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

Martin Fowler
Martin Fowler
Webroot Blog
Webroot Blog
博客园 - 叶小钗
阮一峰的网络日志
阮一峰的网络日志
V
V2EX
雷峰网
雷峰网
Apple Machine Learning Research
Apple Machine Learning Research
博客园 - 【当耐特】
Hugging Face - Blog
Hugging Face - Blog
美团技术团队
云风的 BLOG
云风的 BLOG
IT之家
IT之家
S
Secure Thoughts
U
Unit 42
G
GRAHAM CLULEY
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
N
News and Events Feed by Topic
The Cloudflare Blog
月光博客
月光博客
V
Visual Studio Blog
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
Schneier on Security
Schneier on Security
O
OpenAI News
Hacker News - Newest:
Hacker News - Newest: "LLM"
P
Privacy International News Feed
The Hacker News
The Hacker News
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
T
Tailwind CSS Blog
SecWiki News
SecWiki News
M
MIT News - Artificial intelligence
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Simon Willison's Weblog
Simon Willison's Weblog
Stack Overflow Blog
Stack Overflow Blog
爱范儿
爱范儿
Last Week in AI
Last Week in AI
C
Check Point Blog
D
Docker
Scott Helme
Scott Helme
Engineering at Meta
Engineering at Meta
博客园_首页
W
WeLiveSecurity
MongoDB | Blog
MongoDB | Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
V
Vulnerabilities – Threatpost
D
Darknet – Hacking Tools, Hacker News & Cyber Security
J
Java Code Geeks
NISL@THU
NISL@THU
S
Security Affairs
C
Cybersecurity and Infrastructure Security Agency CISA
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More

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
Create and navigate a documentation library with Notebooks
2022-02-24 · via Datadog | The Monitor blog

Datadog Notebooks enable your teams to create and manage key reports and documentation as they build out, monitor, and maintain their infrastructure. Notebooks can include both text and graphs of any telemetry data you have collected in Datadog, and they support collaborative editing so that multiple team members can edit and leave comments simultaneously.

Today, we’re excited to share a new Notebooks landing page that allows your teams to create and access standardized notebooks from a single place. In this post, we’ll discuss how you can now:

Standardize your notebooks with templates

Notebooks often include key data about investigations or incidents that can be used to make decisions, so it’s important to establish best practices for their content and format. This helps ensure, for example, that every postmortem contains a full account of how an issue was remediated, which can inform your team’s response to similar incidents in the future. Datadog now enables you to standardize your documentation by providing a template gallery of postmortems, RFCs, runbooks, and more, and you can also create custom templates from scratch in order to meet your team’s specific needs.

Browsing Notebook templates

Templating enables you to wireframe documentation procedures for use across your organization. For example, you could create a “Weekly Quality of Service Report” template to measure frontend performance, availability, and errors, which might include weekly follow-up actions, metric graphs, and other visualizations.

Creating a new custom Notebook template

You can also assign a type to any notebook template, or leverage automatic typing based on your notebook’s title. For instance, the “Weekly Quality of Service Report” template would automatically receive the “report” type label. Typing enables you to keep your documentation organized so you can easily find specific notebooks in the future.

Notebook templates are tightly integrated with Datadog Incident Management, so you can seamlessly pivot from viewing incident data to documenting this data in your postmortems. To auto-generate standardized postmortems, simply go to Postmortem Templates in Incidents Settings. Datadog Incident Management will automatically populate a new Notebook with key data, such as the incident impact, root cause, timeline, and post-incident tasks, after the incident has been resolved. For more information on using Incident Management with Datadog Notebooks, see our blog post.

The new Notebooks List shows all your team’s notebooks in one filterable view, so you can easily find the information you’re looking for. For instance, the type label we discussed above enables you to drill down to the type of notebook you’re most interested in. You can also home in on the notebooks you’ve created yourself or filter the list using a keyword search.

Browse, search, and filter your Notebooks from the Notebooks List

These search features help your team members quickly gather the most relevant information as they monitor your applications and respond to incidents. For instance, if one of your services is experiencing prolonged downtime, you’ll want to quickly find all postmortems for that service in order to determine whether a similar issue has cropped up in the past. In the screenshot above, we filtered the Notebooks List to show postmortems, and queried for the name of our service—in this case, “checkout.” The resulting list of notebooks provides full historical context of the current issue, which can accelerate our resolution time.

Browse without leaving a trace

It’s important for your team members to be able to browse their notebooks quickly in time-sensitive situations, but you should also have guard rails in place to maintain the quality of your documentation. Once you’ve drilled down to the notebooks you’re most interested in, you can leverage several new features that make browsing easier and less error-prone. Notebooks in the table now show a preview when you hover over them, enabling you to scan through a document’s content before you pull it up. We’ve also included an option to open notebooks in view-only mode, so you can leave comments without having to worry about making accidental edits. These new improvements help ensure that your notebooks remain high-quality as team members repeatedly reference them over time.

Viewing a preview of a notebook's headers from the Notebooks List

Get started with the new Notebooks landing page

The new Notebooks landing page makes it easier than ever to create and maintain standardized, high-quality internal documentation that can guide your team’s monitoring and troubleshooting efforts. For more information on using Datadog Notebooks, see our documentation. Or, if you’re brand new to Datadog, get started with a 14-day free trial.