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

奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园 - 司徒正美
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
G
Google Developers Blog
T
Threat Research - Cisco Blogs
Cyberwarzone
Cyberwarzone
罗磊的独立博客
S
Security Affairs
D
Docker
Microsoft Azure Blog
Microsoft Azure Blog
G
GRAHAM CLULEY
W
WeLiveSecurity
博客园 - Franky
C
Check Point Blog
The Last Watchdog
The Last Watchdog
F
Full Disclosure
Security Latest
Security Latest
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
AWS News Blog
AWS News Blog
Application and Cybersecurity Blog
Application and Cybersecurity Blog
T
Troy Hunt's Blog
S
Secure Thoughts
Security Archives - TechRepublic
Security Archives - TechRepublic
P
Privacy & Cybersecurity Law Blog
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
P
Privacy International News Feed
S
Schneier on Security
C
Cyber Attacks, Cyber Crime and Cyber Security
T
Tenable Blog
aimingoo的专栏
aimingoo的专栏
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
Recent Announcements
Recent Announcements
IT之家
IT之家
D
DataBreaches.Net
U
Unit 42
博客园 - 聂微东
H
Hacker News: Front Page
GbyAI
GbyAI
T
The Exploit Database - CXSecurity.com
N
News and Events Feed by Topic
Simon Willison's Weblog
Simon Willison's Weblog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
TaoSecurity Blog
TaoSecurity Blog
Google Online Security Blog
Google Online Security Blog
T
Threatpost
博客园 - 叶小钗
V
V2EX
Hugging Face - Blog
Hugging Face - Blog
K
Kaspersky official blog

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
Introducing a new buildpack for monitoring Heroku applications
2018-06-07 · via Datadog | The Monitor blog

Heroku is a popular platform-as-a-service that simplifies application deployment by automating and abstracting much of the underlying infrastructure required to run those applications. One of those abstractions is Heroku’s buildpack. Buildpacks are discrete, chainable bundles of code that are often used to modify the runtime environment for the application that will be deployed. Rather than performing complex installation and configuration tasks for a particular application or service, users can simply add the buildpack to their project.

We’re pleased to share a new Heroku buildpack that installs the latest version of the Datadog Agent, with added support for distributed tracing and APM in Heroku.

Datadog hostmap with Heroku hosts

Building the buildpack

In 2014, Mike Fiedler wrote the first Heroku buildpack to run a Python-based DogStatsD server, enabling applications on Heroku to send custom metrics to Datadog. As the Datadog Agent evolved to become a pre-compiled Go binary rather than a package of Python scripts, it became clear that the buildpack would need to be rewritten.

Heroku uses a container model to package, deploy, and scale applications. Unlike some container-based platforms, however, Heroku does not allow root access or the ability to write to standard application and configuration directories such as /usr/bin or /etc. This limitation ensures that a slug (Heroku’s term for a container image) deployed to a dyno (a running container) remains isolated from the host machine and other dyno tenants sharing the host. However, this security isolation comes at the cost of some convenience.

The new buildpack and Mike’s original buildpack take a similar approach to the limited-access file system by downloading and installing the Datadog Agent to a non-standard but accessible directory.

Once you have your application running on Heroku, you can use the buildpack to begin collecting application metrics, system metrics, and traces. To learn how to install the buildpack, see the documentation.

Visualizing your Heroku metrics

The Heroku buildpack automatically adds tags for your application name (appname), the dyno name, and the dyno type. The application name and dyno name are particularly helpful for filtering and aggregating metrics. Summing a particular metric by the provided dyno name tag provides visibility into the dyno’s aggregate activity and performance, similar to graphing metrics on a per-host basis when monitoring physical hosts. This helps provide better monitoring continuity as dynos move to new hosts.

If your application cycles dynos frequently, you may see a large number of hostnames emitting metrics to Datadog, which can increase your costs. To prevent this, you can configure the buildpack to report the hostname in the form of app-name.dyno-name, which is a more stable construction since it does not use the name of the ephemeral host. The installation instructions show you how you can do this by setting the DD_DYNO_HOST environment variable to true.

When you use the buildpack to install the Agent, you’ll see host system metrics including CPU, memory, and disk metrics. If you need system metrics from individual dynos, see the documentation.

Give it a try

Heroku is a fantastic service that simplifies deploying applications to a robust and scalable platform. The Datadog buildpack makes it easier to monitor those applications with custom application metrics and distributed tracing. If you’re already a Datadog customer, you can install and deploy the buildpack to monitor your Heroku applications today. If you’re not yet using Datadog, give it a try with a free 14-day trial.