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

AI
AI
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
Google DeepMind News
Google DeepMind News
T
Tenable Blog
博客园_首页
S
Securelist
Spread Privacy
Spread Privacy
Google Online Security Blog
Google Online Security Blog
Forbes - Security
Forbes - Security
Engineering at Meta
Engineering at Meta
U
Unit 42
L
LINUX DO - 热门话题
量子位
T
Threat Research - Cisco Blogs
博客园 - 【当耐特】
C
Cyber Attacks, Cyber Crime and Cyber Security
K
Kaspersky official blog
MyScale Blog
MyScale Blog
P
Proofpoint News Feed
The Last Watchdog
The Last Watchdog
Google DeepMind News
Google DeepMind News
GbyAI
GbyAI
Martin Fowler
Martin Fowler
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
Security Latest
Security Latest
Scott Helme
Scott Helme
V
Vulnerabilities – Threatpost
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
I
InfoQ
Know Your Adversary
Know Your Adversary
Cisco Talos Blog
Cisco Talos Blog
The Register - Security
The Register - Security
T
The Blog of Author Tim Ferriss
aimingoo的专栏
aimingoo的专栏
V2EX - 技术
V2EX - 技术
T
Tailwind CSS Blog
月光博客
月光博客
Recent Announcements
Recent Announcements
G
Google Developers Blog
F
Full Disclosure
W
WeLiveSecurity
宝玉的分享
宝玉的分享
腾讯CDC
G
GRAHAM CLULEY
Vercel News
Vercel News
Simon Willison's Weblog
Simon Willison's Weblog
美团技术团队
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Help Net Security
Help Net Security

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
Monitor AWS SES with Datadog
Abril Loya McCloud · 2016-06-10 · via Datadog | The Monitor blog
Abril Loya McCloud

Abril Loya McCloud

Amazon Simple Email Service (SES) is a scalable, affordable email service for outbound emails. SES provides a flexible SMTP or API-based email solution that can easily scale to any size.

As part of AWS, SES integrates with several AWS services you may already be using. These services include, but are not limited to: EC2 instances, Elastic Beanstalk, AWS SNS, AWS S3, AWS KMS, CloudTrail, and the Management Console. Its affordability, reliability, and native integration with other AWS services make SES a highly popular outbound mass email service.

Datadog integrates with AWS SES, allowing you to receive alerts on all aspects of your SES performance.

Monitor AWS SES

When you integrate SES with Datadog, you can monitor your SES metrics according to their respective importance to filter out noise.

The available SES metrics and how they appear in Datadog are listed below:

MetricDescription
aws.ses.max24hour_sendMaximum number of emails that can be sent in a 24 hour period
aws.ses.sentlast24_hoursThe total number of emails sent in the past 24 hours
aws.ses.bouncesThe number of hard bounces
aws.ses.complaintsThe number of complaints
aws.ses.deliveryattemptsThe number of delivery attempts
aws.ses.rejectsRejected send attempts

You can create visualizations to keep track of these metrics over time. These graphs give you better insight into trends in your SES performance and allow you to annotate and collaborate with your team in the case of abnormalities.

monitor aws ses image

Set up

Integrating AWS SES with Datadog is just a click away if you are already set up with the main AWS integration.

Verify that you’ve entered the AWS credentials for each AWS account you would like to send data into Datadog, then click on the AWS SES checkbox under ‘Limit metric collection’ and update your configuration. Once you’ve enabled SES, Datadog will automatically begin to gather your metrics.

Get started

If you’re already a Datadog customer using AWS SES, you can try out the integration today. Otherwise, sign up for a Datadog trial. For information on how to optimally set up monitoring for other AWS technologies you may be using, check out our other AWS articles.