Platform and IT engineers are constantly challenged to build reliable systems while keeping production running during critical failures. However, reactive incident management is consuming valuable engineering capacity and driving significant team burnout. In fact, the majority of engineering teams spend 40 percent or more of their time on incident management instead of innovation.

Read the full report to explore key findings, including:

• The Cost of Alert Fatigue: Discover why nearly half of organizations experienced an outage linked to ignored or suppressed alerts in the past year.
• Financial Exposure: Learn how infrastructure downtime costs 61 percent of organizations $50,000 or more per hour.
• The AI Perception Gap: Understand why 74 percent of C-suite executives believe their organization actively uses AI for incident management while only 39 percent of practitioners agree.
• Barriers to Adoption: Identify the top practical challenges to AI deployment, such as budget constraints, data quality issues, and security concerns.

As organizations scale their cloud infrastructure, engineers often spend countless hours diagnosing complex operational issues, which can delay development cycles and threaten SLAs. Model Rocket, an innovative technology solutions provider, faced these exact operational headwinds as their usage of AWS services expanded.

Download this customer story to learn how Hawkeye transformed Model Rocket’s operations, resulting in:

• 92% MTTR Reduction: Drastically accelerated incident resolution by instantly identifying root causes.
• 24/7 Expert Monitoring: Leveraged AI to provide continuous, automated root cause analysis across the entire AWS environment.
• Enhanced Development Focus: Freed engineers from context-switching between operations and development, allowing them to focus on innovation.
• Strengthened SLAs: Ensured consistent service reliability even during rapid development cycles.

In modern IT environments, engineers are often overwhelmed by alert storms and fragmented data during critical incidents. NeuBird AI functions as a 24/7 SRE assistant, designed to augment your DevOps and engineering teams with real-time analysis, pattern detection, and context-aware recommendations.

Download this data sheet to learn how NeuBird can help your team:

• Reduce Operational Noise: Collapse hundreds of raw alerts into a single, actionable incident with probable root causes identified.
• Detect Root Causes Faster: Unify observability data, change events, and operational knowledge into one seamless system.
• Automate Common Fixes: Safely execute remediation using runbook intelligence and strict execution controls.
• Maintain Data Privacy: Analyze incidents using your private vector database without sending raw telemetry to external models.

Modern Site Reliability Engineering teams are not constrained by a lack of observability, but by the manual effort required after an alert fires. As production environments generate massive volumes of telemetry, the work required to interpret data across multiple platforms has dramatically increased, leading to higher levels of toil and delayed response times.

Download this eBook to explore how autonomous incident resolution is changing SRE operations, including how to:

• Eliminate Manual Toil: Free your engineering teams from the hidden costs of reactive firefighting and repetitive triage.
• Accelerate Incident Resolution: Move from alert to fix significantly faster with automated root cause analysis.
• Build Trust In Automation: Implement secure, explainable, and governed AI workflows that align with your operational standards.
• Integrate Seamlessly: Deploy autonomous agents across your existing hybrid and multi-cloud observability tools without ripping and replacing infrastructure.

Platform and IT engineers are constantly challenged to build reliable systems while keeping production running during critical failures. However, reactive incident management is consuming valuable engineering capacity and driving significant team burnout. In fact, the majority of engineering teams spend 40 percent or more of their time on incident management instead of innovation.

Read the full report to explore key findings, including:

• The Cost of Alert Fatigue: Discover why nearly half of organizations experienced an outage linked to ignored or suppressed alerts in the past year.
• Financial Exposure: Learn how infrastructure downtime costs 61 percent of organizations $50,000 or more per hour.
• The AI Perception Gap: Understand why 74 percent of C-suite executives believe their organization actively uses AI for incident management while only 39 percent of practitioners agree.
• Barriers to Adoption: Identify the top practical challenges to AI deployment, such as budget constraints, data quality issues, and security concerns.

In modern IT environments, engineers are often overwhelmed by alert storms and fragmented data during critical incidents. NeuBird AI functions as a 24/7 SRE assistant, designed to augment your DevOps and engineering teams with real-time analysis, pattern detection, and context-aware recommendations.

Download this data sheet to learn how NeuBird can help your team:

• Reduce Operational Noise: Collapse hundreds of raw alerts into a single, actionable incident with probable root causes identified.
• Detect Root Causes Faster: Unify observability data, change events, and operational knowledge into one seamless system.
• Automate Common Fixes: Safely execute remediation using runbook intelligence and strict execution controls.
• Maintain Data Privacy: Analyze incidents using your private vector database without sending raw telemetry to external models.

Modern Site Reliability Engineering teams are not constrained by a lack of observability, but by the manual effort required after an alert fires. As production environments generate massive volumes of telemetry, the work required to interpret data across multiple platforms has dramatically increased, leading to higher levels of toil and delayed response times.

Download this eBook to explore how autonomous incident resolution is changing SRE operations, including how to:

• Eliminate Manual Toil: Free your engineering teams from the hidden costs of reactive firefighting and repetitive triage.
• Accelerate Incident Resolution: Move from alert to fix significantly faster with automated root cause analysis.
• Build Trust In Automation: Implement secure, explainable, and governed AI workflows that align with your operational standards.
• Integrate Seamlessly: Deploy autonomous agents across your existing hybrid and multi-cloud observability tools without ripping and replacing infrastructure.

Platform and IT engineers are constantly challenged to build reliable systems while keeping production running during critical failures. However, reactive incident management is consuming valuable engineering capacity and driving significant team burnout. In fact, the majority of engineering teams spend 40 percent or more of their time on incident management instead of innovation.

Read the full report to explore key findings, including:

• The Cost of Alert Fatigue: Discover why nearly half of organizations experienced an outage linked to ignored or suppressed alerts in the past year.
• Financial Exposure: Learn how infrastructure downtime costs 61 percent of organizations $50,000 or more per hour.
• The AI Perception Gap: Understand why 74 percent of C-suite executives believe their organization actively uses AI for incident management while only 39 percent of practitioners agree.
• Barriers to Adoption: Identify the top practical challenges to AI deployment, such as budget constraints, data quality issues, and security concerns.

As organizations scale their cloud infrastructure, engineers often spend countless hours diagnosing complex operational issues, which can delay development cycles and threaten SLAs. Model Rocket, an innovative technology solutions provider, faced these exact operational headwinds as their usage of AWS services expanded.

Download this customer story to learn how Hawkeye transformed Model Rocket’s operations, resulting in:

• 92% MTTR Reduction: Drastically accelerated incident resolution by instantly identifying root causes.
• 24/7 Expert Monitoring: Leveraged AI to provide continuous, automated root cause analysis across the entire AWS environment.
• Enhanced Development Focus: Freed engineers from context-switching between operations and development, allowing them to focus on innovation.
• Strengthened SLAs: Ensured consistent service reliability even during rapid development cycles.

In modern IT environments, engineers are often overwhelmed by alert storms and fragmented data during critical incidents. NeuBird AI functions as a 24/7 SRE assistant, designed to augment your DevOps and engineering teams with real-time analysis, pattern detection, and context-aware recommendations.

Download this data sheet to learn how NeuBird can help your team:

• Reduce Operational Noise: Collapse hundreds of raw alerts into a single, actionable incident with probable root causes identified.
• Detect Root Causes Faster: Unify observability data, change events, and operational knowledge into one seamless system.
• Automate Common Fixes: Safely execute remediation using runbook intelligence and strict execution controls.
• Maintain Data Privacy: Analyze incidents using your private vector database without sending raw telemetry to external models.

Modern Site Reliability Engineering teams are not constrained by a lack of observability, but by the manual effort required after an alert fires. As production environments generate massive volumes of telemetry, the work required to interpret data across multiple platforms has dramatically increased, leading to higher levels of toil and delayed response times.

Download this eBook to explore how autonomous incident resolution is changing SRE operations, including how to:

• Eliminate Manual Toil: Free your engineering teams from the hidden costs of reactive firefighting and repetitive triage.
• Accelerate Incident Resolution: Move from alert to fix significantly faster with automated root cause analysis.
• Build Trust In Automation: Implement secure, explainable, and governed AI workflows that align with your operational standards.
• Integrate Seamlessly: Deploy autonomous agents across your existing hybrid and multi-cloud observability tools without ripping and replacing infrastructure.