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Chainguard Partners with Datadog

Chainguard announced a partnership with Datadog. 

Together, Chainguard and Datadog will combine container observability with clear, prioritized actions to help engineering and security teams eliminate common vulnerabilities and exploits (CVEs), and improve software development velocity. Through a new Chainguard dashboard in Datadog, customers can gain real-time insights into container risks, receive clear remediation recommendations, and seamlessly transition to more secure alternatives — accelerating software delivery while reducing security threats.

The integration between Chainguard and Datadog enhances  Datadog's core container observability with new visibility and associated risk remediation potential, surfaced in a dashboard. The Chainguard dashboard organizes container metrics to understand where Chainguard is being used today and identifies environments where a more secure base image is available.

The dashboard will be available to all Datadog customers, offering a holistic view of existing container infrastructure and associated CVE risks, including:

  • Containers built using Chainguard images
  • Longest running container images
  • Vulnerabilities in most widely-used images
  • Chainguard alternatives for insecure container images

"Through our partnership with Datadog, we're combining leading observability with secure, minimal container solutions," said Kim Lewandowski, Chief Product Officer and Co-founder at Chainguard. "Chainguard is building the safe source for open source so customers can build more efficiently and securely from the start. Datadog is leading the way in observability and monitoring across cloud infrastructure. Together, we're empowering companies of all sizes to build software better."

"Tens of thousands of organizations rely on Datadog every day for real-time risk monitoring and visibility into the health and performance of their containerized environments," said Bharat Sajnani, Senior Vice President, Head of Corporate Development and Platform at Datadog. "With our integration with Chainguard, our customers can identify CVE risks within their container infrastructure, seamlessly pinpoint alternatives, and measure progress in implementing these minimal CVE container images. Together, we're helping companies make their container infrastructure more secure while making the most of their engineering resources."

With Chainguard and Datadog's integration, joint customers benefit from reduced risk across their application surface area. Now, security teams can move from reactive alerts to proactive risk reduction by identifying and prioritizing CVE remediation in their most widely deployed and high-risk containers. As a result, engineering teams will spend less time patching one-off containers, so organizations can redirect development resources and ship secure software faster.

The Chainguard and Datadog integration is now generally available. 

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Chainguard Partners with Datadog

Chainguard announced a partnership with Datadog. 

Together, Chainguard and Datadog will combine container observability with clear, prioritized actions to help engineering and security teams eliminate common vulnerabilities and exploits (CVEs), and improve software development velocity. Through a new Chainguard dashboard in Datadog, customers can gain real-time insights into container risks, receive clear remediation recommendations, and seamlessly transition to more secure alternatives — accelerating software delivery while reducing security threats.

The integration between Chainguard and Datadog enhances  Datadog's core container observability with new visibility and associated risk remediation potential, surfaced in a dashboard. The Chainguard dashboard organizes container metrics to understand where Chainguard is being used today and identifies environments where a more secure base image is available.

The dashboard will be available to all Datadog customers, offering a holistic view of existing container infrastructure and associated CVE risks, including:

  • Containers built using Chainguard images
  • Longest running container images
  • Vulnerabilities in most widely-used images
  • Chainguard alternatives for insecure container images

"Through our partnership with Datadog, we're combining leading observability with secure, minimal container solutions," said Kim Lewandowski, Chief Product Officer and Co-founder at Chainguard. "Chainguard is building the safe source for open source so customers can build more efficiently and securely from the start. Datadog is leading the way in observability and monitoring across cloud infrastructure. Together, we're empowering companies of all sizes to build software better."

"Tens of thousands of organizations rely on Datadog every day for real-time risk monitoring and visibility into the health and performance of their containerized environments," said Bharat Sajnani, Senior Vice President, Head of Corporate Development and Platform at Datadog. "With our integration with Chainguard, our customers can identify CVE risks within their container infrastructure, seamlessly pinpoint alternatives, and measure progress in implementing these minimal CVE container images. Together, we're helping companies make their container infrastructure more secure while making the most of their engineering resources."

With Chainguard and Datadog's integration, joint customers benefit from reduced risk across their application surface area. Now, security teams can move from reactive alerts to proactive risk reduction by identifying and prioritizing CVE remediation in their most widely deployed and high-risk containers. As a result, engineering teams will spend less time patching one-off containers, so organizations can redirect development resources and ship secure software faster.

The Chainguard and Datadog integration is now generally available. 

The Latest

IT organizations have historically measured success by how quickly they can respond when something goes wrong. The entire discipline of Incident Management has been optimized around mean time to resolution, first-response SLAs and ticket closure rates. But new research suggests that even though this is a well-executed playbook, it's no longer enough to retain customers ...

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...