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

S
Secure Thoughts
Recent Commits to openclaw:main
Recent Commits to openclaw:main
H
Heimdal Security Blog
SecWiki News
SecWiki News
H
Hacker News: Front Page
N
News | PayPal Newsroom
L
LINUX DO - 最新话题
N
News and Events Feed by Topic
TaoSecurity Blog
TaoSecurity Blog
AI
AI
C
Cybersecurity and Infrastructure Security Agency CISA
Scott Helme
Scott Helme
PCI Perspectives
PCI Perspectives
S
Securelist
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
Cyberwarzone
Cyberwarzone
A
Arctic Wolf
Forbes - Security
Forbes - Security
T
Tor Project blog
Spread Privacy
Spread Privacy
WordPress大学
WordPress大学
I
Intezer
Martin Fowler
Martin Fowler
Help Net Security
Help Net Security
P
Proofpoint News Feed
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
Cisco Talos Blog
Cisco Talos Blog
Latest news
Latest news
博客园 - 司徒正美
W
WeLiveSecurity
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
V
V2EX
P
Palo Alto Networks Blog
Google DeepMind News
Google DeepMind News
IT之家
IT之家
阮一峰的网络日志
阮一峰的网络日志
V
Vulnerabilities – Threatpost
Jina AI
Jina AI
S
Security Affairs
Hacker News - Newest:
Hacker News - Newest: "LLM"
Simon Willison's Weblog
Simon Willison's Weblog
Project Zero
Project Zero
T
Threatpost
P
Privacy International News Feed
人人都是产品经理
人人都是产品经理
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
Application and Cybersecurity Blog
Application and Cybersecurity Blog
博客园 - Franky
Hugging Face - Blog
Hugging Face - Blog
Apple Machine Learning Research
Apple Machine Learning Research

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 your Redis Enterprise clusters with Datadog
2022-04-15 · via Datadog | The Monitor blog

Redis is an in-memory key-value data store that offers fast performance, flexible data structures, and multi-model databases, allowing it to handle a variety of use cases. Redis Enterprise enhances open source Redis with features designed to run distributed applications at scale, such as multi-tenancy, tiered data storage, active-active cluster replication, and support for up to five 9s of availability.

Our new Redis Enterprise integration provides vital KPIs for Enterprise-specific features, helping you monitor the health and efficiency of your databases. You can access a variety of out-of-the-box dashboards, including the Cluster Top View dashboard below, to evaluate the state of your cluster. In this article, we’ll explore how this integration allows you to:

Redis Enterprise Cluster Top View dashboard.

Optimize database performance across your cluster

Database clustering in Redis Enterprise enables you to distribute your databases across multiple nodes for linear scalability over both CPU and RAM.

The Redis Enterprise integration provides dashboards that help you track performance for all multi-tenant databases in your clusters. The Database Overview dashboard displays capacity metrics, such as RAM utilization, to help you gain insight into your workload–and the ability of your Redis database to handle it. The dashboard also enables you to track metrics like latency and cache-hit ratios, so you can proactively identify problems and ensure a smooth user experience.

Redis Enterprise Database Overview dashboard.

Redis Enterprise supports multi-tier storage through Redis on Flash (RoF), reducing storage costs without impacting overall performance. The new Redis Enterprise Flash dashboard allows you to visualize internal tiering metrics as data is moved between RAM and SSD storage. It also displays other metrics, such as average latency across your RoF databases, that can help you quickly assess the performance of your cluster.

Redis Enterprise Flash dashboard.

To stay on top of issues, you can create monitors that alert you when KPIs fail to meet performance standards. When a monitor notifies you of unusual activity, you can dig into metrics to determine the root cause and assess possible remediation strategies. For example, you can set up an alert to get notified when memory usage exceeds 80 percent, the Redis-recommended threshold. If you get alerted, you can check whether there has been a recent spike in the number of operations per second or if data is being evicted. You can then decide whether you need to take action to remediate the issue (e.g., by raising the memory limit of your database). Datadog also tracks significant cluster events, such as upgrades, deletions, and failovers, so you have complete context for rapid troubleshooting.

Visualize the health of your Redis Enterprise clusters

For a complete picture of system health, you need deep visibility into your entire Redis Enterprise cluster. The integration gathers crucial metrics into a Cluster Top View dashboard, supplying a quick summary of the state of your system. Shard counts help you manage how your data is distributed, while capacity data—such as node counts and memory usage (shown below)—help you evaluate whether your cluster has sufficient resources to handle your workload.

Graph showing memory usage percentages across different databases.

You can also pivot to the Database Overview dashboard to see if certain databases are consuming more resources than the rest, allowing you to identify and prioritize areas of optimization.

Additionally, the integration helps you ensure that your databases are highly available and consistent. Redis Enterprise enables you to create geo-distributed Active-Active databases that make it easy to deploy your application across regions, giving you improved reliability and performance. Active-Active databases use Conflict-free Replicated Data Types (CRDT) to keep your data centers in sync. The Active-Active Statistics dashboard allows you to monitor pending writes and lag time, so you can make sure your databases aren’t drifting apart. You can also monitor incoming and outgoing network traffic, which can be a potential indicator of database issues.

Redis Enterprise Active/Active Statistics dashboard.

Get started with the Redis Enterprise integration

With comprehensive metrics and out-of-the-box dashboards, Datadog provides insight into the health and performance of your Redis Enterprise clusters. The integration comes with automated discovery of multi-tenant databases for simple setup.

Check out our documentation to start monitoring your Redis Enterprise clusters. If you’re new to Datadog, you can sign up for a 14-day free trial.