LoadGen Insight : Comprehensive IT Performance and Monitoring Solution

Product Overview

LoadGen Insight is an advanced monitoring and performance management tool designed to provide deep insights into the usage and performance of IT environments. It supports a wide range of environments, including virtual desktops, web applications, and cloud services. LoadGen Insight offers real-time monitoring, detailed analytics, and proactive performance management to ensure optimal system performance and user experience.

Benefits of LoadGen
Insight

Improved User Experience

By continuously monitoring and optimizing performance, LoadGen Insight ensures a superior user experience across all applications and systems.

Enhanced Operational Efficiency

Proactive performance management helps prevent issues before they occur, reducing downtime and improving operational efficiency.

Scalability

Easily scale your monitoring and performance management capabilities as your IT environment grows, ensuring consistent performance and reliability.

LoadGen is made for your virtual desktop environment

... and for your web testing needs

Use Cases

Virtual Desktop Infrastructure Monitoring

Ensure the performance of virtual desktops by monitoring resource usage and user experience, helping to maintain optimal performance and productivity.

Web Application Performance

Monitor web application performance across different browsers and devices to ensure a consistent and high-quality user experience.

Capacity Planning

Use historical data and trend analysis to plan for future capacity needs, ensuring systems are neither over-provisioned nor under-provisioned, thus optimizing resource usage.

Compliance and Reporting

Generate detailed reports to meet compliance requirements and provide insights to stakeholders. The comprehensive data analytics and reporting tools make it easier to adhere to industry standards and regulations.

Data Storage Options

On-Premises or Own Cloud

LoadGen Insight allows you to store all monitoring and performance data on-premises or within your own private cloud. This setup utilizes InfluxDB for time-series data storage and Grafana for data visualization and dashboards.

Hosted by LoadGen

Alternatively, you can choose to have LoadGen host your data, providing a fully managed service that includes data storage, security, and maintenance. This option ensures hassle-free data management and high availability.

L&P Pricing

Key Features

Real-Time Monitoring

Performance Tracking

Continuously monitor key performance indicators (KPIs) such as CPU usage, memory consumption, network throughput, and application performance.

Alerting and Notifications

Set up custom alerts to receive real-time notifications about critical performance issues, enabling prompt responses and resolutions.

Detailed Analytics

Usage Patterns

Analyze detailed usage patterns to understand how applications and systems are utilized. This helps in identifying peak usage times and optimizing resource allocation.

Performance Metrics

Gain insights into various performance metrics across servers, storage, and network components, allowing for a comprehensive understanding of system health and performance.

Customizable Dashboards

Tailored Views

Continuously monitor key performance indicators (KPIs) such as CPU usage, memory consumption, network throughput, and application performance.

Set up custom alerts to receive real-time notifications about critical performance issues, enabling prompt responses and resolutions.

Interactive Widgets

Integration with Existing Tools

Third-Party Integrations

Seamlessly integrate with existing monitoring and management tools like Neotys, CA APM, New Relic, AppDynamics, Dynatrace, and CloudWatch, allowing for a unified monitoring experience.

Use RESTful APIs to integrate LoadGen Insight with other systems and tools within your IT infrastructure for enhanced functionality and data sharing.

API Access

Proactive Performance Management

Predictive Analytics

Utilize predictive analytics to identify potential performance issues before they impact end-users, allowing for proactive management.

Receive recommendations for optimizing system performance based on detailed data analysis and trends.

Optimization Recommendations

Synthetic metrics are essential for understanding the performance characteristics of a system by creating controlled and repeatable test conditions. These metrics provide insights into various aspects of system behavior, such as response times, processing efficiency, and resource utilization.

Metric	Description
Iteration	Tracks the number of times a specific test or operation is repeated.
Loadbot	Identifies the specific bot or agent used to generate the load.
Loadbot_ip_address	Records the IP address of the load-generating bot or agent.
Loadtest_relative_time	Measures the relative time during the load test execution.
Remote_server	Identifies the server being tested or interacted with.
Message	Logs specific messages or events during the test.
Session_time	Tracks the duration of a user session from start to finish.
Sub_transaction_name	Names of specific sub-transactions within a larger transaction.
Sub_transaction_time	Measures the time taken for sub-transactions.
Sub_transaction_time_inclusive	Total time including nested sub-transactions.
Transaction_name	Names of the main transactions being tested.
Transaction_time	Measures the time taken for main transactions.
Transaction_time_inclusive	Total time including all nested transactions.
Type	Specifies the type of metric or transaction.
Waste_time	Tracks time spent on non-productive activities or delays.
Waste_time_subtransaction	Measures waste time specifically within sub-transactions.

System performance metrics are crucial for understanding how different system resources are utilized during operations. These metrics help in identifying bottlenecks and optimizing resource allocation for better performance. Collected every 1 second.

Metric	Description
logical_disk_current	Monitors the current activity on logical disks.
logical_disk_perc_disk_time	Measures the percentage of time that the disk is busy.
logical_disk_perc_idle_time	Tracks the percentage of time that the disk is idle.
memory_available_bytes	Amount of available memory in bytes.
memory_available_gbytes	Amount of available memory in gigabytes.
memory_available_mbytes	Amount of available memory in megabytes.
memory_commited_bytes	Total committed memory in bytes.
memory_committed_gbytes	Total committed memory in gigabytes.
memory_committed_mbytes	Total committed memory in megabytes.
memory_pool_non_paged_bytes	Non-paged pool memory in bytes.
memory_pool_non_paged_gbytes	Non-paged pool memory in gigabytes.
memory_pool_non_paged_mbytes	Non-paged pool memory in megabytes.
memory_pool_paged_bytes	Paged pool memory in bytes.
memory_pool_paged_gbytes	Paged pool memory in gigabytes.
memory_pool_paged_mbytes	Paged pool memory in megabytes.
physical_disk_read_per_sec	Number of disk read operations per second.
physical_disk_transfers_per_sec	Number of disk transfer operations per second.
physical_disk_writes_per_sec	Number of disk write operations per second.
proc_perc_interrupt_time	Percentage of time the processor spends handling interrupts.
processor_perc_processor_time	Overall percentage of processor time used.

Process Information Metrics provide detailed data about processes running on a system, including metadata about the application, its version, and other relevant details. This information is crucial for tracking and auditing processes, understanding application behavior, and identifying potential issues related to process management.

Metric	Description
batch_id	A unique identifier (GUID) for the batch of metrics collected. This helps in grouping and identifying related metrics collected during the same interval.
domain	The domain name under which the process is running. This is particularly useful in multi-domain environments to track where the process is executed.
event_type	The type of event related to the process (e.g., start, stop). This helps in understanding the state changes of the process over time.
executable_path	The file path to the executable of the process. This identifies where the process binary is located, which is useful for verifying the integrity and origin of the application.
file_version	The version of the file being executed. This helps in ensuring that the correct version of the software is running, which is crucial for compliance and troubleshooting.
id	The unique identifier of the process within the system. This is used to track the specific instance of a process.
process_guid	A globally unique identifier for the process, which remains consistent even if the process ID changes during its lifecycle.
process_id	The process ID assigned by the operating system, which is used to track the running process in real-time.
product_version	The version of the product associated with the process. This is important for managing software versions across different systems.
time_created	The timestamp of when the process was created or the event occurred. This is used for chronological tracking and auditing purposes.

Application specifications metrics provide detailed data about the installed applications and updates on a system. This data is critical for managing software inventory, ensuring compliance, and understanding the software landscape within an organization. The following are the key metrics captured for installed applications.

Metric	Description
batch_id	A unique identifier (GUID) for the batch of metrics collected. This groups related metrics collected during the same operation.
name	The name of the installed application.
version	The version number of the installed application.
vendor	The software vendor or publisher.
install_date	The date when the application was installed on the system.
description	A brief description of the application, usually provided by the vendor.
identifying_guid	A globally unique identifier for the application, parsed from the identifying number if available.
caption	A short title or name for the application, often used in user interfaces.
install_source	The source location from which the application was installed, such as a network share or local media.
install_state	The current installation state of the application (e.g., installed, broken, or incomplete).
language	The language code of the application, indicating the language in which the application was installed.
local_package	The path to the local installation package, if available.
package_code	A unique identifier for the installation package used for the application.
sku_number	The stock-keeping unit (SKU) number, which identifies the product version.

System specifications metrics are essential for identifying the hardware characteristics of the system under test. These metrics offer insights into the system's processing power, storage capacity, and overall hardware configuration.

Metric	Description
address_width	The width of the address bus, typically measured in bits, indicating the amount of memory the CPU can address
batch_id	Identifier for the production batch of the CPU.
data_width	The width of the data bus, typically measured in bits, indicating the amount of data the CPU can process at once.
description	General description of the CPU.
logical_core_count	The number of logical cores in the CPU, including both physical cores and virtual (hyper-threaded) cores.
manufacturer	The manufacturer of the CPU.
maximum_clock_speed	The maximum clock speed of the CPU, typically measured in GHz.
name	The name or model of the CPU.
number_of_cores	The total number of physical cores in the CPU.

Metric	Description
device_id	Unique identifier for the storage device.
model	Model number of the storage device.
partitions	Number of partitions on the storage device.
size_in_gb	Total size of the storage device in gigabytes.
size_in_mb	Total size of the storage device in megabytes.
size_in_tb	Total size of the storage device in terabytes.
status	Current status of the storage device (e.g., online, offline).

Process performance metrics are essential for evaluating the efficiency and resource utilization of running processes within a system. These metrics provide detailed insights into how a process interacts with system resources, such as memory, disk I/O, and CPU time. The following are the key metrics captured for process performance:

Metric	Description
process_id	The unique identifier of the process.
handle_count	The total number of handles the process has open. Handles are pointers to system resources like files, registry keys, or threads.
io_read_bytes_sec	The rate at which the process is reading data from disk per second, measured in bytes.
io_read_mbytes_sec	The rate at which the process is reading data from disk per second, converted to megabytes.
io_read_gbytes_sec	The rate at which the process is reading data from disk per second, converted to gigabytes.
io_write_bytes_sec	The rate at which the process is writing data to disk per second, measured in bytes.
io_write_mbytes_sec	The rate at which the process is writing data to disk per second, converted to megabytes.
io_write_gbytes_sec	The rate at which the process is writing data to disk per second, converted to gigabytes.
memory_bytes	The amount of memory currently used by the process, measured in bytes.
memory_mbytes	The amount of memory currently used by the process, converted to megabytes.
memory_gbytes	The amount of memory currently used by the process, converted to gigabytes.
memory_private_bytes	The amount of private memory used by the process that cannot be shared with other processes.
memory_private_mbytes	The amount of private memory used by the process, converted to megabytes.
memory_private_gbytes	The amount of private memory used by the process, converted to gigabytes.
page_file_bytes	The amount of space the process is using in the page file (swap space) on disk.
page_file_mbytes	The amount of space used in the page file, converted to megabytes.
page_file_gbytes	The amount of space used in the page file, converted to gigabytes.
privileged_time_perc	The percentage of time the process spends executing in privileged mode (kernel mode). This metric helps in understanding the CPU time consumed by system-level operations.
processor_time_perc	The overall percentage of CPU time utilized by the process.
thread_count	The total number of threads within the process. Threads are the smallest unit of processing and help in multitasking within a single process.
user_time_perc	The percentage of time the process spends executing in user mode. This metric reflects the CPU time consumed by application-level code.

These metrics are collected when a process establishes a connection, providing detailed information about the data being transmitted and the stability of the connection:

Metric	Description
data_bytes_in	Measures the total amount of data received in bytes.
data_mbytes_in	Measures the total amount of data received in megabytes.
data_gbytes_in	Measures the total amount of data received in gigabytes.
data_bytes_out	Measures the total amount of data sent in bytes.
data_mbytes_out	Measures the total amount of data sent in megabytes.
data_gbytes_out	Measures the total amount of data sent in gigabytes.
data_segs_in	Number of segments received.
data_segs_out	Number of segments sent.
flags	Represents various status flags related to the connection.
inbound_bandwidth	Indicates the inbound bandwidth usage.
inbound_bandwidth_peaked	Shows if the inbound bandwidth has peaked.
inbound_instability	Tracks any instability in the inbound connection.
local_ip	The local IP address used in the connection.
local_port	The local port number used in the connection.
outbound_bandwidth	Indicates the outbound bandwidth usage.
outbound_bandwidth_peaked	Shows if the outbound bandwidth has peaked.
outbound_instability	Tracks any instability in the outbound connection.
remote_ip	The remote IP address connected to.
remote_port	The remote port number connected to.
rcv_next	The next sequence number expected to be received.
segs_in	The number of segments received.
segs_out	The number of segments sent.
snd_max	The maximum sequence number sent.
snd_nxt	The next sequence number to be sent.
snd_una	The oldest unacknowledged sequence number.
soft_error_reason	Describes the reason for any soft errors.
soft_errors	The count of soft errors encountered.
tcp_conn_state	The state of the TCP connection (e.g., ESTABLISHED, CLOSED).
thru_bytes_acked	Total bytes acknowledged by the receiver.
thru_mbytes_acked	Total megabytes acknowledged by the receiver.
thru_gbytes_acked	Total gigabytes acknowledged by the receiver.
thru_bytes_received	Total bytes received by the process.
thru_mbytes_received	Total megabytes received by the process.
thru_gbytes_received	Total gigabytes received by the process.

Metric	Description
batch_id	A unique identifier (GUID) for the batch of metrics collected, linking updates to the same collection cycle.
hotfix_id	The unique identifier for the installed update or hotfix.
description	A brief description of the update, typically provided by the vendor.
installed_on	The date when the update was installed on the system.
caption	A short title or description for the update, often used in user interfaces.
cs_name	The name of the computer system where the update is installed.
fix_comments	Additional comments or notes regarding the update, often related to the fixes it includes.
installed_by	The user account that installed the update.
service_pack_in_effect	Indicates if a service pack is in effect as part of the update.
status	The current status of the update (e.g., installed, pending reboot).
qfe	Indicates whether the update is a Quick Fix Engineering (QFE) patch.
severity	The severity rating of the update, indicating its importance or criticality.
reboot_req	Indicates whether a reboot is required for the update to take effect.

These metrics are collected when a process connection ends, providing key details about the connection at the time of termination:

Metric	Description
local_ip	The local IP address used in the connection.
local_port	The local port number used in the connection.
remote_ip	The remote IP address connected to.
remote_port	The remote port number connected to.

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Deploy & Configure

Integrate with Existing Tools

o Seamlessly integrate LoadGen Insight with your existing monitoring and management tools for a comprehensive view of your IT performance.

Customize Dashboards & Alerts

o Experience the full capabilities of LoadGen Insight with a 21-day free trial, no credit card required.

o Quickly deploy LoadGen Insight within your IT environment and configure it to start monitoring and analyzing performance data.

o Set up custom dashboards and alerts to monitor the most critical aspects of your systems.