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Logz.io Introduces AI-Powered Anomaly Detection for App 360

Logz.io has added AI and ML-powered Anomaly Detection capability to App 360, equipping its application observability solution with automated capabilities that let users respond to real-time performance alerts based on models built from historical telemetry data, reducing the manual tasks that slow down and complicate remediation.

While Logz.io has been offering ML and AI-based Anomaly Detection across the Open 360™ platform since February of 2023, Anomaly Detection for App 360 extends this capability to the new App 360 solution addressing the specific requirements of today's application observability users.

Anomaly Detection for App 360 is the kind of AI-driven automation that customers are asking for to help them optimize user experience while increasing efficiency and driving down costs.

With Anomaly Detection for App 360, Open 360 users can now enlist targeted automation to do more of the work for them — automatically monitoring and alerting any issues occurring within the specific services and microservices they identify as being most critical, which are often those that immediately impact business or SLO-related requirements.

Anomaly Detection for App 360 utilizes powerful automation to make it simple for users to set up and begin monitoring and alerting against their critical services. Whether users prefer a list-based approach using Logz.io Service Overview or topology-based approach using Logz.io Service Map, the new capability also supports these varied use cases oriented to different audiences, including software engineers, SREs, platforming engineering and beyond. Anomaly Detection for App 360 takes users beyond traditional monitoring of critical services by locating and scoring the severity of unusual activity for a more proactive response.

Key Benefits of Anomaly Detection for App 360:

- Faster troubleshooting: Increases app performance through automated detection. This new capability automatically surfaces emerging problems in the most critical services as designated by the user. Troubleshooting is accelerated by enabling the user to focus on those alerts that matter most to application optimization.

- Proactive and real-time: Proactively identifies issues that may otherwise go unnoticed. Advanced automation uncovers hard-to-predict issues before they impact end users. In contrast to traditional point-in-time, threshold-based application monitoring, Anomaly Detection enlists full-stack application observability that is more relevant and real-time.

- Automated insights: Moves away from traditional APM to full-scope application observability. Traditional APM solutions based on threshold-based detection typically require users to manually analyze available data, leaving users chasing high-volume alerts that may or may not be high priority. In contrast, Anomaly Detection for App 360 automatically generates real-time insights into the performance of user-prioritized services, operations, metrics and endpoints. This helps engineering teams accelerate and simplify their work in optimizing application performance, cutting through noise and reducing manual tasks.

"We continue to rapidly expand upon and deepen the capabilities of App 360, our groundbreaking application observability solution," said Asaf Yigal, co-founder and CTO at Logz.io. "Anomaly Detection for App 360 is the kind of AI-driven automation that customers are asking for to help them optimize user experience while increasing efficiency and driving down costs. This added capability helps our customers find the 'unknown unknowns' lurking in their complex microservices architectures, cutting through the mountains of available data to focus on priority issues and troubleshoot faster."

Engineering and ops teams — or anyone responsible for oversight of specific applications services — can use Anomaly Detection for App 360 to ensure they are automatically alerted whenever their services and microservices fall outside expected parameters.

Further, this new capability has been designed to give software engineers, site reliability engineers (SREs) and platform engineering teams the precise manner of utilization they prefer or that best tracks with their roles. Read more about these role-based customization options here.

For existing Logz.io customers, Anomaly Detection for App 360 is already available at no additional cost; it's simply enabled as a new element of the platform.

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Logz.io Introduces AI-Powered Anomaly Detection for App 360

Logz.io has added AI and ML-powered Anomaly Detection capability to App 360, equipping its application observability solution with automated capabilities that let users respond to real-time performance alerts based on models built from historical telemetry data, reducing the manual tasks that slow down and complicate remediation.

While Logz.io has been offering ML and AI-based Anomaly Detection across the Open 360™ platform since February of 2023, Anomaly Detection for App 360 extends this capability to the new App 360 solution addressing the specific requirements of today's application observability users.

Anomaly Detection for App 360 is the kind of AI-driven automation that customers are asking for to help them optimize user experience while increasing efficiency and driving down costs.

With Anomaly Detection for App 360, Open 360 users can now enlist targeted automation to do more of the work for them — automatically monitoring and alerting any issues occurring within the specific services and microservices they identify as being most critical, which are often those that immediately impact business or SLO-related requirements.

Anomaly Detection for App 360 utilizes powerful automation to make it simple for users to set up and begin monitoring and alerting against their critical services. Whether users prefer a list-based approach using Logz.io Service Overview or topology-based approach using Logz.io Service Map, the new capability also supports these varied use cases oriented to different audiences, including software engineers, SREs, platforming engineering and beyond. Anomaly Detection for App 360 takes users beyond traditional monitoring of critical services by locating and scoring the severity of unusual activity for a more proactive response.

Key Benefits of Anomaly Detection for App 360:

- Faster troubleshooting: Increases app performance through automated detection. This new capability automatically surfaces emerging problems in the most critical services as designated by the user. Troubleshooting is accelerated by enabling the user to focus on those alerts that matter most to application optimization.

- Proactive and real-time: Proactively identifies issues that may otherwise go unnoticed. Advanced automation uncovers hard-to-predict issues before they impact end users. In contrast to traditional point-in-time, threshold-based application monitoring, Anomaly Detection enlists full-stack application observability that is more relevant and real-time.

- Automated insights: Moves away from traditional APM to full-scope application observability. Traditional APM solutions based on threshold-based detection typically require users to manually analyze available data, leaving users chasing high-volume alerts that may or may not be high priority. In contrast, Anomaly Detection for App 360 automatically generates real-time insights into the performance of user-prioritized services, operations, metrics and endpoints. This helps engineering teams accelerate and simplify their work in optimizing application performance, cutting through noise and reducing manual tasks.

"We continue to rapidly expand upon and deepen the capabilities of App 360, our groundbreaking application observability solution," said Asaf Yigal, co-founder and CTO at Logz.io. "Anomaly Detection for App 360 is the kind of AI-driven automation that customers are asking for to help them optimize user experience while increasing efficiency and driving down costs. This added capability helps our customers find the 'unknown unknowns' lurking in their complex microservices architectures, cutting through the mountains of available data to focus on priority issues and troubleshoot faster."

Engineering and ops teams — or anyone responsible for oversight of specific applications services — can use Anomaly Detection for App 360 to ensure they are automatically alerted whenever their services and microservices fall outside expected parameters.

Further, this new capability has been designed to give software engineers, site reliability engineers (SREs) and platform engineering teams the precise manner of utilization they prefer or that best tracks with their roles. Read more about these role-based customization options here.

For existing Logz.io customers, Anomaly Detection for App 360 is already available at no additional cost; it's simply enabled as a new element of the platform.

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...