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

Y
Y Combinator Blog
GbyAI
GbyAI
爱范儿
爱范儿
H
Hackread – Cybersecurity News, Data Breaches, AI and More
C
Check Point Blog
M
MIT News - Artificial intelligence
量子位
宝玉的分享
宝玉的分享
MongoDB | Blog
MongoDB | Blog
V
Visual Studio Blog
罗磊的独立博客
F
Fortinet All Blogs
美团技术团队
博客园_首页
博客园 - 【当耐特】
L
LangChain Blog
月光博客
月光博客
腾讯CDC
The Cloudflare Blog
D
Docker
博客园 - 聂微东
Stack Overflow Blog
Stack Overflow Blog
WordPress大学
WordPress大学
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报

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 Google App Engine with Datadog
2014-11-05 · via Datadog | The Monitor blog
Matt Williams

Matt Williams

Editor’s note (May 2021): The text below has been modified to reflect our new integration setup instructions. See our documentation for more details about this integration.

With the release of our Google App Engine (GAE) integration, Datadog has joined the Google Cloud Platform ecosystem. This release allows you to visualize, analyze, and alert on the performance metrics from your Google Cloud Platform infrastructure as well as custom metrics from GAE applications.

Setup and configuration

If you are new to Datadog, create an account and install the Google Cloud Platform integration from the Integrations page. You can also find more detailed instructions in our documentation. Once you’ve configured the integration, Datadog will start collecting metrics on responses, Memcache statistics, task queues, and other data from your App Engine standard and flex environments.

You can also collect custom metrics using the various DogStatsD or API libraries. Google App Engine supports applications written with Python, Java, PHP, and Go and we have libraries available for each of these languages.

Monitoring your Google App Engine applications

Once you’ve enabled our Google App Engine integration, you will see an out-of-the-box dashboard that gives you a pre-configured look at the key metrics, including enhanced latency metrics (p95 and p99 aggregations).

Every project and software version is tagged uniquely, such as project:web_router or version_id:1.0.34.2. And since one of the features of Google App Engine is the ability to gradually migrate visitors to your site from one version to another, you could overlay your dashboard metric graphs with the percentage of users on the newest platform.

Of course, when monitoring Google serverless applications with Datadog, you’ll be able to visualize and alert on data from multiple cloud providers and on-premise servers, correlate data to identify the root cause of issues, and more—all in one place. If you’d like to monitor Google App Engine and the rest of your Google Cloud environment, sign up for a free 14-day trial.