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

Security Archives - TechRepublic
Security Archives - TechRepublic
罗磊的独立博客
T
The Blog of Author Tim Ferriss
The GitHub Blog
The GitHub Blog
Apple Machine Learning Research
Apple Machine Learning Research
The Register - Security
The Register - Security
J
Java Code Geeks
V2EX - 技术
V2EX - 技术
Vercel News
Vercel News
N
News and Events Feed by Topic
腾讯CDC
P
Proofpoint News Feed
N
News | PayPal Newsroom
www.infosecurity-magazine.com
www.infosecurity-magazine.com
爱范儿
爱范儿
O
OpenAI News
酷 壳 – CoolShell
酷 壳 – CoolShell
月光博客
月光博客
Martin Fowler
Martin Fowler
Engineering at Meta
Engineering at Meta
D
Docker
Y
Y Combinator Blog
博客园 - 聂微东
G
Google Developers Blog
S
Security @ Cisco Blogs
Simon Willison's Weblog
Simon Willison's Weblog
S
Schneier on Security
H
Hackread – Cybersecurity News, Data Breaches, AI and More
S
SegmentFault 最新的问题
云风的 BLOG
云风的 BLOG
阮一峰的网络日志
阮一峰的网络日志
C
CXSECURITY Database RSS Feed - CXSecurity.com
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
C
CERT Recently Published Vulnerability Notes
I
Intezer
G
GRAHAM CLULEY
有赞技术团队
有赞技术团队
Attack and Defense Labs
Attack and Defense Labs
V
Visual Studio Blog
博客园 - Franky
博客园 - 三生石上(FineUI控件)
W
WeLiveSecurity
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
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
Hugging Face - Blog
Hugging Face - Blog
Scott Helme
Scott Helme
T
Troy Hunt's Blog
Hacker News - Newest:
Hacker News - Newest: "LLM"
L
LINUX DO - 最新话题
C
Cybersecurity and Infrastructure Security Agency CISA

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 Sidekiq with Datadog
Kai Xin Tai · 2020-05-04 · via Datadog | The Monitor blog
Kai Xin Tai

Kai Xin Tai

Sidekiq is a Ruby framework for background job processing. Developers can use Sidekiq to asynchronously run computationally intensive tasks—such as bulk email sending, payment processing, and data importing—to help speed up the response times of their applications.

If you’re using Sidekiq Pro or Enterprise, Datadog’s integration helps you monitor the progress of your jobs and the applications that depend on them, all in a single platform. Once you’re collecting metrics from Sidekiq, you can immediately visualize them in a customizable out-of-the-box dashboard. Additionally, if you enable the collection of logs and distributed traces, you can correlate them with metrics to investigate issues such as failed jobs, backlogged queues, and resource-intensive processes.

Datadog displays key Sidekiq metrics in a customizable out-of-the-box dashboard.

Track the progress of jobs and alert on any failures

Sidekiq leverages Redis as an in-memory data store to hold its jobs in queues until they are ready to be processed. Each Sidekiq worker fetches one job at a time from a queue and processes it. Before a Sidekiq job completes, it moves through a series of possible states, such as Enqueued, Scheduled, and Busy. And if any errors arise during the processing of a job, it is automatically retried up to 25 times before it terminates and enters the Dead state.

Datadog’s out-of-the-box dashboard shows how often jobs have succeeded and failed, as well as how many jobs are queued, waiting to be processed. You can also set up alerts to be automatically notified of potential issues, such as when there is an anomalous spike in overall job retries (sidekiq.retries) or failures (sidekiq.failures), so you can begin troubleshooting right away. This helps you keep tabs on whether your jobs are being executed as expected and ensure that you’re meeting your service level agreements (SLAs).

Set up a monitor to detect anomalies in failed jobs.

Effectively troubleshoot congested queues

If your application experiences a surge in traffic—and your workers are not able to keep up with the rate of incoming jobs—your queues can start to become backlogged. As your queues grow, Redis could potentially run out of memory and begin swapping idle pages to disk, resulting in a significant increase in latency. To prevent Sidekiq data from being dropped when Redis’s memory limit has been reached, Sidekiq recommends setting the maxmemory-policy parameter in Redis to noeviction.

Correlate queue size with Redis memory usage to identify bottlenecks in your job workflows.

Datadog also includes built-in support for Redis so you can correlate the number of queued Sidekiq jobs (sidekiq.enqueued) with the amount of memory used by Redis (redis.mem.used) to determine whether your job processor is able to keep up with its workload. If memory is a bottleneck, you can consider provisioning more resources to your Redis instance or partitioning jobs across multiple Redis instances. To learn more about other key Redis metrics you should monitor, see our guide.

Investigate long-running Sidekiq jobs

Slow jobs will delay other jobs in the queue from starting, so you should monitor Sidekiq job latency and troubleshoot any issues as soon as possible. Datadog APM auto-instruments your Ruby applications so you can quickly start tracing all your Sidekiq jobs as they propagate across your infrastructure. By inspecting the traces of long-running jobs, you can easily determine if time is mostly spent in Sidekiq itself or in external services—and drill into particular problem areas.

Use Datadog APM to drill down to specific spans that are contributing to your Sidekiq job’s latency

Long-running jobs risk timing out before they complete, which is why Sidekiq generally recommends breaking large jobs down into smaller jobs that can be processed in parallel. For instance, instead of running one job to send an email notification to all your users, it is better to create a batch of jobs that each send one email. This way, you are able to leverage concurrency to speed up processing without losing the ability to monitor similar types of tasks as a group.

Start monitoring Sidekiq

Whether you have hundreds—or hundreds of thousands—of jobs, Datadog’s Sidekiq integration provides the metrics, logs, and distributed traces you need to comprehensively monitor your deployment in real time. If you’re already using Datadog, check out our documentation to learn how you can start monitoring Sidekiq alongside Redis and 1,000+ other technologies. Otherwise, sign up for a 14-day free trial today.