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Documentation
This Help Center provides documentation on all aspects of the HCL Commerce+ product, from installation and deployment to operating and customization.
Performance
Topics in the Performance section describe the means by which to plan, implement, test, and re-visit the optimization of Commerce+ site performance.
Elasticsearch performance tuning
You have numerous options when tuning the performance of NiFi and Elasticsearch. The following guide introduces tools for monitoring performance and validating key tuning parameters, and provides a performance tuning strategy that you can use with the component.
Elastic monitoring and tuning
The Elastic cluster is a key component of the search solution for Commerce+. A number of monitoring tools are provided with key metrics that you should continuously monitor. The following topics describe these tools and demonstrate how to troubleshoot potential issues. While every possible situation is not covered, the most frequent events and problems are noted and resolutions provided.
Monitoring Elastic cluster
The Elastic monitoring dashboard page displays numerous metric displays, ranging from KPI, Shards and JVM Garbage Collection, to CPU and Memory, Disk and Network information. In-depth knowledge of Elastic operations is required for a complete understanding of some metrics, but the crucial indicators for monitoring and troubleshooting Elastic are broad enough that they are easy to use.

Documentation
This Help Center provides documentation on all aspects of the HCL Commerce+ product, from installation and deployment to operating and customization.
- Overview
  Welcome to the HCL Commerce+ overview. Explore these feature overviews to learn how Commerce+ operates. Refer to the related links listed at the end of each topic to access expanded product documentation.
- Deploying
  This section provides details on deploying HCL Commerce+. It explains how to download the Docker images and Git bundles that comprise the product, how to create a minimal environment, and how to plan for a full deployment. It details supported software versions, patches, and configurations to ensure the platform performs well.
- Migrating
  The following topics show how to migrate an existing HCL Commerce Version 9.1 environment to Commerce+. The process consists of an initial migration of your database contents. This is followed by a code migration. Both are fully described.
- Operating
  The topics in this section focus on tasks that are performed by business users, marketers, and customer support representatives to connect with partners and attract and satisfy customers.
- Administering
  The site administrator performs the tasks needed to support day to day operations of the Commerce+ site.
- Extending
  Using Commerce+'s xC programming model, you can use HCL-provided extension points to extend existing Commerce logic. You can implement these extensions with the xC Customization toolkit provided by HCL. Commerce+ also provides Packaged Business Capability integrations that extend the product's reach and functionality.
- Securing
  These topics describe the security features of Commerce+ and how to configure these features.
- Performance
  Topics in the Performance section describe the means by which to plan, implement, test, and re-visit the optimization of Commerce+ site performance.
  - Methodology
    Like site security, a proper approach to site performance requires planning, execution, testing, monitoring, and maintenance. The following collections of topics describe each phase of this process, and contain the recommended considerations, and best practices for getting the most out of your Commerce+ deployment.
  - OpenTelemetry
    OpenTelemetry is an open source framework for gathering performance traces, metrics and logs from your HCL Commerce+ system.
  - HCL Cache
    The HCL Cache integrates with DynaCache and improves performance and scalability with features such as remote caching, real-time monitoring, and auto-tuning capabilities.
  - Experiments considerations
    When experiments that you have created in WebSphere Commerce Accelerator are running in the store, the Scheduler launches a job that determines whether any of the current experiments have expired. The job compares the expiration date specified in the experiment to the current system date. When an experiment is identified as expired, its status is updated in the database, and the experiment is prevented from displaying to customers.
  - Website performance tuning
    There are four steps for evaluating performance of an Commerce+ website that is based on Transaction server.
  - Tuning the price rule object cache
    You can improve performance by changing the size of the cache used to store price rule business objects during storefront runtime.
  - Data Load utility performance tuning
    Scheduled Data Load utility jobs can affect Commerce+ performance. You can reduce the impact of this process by tuning the data load performance appropriately for your implementation.
  - Workspaces performance tuning
    Workspaces use database views instead of tables to retrieve data. Retrieval of underlying data might be more time-consuming because of the complexity of SQL statements that are used in workspace view definitions.
  - Thread Monitor - Yaml configuration file
    The Thead Monitor tool gathers thread dumps and Javacores at a configured interval, and during events such as high WebContainer/Default_Executor pool thread usage. Yaml configuration file must exist with name /SETUP/support/thread_monitor.yaml, or under the location specified with the THREAD_MONITOR_CFG environment variable.
  - Elasticsearch performance tuning
    You have numerous options when tuning the performance of NiFi and Elasticsearch. The following guide introduces tools for monitoring performance and validating key tuning parameters, and provides a performance tuning strategy that you can use with the component.
    - Elastic monitoring and tuning
      The Elastic cluster is a key component of the search solution for Commerce+. A number of monitoring tools are provided with key metrics that you should continuously monitor. The following topics describe these tools and demonstrate how to troubleshoot potential issues. While every possible situation is not covered, the most frequent events and problems are noted and resolutions provided.
      - Monitoring Elastic cluster
        The Elastic monitoring dashboard page displays numerous metric displays, ranging from KPI, Shards and JVM Garbage Collection, to CPU and Memory, Disk and Network information. In-depth knowledge of Elastic operations is required for a complete understanding of some metrics, but the crucial indicators for monitoring and troubleshooting Elastic are broad enough that they are easy to use.
      - Key monitoring metrics
        The query time dashboard and CPU utilization dashboard are the two primary monitoring metrics that will enable you to monitor the Elastic (ES) cluster and identify changes over time dynamically.
      - Active threads dashboards
        Thread pool dashboards display real-time information about worker threads and their operations on the cluster, with metrics including the number of tasks waiting to be executed and the number of active threads. Understanding the role of each thread pool, such as the Generic, Search, Bulk, Index, GET, Write, and Analysis pools, is crucial for troubleshooting problems and optimizing performance in Elastic (ES). Additionally, the field data and query caches help speed up search operations but may need to be cleared periodically, causing temporary slowdowns.
      - Total Operations dashboard
        The total operations dashboard displays a breakdown of the total number of index, search, get, and delete operations carried out on your Elastic cluster.
      - Multiple or concurrent Elastic operations
        Multiple or concurrent Elastic operations can reduce performance. Finding the cause should be done with attention and planning.
      - Tuning knobs in Elasticsearch
        Elastic has several configuration points that may be changed for optimal performance and the allocation of resources. The following are some critical tuning knobs to think about.
    - Understanding the Grafana graphs
      You can use Grafana to analyze the performance of the ingest pipeline.
    - Optimizing index build and overall flow
      Optmizations are provided full index builds and for tuning parameters. Potential improvements that can be implimented for Near Real Time (NRT) index updates are not described.
    - Tunable setup parameters
      How you can modify the values for the tunable parameters, and some default values and how they can be improved in different circumstances.
    - Scaling and hardware requirements
      You can achieve additional capacity by implementing or extending pod clustering on Elasticsearch, NiFi, or both. You can also consider the hardware footprint and key resources that impact the processing and index creation speed.
  - Tuning ingest performance in Elastic part II
  - Recommended Parameters for NIFI and Elastic
    You can run your Elastic and NiFi environments using the default settings, which provides a minimal resource set. For best performance, tune your configuration or use the recommended parameters for CPU, memory and system resources.
  - Measurement
    As each deployment of Commerce+ is different, a measured approach to modifying your defaults must be taken to successfully tune your site. The following collection of topics provides details on how to measure and troubleshoot site performance.
  - Emerald REST Caching On TS Server for Commerce 9.1
    Emerald Store is powered by the REST framework, and the cache is implemented using a REST servlet.
- Troubleshooting
  Topics in the Troubleshooting section highlight common issues that are encountered with Commerce+, and how they can be addressed or mitigated.
- Reference
  Topics in the Reference section contain all of the Commerce+ reference documentation.

Monitoring Elastic cluster

The Elastic monitoring dashboard page displays numerous metric displays, ranging from KPI, Shards and JVM Garbage Collection, to CPU and Memory, Disk and Network information. In-depth knowledge of Elastic operations is required for a complete understanding of some metrics, but the crucial indicators for monitoring and troubleshooting Elastic are broad enough that they are easy to use.

The Elastic monitoring dashboard shows a variety of metric displays.

KPI: Displays several metrics by single number value.
Shards: Displays high level shard information.
JVM Garbage Collection: Garbage collection is the automated process of cleaning up objects used by code in memory.
Breakers: circuit breakers dashboards that displays tripped circuit breakers, their frequency and value of the metrics that tripped them.
CPU and Memory
Disk and Network
Documents: Displays dashboards that show the documents and the operations done on them.
Total Operations Statistics
Times: Dashboards that show service times to the following operations: Query, Indexing, Merging and Throttle time.
Thread Pool: Critical dashboard that shows activity of the worker threads.
Caches: Dashboard presenting the Elastic caches.
Segments
Indices: Count of documents and total Size.
Indices: Doc values.
Indices: Refreshes.
Indices: Fields.

For a complete understanding of some metrics, in-depth knowledge of Elastic operations is required. You should concentrate on the crucial indicators that are essential for monitoring and troubleshooting Elastic until you develop expertise in using Elastic with Commerce+..