惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

N
News and Events Feed by Topic
爱范儿
爱范儿
Blog — PlanetScale
Blog — PlanetScale
The GitHub Blog
The GitHub Blog
C
Check Point Blog
小众软件
小众软件
I
InfoQ
罗磊的独立博客
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Engineering at Meta
Engineering at Meta
酷 壳 – CoolShell
酷 壳 – CoolShell
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
Hugging Face - Blog
Hugging Face - Blog
博客园 - 三生石上(FineUI控件)
MyScale Blog
MyScale Blog
The Cloudflare Blog
Last Week in AI
Last Week in AI
腾讯CDC
Y
Y Combinator Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
雷峰网
雷峰网
B
Blog
T
Tailwind CSS Blog
MongoDB | Blog
MongoDB | Blog
A
About on SuperTechFans
D
Docker
博客园 - 司徒正美
博客园_首页
Recent Announcements
Recent Announcements
D
DataBreaches.Net
阮一峰的网络日志
阮一峰的网络日志
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
G
Google Developers Blog
Microsoft Security Blog
Microsoft Security Blog
F
Fortinet All Blogs
Stack Overflow Blog
Stack Overflow Blog
aimingoo的专栏
aimingoo的专栏
N
Netflix TechBlog - Medium
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
博客园 - 聂微东
GbyAI
GbyAI
Jina AI
Jina AI
V
V2EX
Vercel News
Vercel News
IT之家
IT之家
WordPress大学
WordPress大学
M
MIT News - Artificial intelligence
NISL@THU
NISL@THU
V
Visual Studio Blog
C
Cybersecurity and Infrastructure Security Agency CISA

Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - February 2026 Amazon EC2 security: How misconfigured and public AMIs expand your cloud attack surface Enable end-to-end visibility into your Java apps with a single command Measure and improve mobile app startup performance with Datadog RUM Evaluating our AI Guard application to improve quality and control cost Identify untested code across every level of your codebase Make use of guardrail metrics and stop babysitting your releases Monitor Versa Networks SD-WAN performance in Datadog Improve performance and reliability with APM Recommendations Remediate transitive vulnerabilities faster with Datadog Software Composition Analysis Generate audit-ready vulnerability and compliance reports with Datadog Sheets Monitor Fortinet FortiManager performance in Datadog Improve test coverage across codebases with Datadog Code Coverage Move fast, don’t break things: Consistent testing standards at scale Enrich logs with ServiceNow CMDB context before routing to any SIEM or logging tool Monitor Lustre with Datadog Make faster, better product decisions with Datadog Product Analytics Surface and remediate runtime posture issues with Workload Protection Findings Protect agentic AI applications with Datadog AI Guard How to optimize JavaScript code with CSS Trace Google Pub/Sub workloads in Cloud Run with Datadog Detect human names in logs with ML in Sensitive Data Scanner How we cut our NLQ agent debugging time from hours to minutes with LLM Observability Debug PostgreSQL query latency faster with EXPLAIN ANALYZE in Datadog Database Monitoring Datadog acquires Propolis Unify and correlate frontend and backend data with retention filters Scale compliance across global frameworks with Datadog Cloud Security Monitor Arista VeloCloud SD-WAN performance with Datadog Building reliable dashboard agents with Datadog LLM Observability Simplify log collection and aggregation for MSSPs with Datadog Observability Pipelines Mitigation for Node.js denial-of-service vulnerability affecting Datadog APM Automate flaky test fixes with the Bits AI Dev Agent and Test Optimization How we built an AI SRE agent that investigates like a team of engineers Datadog integrations 2025 recap: Observability for AI, security, and hybrid cloud Design effective executive dashboards with Datadog Implement dbt data quality checks with dbt-expectations Bring faster visibility into AWS Lambda functions with remote instrumentation Troubleshoot faster with the GitLab Source Code integration in Datadog How Cambia Health Solutions saved $30,000 monthly with Cloud Cost Management and the Datadog Resource Catalog Normalize any logs for Cloud SIEM with Datadog's OCSF processor Optimizing Datadog at scale: Cost-efficient observability at Zendesk Detect, diagnose, and resolve network issues easily with CNM Network Health Connect engineering errors to user impact in early-stage products Cilium configuration for Kubernetes operations at scale Designing feedback loops for progressive delivery Ship features faster and safer with Datadog Feature Flags Choosing the right OpenTelemetry Collector distribution Route your monitor alerts with Datadog monitor notification rules Automate Cloud SIEM investigations with Bits AI Security Analyst Cloud threat detection: How to identify risky activity across control and data planes Collecting Kafka performance metrics Monitoring Kafka with Datadog Monitoring Kafka performance metrics
Build Vega-Lite visualizations natively in Datadog with the Wildcard widget
2025-05-28 · via Datadog | The Monitor blog
Candace Shamieh

Candace Shamieh

Amy Zhou

Amy Zhou

Datadog dashboards provide a unified view of your applications, infrastructure, logs, and other observability data—making it easy to monitor health, investigate issues, and share insights across teams. While native Datadog widgets support a broad range of visualization types, some use cases call for more customized representations, particularly when you’re working with unconventional data formats, external sources, or specific transformations. Whether you’re visualizing performance patterns, grouped metrics, or enriched datasets, having more control over how your data is displayed can help surface insights that standard charts may not reveal.

To support these advanced visualization needs, we’re proud to announce the Wildcard widget. Using the open source Vega-Lite grammar of graphics, the Wildcard widget enables you to build custom, code-defined visualizations directly in Datadog dashboards and notebooks.

In this post, we’ll discuss how the Wildcard widget enables you to create bespoke visualizations by using Vega-Lite syntax and enrich, preview, and refine your visualizations with built-in tooling.

Code custom visualizations with Vega-Lite

The Wildcard widget is the first Datadog widget that enables you to code your own custom visualizations. Using Vega-Lite—a declarative language for building expressive, interactive graphics—you can render visualizations that are tailored to your specific use case, including grouped bar charts, textual scatterplots, 3D geomaps, clock visualizations, and more.

The Vega-Lite integration brings the full flexibility of the grammar-of-graphics model to Datadog. You can define visual encodings, scales, axes, legends, and interactive behaviors—all through a clean JSON specification. This makes it possible to create layered or faceted charts, use multiple mark types (such as bar and line overlays), or highlight subsets of data conditionally.

Because the Wildcard widget integrates into existing dashboards, you can supplement your out-of-the-box monitoring views with completely customized graphics. Datadog-specific visualizations can be built, like categorical heatmaps, which provide a compact, scannable view of high-cardinality data. For example, you can design a categorical heatmap that enables you to track the number of pull requests closed per day across dozens of repositories.

View of a category heatmap that displays the number of PRs closed per day in each repository

Instead of trying to analyze a timeseries containing over 20 lines, the heatmap makes it easy to compare repository activity at a glance.

Enrich, preview, and refine visualizations with built-in tooling

The Wildcard widget contains a powerful query editor that gives you full control over how your data is presented. The editor enables you to perform complex data transformations, join internal data with external sources to enrich your visualizations by using Datadog Reference Tables, and choose your preferred data format, such as scalar, timeseries, events (list), or histogram.

The query editor’s capabilities enable you to build layered, meaningful visualizations. For example, you can create interactive geomaps that visualize system health for your organization’s warehouses across the globe, combining infrastructure metrics with location data pulled from external sources.

View of an interactive geomap that displays the locations of providers based in Europe

The Wildcard widget takes advantage of Vega-Lite’s conditional formatting capabilities. You can customize the format of text and numbers, making it easier for you to understand your data at a quick glance.

To help you design accurate visualizations, the query editor also includes a Data Preview feature. Data Preview enables you to validate that your data will appear in the right shape before rendering. It also includes shortcuts for quickly mapping fields to encodings, like adding a data column to a color encoding with a single click.

View of the built-in Data Preview tool that ensures a timeseries query appears in the right shape before rendering

For example, you can use Vega-Lite layering capabilities to create a histogram that compares error durations to overall trace durations. By visually overlapping these distributions, you can quickly identify anomalies or performance outliers.

When you need to edit a visualization, you can use the Wildcard widget’s command palette, a built-in menu that provides convenient shortcuts for making common configuration changes.

View of the built-in command palette tool that enables you to make common configuration changes in a few clicks

With the ability to rearrange axes, modify color schemes, or add tooltips in a few clicks, you can iterate on designs and fine-tune your visualizations faster.

Build more expressive dashboards today

The Wildcard widget expands upon Datadog’s native widget capabilities, enabling you to create highly customized, code-defined visualizations by using the flexibility of Vega-Lite. Whether you’re exploring massive trace datasets, analyzing from external sources, or just taking more control over how your data is visualized, the Wildcard widget helps you turn complexity into clarity.

To get started, visit the Wildcard widget documentation. Looking for inspiration? Check out our examples gallery and Vega-Lite’s public gallery. If you’re new to Datadog, sign up for a 14-day free trial and begin building your own custom visualizations today.