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Informatica IICS Training | Best Informatica Cloud IDMC

Monitor Jobs and Troubleshoot Errors in Informatica Cloud

Introduction

Monitoring jobs and troubleshooting errors is a critical aspect of ensuring seamless operations in Informatica Intelligent Cloud Services (IICS). Whether you’re working with Cloud Data Integration (CDI) or Cloud Application Integration (CAI), understanding how to detect, analyse, and resolve job failures or performance bottlenecks is essential for maintaining data accuracy, performance, and reliability.

This article covers the key features and best practices used to monitor jobs and troubleshoot errors in Informatica Cloud, helping administrators and developers gain better control over their integration environment.

Job Monitoring in Informatica Cloud

Informatica Cloud provides a centralized interface called the Activity Monitor to track the status of all jobs and tasks. Here’s how it works: IICS Online Training

1. Activity Monitor Dashboard

The Activity Monitor is the primary tool for tracking job execution status. It provides details such as:

Task name

Status (Success, Failed, In Progress)

Start and End time

Duration

Error messages or warnings

This dashboard allows you to filter by date, task type, and status, making it easier to pinpoint specific executions.

2. Task Logs

Every job run in IICS generates a detailed log file. These logs provide insight into: Informatica Cloud Training

Execution steps

Transformation details

Source and target counts

Data preview

Error codes and failure messages

To access logs:  

Navigate to My Jobs or Activity Monitor

Click on the log icon for the specific task

Review or download the log for detailed analysis

3. Email Notifications

Informatica allows you to configure email notifications for job success or failure. These alerts help teams stay proactive by receiving real-time updates on job statuses. Informatica IICS Training

Troubleshooting Errors in Informatica Cloud

When a task fails, identifying the root cause quickly is key to minimizing downtime. Here's how you can troubleshoot effectively:

1. Check Error Codes

Informatica Cloud generates error codes and descriptive messages when a task fails. These messages often indicate:

Connection issues (e.g., invalid credentials)

Transformation logic failures

Source/target schema mismatches

Permissions errors

Use the Informatica Knowledge Base or support documentation to search error codes for solutions.

2. Secure Agent Logs

For more advanced troubleshooting, review the Secure Agent logs on the host machine. These logs provide deeper insights into:

Agent performance

Connectivity issues

Internal errors

The logs are located in the logs directory under the Informatica Cloud Secure Agent installation path.

3. Validate Connections and Mappings

Revalidate source and target connections to ensure credentials or endpoints haven’t changed.

Open the mapping or task and perform a validation to identify compile-time issues.

Use the Data Preview option (for CDI) to test if expected results are being generated. Informatica Cloud IDMC Training

4. Retry Failed Jobs

In many cases, retrying a failed job after addressing a connectivity or configuration issue can lead to success. You can do this directly from the Activity Monitor.

Best Practices

Schedule regular audits of failed jobs and monitor trends.

Implement parameterization to reduce human error in configurations.

Use reusable mappings and templates to ensure consistency across tasks.

Document known issues and resolutions as part of your operational runbook.

Conclusion

Being able to effectively monitor jobs and troubleshoot errors in Informatica Cloud is essential for maintaining a healthy and efficient data integration ecosystem. Tools like the Activity Monitor, task logs, and Secure Agent logs, combined with a systematic approach to troubleshooting, empower users to quickly detect and resolve issues.

By following these best practices, you can ensure data integrity, improve job success rates, and optimize performance across your Informatica Cloud environment.

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Informatica Training in India | Informatica Cloud IDMC

Different logging mechanisms in Informatica IICS

Introduction

Informatica Intelligent Cloud Services (IICS) offers a robust platform for cloud data and application integration. Whether working with Cloud Data Integration (CDI) or Cloud Application Integration (CAI), effective logging and monitoring are essential for ensuring smooth data workflows, process orchestration, and real-time integrations. Logging not only helps in troubleshooting but also supports auditing, compliance, and performance analysis.

This article explores the different logging mechanisms in Informatica IICS, shedding light on how logs are generated, accessed, and used for efficient data operations.

1. Activity Log

The Activity Log in IICS provides a summary of all activities performed in the organization, including job executions, user logins, task deployments, and other administrative events. This log is crucial for tracking overall platform usage. IICS Online Training

Key Features:

Tracks user-level actions

Shows job start, end, and status information

Allows filtering by asset type, user, or date

Useful for audit and security monitoring

2. Secure Agent Logs

The Secure Agent plays a key role in executing tasks. It generates logs that are saved locally on the machine where the agent is installed.

Key Log Types:

Service Manager Log: Captures the status of services, startup, shutdown, and heartbeats.

Tomcat Log: Captures web service call logs, especially useful in CAI.

Data Integration Service Log: Tracks execution of mappings and workflows.

Process Server Log: Critical for CAI processes and real-time task logs.

These logs provide in-depth details, especially when troubleshooting complex job failures or agent-level issues.

3. Job Logs

Each job execution in IICS generates a Job Log (also known as Session Log), accessible from the Monitor or My Jobs tab. Informatica Cloud Training

Includes:

Start and end times

Row-level data processing statistics

Transformation logic and expression evaluations

Errors and warning messages

Performance metrics like throughput and latency

These logs are the primary source for developers and admins to debug mapping issues and performance bottlenecks.

4. Application Integration Logs

For CAI, logs are more process-oriented. You can access: Informatica IICS Training

Process Execution Logs from the Process Console

Service Connector Logs for API-level integration

Message Logs when using messaging and queues

These logs show the real-time flow of data and are crucial for diagnosing failures in service orchestration, REST/SOAP API calls, and integration endpoints.

5. Error Logs and Debugging Tools

IICS provides advanced debugging and error handling tools:

Log Level Settings: You can configure the level of detail captured (Normal, Verbose, Debug).

Debug Mode in CAI: Allows step-by-step process execution with intermediate variable tracking.

Error Handling in Mappings: Use Error logs and rejection data sets to manage failed records separately. Informatica Cloud IDMC Training

6. Audit Logs

Audit logs are specifically meant for compliance and governance purposes. They capture who accessed or modified what and when, including asset creation, updates, and deletions.

Useful For:

Regulatory compliance

Change management

User activity tracking

Conclusion

Effective logging is the backbone of any enterprise-level data integration strategy. Informatica IICS offers multiple logging mechanisms — from Secure Agent logs and job-level logs to audit and real-time process logs — enabling users to ensure operational visibility, debug efficiently, and meet compliance requirements. Mastering these logging features is essential for any data engineer, developer, or administrator working with Informatica Cloud.

Whether you're handling batch ETL jobs or orchestrating APIs in real-time, understanding logging mechanisms in Informatica IICS will significantly improve your ability to deliver robust and reliable data solutions.

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What is the Role of Taskflows in CDI?

Informatica Cloud Data Integration (CDI) is a powerful platform that enables organizations to design, schedule, and execute data integration tasks in the cloud. One of the key features that makes CDI robust and flexible is the concept of Taskflows. Taskflows play a vital role in automating, orchestrating, and managing the flow of tasks in a logical and structured manner.

In this article, we’ll explore what Taskflows are, their core components, and how they are used in Informatica Cloud Data Integration to streamline and control complex data workflows.

Understanding Taskflows

Taskflows in Informatica Cloud act as workflows that allow you to link multiple tasks—such as mappings, mapping tasks, data synchronization tasks, and other taskflows—into a single, manageable process. This helps in organizing complex data pipelines, applying logic, handling errors, and scheduling operations efficiently. Informatica IDMC Training

Think of a taskflow as an orchestration layer that coordinates the execution of several integration tasks based on a specific sequence, logic, or condition.

Key Features of Taskflows

Sequential and Parallel Execution Taskflows allow you to execute tasks in a step-by-step sequence or in parallel. This helps in building optimized data pipelines depending on the nature of your workload.

Conditional Logic (IF/ELSE, SWITCH) With built-in decision-making logic, Taskflows can route the process based on conditions, such as the success or failure of previous tasks, parameter values, or runtime variables. Informatica IICS Training

Error Handling and Notifications Taskflows enable you to define error handling steps to manage failures gracefully. You can set up actions like sending alerts, stopping execution, or redirecting the flow when an error occurs.

Looping and Iteration You can use looping constructs like Repeat or For Each to repeat actions based on a list of values or until a condition is met, which is extremely useful for processing batch data or repetitive tasks.

Parameterization Taskflows support input parameters, which allows dynamic execution of tasks using different configurations. This makes your workflows reusable and more adaptable.

Scheduling and Monitoring Taskflows can be scheduled to run at specific times or intervals. You can also monitor their execution status, track errors, and review logs via the Informatica Cloud Monitor or Activity Log.

Real-Time Use Cases of Taskflows

Here are some common use cases where Taskflows add significant value:

ETL Orchestration: Execute multiple ETL jobs sequentially with conditions and dependency checks. Informatica Cloud Training

Data Validation: Run data quality checks before or after data loading tasks.

Data Distribution: Distribute data across multiple targets using conditional branching.

Incremental Load Control: Automate data load control using parameters and condition-based looping.

Error-Driven Workflows: Re-run or skip failed jobs based on exception handling steps.

Benefits of Using Taskflows in CDI

Automation: Reduces manual intervention by automating the execution and decision-making of multiple tasks.

Efficiency: Ensures data flows are optimized and handled logically, reducing runtime and resource usage. IICS Online Training

Scalability: Supports both simple and complex data processes, making it ideal for enterprise-level workflows.

Error Management: Enhances system stability by managing failures and exceptions with clear rules and alerts.

Reusability: Parameterized taskflows can be reused across projects, saving development time.

Conclusion

Taskflows in Informatica Cloud Data Integration serve as the backbone for building intelligent, scalable, and automated data pipelines. They provide the control and flexibility needed to manage diverse data integration tasks efficiently, with the ability to handle logic, errors, and schedules in one unified process. Whether you are managing small data sync jobs or orchestrating enterprise-level ETL flows, Taskflows are an essential component of your Informatica IICS toolkit.

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Informatica Cloud Support for API-Based Integrations

Informatica Cloud, a leading Integration Platform as a Service (iPaaS), provides robust capabilities for API-driven data integration, enabling businesses to automate processes, connect disparate systems, and streamline workflows efficiently. This article explores how Informatica Cloud supports API-based integrations and the key features that make it an ideal choice for modern enterprise architectures. In today’s digital-first landscape, organizations rely heavily on API-based integrations to ensure seamless data connectivity between applications, platforms, and services.

What is Informatica Cloud?

Informatica Cloud is a scalable, cloud-native integration platform that allows organizations to connect data sources across on-premise and cloud environments. It enables real-time data synchronization, ETL (Extract, Transform, Load) processes, data quality management, and API-based integration. The platform’s versatility makes it suitable for use cases ranging from customer data integration to business process automation. Informatica IICS Training

Understanding API-Based Integration

API (Application Programming Interface) integration involves connecting different systems or applications via APIs to facilitate the exchange of data and services. It allows applications to "talk" to each other without human intervention, enabling faster, more reliable data flow. With businesses increasingly adopting SaaS, mobile apps, and microservices, API integrations have become a cornerstone of digital transformation strategies.

How Informatica Cloud Enables API Integration

1. Informatica Cloud Application Integration

The Informatica Cloud Application Integration service allows users to design and deploy integration processes that can be triggered through APIs. This means you can create APIs to invoke real-time data workflows, making it easier to connect applications like Salesforce, NetSuite, Workday, and more.

Real-time APIs: Create REST or SOAP APIs that trigger workflows on-demand.

Event-driven Architecture: Supports asynchronous communication using events and queues.

Business Process Automation: Integrate with external systems to orchestrate complex business workflows through APIs.

2. API and Microservices Management

Informatica Cloud provides a low-code environment to develop, manage, and deploy APIs as microservices. These APIs can then be consumed by external applications or internal teams, allowing for reusable and scalable integration patterns. IICS Online Training

REST and SOAP support: Build APIs in both common formats.

Security & Governance: Apply OAuth, SAML, and other security protocols to protect your integrations.

API Lifecycle Management: Monitor, version, and control access to APIs easily.

3. Service Connectors and Adapters

Informatica Cloud comes equipped with prebuilt connectors and adapters for popular applications and services. These simplify the process of integrating APIs by abstracting the underlying complexity.  

Out-of-the-box connectors for Salesforce, AWS, Microsoft Azure, SAP, and others.

Custom connectors can be created for niche or proprietary APIs.

Parameterization & Reusability: Promote reusability across projects with standardized templates and configurations. Informatica Cloud IDMC Training

Benefits of API-Based Integration in Informatica Cloud

Faster Time to Market: Quickly build integrations without writing extensive code.

Improved Data Accuracy: Real-time synchronization minimizes data discrepancies.

Enhanced Scalability: Easily manage integrations across hybrid and multi-cloud environments.

Reduced Costs: Automate manual tasks and reduce development overhead.

Real-World Use Cases

Customer 360: Integrate CRM, ERP, and support systems to create a unified customer view. Informatica Cloud Training

E-commerce Automation: Connect inventory, shipping, and order management platforms through real-time APIs.

IoT Data Flow: Use APIs to collect and process data from connected devices in real time.

Final Thoughts

Informatica Cloud API Integration empowers businesses to connect and orchestrate data across various platforms efficiently. Whether you’re modernizing legacy systems, enabling mobile apps, or building a scalable cloud infrastructure, Informatica’s robust API capabilities provide the tools needed for fast, secure, and future-ready integration. As businesses continue to evolve digitally, leveraging API-based integrations through Informatica Cloud can be a game-changer in staying competitive and data-driven.

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How to Integrate CDI with Snowflake, AWS, or Azure

Cloud Data Integration (CDI) tools, such as Informatica CDI, provide the agility to move, transform, and synchronize data between cloud services and on-premise systems. In this article, we’ll explore how to integrate CDI with Snowflake, AWS, or Azure, enabling scalable and efficient data pipelines for analytics and business intelligence. In today’s cloud-first data landscape, the ability to seamlessly connect and manage data across various platforms is critical.

What is Cloud Data Integration (CDI)?

CDI is a cloud-native service designed for real-time and batch data integration. It enables organizations to build, deploy, and manage data pipelines that move data from multiple sources to target systems like Snowflake, Amazon Web Services (AWS), or Microsoft Azure. It supports transformations, data quality, and orchestration – all from a unified platform. Informatica Cloud IDMC Training

Why Integrate CDI with Cloud Platforms?

Integrating CDI with platforms like Snowflake, AWS, or Azure allows businesses to:

Perform seamless ETL/ELT operations in the cloud.

Enable real-time analytics with scalable cloud storage.

Simplify data movement between SaaS, on-premise, and cloud systems.

Reduce costs and complexity with automated workflows and prebuilt connectors.

Integrating CDI with Snowflake

Snowflake is a leading cloud data warehouse known for its performance, scalability, and separation of storage/compute. CDI supports native connectivity to Snowflake through the following steps: IICS Online Training

Set Up the Connection:

In Informatica Cloud, create a new connection using the Snowflake connector.

Provide necessary credentials such as Account Name, Warehouse, Database, Schema, and Authentication details.

Build Data Integration Tasks:

Use Mapping Designer to define source, transformation logic, and Snowflake as the target.

Apply transformations such as joins, filters, or expressions as needed.

Data Load Optimization:

Leverage bulk load APIs or Snowpipe for high-volume data ingestion.

Choose the appropriate write mode: insert, update, or merge.

Schedule and Monitor: Informatica Cloud Training

Use CDI’s scheduler or integrate with job orchestration tools to automate workflows.

Monitor jobs in real-time via Informatica’s monitoring dashboard.

Integrating CDI with AWS

CDI supports multiple AWS services like Amazon S3, Redshift, RDS, and Glue. Here’s how integration works:

Create AWS Connections:

In CDI, configure connectors for S3, Redshift, or RDS by providing access keys, secret keys, and region info.

Leverage Amazon S3 as a Landing Zone:

Use S3 to stage data before further processing.

Set up preprocessing or cleansing tasks in CDI before writing to Redshift or RDS.

Secure Integration:

Utilize IAM roles, VPC peering, and KMS encryption for secure data transfer.

Data Transformation and Load:

Design mapping tasks in CDI to apply business logic and load data into AWS targets efficiently.

Integrating CDI with Azure

CDI offers built-in support for Azure Data Lake, Azure SQL Database, Synapse Analytics, and more. Informatica IICS Training

Configure Azure Connections:

Provide account credentials, client secrets, and tenant IDs when connecting to Azure services.

Use Azure Data Lake for Storage:

Store raw data in ADLS Gen2, then process and transfer it using CDI workflows.

Write to Azure Synapse or SQL Database:

Build mappings with Synapse as the target to support big data analytics and reporting.

Automation with Azure Data Factory (Optional):

Integrate CDI workflows into ADF pipelines for hybrid orchestration and management.

Final Thoughts

The integration of CDI with Snowflake, AWS, or Azure simplifies and accelerates modern data architecture initiatives. Whether you’re building a cloud data warehouse, implementing real-time analytics, or modernizing legacy ETL systems, CDI provides the tools and connectors needed for scalable, efficient, and secure data integration. As cloud technologies evolve, leveraging CDI’s capabilities will empower organizations to stay agile, data-driven, and competitive.

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How to Optimize Performance in Informatica (CDI)

Informatica Cloud Data Integration (CDI) is a powerful ETL and ELT tool used for cloud-based data integration and transformation. Optimizing performance in Informatica CDI is crucial for handling large datasets efficiently, reducing execution time, and ensuring seamless data processing. Below are the key strategies for optimizing performance in Informatica CDI.

1. Use Pushdown Optimization (PDO)

Pushdown Optimization (PDO) enhances performance by offloading transformation logic to the target or source database, reducing the amount of data movement. There are three types of pushdown optimization:

Source Pushdown: Processes data at the source level before extracting it.

Target Pushdown: Pushes the transformation logic to the target database.

Full Pushdown: Pushes all transformations to either the source or target system.

To enable PDO, configure it in the Mapping Task under the "Advanced Session Properties" section. IICS Online Training

2. Use Bulk Load for High-Volume Data

When working with large datasets, using bulk load instead of row-by-row processing can significantly improve performance. Many cloud-based data warehouses, such as Snowflake, Amazon Redshift, and Google BigQuery, support bulk loading.

Enable Bulk API in target settings.

Use batch mode for processing instead of transactional mode.

3. Optimize Data Mapping and Transformations

Well-designed mappings contribute to better performance. Some best practices include: Informatica Cloud Training

Minimize the use of complex transformations like Joiner, Lookup, and Aggregator.

Filter data as early as possible in the mapping to reduce unnecessary data processing.

Use sorted input for aggregations to enhance Aggregator transformation performance.

Avoid unnecessary type conversions between string, integer, and date formats.

4. Optimize Lookup Performance

Lookup transformations can slow down processing if not optimized. To improve performance:

Use cached lookups instead of uncached ones for frequently used data.

Minimize lookup data by using a pre-filter in the source query.

Index the lookup columns in the source database for faster retrieval.

Use Persistent Cache for static lookup data. Informatica IICS Training

5. Enable Parallel Processing

Informatica CDI allows parallel execution of tasks to process data faster.

Configure Concurrent Execution in the Mapping Task Properties to allow multiple instances to run simultaneously.

Use Partitioning to divide large datasets into smaller chunks and process them in parallel.

Adjust thread pool settings to optimize resource allocation.

6. Optimize Session and Task Properties

In the session properties of a mapping task, make the following changes:

Enable high-throughput mode for better performance.

Adjust buffer size and cache settings based on available system memory.

Configure error handling to skip error records instead of stopping execution.

7. Use Incremental Data Loads Instead of Full Loads

Performing a full data load every time increases processing time. Instead:

Implement Change Data Capture (CDC) to load only changed records.

Use Last Modified Date filters to process only new or updated data.

8. Reduce Network Latency

When working with cloud environments, network latency can impact performance. To reduce it: Informatica Cloud IDMC Training

Deploy Secure Agents close to the data sources and targets.

Use direct database connections instead of web services where possible.

Compress data before transfer to reduce bandwidth usage.

9. Monitor and Tune Performance Regularly

Use Informatica Cloud’s built-in monitoring tools to analyze performance:

Monitor Task Logs: Identify bottlenecks and optimize accordingly.

Use Performance Metrics: Review execution time and resource usage.

Schedule Jobs During Off-Peak Hours: To avoid high server loads.

Conclusion

Optimizing performance in Informatica Cloud Data Integration (CDI) requires a combination of efficient transformation design, pushdown optimization, bulk loading, and parallel processing. By following these best practices, organizations can significantly improve the speed and efficiency of their data integration workflows, ensuring faster and more reliable data processing in the cloud.

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What is a Dynamic Mapping Task, and How Does It Work?

Introduction

Informatica Cloud Training provides powerful tools to automate and streamline data workflows. One such feature is the Dynamic Mapping Task, a vital component in Informatica Intelligent Cloud Services (IICS). This article will delve into what a Dynamic Mapping Task is, how it works, and why it's crucial for modern data integration. In today's fast-paced, data-driven world, businesses require agile and scalable solutions for seamless data integration.

What is a Dynamic Mapping Task?

A Dynamic Mapping Task is a type of task in Informatica Cloud that allows users to create mappings with flexible logic. Unlike traditional mappings, which require predefined transformations and data sources, dynamic mappings provide adaptability by enabling parameterization. This means that instead of hardcoding sources, targets, and transformation logic, users can define parameters that change based on runtime conditions.

Key Features of Dynamic Mapping Task

Parameterization: Enables flexible and reusable mappings by defining sources, targets, and transformation logic dynamically.

Scalability: Helps manage large-scale data integrations without redesigning mappings.

Automation: Reduces manual effort by allowing dynamic data flow adjustments.

Reusability: One mapping can be reused across different data integration scenarios.

How Does a Dynamic Mapping Task Work?

Step 1: Defining the Dynamic Mapping

To create a Dynamic Mapping Task, users start by designing a mapping in IICS Online Training. Here, placeholders or parameters are set instead of static values for sources, targets, and transformations.

Step 2: Configuring Parameters

Users define the following types of parameters:

Source Parameters: Dynamic selection of source objects based on conditions.

Target Parameters: Destination tables or databases defined at runtime.

Transformation Parameters: Functions, expressions, or filters that change dynamically.

Step 3: Deploying the Mapping Task

After configuring the dynamic mapping, the task is deployed and executed. During execution, it retrieves parameter values and adapts the data flow accordingly.

Step 4: Running and Monitoring

Once deployed, the task can be scheduled or triggered manually. IICS Training in Hyderabad emphasizes monitoring tools that allow users to track task performance and logs for troubleshooting.

Benefits of Using Dynamic Mapping Tasks

1. Improved Flexibility

With dynamic mappings, organizations can integrate various data sources without creating multiple mappings. This adaptability is crucial for enterprises dealing with frequently changing data structures.

2. Enhanced Productivity

By eliminating the need for repetitive mapping creation, teams can focus on optimizing data processes rather than performing redundant tasks.

3. Cost Efficiency

Dynamic mappings reduce development time and operational costs by providing a reusable framework, leading to better resource utilization.

4. Seamless Integration with Cloud Platforms

Dynamic Mapping Tasks support various cloud platforms, making them an essential component of Informatica Cloud Training for businesses leveraging cloud-based data solutions.

Use Cases of Dynamic Mapping Tasks

Data Warehousing

Companies use dynamic mappings to load data from multiple sources into a centralized data warehouse without modifying the mapping logic.

Real-Time Data Processing

For real-time data updates, dynamic mappings adjust parameters on the fly, ensuring accurate and up-to-date information across systems.

Cross-Platform Data Migration

Organizations migrating data across different cloud environments benefit from dynamic mappings as they allow adaptable transformation logic based on the target system.

Conclusion

The Dynamic Mapping Task in IICS Online Training is a powerful feature that streamlines data integration by allowing flexibility and reusability. It enables businesses to adapt to changing data structures while reducing development efforts. Whether you're working on Informatica Cloud Training for data migration, warehousing, or automation, mastering dynamic mapping tasks is essential for optimizing your data workflows.

If you're looking to upskill in cloud-based data integration, consider enrolling in IICS Training in Hyderabad to gain hands-on experience with Dynamic Mapping Tasks and other advanced Informatica Cloud functionalities.

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