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

博客园_首页
Microsoft Azure Blog
Microsoft Azure Blog
aimingoo的专栏
aimingoo的专栏
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
阮一峰的网络日志
阮一峰的网络日志
Martin Fowler
Martin Fowler
B
Blog
The GitHub Blog
The GitHub Blog
T
Tailwind CSS Blog
Stack Overflow Blog
Stack Overflow Blog
L
LangChain Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
D
DataBreaches.Net
月光博客
月光博客
人人都是产品经理
人人都是产品经理
IT之家
IT之家
GbyAI
GbyAI
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
WordPress大学
WordPress大学
博客园 - Franky
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
The Cloudflare Blog
C
Check Point Blog
罗磊的独立博客

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
CloudCheckr + Datadog: Better rightsizing of cloud resources
2017-03-01 · via Datadog | The Monitor blog

Cloud-based infrastructure is ideal for companies that need to scale up and down quickly to meet demand. However, scalability can come at a high cost as resource consumption balloons and resource management becomes inefficient. CloudCheckr is a web-based platform that allows you to monitor and optimize the cost and performance of your AWS infrastructure by providing customized recommendations. By using Datadog and CloudCheckr together, you can quickly make data-driven decisions based on current and past resource consumption to maintain an agile, cost-effective infrastructure.

Keep your cloud in check

CloudCheckr makes cloud resource management easier by providing historical data, performance trends, and recommendations based on your AWS usage in one dashboard. Datadog’s integration with CloudCheckr provides granular memory usage metrics for every AWS instance, which CloudCheckr uses to better inform its analyses.

Cost optimization

Datadog’s memory data allows you to evaluate how your instances are using critical resources and can signal mismatches between provisioned capacity and utilization. By taking this memory usage data into consideration in their Right-Sizing Report, CloudCheckr provides you with best practice recommendations to rebalance and optimize your instances while saving your organization money. CloudCheckr’s Right-Sizing Report takes both your memory usage data as well as your CPU usage to produce a utilization score in the range of zero to 10. Low-scoring instances are underused while high-scoring instances are being overused, so you can rebalance your instances to improve your AWS performance.

Rightsizing report

Once you have the data to understand and optimize your AWS resource usage, you can set custom alerts in CloudCheckr to track your consumption or spending.

Rightsizing report

Get started

Adding Datadog metrics to CloudCheckr is simple; all you have to do is click into your CloudCheckr Extensions and add your Datadog API and application keys. Within minutes, Datadog metrics will start flowing into your CloudCheckr account.

If you’d like to monitor and optimize your AWS usage, you can sign up for a free Datadog trial and connect it up to CloudCheckr today.