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Logz.io Unveils Enhancements to Observability Platform

Logz.io announced notable updates to its observability platform. Available later this year, the combination of capabilities including Unified Dashboards, Anomaly Detection, Service Performance Monitoring, and Security Event Management, supported by further adoption of OpenSearch, deliver a wide array of more advanced and mission-critical capabilities needed to support today’s unified full stack observability.

New product enhancements announced at ScaleUP 2021 are:

- Unified Dashboards: Enables customers to quickly search for the root cause of production issues and perform centralized analysis across their full observability stack – using any combination of logs, metrics, and traces monitored using Logz.io. Allows customers to quickly consolidate data without manually switching between products and unify any/all of their data in unified dashboards to get the full picture of their environment, enable teams, and resolve problems sooner.

- Anomaly Detection: Harnesses the power of AI to allow customers to automatically isolate and investigate emerging problems in their environments, based on unusual patterns and behaviors. To locate and alert on issues, Logz.io AI engine monitors data and builds a model that takes into account unique trends in the environment and begins monitoring for unusual behavior on an ongoing basis. The system improves precision over time based on the continued application of machine learning and human inputs.

- Service Performance Monitoring: Advances the ability of customers to monitor application performance in microservices architectures using Logz.io Distributed Tracing, based on Jaeger. Enables users to gain a bird’s eye view into their systems’ health metrics to quickly locate anomalies and spikes and drill down to sample traces with a single click. Based on Logz.io’s work with the OSS community to enhance Jaeger and OpenTelemetry, including contribution of the OTEL Span Metrics Processor.

- Security Event Management: Delivers capabilities required by security analysts to better classify, prioritize and collaborate on the mitigation of events, gaining the specific ability to enact targeted workflows aimed at threat response. Event Management supports key workflows around emerging security threats identification, assignment and handling, severity-based triage and subsequent mitigation – providing teams with visibility into event trends, resolution status and other key response metrics.

- OpenSearch: In keeping with its strong commitment to open source, Logz.io has adopted OpenSearch as its backend engine for logs and search in its cloud native observability platform. Since Elastic announced its intent to close-source Elasticsearch, Logz.io has worked closely with AWS and others to advance OpenSearch, enabling users to safeguard their existing investments while providing faster, more responsive log data ingestion, querying and analysis.

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Logz.io Unveils Enhancements to Observability Platform

Logz.io announced notable updates to its observability platform. Available later this year, the combination of capabilities including Unified Dashboards, Anomaly Detection, Service Performance Monitoring, and Security Event Management, supported by further adoption of OpenSearch, deliver a wide array of more advanced and mission-critical capabilities needed to support today’s unified full stack observability.

New product enhancements announced at ScaleUP 2021 are:

- Unified Dashboards: Enables customers to quickly search for the root cause of production issues and perform centralized analysis across their full observability stack – using any combination of logs, metrics, and traces monitored using Logz.io. Allows customers to quickly consolidate data without manually switching between products and unify any/all of their data in unified dashboards to get the full picture of their environment, enable teams, and resolve problems sooner.

- Anomaly Detection: Harnesses the power of AI to allow customers to automatically isolate and investigate emerging problems in their environments, based on unusual patterns and behaviors. To locate and alert on issues, Logz.io AI engine monitors data and builds a model that takes into account unique trends in the environment and begins monitoring for unusual behavior on an ongoing basis. The system improves precision over time based on the continued application of machine learning and human inputs.

- Service Performance Monitoring: Advances the ability of customers to monitor application performance in microservices architectures using Logz.io Distributed Tracing, based on Jaeger. Enables users to gain a bird’s eye view into their systems’ health metrics to quickly locate anomalies and spikes and drill down to sample traces with a single click. Based on Logz.io’s work with the OSS community to enhance Jaeger and OpenTelemetry, including contribution of the OTEL Span Metrics Processor.

- Security Event Management: Delivers capabilities required by security analysts to better classify, prioritize and collaborate on the mitigation of events, gaining the specific ability to enact targeted workflows aimed at threat response. Event Management supports key workflows around emerging security threats identification, assignment and handling, severity-based triage and subsequent mitigation – providing teams with visibility into event trends, resolution status and other key response metrics.

- OpenSearch: In keeping with its strong commitment to open source, Logz.io has adopted OpenSearch as its backend engine for logs and search in its cloud native observability platform. Since Elastic announced its intent to close-source Elasticsearch, Logz.io has worked closely with AWS and others to advance OpenSearch, enabling users to safeguard their existing investments while providing faster, more responsive log data ingestion, querying and analysis.

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...