Sysdig achieved the Amazon Web Services (AWS) Cloud Operations Competency in the categories of Compliance and Auditing and Monitoring and Observability.
The new AWS Cloud Operations Competency allows customers to select validated AWS Partners who offer comprehensive solutions with an integrated approach across all five solution areas of Cloud Operations: Cloud Financial Management, Cloud Governance, Monitoring and Observability, Compliance and Auditing, and Operations Management. As an AWS Cloud Operations Competency Partner, Sysdig has demonstrated expertise in helping customers build a strong and scalable foundation for their end-to-end Cloud Operations. Sysdig previously achieved six other AWS Competency designations.
AWS Cloud Operations Competency Partners have proven customer success in delivering solutions to help customers set up, build, migrate, and operate securely and efficiently with an integrated approach to Cloud Operations.
The AWS Cloud Operations Competency differentiates AWS Partner Network (APN) members with significant expertise in providing cross-functional guidance across the five solution areas of Cloud Operations. Sysdig follows AWS best practices and has proven experience in:
- Compliance and Auditing — Sysdig Secure allows customers to easily implement compliance processes faster. Customers can automate processes, continually oversee the compliance posture of their AWS resources, and automatically collect evidence to improve their audit readiness and ongoing real-time internal reporting and monitoring.
- Monitoring and Observability — Sysdig Monitor has a proven track record of helping customers use observability services to understand what is happening across their technology stack at any time, leveraging AWS-native services, Application Performance Monitoring (APM), and open-source solutions. With validated AWS Partners, customers can get an end-to-end view into events in cloud, hybrid, or on-premises environments. They also gain insights into the behavior, performance, and health of their systems to reduce time to detect and resolve issues.
AWS is enabling scalable, flexible, and cost-effective solutions from startups to global enterprises. To support the seamless integration and deployment of these solutions, AWS established the AWS Competency Program to help customers identify AWS Partners with deep industry experience and expertise.
Sysdig secures cloud innovation with the power of runtime insights. By applying visibility from runtime across the software lifecycle, Sysdig Secure helps security and DevSecOps teams prioritize risk to prevent, detect, and respond at cloud speed. Organizations running applications on AWS can manage cloud security posture, implement continuous compliance, automate the enforcement of governance, and pass audits with detailed evidence.
Sysdig also radically simplifies cloud and Kubernetes monitoring and helps lower costs with deep visibility into cloud-native workloads. Sysdig allows AWS customers to get insights into cloud health and performance at scale with observability based on open standards, including open source Prometheus. Unlike other tools that provide limited Kubernetes detail, Sysdig Monitor displays all important information in a single unified view with actionable remediation steps. Cost-saving recommendations based on utilization metrics help DevOps teams prioritize rightsizing efforts to save an average of 40 percent on their cloud bills.
“Attaining the AWS Cloud Operations Competency speaks to the deep expertise of the Sysdig solution. Customers know when they choose Sysdig, they are getting a solution that can help them achieve their cloud goals,” said Phil Williams, SVP, Corporate Development & Alliances, Sysdig. “Sysdig provides a comprehensive solution that brings security and observability to cloud environments. Our customers find value in our ability to detect threats faster, instantly detect risk changes, and prioritize what really matters.”
The Latest
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.