AWS DevOps Agent Customers

As one of the world's leading specialty chemical companies, Clariant contributes to value creation with innovative and sustainable solutions for customers from many industries. Our digital operations support everything from supply chain management to customer portals, and system reliability is critical to serving our customers effectively.Since deploying AWS DevOps Agent integrated with Dynatrace, we've experienced firsthand how the combination transforms our cloud operations. Dynatrace provides comprehensive visibility into our infrastructure and application performance, instantly identifying affected systems and quantifying business impact when issues occur. AWS DevOps Agent then takes this a step further by autonomously investigating our AWS environment — pinpointing specific infrastructure changes and configuration issues causing problems, and delivering actionable mitigation plans. This integration eliminates the need for our operations teams to manually collect data from multiple AWS services or spend valuable time correlating events across different systems.

As a specialty chemicals company with operations spanning multiple continents, reducing the time it takes to understand and address cloud infrastructure issues directly impacts our ability to serve our customers. The automated investigation capabilities from AWS DevOps Agent, combined with the deep observability insights from Dynatrace, have enhanced our IT teams' productivity, while each investigation's detailed findings continuously strengthen our operational knowledge base. These efficient cloud operation tools directly support our broader business objectives as we advance our digital transformation journey in the specialty chemicals industry.“

- Daniel Galera, Senior IT Manager Cloud Engineering, Clariant

Commonwealth Bank of Australia is one of Australia's leading providers of integrated financial services serving over 17 million customers. The bank's Cloud Foundations group manages over 1,700 AWS accounts and provides centralized cloud operation services for thousands of engineers. While prototyping their next-generation internal platform, the team replicated a complex network and identity management issue to test AWS DevOps Agent. These types of issues can take a seasoned DevOps engineer hours to identify, and the agent found the root cause in under 15 minutes. "AWS DevOps Agent thinks and acts like a seasoned DevOps Engineer, helping our engineers build a banking infrastructure that’s faster, more resilient, and designed to deliver better experiences for our customers. This isn't just about faster resolution times—it's about maintaining the trust our customers put in us."

“AWS DevOps Agent's seamless integration with our existing enterprise tools including ServiceNow, Splunk, and our custom MCP servers makes it even more valuable for our operations. For CBA, this opens significant opportunities. We're exploring ways to scale this across our platform teams and help every internal customer leverage these capabilities. The ability to integrate with our existing SLOs through Grafana and Prometheus makes it even more valuable for our operations. AWS DevOps Agent is helping us build a more resilient, efficient banking infrastructure for millions of Australians.”

- Jason Sandery, Head of Cloud Services, Commonwealth Bank of Australia

Deriv is one of the world's largest online brokers, serving more than 3 million traders worldwide. It offers an expansive range of trade types and features over 300 assets across popular markets, available on Deriv's award-winning, intuitive trading platforms. At Deriv, we've built our 25-year legacy on technological innovation and have now embraced an AI-first approach across our operations. Since deploying AWS DevOps Agent, the service has become a core part of our incident response workflow. When an alert fires, the agent immediately begins correlating metrics, logs, and infrastructure dependencies to surface a root cause, often delivering a root cause analysis within minutes of the first alert. This work previously required our engineers to manually piece together information across multiple tools and systems. With its seamless integration into our existing AWS and third-party toolchain, we've reduced our mean time to resolution by over 40% and cut the time our engineers spend on manual investigation by at least half. AWS DevOps Agent delivers on our AI-first vision by giving our engineering teams an intelligent, always-on operational partner that drives reliability and an exceptional customer experience.

- Najib Huq, Engineering Senior Manager, Deriv

"Dhan is a leading online trading platform for stocks, options, futures and commodities, serving over 1.2 million active customers and processing over 9 million transactions daily. For a regulated trading platform like ours, maintaining high availability is crucial. We expect AWS DevOps Agent's automated analysis and contextual recommendations will help our teams ensure consistent service delivery. The agent's ability to learn from our operational patterns while maintaining compliance standards will be particularly valuable across our extended trading hours, from market open through late-night sessions. We anticipate AWS DevOps Agent will enhance our ability to maintain reliable trading infrastructure and meet strict financial service requirements. The AWS DevOps Agent's integration with our existing monitoring stack will help us consolidate alerts across multiple systems and streamline our operational processes.“

- Alok Pandey, Co-Founder and CTO, Dhan (Raise Holdings)

Granola is an AI-powered notepad that handles the heavy lifting of transcription and summarization, allowing customers to stay fully focused rather than distracted by manual note-taking. AWS DevOps Agent integrates seamlessly into Granola's AI-powered incident management workflow, accelerating root cause analysis and reducing mean time to resolution. "We've integrated AWS DevOps Agent directly into our incident response process, where it automatically triggers investigations on high-severity CloudWatch alarms," said Eddie Bruce at Granola. "DevOps Agent's database investigation capabilities consistently outperform other tools we've evaluated, particularly for analyzing PostgreSQL logs and surfacing RDS performance insights. As we scale our SRE capabilities, DevOps Agent has proven to be a reliable part of our incident management toolkit."

- Eddie Bruce, Product Engineer, Granola

"AWS DevOps Agent is helping us transform how we investigate and resolve infrastructure issues. The agent's prevention-based analysis identified patterns across incidents and recommends improvements before issues reach production. This shifts us from reactive firefighting to proactive optimization. During preview testing in a test environment, the agent successfully diagnosed mismatched VPN PSKs, routing misconfigurations, CloudFormation failures, and performance issues with minimal input. Its deep technical analysis examines not just symptoms but underlying patterns across network, application and infrastructure layers. The integrations with CloudWatch logs, automated Skills creation, and learned topology discovery will accelerate our DevOps practices significantly."

- Jim Plourde, EVP Cloud Services, Infor

“AWS DevOps Agent is proving to be a game-changer in our pursuit of zero-touch engineering at RMIT University. As a renowned global university serving over 105,000 students and 12,000 staff and researchers, we are constantly pushing the boundaries of cloud innovation. What’s remarkable about AWS DevOps Agent is its ability to reason across our entire landing zone topology - understanding the relationships between our workload, network, and management accounts as one cohesive ecosystem. We have tested and seen it dissect complex deployment issues in minutes, identifying network communication problems and dependency conflicts that would typically require extensive manual investigations across multiple teams. This level of intelligent automation will transform our troubleshooting cycles from 4-7 hours to under 30 minutes. We are building a future here where cloud operations are proactive, intelligent, and increasingly autonomous.”

- Ken Mirvis, Senior Manager Cloud Engineering, RMIT University

"When AWS introduced DevOps Agent, T-Mobile was at the table from day one. As a design partner, we saw how AWS DevOps Agent can significantly improve root cause analysis across production environments. Our real-world feedback directly influenced how the product evolved.

Our infrastructure spans multiple clouds and on-premises environments, with application logs centralized in our on-premises Splunk deployment. AWS DevOps Agent's ability to integrate seamlessly with Splunk and analyze logs across these diverse environments has been impactful as we continue to pilot the solution."

- Aravind Manchireddy, SVP, Technology Operations, T-Mobile

At United Airlines, we transport more than 500,000 passengers daily. We have about 38,000 Dynatrace OneAgents monitoring across a hybrid cloud environment, more than 500 AWS accounts, 20,000 AWS Lambda functions, Amazon ECS microservices, and numerous other services. At this scale, we previously used multiple tools performing the same functions across different domains, which created gaps and black boxes during troubleshooting. The AWS DevOps Agent with Dynatrace completely changes that. Dynatrace swiftly and accurately detects issues, identifies the responsible application layer, and then the agent investigates further and provides precise steps to resolve the problem — all directly fed into Dynatrace. Instead of initiating an incident call at 3 a.m. and switching between tools, we now have the answers ready—a single pane of glass.

- Jason Eckhart, Principal Engineer, Reliability and Observability, United Airlines

Western Governor's University (WGU), a leading online university serving over 191,000 students, was among the first organizations to deploy Amazon DevOps Agent into production, doing so even ahead of the preview launch at re:Invent. As a large-scale Dynatrace user, WGU leverages the DevOps Agent's native Dynatrace integration, enabling Dynatrace Intelligence to automatically route problem records to the Agent for investigation and return enriched findings directly back into Dynatrace.

During a recent production investigation, WGU's SRE team used the DevOps Agent to analyze a service disruption scenario, reducing total resolution time from an estimated two hours to just 28 minutes—a 77% improvement in MTTR. The Agent quickly pinpointed the root cause within a Lambda function's configuration, surfacing critical operational knowledge that had previously existed only in undiscovered internal documentation.

"It was able to provide the smoking gun, identified the Lambda was the cause. The investigation had almost flawless metrics that matched what we saw on the front-end." He added, "Yesterday was a huge victory, if we can continue to accelerate discovery, I can't describe how much of a victory that would be for our organization," said Angel Marchena, Director of Technical Operations at WGU. With plans to leverage the DevOps Agent Skills feature, WGU is on track to compress investigation time even further.

-Angel Marchena, Director of Technical Operations at WGU

Zenchef is a restaurant technology platform that helps restaurants manage reservations, table operations, digital menus, payments, and guest marketing from a single commission-free system. With a focused DevOps team managing several production environments across multiple business units, they faced a real test when an API integration issue affecting a downstream partner surfaced during a company hackathon, with engineers engaged in the event and nothing significant showing up in monitoring to point them in the right direction.

Rather than pulling engineers off the hackathon, the team brought the issue to DevOps Agent. It worked through the problem systematically, ruling out authentication as a contributing factor, shifting investigation focus to ECS deployments, and ultimately tracing the root cause to a code regression in which a new version failed to handle an unrecognized enum value in the database. The full investigation wrapped in 20-30 minutes, roughly a 75% reduction compared to the 1-2 hours it would have taken manually, and the findings were shared directly with the responsible engineer.

"During the hackathon, we had nearly no available bandwidth to investigate - and we didn't need it. We're always trying to be a couple moves ahead, and this kind of proactive investigation just isn't always possible otherwise. DevOps Agent is enabling new ways of understanding how our platforms behave."

- Theo Massard, Platform Engineering Manager, Zenchef

Running an MSP across 200+ AWS accounts means our operations team lives inside incidents. Every minute spent diagnosing a Lambda failure is a minute not spent improving the reliability posture of our customers' environments. That is the problem we brought to AWS DevOps Agent.

We put it through real investigations, not synthetic benchmarks. Five production Lambda error cases, each with messy logs, scattered observability signals, and recent deployment changes to untangle. The agent nailed the root cause in every single case. Our average resolution time dropped from 15 to 20 minutes per incident to 7.6 minutes, a 50% reduction in MTTR. Scale that across the 100+ Lambda incidents we handle monthly, and we are looking at 20 to 25 engineer hours returned to the team every month. Hours that now go toward architecture reviews, proactive monitoring, and customer-facing improvements instead of repetitive triage.

We did not adopt AWS DevOps Agent because the numbers looked good on a slide. We adopted it because our engineers stopped wanting to go back to the old way of working. It is now embedded in how we run incident response across every managed client environment.

- Kelvin Kok, Chief Architect, Axrail

As a born in the cloud AWS Premier Partner since 2010, recognized as a Niche Player in the 2023 Gartner® Magic Quadrant™ for Public Cloud IT Transformation Services, Blazeclan, now an ITC Infotech brand backed by ITC Limited, manages 10,000 monthly incidents across 50+ AWS accounts spanning Manufacturing, BFSI, and CPG domains. With 750+ cloud experts, 250+ global clients across 41 countries, and a combined ITC Infotech workforce of 13,000+ employees across 17 delivery locations, we evaluated AWS DevOps Agent to elevate our managed service operations at scale.

Across 5 triggered investigations covering Lambda errors, API latency, and EC2/compute issues, the agent reduced average resolution time from 45 to 60 minutes down to 25 to 30 minutes, a 35.00% MTTR improvement, with root cause identification completed in an average of 6 minutes. We project this will free approximately 35 FTE hours per month, translating to $4,000 in monthly operational savings and enabling our engineers to shift from reactive triage to proactive customer value delivery and deeper analysis.

Integration with CloudWatch and New Relic was seamless, and end to end setup was completed in under 40 minutes with no disruption to existing workflows. With $150,000 in annual contract value protected, $20,000 in SLA penalty avoidance, and $50,000 in ARR expansion potential across 3 to 5 customer accounts, AWS DevOps Agent directly supports our FY26 strategic priorities, scaling agentic AI adoption across our services portfolio, accelerating cloud migrations, and driving differentiated industry solutions. As we launch our AWS co branded AI Executive Briefing Centre  and target $4.2M in FY26 launches, we see AWS DevOps Agent as a force multiplier for operational productivity and service quality at scale."

- Varoon D. Rajani, SVP - Cloud First Service Line, Blazeclan(an ITC Infotech brand)

With over 10 years supporting 5,000+ companies across 35,000+ AWS environments, we evaluated AWS DevOps Agent to enhance our managed service operations. Across 200 investigations, we expect the agent to reduce root cause identification time from an average of 45 minutes to approximately 8 minutes, a projected 82% improvement, with an anticipated accuracy of 89% in correctly identifying root causes. We estimate this could reduce approximately 120 hours of investigation work per month, translating to significant projected operational savings. Integration with Slack and Datadog is expected to be completed in under 15 minutes each, with no changes required to existing workflows. Our operations team looks forward to redirecting this capacity toward deeper analysis and proactive customer value creation, improving both productivity and service quality.

- Satoshi Yokota, CEO, Classmethod, Inc.

AWS DevOps Agent reduced our average investigation time by 77%, from 45 minutes down to 10 minutes per incident, across 50 investigations spanning Lambda, EKS, RDS, and VPC workloads. With 84% root cause accuracy and zero false positives, the agent freed our DevOps engineers from manual log correlation, allowing them to focus on remediation. Managing 50 to 60 incidents monthly across 20+ customer accounts, the agent has become a force multiplier for our team.

The agent's automated root cause analysis across multiple AWS services seamlessly correlated infrastructure components across EC2, VPC, S3, EKS, and IAM, consolidating multi-service checks into single investigation workflows. The CloudTrail configuration change correlation automatically identified configuration changes during incident timeframes and linked network and security changes to connectivity issues. For our MSP operations, this capability has transformed how we deliver managed services across the APJ region. AWS DevOps Agent is helping us scale our operations while maintaining the high-quality service our customers expect.

- Bhavesh Goswami, Founder & CEO, CloudThat (APJ Premier MSP Partner)

AWS DevOps Agent delivered exceptional MTTR reduction and productivity gains across all validation scenarios. During an EKS add-on failure investigation, the agent completed the analysis in approximately 5 minutes with precise root cause identification and an actionable mitigation plan in a single response, no follow-up prompting required. This represents an 80-83% MTTR reduction compared to our estimated 25-30 minute manual baseline, a 5-6x speed improvement. Its ability to autonomously investigate and return accurate root cause analysis in one shot is a significant advantage for complex infrastructure issues where correctness matters.

What impressed us most was the agent's operational maturity and investigation transparency. During an EKS pod investigation, the agent transparently communicated its permission boundaries, provided step-by-step RBAC role binding instructions, and successfully completed the investigation after access was granted. This self-correction workflow is genuinely useful for production environments. The agent's step-by-step reasoning with timestamps, findings, and preventive recommendations builds significant user trust in the analysis process. For Inspector vulnerability reporting, the agent delivered executive-ready security summaries covering CVE IDs, severity tiers, CVSS scores, exploit availability, and fix guidance in a single pass, exactly what reliability engineering teams need. For our MSP operations managing customer environments across APJ, this level of autonomous investigation capability and measurable MTTR improvement represents a transformative operational advantage. For an MSP handling 100 similar EKS incidents annually, the 80-83% MTTR reduction translates to approximately 40-42 engineer hours saved per year for this incident type alone.

- Vivek Anand, Associate Vice President, Practice Head, AI & DevOps, Hitachi Systems India Pvt. Ltd.

Using Infosys Topaz, our generative and agentic AI suite, we’re unlocking AI value at scale. Working with AWS, Infosys tested the AWS DevOps Agent, identified root cause and recommended prevention mechanisms by correlating infrastructure anomalies along with recent code and configuration changes—significantly speeding up incident diagnosis and strengthening DevOps and SRE resilience.

- Balakrishna D. R. (Bali), Executive Vice President, Global Services Head, AI and Industry Verticals, Infosys

"In our testing, AWS DevOps Agent significantly reduced the time spent investigating incidents, particularly in complex environments with microservices and serverless workloads. For a typical EC2 performance issue, what would normally take 1 to 2 hours of manual investigation was reduced to approximately 10 minutes by providing the agent with the right data and context. That represents an 83% to 92% reduction in Mean Time to Resolution per incident and translates to 50 to 110 minutes of productivity gains per investigation. This allows our engineers to focus on higher-value work instead of manually correlating data across multiple tools. The more context you provide the agent, the more actionable and accurate its findings become. We see strong potential for AWS DevOps Agent to drive measurable operational efficiency improvements across our managed services practice."

- Gregor Blaj, Technical Director, Lancom Technology

AWS DevOps Agent helped us quickly isolate and analyze only the resources relevant to our service within a highly complex AWS account. In our evaluation, it demonstrated strong root cause analysis accuracy across EKS and serverless-based architectures, while also providing clear and actionable remediation guidance. Notably, for engineers less familiar with the system, investigation time was reduced by over 90%, from multiple days to approximately 30–40 minutes. While occasional human validation was still needed, the agent significantly accelerated troubleshooting and improved overall operational efficiency."

- YoungSeok SONG, Vice President, Cloud Launch Center, LG CNS

As South Korea's largest and strategic Cloud MSP managing thousands of AWS environments across a broad customer portfolio, our operations teams handle a high volume of incidents daily across Lambda, EKS, IAM, and S3 workloads. We tested AWS DevOps Agent across 28 investigations, and the results were immediate: root cause accuracy of 66–72%, with 80% accuracy on Container/EKS issues and 75% on Lambda errors, our highest-volume incident types. Investigation times dropped from 25–35 minutes to just 3–3.5 minutes, a 7–10x improvement. AWS DevOps Agent thinks and acts like a seasoned DevOps engineer, pinpointing exact IAM roles and S3 bucket configurations behind AccessDenied errors, complete with actionable JSON policy snippets our teams could apply immediately. This isn't just about faster resolution times. For an MSP at our scale, this directly reduces SLA penalty exposure and FTE overhead across our entire customer portfolio, enabling our teams to focus on proactive service optimization and delivering better outcomes for our customers.

- Doug Yeum, President and CEO, MegazoneCloud, AWS Premier Partner, Korea

NCS Australia deployed AWS DevOps Agent as a first responder for incident investigation workflows, automating the correlation of logs, metrics, and configuration data across multiple AWS services, replacing manual triage that previously required 20 to 40 minutes per incident.

"AWS DevOps Agent has transformed our incident response operations. We've achieved a 73% reduction in Mean Time to Resolution, bringing our average investigation time from 25 minutes down to just 5 minutes. That's 3x faster incident resolution. The agent achieved 100% root cause accuracy across all investigations, identifying issues like NGINX service failures, security group misconfigurations, and SSH access problems in 14 to 18 minutes with zero false positives. For our MSP operations managing multiple customer environments 24/7, this translates to approximately 23 hours per month in engineering time saved, equivalent to freeing up a significant portion of an FTE. Time our team can invest in proactive optimization and strategic initiatives rather than reactive troubleshooting. The seamless integration with Amazon CloudWatch and our existing operational toolchain makes it invaluable for delivering faster, more reliable managed services to our customers across the region. We are also already extending this implementation to other customers directly into their own self-managed environments as part of our AWS professional services offering, enabling us to consistently deliver those same benefits of the scalable DevOps agent across multiple environments using proven best practices."

- David Rosengrave, AWS National Sales Leader, NCS Australia

Our QUMOA platform supports mission-critical cloud infrastructure for some of Japan's largest enterprises, so any improvement in incident response quality has a direct impact on client trust. In our evaluation, AWS DevOps Agent stood out for its ability to distinguish symptoms from root causes — particularly on complex API Gateway backend connectivity issues — delivering actionable remediation steps that our engineers could act on immediately. The 30% reduction in MTTR we observed translates to meaningful capacity gains: for every 100 monthly incidents, we estimate freeing 8–15 engineer hours that can be redirected toward proactive monitoring and deeper client engagement. We see AWS DevOps Agent as a strategic enabler for QUMOA — accelerating not just incident resolution, but NRI's ability to help enterprise clients advance their digital transformation with confidence.

- Yuichi Yamamoto, Deputy Division Manager, Multi Cloud Integration Division, Nomura Research Institute, Ltd. (MSP Partner, APJ)

Presidio is a leading IT services and solutions provider that helps customers connect IT of today to IT of tomorrow. "As an AWS Premier Consulting Partner, we see this as a practical addition to our customers' cloud operations toolkit. AWS DevOps Agent is a powerful way for our teams and customers to streamline cloud operations and accelerate incident investigations. The ability to incorporate organizational knowledge and past incident data enables our teams to standardize proven practices across diverse customer environments. By automating investigations and integrating with existing monitoring and ticketing tools, it helps teams act faster, stay compliant, and drive consistent operational excellence."

- Ali Tehrani, Modern Networks and Platform SVP, Presidio

“Faster resolution is yesterday's benchmark. We're helping customers redefine the goal entirely: not "how quickly can we fix it?" but "how do we make sure it never breaks?"

That's the shift AWS DevOps Agent makes possible — and the numbers tell the story. Our Customers are seeing MTTR drop by up to 40% to 60%, not because they're getting better at fighting fires, but because the fires are starting to go out. Incident volume is down. Mean time between failures is climbing.

Our customers aren't just resolving incidents faster, they're preventing them entirely. With AWS DevOps Agent, we're helping teams shift from reactive firefighting to proactive reliability engineering. That's the shift we’re leading and driving with our AWS customers.“

- Vikram Reddy Kosanam, Sr Director/VP of Data, Analytics andAI/ML Services, Rackspace

Running managed services at scale means our operations team is the first line of defense for every customer we support. Across 500+ AWS accounts and 150+ monthly incidents spanning Lambda, EC2, EKS, RDS, and AI/ML workloads, the pressure to diagnose and resolve issues quickly is constant. Before AWS DevOps Agent, our engineers spent significant time manually correlating CloudWatch metrics, tracing service dependencies, and building investigation timelines from scratch.

Since deploying AWS DevOps Agent integrated with Amazon CloudWatch and Slack, we have seen our mean time to resolution drop from 45 minutes to 12 minutes per incident, a 73% reduction. Across 50 investigations during our evaluation, the agent delivered 92% root cause accuracy with zero false positives, saving an average of 30 minutes per investigation. That translates to roughly 25 engineering hours reclaimed every week, the equivalent of one full-time site reliability engineer.

What sets DevOps Agent apart for an MSP like Rapyder is how it changes the economics of incident response. Instead of adding headcount to keep pace with growing customer environments, we now have an intelligent first responder that handles the heavy lifting of investigation and surfaces precise, actionable fixes. In one example, a Lambda function failed because of a missing Secrets Manager IAM permission. The agent traced the failure chain, identified the exact missing policy, and recommended the fix in under three minutes. That same diagnosis would have taken our team upwards of 40 minutes manually.

For managed service providers looking to raise the bar on operational excellence without proportionally increasing team size, AWS DevOps Agent is a step change.

- Athreya Ramadas, CTO, Rapyder Cloud Solutions

Traditionally, engineers have spent an average of 30 to 60 minutes per incident on manual triage, specifically focusing on CloudWatch Logs correlation and the cross-referencing of deployment histories. However, in our recent verification program covering five distinct scenarios—which involved extensive investigations across more than 30 Lambda functions and 300 resources—the DevOps Agent successfully identified the root cause in all five cases, achieving a 100% accuracy rate. Most notably, the Agent autonomously discovered complex issues that are typically difficult to identify manually, such as PyO3 compatibility conflicts following Lambda runtime updates and VPC configuration errors at the CDK definition level.
The average investigation time was significantly reduced to just 11.5 minutes, with the fastest case resolved in 6 minutes and 5 seconds, effectively demonstrating that engineering man-hours can be reduced by approximately 75%. Furthermore, by integrating with GitHub, the Agent automated advanced analysis by directly correlating Pull Request diffs with metric fluctuations, allowing 100% of the investigations to be completed without any human intervention. As a Managed Services Provider, Serverworks believes that this DevOps Agent goes far beyond simple log analysis; it is a groundbreaking service for incident response that empowers engineers to work three to five times faster than ever before.

- Yuji Tamaki Executive Officer, General Manager of the Managed Service Department 

“The AWS DevOps Agent delivered exceptional mean time to resolution (MTTR) improvements—nearly three to four times faster than manual methods thanks to its ability to execute multi‑step actions across complex environments. These productivity gains mean IT operations teams can shift from reactive firefighting to strategic enablers.”

- Amit Kumar, AWS Enterprise Architect, TCS

Velocis Systems has built its managed services practice around a simple principle: the faster and more accurately you resolve incidents, the more trust you earn from customers. As an AWS Advanced Consulting Partner and MSP operating across mid-market and enterprise accounts in India, Velocis manages the full cloud lifecycle for its customers, with DevOps automation and 24x7 operations at the center of its delivery model.

When Velocis joined the AWS DevOps Agent preview, the team deployed it directly into live managed environments, not sandboxed test accounts, to measure its real impact on the daily rhythm of MSP operations. The focus was practical: could the agent meaningfully change how a lean operations team handles 50 to 60 incidents a month without adding headcount?
The answer was clear. AWS DevOps Agent reduced Mean Time to Resolution by 40 to 50% and cut manual investigation effort by 25 to 30% across the incident types where it was deployed. At that incident volume, Velocis estimates recovering 10 to 18 engineer hours for every 100 monthly incidents, with projected annual savings of 60 to 130 hours across the portfolio. Those hours are not theoretical. They are being redirected into proactive monitoring, architecture reviews, and deeper customer engagement that was previously deprioritized under operational load.

“What changed for us was not just speed. It was the quality of the first response. Before AWS DevOps Agent, our engineers would spend significant time manually correlating logs, metrics, and resource states to understand what was actually happening during an incident. The agent does that correlation upfront, surfaces a probable root cause, and recommends specific remediation steps. That shift from reactive investigation to informed action is what drove the 40 to 50% MTTR improvement we observed. The Topology View also changed how we onboard new team members onto customer accounts. Instead of spending days building mental models of a customer’s architecture, engineers can see resource relationships and dependencies immediately. For an MSP operating across multiple customer environments, that kind of visibility compounds quickly. We are now planning to make AWS DevOps Agent a standard part of our incident response workflow across the portfolio. The goal is not just faster resolution. It is building the operational foundation for proactive, eventually autonomous, cloud operations that lets us scale service quality without scaling headcount at the same rate.”

- Rajesh Singh, AVP, Cloud | Head, Cloud Technology & Operations Velocis Systems Pvt. Ltd. (Advanced Consulting Partner, India)

We evaluated the preview of AWS DevOps Agent in a representative environment designed to simulate real-world incident scenarios within our managed services operations. This allowed us to assess its ability to act as a first responder, automating root cause analysis and reducing manual triage effort for our cloud engineering team. The agent correlates CloudWatch logs, metrics, and deployment data across multi-account setups, providing comprehensive investigation context without manual context switching between accounts.

During our evaluation, the agent reduced mean time to resolution from an average of 60 minutes to 15 minutes—a 75% improvement—with an accuracy rate of over 80% in correctly identifying root causes. In one simulated scenario, the agent identified an outbound security group misconfiguration causing an ECS Service Health Check Failure in just 16 minutes, compared to 66 minutes manually. It also surfaced a root cause initially missed during manual investigation. This scenario alone reflected a 50-minute time saving and achieved a 5/5 quality rating across evidence gathering, reasoning logic, root cause depth, and recommendation actionability.

Based on these results, we see strong potential in scaling AWS DevOps Agent across our operations. It can act as a force multiplier—enhancing efficiency and enabling teams to manage more environments at a consistently high standard of service, without proportionally increasing headcount.”

- James Leong, Founder and CEO, Xtremax Pte. Ltd.