{"id":9032484684050,"title":"Glances","handle":"glances","description":"\u003cbody\u003e\n\n\n \u003cmeta charset=\"utf-8\"\u003e\n \u003ctitle\u003eGlances Monitoring | Consultants In-A-Box\u003c\/title\u003e\n \u003cmeta name=\"viewport\" content=\"width=device-width, initial-scale=1\"\u003e\n \u003cstyle\u003e\n body {\n font-family: Inter, \"Segoe UI\", Roboto, sans-serif;\n background: #ffffff;\n color: #1f2937;\n line-height: 1.7;\n margin: 0;\n padding: 48px;\n }\n h1 { font-size: 32px; margin-bottom: 16px; }\n h2 { font-size: 22px; margin-top: 32px; }\n p { margin: 12px 0; }\n ul { margin: 12px 0 12px 24px; }\n \/* No link styles: do not create or style anchors *\/\n \u003c\/style\u003e\n\n\n \u003ch1\u003eTurn Real-Time IT Monitoring into Business Confidence with Glances and AI Automation\u003c\/h1\u003e\n\n \u003cp\u003eGlances is a lightweight, flexible monitoring tool that captures real-time health and performance data across servers, virtual machines, and containers. It surfaces CPU, memory, disk, network, process, and other operational metrics in a compact, easy-to-read format so teams can see what’s happening now — not just after the fact. For organizations that need quick visibility without heavy infrastructure, Glances is a practical foundation for observability.\u003c\/p\u003e\n \u003cp\u003eWhen Glances is combined with modern AI integration and workflow automation, that raw visibility becomes proactive intelligence. Instead of a dashboard full of numbers, leaders get prioritized alerts, automated remediation for common issues, and AI agents that enrich incidents with context. The result is more predictable operations, less manual firefighting, and measurable business efficiency gains.\u003c\/p\u003e\n\n \u003ch2\u003eHow It Works\u003c\/h2\u003e\n \u003cp\u003eThink of Glances as the central nervous system of your operational environment. Small agents run where your workloads live and constantly report short summaries of system health. Those summaries feed dashboards and alerting rules so a single pane of glass reveals whether systems are operating as expected or if attention is required.\u003c\/p\u003e\n \u003cp\u003eOn its own, Glances gives teams immediate situational awareness: which hosts are spiking, which services are consuming the most memory, and which disks are nearing capacity. The real value emerges when those live signals are treated as triggers for business workflows. An alert can create a ticket, populate a chat thread with context, or call a remediation playbook — and each of those actions can be tailored to match the risk profile of the environment.\u003c\/p\u003e\n\n \u003ch2\u003eThe Power of AI \u0026amp; Agentic Automation\u003c\/h2\u003e\n \u003cp\u003eAdding AI agents and workflow automation turns monitoring from a passive feed into an active problem solver. AI agents read the same signals humans do but at scale and across many sources. They reduce noise, suggest likely causes, and can take safe, repeatable actions when appropriate. This layered approach improves response times, reduces human error, and helps operations scale without linear increases in headcount.\u003c\/p\u003e\n \u003cul\u003e\n \u003cli\u003eSmart triage: AI analyzes alert patterns across systems to cluster related events, reduce duplicates, and surface the most likely root causes so teams don’t waste time chasing symptoms.\u003c\/li\u003e\n \u003cli\u003ePredictive insights: Machine learning detects slow-moving trends — like steadily increasing swap usage or recurring I\/O spikes — and warns teams before incidents materialize, enabling planned maintenance instead of emergency fixes.\u003c\/li\u003e\n \u003cli\u003eAutomated remediation: For low-risk, high-frequency issues, automated playbooks execute trusted actions — restarting hung services, clearing temporary files, or gracefully draining traffic — and log outcomes for auditability.\u003c\/li\u003e\n \u003cli\u003eContext aggregation: When an incident starts, agents collect the right artifacts — recent deploys, process snapshots, error logs, and configuration diffs — and present a concise brief that accelerates decision-making.\u003c\/li\u003e\n \u003cli\u003eCollaborative routing: Chat-based AI agents summarize incidents into human-friendly language, recommend owners based on past resolutions, and route work to the right team with the right priority and context.\u003c\/li\u003e\n \u003c\/ul\u003e\n\n \u003ch2\u003eReal-World Use Cases\u003c\/h2\u003e\n \u003cul\u003e\n \u003cli\u003eProactive incident detection: During a promotional campaign, an AI agent detects rising memory consumption on a key cluster node and opens a prioritized ticket with process and deployment context. Engineers resolve the issue before page load times degrade and conversion drops.\u003c\/li\u003e\n \u003cli\u003eAutomated remediation for routine faults: A web service intermittently becomes unresponsive. A workflow bot attempts a safe restart, records the outcome, and only notifies engineers if the restart fails twice, eliminating repetitive wake-up calls for the on-call team.\u003c\/li\u003e\n \u003cli\u003eCapacity planning and cost control: Trend analysis across months shows several cloud instances are underutilized during off-peak hours. An automation schedules noncritical batch jobs to run during low-cost windows and recommends right-sizing for savings.\u003c\/li\u003e\n \u003cli\u003eSecurity anomaly detection: Unusual network spikes combined with unexpected process executions trigger an AI agent that gathers forensic context and prepares an initial incident dossier for the security team, reducing investigation time by delivering curated evidence.\u003c\/li\u003e\n \u003cli\u003eCompliance and reporting automation: Scheduled agents compile system health, uptime, and inventory snapshots into standardized reports for audits. The AI fills gaps by correlating changes to tickets and deploy logs, which reduces manual effort and audit friction.\u003c\/li\u003e\n \u003cli\u003eIntelligent chat routing and escalation: An intelligent chatbot parses incoming incident messages, identifies urgency and impact, and routes the case to the right escalation path — DevOps for platform issues, SRE for availability, or Security for suspicious activity — preserving focused attention where it matters.\u003c\/li\u003e\n \u003cli\u003eAI-assisted post-incident reviews: After a major incident, an AI assistant aggregates logs, timeline events, and remediation steps into a draft postmortem that engineers can refine. This accelerates learning cycles and improves institutional knowledge capture.\u003c\/li\u003e\n \u003c\/ul\u003e\n\n \u003ch2\u003eBusiness Benefits\u003c\/h2\u003e\n \u003cp\u003eWhen real-time monitoring is extended with AI integration and workflow automation, organizations convert observability into business outcomes: fewer outages, faster recovery, predictable costs, and a more productive engineering culture. Those effects translate directly into improved customer experience and lower operational risk.\u003c\/p\u003e\n \u003cul\u003e\n \u003cli\u003eReduced downtime and faster MTTR: Early detection and automated playbooks shorten mean time to repair, minimizing revenue and productivity losses from outages.\u003c\/li\u003e\n \u003cli\u003eTime savings and fewer distractions: Intelligent filtering and automated resolution of routine incidents free engineers to focus on strategic projects that drive innovation and growth.\u003c\/li\u003e\n \u003cli\u003eBetter decision-making: Consolidated context and predictive alerts enable prioritization based on business impact rather than raw telemetry, reducing costly back-and-forth between teams.\u003c\/li\u003e\n \u003cli\u003eScalability without headcount growth: Automation and AI agents let operations teams cover more systems and services without a proportional increase in staff, supporting rapid scaling and digital transformation.\u003c\/li\u003e\n \u003cli\u003eLower total cost of ownership: Proactive management and right-sizing recommendations help control cloud spend, reduce emergency remediation expenses, and extend the lifespan of existing infrastructure investments.\u003c\/li\u003e\n \u003cli\u003eStronger collaboration and knowledge capture: Agents summarize incidents, attach relevant playbook outputs, and record resolution steps, so teams learn faster and institutional knowledge accumulates rather than relying on tribal memory.\u003c\/li\u003e\n \u003cli\u003eImproved compliance and auditability: Automated collection of evidence and versioned remediation procedures make it simpler to demonstrate controls and maintain an auditable trail for regulators and stakeholders.\u003c\/li\u003e\n \u003c\/ul\u003e\n\n \u003ch2\u003eHow Consultants In-A-Box Helps\u003c\/h2\u003e\n \u003cp\u003eConsultants In-A-Box approaches Glances and AI-enabled monitoring with a business-first mindset. We focus on practical outcomes: reducing downtime, cutting operational overhead, and improving team effectiveness. Our engagements follow a structured sequence that balances quick wins with longer-term capability building.\u003c\/p\u003e\n \u003cp\u003eAssessment: We begin by aligning on business objectives — uptime targets, cost constraints, compliance needs, and where the biggest operational pain points exist. That lets us prioritize which metrics to monitor, where to deploy agents, and which integrations will unlock the most value.\u003c\/p\u003e\n \u003cp\u003eDesign \u0026amp; integration: We design dashboards and alerting that map to business outcomes rather than technical thresholds, and we connect Glances into ticketing, chat, incident response, and configuration management systems so alerts carry the context people need to act.\u003c\/p\u003e\n \u003cp\u003eAutomation \u0026amp; AI: We author tested automation playbooks for routine, low-risk remediations and develop AI agent behaviors that cluster alerts, recommend owners, and assemble investigative context. Everything is safety-first: actions are reversible, auditable, and matched to governance requirements.\u003c\/p\u003e\n \u003cp\u003eRunbooks \u0026amp; enablement: We produce concise runbooks and run hands-on training so teams understand agent behavior, can trust automated actions, and know how to override or escalate when necessary. The emphasis is on practical trust, not black-box automation.\u003c\/p\u003e\n \u003cp\u003eManaged evolution: As your environment and priorities change, we continue to iterate on rules, thresholds, and AI models. This managed evolution ensures monitoring remains aligned with shifting workloads and the organization’s digital transformation goals.\u003c\/p\u003e\n\n \u003ch2\u003eSummary\u003c\/h2\u003e\n \u003cp\u003eGlances offers fast, lightweight visibility into system health; when paired with AI integration and workflow automation it becomes a strategic tool for business efficiency. AI agents reduce noise, predict emerging issues, and automate repeatable fixes while preserving human oversight for complex problems. The combined approach cuts downtime, reduces costs, and scales operational capability — enabling teams to spend less time reacting and more time delivering value.\u003c\/p\u003e\n\n\u003c\/body\u003e","published_at":"2024-01-20T07:19:44-06:00","created_at":"2024-01-20T07:19:45-06:00","vendor":"Consultants In-A-Box","type":"Productivity software","tags":["Accounting software","Advisory services","Advisory solutions","Automation","Business applications","Business consultants","Business development","Business experts","Cloud computing","Comprehensive solutions","Consulting packages","Consulting services","Customized consultancy","Data management","E-Commerce Software","Expert advice","Glance app","Glance dashboard","Glance features","Glance productivity","Glance software","Glance solutions","Glance technology","Glances","Industry specialists","IT consulting","IT infrastructure","IT services","IT solutions","Management consulting","Marketing Software","Productivity software","Professional guidance","Quick insights","Real-time information","Sales Software","Software development","Software engineering","Software solutions","Strategic advisors","Tailored consulting","Tech solutionsSoftware integration","Technology platform"],"price":0,"price_min":0,"price_max":0,"available":true,"price_varies":false,"compare_at_price":null,"compare_at_price_min":0,"compare_at_price_max":0,"compare_at_price_varies":false,"variants":[{"id":47859559891218,"title":"Default Title","option1":"Default Title","option2":null,"option3":null,"sku":"","requires_shipping":true,"taxable":true,"featured_image":null,"available":true,"name":"Glances","public_title":null,"options":["Default Title"],"price":0,"weight":0,"compare_at_price":null,"inventory_management":null,"barcode":null,"requires_selling_plan":false,"selling_plan_allocations":[]}],"images":["\/\/consultantsinabox.com\/cdn\/shop\/products\/5c232fabefb0f62b51467b216cce30f5.png?v=1705756785"],"featured_image":"\/\/consultantsinabox.com\/cdn\/shop\/products\/5c232fabefb0f62b51467b216cce30f5.png?v=1705756785","options":["Title"],"media":[{"alt":"Glances logo","id":37203981074706,"position":1,"preview_image":{"aspect_ratio":1.0,"height":200,"width":200,"src":"\/\/consultantsinabox.com\/cdn\/shop\/products\/5c232fabefb0f62b51467b216cce30f5.png?v=1705756785"},"aspect_ratio":1.0,"height":200,"media_type":"image","src":"\/\/consultantsinabox.com\/cdn\/shop\/products\/5c232fabefb0f62b51467b216cce30f5.png?v=1705756785","width":200}],"requires_selling_plan":false,"selling_plan_groups":[],"content":"\u003cbody\u003e\n\n\n \u003cmeta charset=\"utf-8\"\u003e\n \u003ctitle\u003eGlances Monitoring | Consultants In-A-Box\u003c\/title\u003e\n \u003cmeta name=\"viewport\" content=\"width=device-width, initial-scale=1\"\u003e\n \u003cstyle\u003e\n body {\n font-family: Inter, \"Segoe UI\", Roboto, sans-serif;\n background: #ffffff;\n color: #1f2937;\n line-height: 1.7;\n margin: 0;\n padding: 48px;\n }\n h1 { font-size: 32px; margin-bottom: 16px; }\n h2 { font-size: 22px; margin-top: 32px; }\n p { margin: 12px 0; }\n ul { margin: 12px 0 12px 24px; }\n \/* No link styles: do not create or style anchors *\/\n \u003c\/style\u003e\n\n\n \u003ch1\u003eTurn Real-Time IT Monitoring into Business Confidence with Glances and AI Automation\u003c\/h1\u003e\n\n \u003cp\u003eGlances is a lightweight, flexible monitoring tool that captures real-time health and performance data across servers, virtual machines, and containers. It surfaces CPU, memory, disk, network, process, and other operational metrics in a compact, easy-to-read format so teams can see what’s happening now — not just after the fact. For organizations that need quick visibility without heavy infrastructure, Glances is a practical foundation for observability.\u003c\/p\u003e\n \u003cp\u003eWhen Glances is combined with modern AI integration and workflow automation, that raw visibility becomes proactive intelligence. Instead of a dashboard full of numbers, leaders get prioritized alerts, automated remediation for common issues, and AI agents that enrich incidents with context. The result is more predictable operations, less manual firefighting, and measurable business efficiency gains.\u003c\/p\u003e\n\n \u003ch2\u003eHow It Works\u003c\/h2\u003e\n \u003cp\u003eThink of Glances as the central nervous system of your operational environment. Small agents run where your workloads live and constantly report short summaries of system health. Those summaries feed dashboards and alerting rules so a single pane of glass reveals whether systems are operating as expected or if attention is required.\u003c\/p\u003e\n \u003cp\u003eOn its own, Glances gives teams immediate situational awareness: which hosts are spiking, which services are consuming the most memory, and which disks are nearing capacity. The real value emerges when those live signals are treated as triggers for business workflows. An alert can create a ticket, populate a chat thread with context, or call a remediation playbook — and each of those actions can be tailored to match the risk profile of the environment.\u003c\/p\u003e\n\n \u003ch2\u003eThe Power of AI \u0026amp; Agentic Automation\u003c\/h2\u003e\n \u003cp\u003eAdding AI agents and workflow automation turns monitoring from a passive feed into an active problem solver. AI agents read the same signals humans do but at scale and across many sources. They reduce noise, suggest likely causes, and can take safe, repeatable actions when appropriate. This layered approach improves response times, reduces human error, and helps operations scale without linear increases in headcount.\u003c\/p\u003e\n \u003cul\u003e\n \u003cli\u003eSmart triage: AI analyzes alert patterns across systems to cluster related events, reduce duplicates, and surface the most likely root causes so teams don’t waste time chasing symptoms.\u003c\/li\u003e\n \u003cli\u003ePredictive insights: Machine learning detects slow-moving trends — like steadily increasing swap usage or recurring I\/O spikes — and warns teams before incidents materialize, enabling planned maintenance instead of emergency fixes.\u003c\/li\u003e\n \u003cli\u003eAutomated remediation: For low-risk, high-frequency issues, automated playbooks execute trusted actions — restarting hung services, clearing temporary files, or gracefully draining traffic — and log outcomes for auditability.\u003c\/li\u003e\n \u003cli\u003eContext aggregation: When an incident starts, agents collect the right artifacts — recent deploys, process snapshots, error logs, and configuration diffs — and present a concise brief that accelerates decision-making.\u003c\/li\u003e\n \u003cli\u003eCollaborative routing: Chat-based AI agents summarize incidents into human-friendly language, recommend owners based on past resolutions, and route work to the right team with the right priority and context.\u003c\/li\u003e\n \u003c\/ul\u003e\n\n \u003ch2\u003eReal-World Use Cases\u003c\/h2\u003e\n \u003cul\u003e\n \u003cli\u003eProactive incident detection: During a promotional campaign, an AI agent detects rising memory consumption on a key cluster node and opens a prioritized ticket with process and deployment context. Engineers resolve the issue before page load times degrade and conversion drops.\u003c\/li\u003e\n \u003cli\u003eAutomated remediation for routine faults: A web service intermittently becomes unresponsive. A workflow bot attempts a safe restart, records the outcome, and only notifies engineers if the restart fails twice, eliminating repetitive wake-up calls for the on-call team.\u003c\/li\u003e\n \u003cli\u003eCapacity planning and cost control: Trend analysis across months shows several cloud instances are underutilized during off-peak hours. An automation schedules noncritical batch jobs to run during low-cost windows and recommends right-sizing for savings.\u003c\/li\u003e\n \u003cli\u003eSecurity anomaly detection: Unusual network spikes combined with unexpected process executions trigger an AI agent that gathers forensic context and prepares an initial incident dossier for the security team, reducing investigation time by delivering curated evidence.\u003c\/li\u003e\n \u003cli\u003eCompliance and reporting automation: Scheduled agents compile system health, uptime, and inventory snapshots into standardized reports for audits. The AI fills gaps by correlating changes to tickets and deploy logs, which reduces manual effort and audit friction.\u003c\/li\u003e\n \u003cli\u003eIntelligent chat routing and escalation: An intelligent chatbot parses incoming incident messages, identifies urgency and impact, and routes the case to the right escalation path — DevOps for platform issues, SRE for availability, or Security for suspicious activity — preserving focused attention where it matters.\u003c\/li\u003e\n \u003cli\u003eAI-assisted post-incident reviews: After a major incident, an AI assistant aggregates logs, timeline events, and remediation steps into a draft postmortem that engineers can refine. This accelerates learning cycles and improves institutional knowledge capture.\u003c\/li\u003e\n \u003c\/ul\u003e\n\n \u003ch2\u003eBusiness Benefits\u003c\/h2\u003e\n \u003cp\u003eWhen real-time monitoring is extended with AI integration and workflow automation, organizations convert observability into business outcomes: fewer outages, faster recovery, predictable costs, and a more productive engineering culture. Those effects translate directly into improved customer experience and lower operational risk.\u003c\/p\u003e\n \u003cul\u003e\n \u003cli\u003eReduced downtime and faster MTTR: Early detection and automated playbooks shorten mean time to repair, minimizing revenue and productivity losses from outages.\u003c\/li\u003e\n \u003cli\u003eTime savings and fewer distractions: Intelligent filtering and automated resolution of routine incidents free engineers to focus on strategic projects that drive innovation and growth.\u003c\/li\u003e\n \u003cli\u003eBetter decision-making: Consolidated context and predictive alerts enable prioritization based on business impact rather than raw telemetry, reducing costly back-and-forth between teams.\u003c\/li\u003e\n \u003cli\u003eScalability without headcount growth: Automation and AI agents let operations teams cover more systems and services without a proportional increase in staff, supporting rapid scaling and digital transformation.\u003c\/li\u003e\n \u003cli\u003eLower total cost of ownership: Proactive management and right-sizing recommendations help control cloud spend, reduce emergency remediation expenses, and extend the lifespan of existing infrastructure investments.\u003c\/li\u003e\n \u003cli\u003eStronger collaboration and knowledge capture: Agents summarize incidents, attach relevant playbook outputs, and record resolution steps, so teams learn faster and institutional knowledge accumulates rather than relying on tribal memory.\u003c\/li\u003e\n \u003cli\u003eImproved compliance and auditability: Automated collection of evidence and versioned remediation procedures make it simpler to demonstrate controls and maintain an auditable trail for regulators and stakeholders.\u003c\/li\u003e\n \u003c\/ul\u003e\n\n \u003ch2\u003eHow Consultants In-A-Box Helps\u003c\/h2\u003e\n \u003cp\u003eConsultants In-A-Box approaches Glances and AI-enabled monitoring with a business-first mindset. We focus on practical outcomes: reducing downtime, cutting operational overhead, and improving team effectiveness. Our engagements follow a structured sequence that balances quick wins with longer-term capability building.\u003c\/p\u003e\n \u003cp\u003eAssessment: We begin by aligning on business objectives — uptime targets, cost constraints, compliance needs, and where the biggest operational pain points exist. That lets us prioritize which metrics to monitor, where to deploy agents, and which integrations will unlock the most value.\u003c\/p\u003e\n \u003cp\u003eDesign \u0026amp; integration: We design dashboards and alerting that map to business outcomes rather than technical thresholds, and we connect Glances into ticketing, chat, incident response, and configuration management systems so alerts carry the context people need to act.\u003c\/p\u003e\n \u003cp\u003eAutomation \u0026amp; AI: We author tested automation playbooks for routine, low-risk remediations and develop AI agent behaviors that cluster alerts, recommend owners, and assemble investigative context. Everything is safety-first: actions are reversible, auditable, and matched to governance requirements.\u003c\/p\u003e\n \u003cp\u003eRunbooks \u0026amp; enablement: We produce concise runbooks and run hands-on training so teams understand agent behavior, can trust automated actions, and know how to override or escalate when necessary. The emphasis is on practical trust, not black-box automation.\u003c\/p\u003e\n \u003cp\u003eManaged evolution: As your environment and priorities change, we continue to iterate on rules, thresholds, and AI models. This managed evolution ensures monitoring remains aligned with shifting workloads and the organization’s digital transformation goals.\u003c\/p\u003e\n\n \u003ch2\u003eSummary\u003c\/h2\u003e\n \u003cp\u003eGlances offers fast, lightweight visibility into system health; when paired with AI integration and workflow automation it becomes a strategic tool for business efficiency. AI agents reduce noise, predict emerging issues, and automate repeatable fixes while preserving human oversight for complex problems. The combined approach cuts downtime, reduces costs, and scales operational capability — enabling teams to spend less time reacting and more time delivering value.\u003c\/p\u003e\n\n\u003c\/body\u003e"}