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Cloud Canaries Introduces Intelligent Canaries

Cloud Canaries launched to improve how organizations monitor and optimize their cloud environments.

Its Intelligent Canaries help software engineering and delivery teams practicing DevOps proactively detect, predict and autonomously resolve system issues before they impact operations. With Cloud Canaries, teams can create and deploy canaries in minutes and at a fraction of the cost of today's observability solutions.

Cloud Canaries is angel-funded, and is founded by industry veteran Mark Callahan, who brings over 17 years of experience at Oracle, specializing in retail applications and Oracle Cloud Infrastructure. The company's technical team includes a Harvard Ph.D. specializing in Neural Networks and AI, data analysts, DevOps leaders and experts in time series data and AWS deployment.

"Developers can create and share canaries to address the most common use cases to observe, secure and govern the cloud at 10% of today's costs," said Cloud Canaries' CEO Callahan. "By embracing open-source principles, Intelligent Canaries offer software teams the flexibility to address unique cloud environments while sharing knowledge within the Cloud Intelligence community."

With Cloud Canaries' workload-based solution, DevOps teams have a more efficient approach that allows for observability without instrumentation. Intelligent Canaries are lightweight agents that detect issues, safeguard change and risk management, and provide real-time performance monitoring and precise problem resolution. They allow software developers and engineering teams to innovate fearlessly while empowering IT managers to transform observability into a value-based initiative.

"Cloud Intelligence differs from today's legacy observability software as it offers a more cost-effective and flexible approach to monitor and optimize cloud environments," said Callahan. "Intelligent Canaries free teams from the system issues and operational obstacles that block innovation."

Cloud Intelligence represents a paradigm shift in system observability to improve DevOps and increase innovation by eliminating unplanned and distracting roadblocks. It supports DevOps' purpose to deploy small, controlled changes while empowering teams to control their destiny.

Intelligent Canaries are highly effective at:

- Early Detection of Issues: Intelligent Canaries act as early indicators by proactively detecting and pinpointing the root cause of potential problems or anomalies to isolate and address issues promptly.

- Risk Mitigation: By introducing changes gradually to a small subset of the system, teams can assess the impact of changes in a controlled environment, reducing the risk of widespread failures.

- Performance Monitoring: Intelligent Canaries provide real-time feedback on system performance, helping teams monitor key metrics and ensure systems operate within acceptable parameters.

- Continuous Improvement: Teams can refine processes, performance and reliability for incremental improvements by monitoring insights from Intelligent Canaries.

- Always Proactive: Intelligent Canaries maintain system stability and resilience by facilitating autonomous fixing issues and system optimization.

"The DevOps industry faces challenges such as manual processes, reactive problem-solving, outdated architectures and poor team collaboration," says Helen Beal, Chief Community Builder at Cloud Canaries. "Intelligent Canaries align perfectly with DevOps principles and address these issues while meeting the evolving needs of complex cloud environments."

The Latest

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

Cloud Canaries Introduces Intelligent Canaries

Cloud Canaries launched to improve how organizations monitor and optimize their cloud environments.

Its Intelligent Canaries help software engineering and delivery teams practicing DevOps proactively detect, predict and autonomously resolve system issues before they impact operations. With Cloud Canaries, teams can create and deploy canaries in minutes and at a fraction of the cost of today's observability solutions.

Cloud Canaries is angel-funded, and is founded by industry veteran Mark Callahan, who brings over 17 years of experience at Oracle, specializing in retail applications and Oracle Cloud Infrastructure. The company's technical team includes a Harvard Ph.D. specializing in Neural Networks and AI, data analysts, DevOps leaders and experts in time series data and AWS deployment.

"Developers can create and share canaries to address the most common use cases to observe, secure and govern the cloud at 10% of today's costs," said Cloud Canaries' CEO Callahan. "By embracing open-source principles, Intelligent Canaries offer software teams the flexibility to address unique cloud environments while sharing knowledge within the Cloud Intelligence community."

With Cloud Canaries' workload-based solution, DevOps teams have a more efficient approach that allows for observability without instrumentation. Intelligent Canaries are lightweight agents that detect issues, safeguard change and risk management, and provide real-time performance monitoring and precise problem resolution. They allow software developers and engineering teams to innovate fearlessly while empowering IT managers to transform observability into a value-based initiative.

"Cloud Intelligence differs from today's legacy observability software as it offers a more cost-effective and flexible approach to monitor and optimize cloud environments," said Callahan. "Intelligent Canaries free teams from the system issues and operational obstacles that block innovation."

Cloud Intelligence represents a paradigm shift in system observability to improve DevOps and increase innovation by eliminating unplanned and distracting roadblocks. It supports DevOps' purpose to deploy small, controlled changes while empowering teams to control their destiny.

Intelligent Canaries are highly effective at:

- Early Detection of Issues: Intelligent Canaries act as early indicators by proactively detecting and pinpointing the root cause of potential problems or anomalies to isolate and address issues promptly.

- Risk Mitigation: By introducing changes gradually to a small subset of the system, teams can assess the impact of changes in a controlled environment, reducing the risk of widespread failures.

- Performance Monitoring: Intelligent Canaries provide real-time feedback on system performance, helping teams monitor key metrics and ensure systems operate within acceptable parameters.

- Continuous Improvement: Teams can refine processes, performance and reliability for incremental improvements by monitoring insights from Intelligent Canaries.

- Always Proactive: Intelligent Canaries maintain system stability and resilience by facilitating autonomous fixing issues and system optimization.

"The DevOps industry faces challenges such as manual processes, reactive problem-solving, outdated architectures and poor team collaboration," says Helen Beal, Chief Community Builder at Cloud Canaries. "Intelligent Canaries align perfectly with DevOps principles and address these issues while meeting the evolving needs of complex cloud environments."

The Latest

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...