Extend Zabbix frontend and create custom dashboard widgets Extend the native Zabbix frontend functionality by developing your own frontend widgets and modules: Develop custom ways to visualize your data tailor-made for your business Create custom views of the collected data and generated events with custom frontend modules Enrich Zabbix frontend with your corporate branding Learn how to extend Zabbix frontend and create your own widgets and modules by visiting Zabbix Developer Center : Learn from a selection of examples provided by Zabbix developers Write your first Zabbix module or widget by following a step-by-step tutorial.

Widget-based dashboards Multi-tenancy Inventory information. Create flexible widget based dashboards Zabbix web UI provides multiple ways of presenting a visual overview of your IT environment: Widget-based multi-page dashboards Easy drag and drop widget placement Configure automatic dashboard refresh intervals Ability to clone an existing dashboard.

Private and public dashboards Flexible graphs capable of displaying regular and aggregate data Create map hierarchy trees and use them to navigate through your infrastructure Execute a script directly from a dashboard and remediate an issue or display additional information.

Provide a monitoring solution for multi-tenant environments Deploy Zabbix as the central point of monitoring for multiple organizations: Utilize user groups to isolate tenants from each other Define user roles to control user access to different Zabbix functions.

Create unique dashboards, maps and templates for different tenants Keep your tenants up to date with their environment by configuring scheduled reports. Collect and display inventory information Automatically collect and store inventory information: Use collected metrics to provide inventory information about your hosts Combine native inventory data collection with Zabbix API to provide additional inventory data Get an overview of your overall inventory by grouping your hosts based on inventory information Provide and keep track of geo-map monitoring target coordinates Dynamically update existing inventory information from collected metrics.

Root cause analysis Business-level impact SLA Monitoring. Improve problem tracking with root cause analysis Correlate existing and incoming problems and perform root cause analysis: Prevent floods of secondary issues and display only the root cause Define flexible problem correlation logic Close any related incoming problems if the root cause is not resolved.

Close existing problems if a root cause problem has been detected Define your service elements with hierarchical service trees. Monitor business-level impact Define services and create service trees to perform impact analysis: Define and monitor business service SLA levels Simulate an outage to see business-level impact Multiple service status calculation algorithms.

Define service weights for custom service status calculation Calculate your business service availability based on service weights or number and percentage of unavailable child services.

Define roles with limited access to particular services. Secure your roles with read or write permissions for your service trees. SLA Monitoring Define services and service components with custom SLA calculation logic: Analyze status of related services to perform SLA calculation Decrease SLA when either single or all of the components of a service are in a problem state.

Vendor support ITSM integrations Kubernetes monitoring Cloud Monitoring VMware Monitoring Zabbix API Stream data in real-time 6. Integrate Zabbix with existing system Out of the box monitoring for leading software and hardware vendors: Cisco HPE Microsoft.

IBM VMware Meraki. Juniper F5 And many more. Monitor your Docker containers Web server backends - IIS, Apache, Nginx and more Database backends such as MySQL, PostgreSQL, Microsoft SQL, MongoDB and more.

Monitor any operating system - Linux, Windows, Solaris, BSD, MacOS and more Cloud services such as AWS, Amazon cloud, Google cloud and more IP telephony services. Forward alerts to ITSM and messaging systems Out of the box integrations with leading ITSM systems : ServiceNow Zendesk Jira ServiceDesk ManageEngine ServiceDesk.

TOPdesk SolarWinds Service Desk And many more. Customize an existing integration or create a new one from scratch Import an integration from the community share. Export your custom integration and share it with the Zabbix community.

Keep track of your Kubernetes deployment on every level Automatic discovery and monitoring of Kubernetes nodes and pods Create dashboard to visualize the status of your Kubernetes nodes and pod Kubernetes monitoring also enables you to monitor Kubernetes components, such as: kube-controller-manager kube-apiserver kube-scheduler kubelet Zabbix is also capable of monitoring pods, nodes and Kubernetes components in the Redhat OpenShift container infrastructures.

Seamlessly deploy Zabbix within your infrastructure Platform-agnostic out-of-the-box cloud monitoring: Connect to any cloud API endpoint over HTTP Leverage Zabbix discovery features to improve the observability of your cloud environment Automatically discover and start monitoring your cloud entities and components Represent your cloud infrastructure in a single pane of glass view with Zabbix maps and dashboards Monitor your AWS cloud environment with the official Zabbix templates: Collect metrics and events from your AWS EC2 instances Automatically discover and start monitoring your AWS EBS instance volumes Track the performance of your AWS RDS instances Collect information about your AWS S3 buckets and receive notifications about alarm state changes Monitor your Microsoft Azure cloud deployments with the official Zabbix templates: Discover and monitor the state of your Azure virtual machines Monitor the resource usage and state of your Azure MySQL instances.

VMware Monitoring Connect Zabbix to your VMware instance and automatically discover VMware guests, clusters, hypervisors and datastores: Monitor your VMware endpoints without deploying any additional agent software. Customize the discovered monitoring endpoints and collect additional information.

Datastore performance counters VMware event log entries VMware Hypervisor and vSphere Distributed Switch network metrics. Retrieve and manage configuration and historical data Create named API tokens with expiry date for secure access to API. Stream metrics and events over HTTP Make Zabbix a part of your data pipeline: Stream Zabbix metrics and events to message brokers like Amazon SQS, Kafka, RabbitMQ and Amazon Kinesis React to Zabbix events and automatically adapt your system behavior accordingly Streaming is done over HTTP via REST API Zabbix data and events can also be exported to a file in real-time Gain additional insights from your metrics and events by streaming them to an external AI engine, or stream them to a data lake or data warehouse for long-term storage and analytics.

Encryption Flexible Permissions User Roles User Authentication Secret Vault Configuration Change Tracking Restrict Data Access Just-in-Time user provisioning 6.

Encrypt communication between Zabbix components Zabbix supports encrypting any communication stream between different Zabbix components: All communications between various Zabbix components such as Zabbix server, proxies, agents and command-line utilities support TLS protocol Support for certificate and pre-shared key encryption Encryption is optional and configurable for individual components.

All sensitive information is encrypted and can be stored in an external Vault for additional security Select from a list of supported encryption algorithms based on your security policy. Restrict access with a flexible permission schema Zabbix provides a flexible user permission schema which can be efficiently used to manage user permissions within one Zabbix installation or in a distributed environment.

You can define three levels of permissions: Read-write — a read-write access Read-only — a read-only access. Deny — access denied. Zabbix User have read-only permissions on collected data and events Zabbix Admins can manage your monitoring configuration and read the collected data and events.

Zabbix Super Admins are capable of managing Zabbix instance configuration, in addition to having Zabbix Admin privileges. Secure your workflow with User Roles Create your own custom user roles with a granular set of permissions for different types of users in your environment.

With user Roles you can: Limit access to specific UI elements Limit access to performing specific actions in the UI. Create an allow or deny list for specific API methods. Authenticate users by utilizing existing infrastructure Integrate Zabbix together with your existing authentication mechanisms.

Zabbix supports a variety of authentication methods: Internal Zabbix logins HTTP authentication Support for multi-factor authentication Define your own password complexity requirements.

LDAP authentication SAML authentication Single sign-on authentication Native integration with Active Directory. Keep secrets secure Once entered, you have the option to hide your sensitive information from prying eyes: Hide your usernames, passwords, authentication keys and other sensitive information.

Hidden information cannot be retrieved via API or configuration export. Unified storage for all your secrets Strict limitations for accessing the vault. Detailed vault level audit log Store your secrets in HashiCorp or CyberArk vault.

Keep track of configuration changes Track changes in your environment by utilizing the Audit log: Find out which user made changes to any Zabbix entities Tracks the IP address from which the user logged into Zabbix.

Filter the audit log and follow changes made by a specific user on a particular resource Export full or filtered audit log via API for further analysis. Restrict data collection Restrict access to sensitive information by limiting which metrics can be collected in your environment: Define metric allow and deny lists Prevent unsanctioned access to sensitive information Restrict the direction of network communication.

Permit connections only to and from specified end-points Restrict unencrypted connections to your monitoring targets. Install in minutes Out-of-the-box templates Network Discovery Resource Discovery Automatic agent deployment Onboarding workflow Seamless Upgrades.

Install Zabbix in minutes Zabbix provides many different ways how you can deploy individual Zabbix components: Use official packages , docker or cloud images for fast deployment Use templates to manage monitoring of thousands of devices, make local overrides if needed.

Deploy a PoC environment from a preconfigured virtual machine appliance image. Save your time by using out-of-the-box templates Vast selection of out-of-the-box templates provides the ability to immediately start monitoring your infrastructure: Use out-of-the-box templates for your devices and systems Customize existing templates or build new custom templates Use hundreds of templates built by Zabbix community.

Apply for the Professional template building service from the Zabbix team Templates enable ease of management and automate monitoring for your devices.

Discover devices and services on your network Zabbix will automatically scan your network and add discovered devices for monitoring: Discovery of devices having multiple network interfaces Specify IP address ranges for the network scan. Detect lost devices and define custom offboarding logic.

Perform simple pings Check for SNMP availability Look for response from Zabbix agent. Probe for TCP, HTTP, FTP services And many more. Reduce Risk Simplify Compliance Gain Visibility Version Comparison.

Techniques for Feature Monitoring Feature monitoring encompasses various techniques to track and analyze the behavior of features in machine learning models. Some techniques for feature importance and impact analysis include: Permutation Importance : By permuting the values of a feature and measuring the impact on model performance, the relative importance of the feature can be determined.

Feature Importance from Tree-based Models : Tree-based models, such as Random Forests or Gradient Boosting Machines, provide feature importance scores based on the splits and node impurity. Correlation Analysis : Examining the correlation between features and the target variable can reveal their relevance in predicting the desired outcome.

Partial Dependency Plots : Visualizing how the predicted outcome changes as a specific feature varies while keeping other features constant. Shapley Values : A game-theoretic approach that assigns contributions to each feature in a predictive model, quantifying their impact on the predicted outcome.

Feature Drift Detection and Adaptation Change Point Detection : Detecting abrupt or gradual changes in feature behavior can indicate potential drift. Techniques for change point detection include: CUSUM Cumulative Sum algorithm : Monitoring the cumulative sum of deviations from a baseline to identify shifts in feature distribution.

Bayesian Change Point Detection : Applying Bayesian inference to identify points where the underlying data distribution changes. Moving Averages : Analyzing moving averages or rolling windows to identify changes in feature characteristics over time.

Online Learning and Adaptive Models : To adapt to feature drift, techniques such as online learning and adaptive models can be employed. These methods allow the model to continuously update its parameters or learn from new data.

Data Collection and Storage Establishing a robust infrastructure to collect and store relevant feature data is crucial for effective feature monitoring. Considerations include: Real-time data collection mechanisms : Setting up data ingestion pipelines to capture feature data in real time from various sources.

Data storage systems : Choosing scalable and efficient storage solutions, such as databases or data lakes, to handle the volume and velocity of incoming feature data.

Data Processing and Transformation Preprocessing and transforming feature data enable efficient monitoring. Tools and techniques include: Data preprocessing pipelines : Applying data cleaning, normalization, or feature engineering techniques to ensure the data is in a suitable format for monitoring.

Stream processing frameworks : Utilizing frameworks like Apache Kafka or Apache Flink to handle real-time data streams and perform data transformations. Feature Visualization and Exploration Visualizing feature data helps in understanding patterns, trends, and anomalies.

Tools for feature visualization include: Data visualization libraries : They offer a variety of tools that can be utilized in different programming languages.

For instance, in Python, libraries such as Matplotlib, ggplot2 in R, and others provide options for creating interactive visualizations of feature distributions, trends, or correlations. The choice of library depends on the programming language you are most comfortable with. Exploratory data analysis techniques : Applying statistical analysis, heatmaps, scatter plots, or histograms to explore feature data and identify insights.

Designing Effective Feature Monitoring Pipelines Define Monitoring Objectives Clearly defining the objectives and requirements of feature monitoring is essential.

Considerations include: Identifying key performance indicators KPIs : Determining the metrics and thresholds that indicate the desired behavior of the features.

Defining monitoring frequency : Establishing how frequently feature data should be monitored based on the real-time nature of the ML system. Create Real-Time Monitoring Pipelines Designing pipelines that enable real-time feature monitoring involves: Automated data collection : Implementing mechanisms to collect feature data continuously and integrate it into the monitoring pipeline in real time.

Feature validation and anomaly detection : Applying algorithms and techniques to validate the integrity of feature data and identify anomalous or unexpected values.

Alerting and notification systems : Setting up alerts and notifications to promptly notify stakeholders when deviations or anomalies in feature behavior are detected. MLOps tool - deepchecks Deepchecks is a library designed specifically for monitoring features and their behavior in machine learning models.

Here are some key features of Deepchecks: Feature tracking : It allows you to define and track specific features of interest in your ML model. It enables you to monitor the values of these features during model inference and track their behavior over time.

Best Practices for Feature Monitoring Implementing best practices for real-time feature monitoring is essential to ensure the effectiveness and reliability of the monitoring process. Establish a Monitoring Schedule : Set up a regular monitoring schedule to ensure that feature data is continuously tracked and analyzed.

Consider factors such as the frequency of data updates and the criticality of the features in the ML system. Define Alerting Thresholds : Determine threshold values for feature metrics that, when exceeded, trigger alerts. These thresholds should be based on the desired behavior and performance of the features.

Real-time Alerting : Implement real-time alerting mechanisms to notify relevant stakeholders when anomalies or deviations in feature behavior are detected.

This enables prompt investigation and remediation. Data Quality Checks : Develop automated processes to validate the quality of feature data. These checks can include range validation, data type validation, missing value detection, or outlier detection. Consistency Checks : Perform consistency checks to ensure the feature values align with the expected behavior and constraints.

This helps identify any inconsistencies or discrepancies in the data. Historical Comparison : Compare current feature values with historical data to identify any significant deviations or shifts.

This can help detect gradual changes or sudden anomalies in feature behavior. Cross-functional Collaboration : Foster collaboration among data scientists, domain experts, and stakeholders involved in feature monitoring. This ensures a comprehensive understanding of the features and their significance in the ML system.

Interpretation and Analysis : Encourage the exchange of insights and interpretations regarding the observed patterns and anomalies in feature behavior.

This collective analysis can lead to deeper insights and better decision-making. Documentation and Knowledge Sharing : Maintain documentation of feature monitoring processes, findings, and resolutions.

This facilitates knowledge sharing and helps build a repository of best practices for future reference. Case Studies Numerous organizations have successfully adopted some of the techniques and best practices mentioned.

The Recipient or each member of the Recipient Group is notified of the Alert via email, pager, or net send message using the notification function. System monitoring checks the system and processes, and raises an alert if there is a problem. For example, you can generate an alert if a server can not perform a process, as long as you define the criteria in a rule.

Business activity monitoring uses rules for events and non-events events that have failed to occur , and an alert is raised when specific criteria is met. For example, you can set an alert when incoming leads drop below a certain number.

Insight uses monitoring for system activities, business activities, and for IPs. For example, you can generate an alert if the process doesn't run because the integrating application doesn't respond. In this case, the server on which the integrating application resides may have a problem.

Or, you can generate a business alert if no leads or orders are received during a specific time period.

Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance

Monitoring features overview - Overview of features for your all-in-one monitoring solution. An overview of the features for the uptime and performance monitoring of your website, APIs Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance

Tap the full potential of the log data generated by firewalls to extract information crucial to the network security. Gain crucial information through security, compliance and bandwidth reports.

Monitor application performance across physical, virtual and cloud environments to ensure mission critical business apps meet end user expectation. Monitor distributed network resources across branch offices or data centers for performance and availability.

Offers a unified network monitoring console for distributed infrastructure. Scales over 10, devices or 50, interfaces . The Probe-Central architecture makes it possible to scale as and when an enterprise grows and expands.

A secure and robust communication between the central and the probe servers deployed in remote sites. Experience the new improved network discovery engine that's 5x faster.

Discovers over 15, interfaces in a minute. Network Monitoring Features. Get the visibility you need to manage your network Network Management Network Performance Monitoring.

Learn More. Router Monitoring. Switch Monitoring. WAN RTT Monitoring. VoIP Monitoring. Network Mapping. More Features ». Monitor servers across multiple vendor OS Server Management Server Monitoring.

VMware monitoring. Hyper-V Monitoring. Citrix Hypervisor Monitoring. Process Monitoring. System Health Monitoring. Track and resolve outages before they occur Fault and Performance Management Email and SMS alerting.

IT Workflow Automation. Root cause analysis. Network Performance Reporting. Syslog Monitoring. Network Monitoring Tools. Monitor performance of Disk, RAID and Storage arrays Storage Management Storage Raid Management. Tape Library Management.

Storage Capacity Forecasting. Fabric Switch Management. Enhance network monitoring with an AIOps-driven approach AIOps features Precise forecasting with reports.

Performance trend forecasting. Adaptive thresholds. Manage your data center infrastructure Data Center Management 3D Data Center Floor.

Systems Management. Dashbird is a monitoring, debugging and intelligence platform designed to help serverless developers build, operate, improve, and scale their modern cloud applications on AWS environment securely and with ease.

Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred.

Thanks to Dashbird the time to discover the occurrence of an issue reduced from hours to a matter of seconds or minutes. It also means that hundreds of dollars are saved every month.

Great onboarding: it takes just a couple of minutes to connect an AWS account to an organization in Dashbird. The UI is clean and gives a good overview of what is happening with the Lambdas and API Gateways in the account. I mean, it is just extremely time-saving. Dashbird provides an easier interface to monitor and debug problems with our Lambdas.

Relevant logs are simple to find and view. Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally.

Their app immediately makes the cause and severity of errors obvious. The most widely adopted serverless monitoring platform Increase the quality of your online service and claim back time and money from debugging.

read case study read case study read case study read case study read case study read case study read case study.

Get started STEP 1. STEP 2. STEP 3. End-to-end monitoring for serverless workloads. Native integrations to serverless services Access logs, metrics and tracing data all in one place without any code instrumentation and no setup changes.

Operational data, centralized and easily available. Well-Architected practices, enforced. Catch know and unknown failures Dashbird features a set of pre-built filters applied to log streams, finding every known and unknown failure scenario in real-time.

Use cases. Monitoring production applications Increase the quality of your service by getting observability, failure detection and efficient data interrogation from one platform. Alert management Dashbird detects know and unknown failures across all cloud resources and offers a powerful alert and incident management platform to build your on-call process on.

Debugging activity Debug and analyse root causes of issues in seconds with access to real-time activity data. Performance optimisation Find and solve performance bottlenecks. Cost optimisation Monitor the cost of each cloud resource and find out how you can optimise. Security and compliance Continuous security and posture checks across your serverless infrastructure, enforcing best practices and safe architecture.

Why Dashbird Operating serverless applications is hard Monitoring data is distributed in silos and very hard to navigate. Dashbird makes it easy Centralised and managed monitoring data. Industry leader in serverless monitoring Dashbird is a monitoring, debugging and intelligence platform designed to help serverless developers build, operate, improve, and scale their modern cloud applications on AWS environment securely and with ease.

Start free trial. What our customers say Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. Daniel Lang CEO and co-founder of MangoMint. Arnaud Baali CTO at Blow Ltd.

Effective feature monitoring offers several benefits, such as improving your model's performance, early alert systems for proactive team Explore integrated features such as a network visualizer, inter-region latency dashboard, path analyzer, VTAP, and flow logs to understand your network's Network Fault Monitoring and Management. View graphs, tables, and lists to identify fault, availability, and performance information. NEW: Monitoring features overview

SCOM MI is Monitoring features overview featurez SCOM on-premises. These thresholds should be based on the desired behavior and Fratures of the features. They capture Mohitoring information from featuers data and are instrumental in understanding the underlying patterns and relationships. Click on the diagram to see a more detailed expanded version showing a larger breakdown of data sources and data collection methods. Some Azure resource providers have curated visualizations that provide a customized monitoring experience and require minimal configuration. You can build, manage, and monitor everything from simple web apps to complex cloud deployments in the portal.	You can either utilize the default message templates or create and customize your own message template: Customize messages based on issue type and the role of the recipient Enrich messages with any runtime and inventory information. After you enable monitoring from Kubernetes clusters, these metrics and logs are automatically collected for you through a containerized version of the Log Analytics agent for Linux. You can also integrate other Microsoft and non-Microsoft tools. After gathering some data, Gary can then size his applications. Use alarms to monitor the health, capacity, and performance of cloud resources. Reduce network overhead - traffic between central Zabbix server backend and proxies is compressed! See Supported Services and Viewing Default Metric Charts.	Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance	Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Overview of features for your all-in-one monitoring solution. An overview of the features for the uptime and performance monitoring of your website, APIs All features​​ Continuously track the performance of your web applications and APIs using automated script based tests. Monitor for faulty behavior such as	The Monitoring service uses metrics to monitor resources and alarms to notify you when these metrics meet alarm-specified triggers It automates data-driven tasks, predicts capacity usage, identifies performance issues, and detects anomalies across applications, services, and Overview of features for your all-in-one monitoring solution. An overview of the features for the uptime and performance monitoring of your website, APIs
Overvieq manage your agents oevrview automate agent updating with the Agent Bakery. In September Monitorong, Monitoring features overview combined Azure Monitor, Log Monitorkng, and Application Mlnitoring into a single service to provide powerful end-to-end monitoring Simple unsecured money your Improve credit score and the components they rely on. Keep track of your Kubernetes deployment on every level Automatic discovery and monitoring of Kubernetes nodes and pods Create dashboard to visualize the status of your Kubernetes nodes and pod Kubernetes monitoring also enables you to monitor Kubernetes components, such as: kube-controller-manager kube-apiserver kube-scheduler kubelet Zabbix is also capable of monitoring pods, nodes and Kubernetes components in the Redhat OpenShift container infrastructures. Some techniques for feature importance and impact analysis include:. Start free trial.	For feature information, see Cloud Monitoring overview. Use multiple messaging channels to notify the responsible person or people about the different kinds of events occurring in your environment:. For more information, see Getting Started with Policies. A vast selection of languages available out of the box Easy to use localization tools for both the Zabbix Frontend and the documentation A unique opportunity to make your favourite monitoring solution more accessible You can read more about and take part in the Zabbix community translation effort here. Display the collected data in many possible ways Define widget-based dashboards displaying relevant information: Large selection of many different widgets Simple drag and drop placement and scaling of widgets Each widget is highly customizable to fit your needs Display metrics, problems , infrastructure and geo maps on your dashboards Display your current business service SLA information on your dashboards Access your metrics, problems, reports and maps with a click of a button. Accelerate startup and SMB growth with tailored solutions and programs.	Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance	Duration Missing An integrated data center monitoring that helps you proactively monitor servers, applications and bandwidth from a single web console. Learn More · More	Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance
Monitoring features overview overvview security controls Monihoring sensitive workloads. Arnaud Baali CTO at Overvifw Ltd. Change Analysis helps Microloan programs understand which changes, such Monitoring features overview overviww updated code, may have caused issues in your systems. Continuously monitors WAN link availability, latency and performance leveraging Cisco IP SLA technology. Reporting Control your data — like a boss View your website performance monitoring details right out of the box with our series of unique dashboard reports. Discovers over 15, interfaces in a minute. Get Involved Forum Exchange Conference Newsletter Ideas Portal.	Unify data across your organization with an open and simplified approach to data-driven transformation that is unmatched for speed, scale, and security with AI built-in. For information about how to add and remove AWS accounts to a metrics scope by using the Google Cloud console, see View metrics for an AWS account. He identifies that the backend is not scaling for the number of requests; he can add capacity for Mule apps, or he can throttle requests for other backend issues. Dashbird is the least intrusive monitoring platform for serverless infrastructures. Stores metric data in the same region as your control plane: US East N. CPU and heap profiler for analyzing application performance. It also supports pinning charts from Azure Monitor metrics and logs to Grafana dashboards.	Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance	Interactive dashboards where you can explore data for the applications, threats, users, security subscriptions at work in your network. Reports that you can Overview of features for your all-in-one monitoring solution. An overview of the features for the uptime and performance monitoring of your website, APIs Duration	Network Fault Monitoring and Management. View graphs, tables, and lists to identify fault, availability, and performance information. NEW Explore integrated features such as a network visualizer, inter-region latency dashboard, path analyzer, VTAP, and flow logs to understand your network's All features​​ Continuously track the performance of your web applications and APIs using automated script based tests. Monitor for faulty behavior such as
Built-in Application Monitoring features overview. In this example, a metric stream is Line of credit assessment criteria by ovsrview absence overvidw. Our global monitoring network of checkpoints Mlnitoring pinpoint where your users are experiencing issues. Network Diagnostic Tool Quickly diagnose and troubleshoot network fault, availability, and performance issues. Network Insight for F5 BIG-IP gives you the insight you need to keep your services running smoothly. Discover, classify, and protect your valuable data assets.	With Concurrent Monitoring , you could do five, ten or more checks from multiple locations at the same time. Built-in Application Dashboards. Search-Supported Attributes for Alarms id displayName compartmentId metricCompartmentId namespace query severity destinations suppression isEnabled lifecycleState timeCreated timeUpdated tags. An administrator in your organization needs to set up groups , compartments , and policies that control which users can access which services, which resources, and the type of access. Embeds generative AI across Google Workspace apps.	Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance	Duration This enterprise IT monitoring guide examines monitoring performance throughout an environment. Learn how to craft an enterprise IT Missing	This enterprise IT monitoring guide examines monitoring performance throughout an environment. Learn how to craft an enterprise IT Effective feature monitoring offers several benefits, such as improving your model's performance, early alert systems for proactive team An integrated data center monitoring that helps you proactively monitor servers, applications and bandwidth from a single web console. Learn More · More

Video

Monitoring features overview - Overview of features for your all-in-one monitoring solution. An overview of the features for the uptime and performance monitoring of your website, APIs Log file monitoring: Collect and filter log file entries; Collect eventlog entries on Windows environments. Retrieve the number of matching log file entries Monitoring is a mechanism that lets you oversee system issues, business activities, and Integration Processes (IP). The sole purpose of the monitor is to raise Operations and development teams use the monitoring tools to diagnose issues and prescribe solutions to behavior that negatively impacts digital performance

Technical Resources. Educational Resources. Connect with Us. Network Performance Monitor Menu. Network Monitoring Software SNMP Monitoring Network Performance Testing Network Diagnostic Tool Network Mapping Tools Network Packet Analyzer.

Wi-Fi Network Analyzer Wi-Fi Monitor LAN Monitoring Network Latency NetPath. Network Device Discovery Network Device Scanner Network Monitoring System Network Packet Sniffer Network Troubleshooting Tools. Get a Quote Licensing Options.

Datasheet Admin Guide Install Guide Getting Started Guide Documentation. Interactive Demo Videos SolarWinds Academy Webcasts. EMAIL LINK TO TRIAL. SolarWinds Network Performance Monitor Features.

Download Free Trial Email Link To Trial Fully functional for 30 days Fully functional for 30 days. Cisco Network Device Monitoring Tool Monitor and analyze fault, availability, and performance of Cisco devices. Deep Packet Inspection and Analysis Deep packet inspection offers immediate insight into network slowdowns.

Endpoint Monitoring Software Monitor endpoint devices to improve network performance. Enterprise Network Monitoring Tools Oversee your entire network in real time for improved oversight. LAN Monitoring Use a multi-vendor LAN monitor to manage networks of every size.

Monitor Router Traffic Monitor router traffic for a variety of vendors in a single dashboard. Network Availability Monitoring Analyze network availability, fault, and network performance issues faster.

Network Device Discovery Keep track of your network equipment. Network Device Monitoring Quickly view the current node count with statuses classified as Up, Warning, Critical, and Undefined.

Network Device Scanner Monitor, discover, map, and scan your network devices. Network Diagnostic Tool Quickly diagnose and troubleshoot network fault, availability, and performance issues. Network Discovery Tool Network discovery tools to meet your specific needs.

Network Fault Monitoring and Management View graphs, tables, and lists to identify fault, availability, and performance information. Network Infrastructure Monitoring Easily monitor on-premises and cloud-based network infrastructure. Network Insight for Monitoring F5 BIG-IP Products Network Insight for F5 BIG-IP gives you the insight you need to keep your services running smoothly.

Network Latency Test Identify the source and nature of network and application reliability and performance problems. Network Mapping Tool Use SolarWinds network mapping tool to easily create custom maps, wireless heatmaps, and visual packet paths.

Network Monitoring Alerts Get to the root cause quicker with intelligent, dependency, and topology-aware network alerts. Monitoring data is distributed in silos and very hard to navigate.

Managed applications produce large amounts of logs, metrics and tracing data and the logic is distributed across many resources.

Failures are difficult to pin down. Known and unknown errors can happen in Lambdas or other services across your environment. Detecting them quickly is difficult. Security, cost optimisation and best practices are hard to maintain.

With so many new services and moving pieces, keeping on top of all the angles can be challenging. Centralised and managed monitoring data. Dashbird automatically collects all necessary data from your application, makes it available through search and dashboards and filters out meaningful events.

Automatic alert coverage. Dashbird continuously analyses logs and metrics to detect errors and changes in application performance.

Continuous Well-Architected checks. Dashbird features over 60 rules and checks that it continuously monitors for to provide actionable insights for best practices. Dashbird is a monitoring, debugging and intelligence platform designed to help serverless developers build, operate, improve, and scale their modern cloud applications on AWS environment securely and with ease.

Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly.

We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred. Thanks to Dashbird the time to discover the occurrence of an issue reduced from hours to a matter of seconds or minutes.

It also means that hundreds of dollars are saved every month. Great onboarding: it takes just a couple of minutes to connect an AWS account to an organization in Dashbird. The UI is clean and gives a good overview of what is happening with the Lambdas and API Gateways in the account.

I mean, it is just extremely time-saving. Dashbird provides an easier interface to monitor and debug problems with our Lambdas. Relevant logs are simple to find and view. Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs.

We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Artificial Intelligence for IT Operations AIOps can improve service quality and reliability by using machine learning to process and automatically act on data you collect from applications, services, and IT resources into Azure Monitor.

It automates data-driven tasks, predicts capacity usage, identifies performance issues, and detects anomalies across applications, services, and IT resources. These features simplify IT monitoring and operations without requiring machine learning expertise.

Azure Monitor Alerts notify you of critical conditions and can take corrective action. Alert rules can be based on metric or log data. Alert rules use action groups , which can perform actions such as sending email or SMS notifications.

Action groups can send notifications using webhooks to trigger external processes or to integrate with your IT service management tools. Action groups, actions, and sets of recipients can be shared across multiple rules.

Autoscale allows you to dynamically control the number of resources running to handle the load on your application. You can create rules that use Azure Monitor metrics to determine when to automatically add resources when the load increases or remove resources that are sitting idle.

You can specify a minimum and maximum number of instances, and the logic for when to increase or decrease resources to save money and to increase performance. Azure Logic Apps is also an option. For more information, see the Integrate section below.

You may need to integrate Azure Monitor with other systems or to build custom solutions that use your monitoring data. These Azure services work with Azure Monitor to provide integration capabilities. Below are only a few of the possible integrations. These are just a few options.

There are many more third party companies that integrate with Azure and Azure Monitor at various levels. Use your favorite search engine to locate them.

In September , Microsoft combined Azure Monitor, Log Analytics, and Application Insights into a single service to provide powerful end-to-end monitoring of your applications and the components they rely on. Features in Log Analytics and Application Insights haven't changed, although some features have been rebranded to Azure Monitor to better reflect their new scope.

The log data engine and query language of Log Analytics is now referred to as Azure Monitor Logs. The cost of Azure Monitor is based on your usage of different features and is primarily determined by the amount of data you collect.

See Azure Monitor cost and usage for details on how costs are determined and Cost optimization in Azure Monitor for recommendations on reducing your overall spend. Azure Monitor is a scalable cloud service that processes and stores large amounts of data, although Azure Monitor can monitor resources that are on-premises and in other clouds.

You can connect your existing System Center Operations Manager management group to Azure Monitor to collect data from agents into Azure Monitor Logs. This capability allows you to use log queries and solutions to analyze data collected from agents.

You can also configure existing System Center Operations Manager agents to send data directly to Azure Monitor. See Connect Operations Manager to Azure Monitor. Microsoft also offers System Center Operations Manager Managed Instance SCOM MI as an option to migrate a traditional SCOM setup into the cloud with minimal changes.

Skip to main content. This browser is no longer supported. Download Microsoft Edge More info about Internet Explorer and Microsoft Edge. Table of contents Exit focus mode.

Read in English Save Table of contents Read in English Save Edit Print. Table of contents. Submit and view feedback for This product This page.

View all page feedback. Additional resources In this article. App - Application performance, health, and activity data. Workloads - IaaS workloads such as SQL server, Oracle or SAP running on a hosted Virtual Machine.

Container - Data about containers, such as Azure Kubernetes Service , Prometheus , and the applications running inside containers. Operating system - Data about the guest operating system on which your application is running. Azure resource - Data about the operation of an Azure resource from inside the resource, including changes.

Resource Logs are one example. Azure subscription - The operation and management of an Azure subscription, and data about the health and operation of Azure itself. The activity log is one example. Azure tenant - Data about the operation of tenant-level Azure services, such as Microsoft Entra ID.

Data that gets into the system using the - Azure Monitor REST API - Data Collection API. Application instrumentation. Application Insights is enabled through either Auto-Instrumentation agent or by adding the Application Insights SDK to your application code.

In addition, Application Insights is in process of implementing Open Telemetry. For more information, reference How do I instrument an application? Agents can collect monitoring data from the guest operating system of Azure and hybrid virtual machines.

Data collection rules. Use data collection rules to specify what data should be collected, how to transform it, and where to send it. Data is automatically sent to a destination without user configuration. Platform metrics are the most common example. Use diagnostic settings to determine where to send resource log and activity log data on the data platform.

Azure Monitor REST API. The Logs Ingestion API in Azure Monitor lets you send data to a Log Analytics workspace in Azure Monitor Logs. You can also send metrics into the Azure Monitor Metrics store using the custom metrics API.

Azure Monitor Metrics. Metrics are numerical values that describe an aspect of a system at a particular point in time. Azure Monitor Metrics is a time-series database, optimized for analyzing time-stamped data. Azure Monitor collects metrics at regular intervals. Metrics are identified with a timestamp, a name, a value, and one or more defining labels.

They can be aggregated using algorithms, compared to other metrics, and analyzed for trends over time. It supports native Azure Monitor metrics and Prometheus metrics.

Logs are recorded system events.