latency, and so on. In this blog post, we will look at what memory leaks are and how you can avoid them in your NodeJS application. Though this is more focused on NodeJS, it should generally apply to JavaScript and TypeScript as well.
An Exploration of Runtime Metrics: Node's Event Loop
What Are Runtime Metrics? Runtime metrics can help us understand how an application is performing. SolarWinds® AppOptics™, a SaaS-based, full-stack infrastructure and application monitoring tool, now reports four categories of runtime metrics: CPU, memory, garbage collection times, and event loop times. Each metric category provides a view into how resources are used by an application.
NodeJS Instrumentation - Adding Custom Tags to Spans | Datadog Tips & Tricks
In part 1 of this 4 part series, you’ll learn how to use manual instrumentation to add additional detail to traces. We’ll add new tags, or attributes, to the spans generated by our NodeJS application, allowing for more insightful data visualizations in App Analytics.
NodeJS Instrumentation - Creating Custom Spans for Method-Level Visibility | Datadog Tips & Tricks
In part 2 of this 4 part series, you’ll learn how to instrument your NodeJS application to capture custom method-level spans, allowing visibility into how specific methods behave in your application. Flame graphs allow for deep insight into the performance of your code. During instrumentation, we can capture custom spans for deeper layers of visibility in the resulting flame graphs. In this video, we use instrumentation to capture a method-level span, allowing us to see the performance of that specific method in our flame graphs in the Datadog UI.
NodeJS Instrumentation - Capturing Performance of External Services | Datadog Tips & Tricks
In part 3 of this 4 part series, you’ll learn how to capture critical APM data—such as hits, errors, and latency—for external service calls, allowing you to track external service SLOs.
NodeJS Instrumentation - Adding Analyzed Spans for Improved Data Analytics | Datadog Tips & Tricks
In part 4 of this 4 part series, you’ll learn how to add Analyzed Spans to your traces to open up even more data search and aggregation capabilities via App Analytics. In this video, we will walk you through how you can turn any span into an Analyzed Span. Analyzed Spans function like the root spans of a trace, allowing us to turn the tags embedded in them into facets for advanced data aggregation and searching in App Analytics. You can check out how to add tags to spans—and how to utilize them in App Analytics—in our first video of the series here (link to the first video).