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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you monitor disk and CPU usage in a Bigtable instance, update an existing cluster to apply node autoscaling, implement replication in an instance, and back up and restore data in Bigtable.
Register for this course and see more details by visiting:
OpenCourser.com/course/tsvkgh/monitoring
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches Bigtable administration in a hands-on manner
Suitable for those wanting to manage a Bigtable instance
Covers core Bigtable administration tasks
Taught by Google Cloud engineers
Taught through Google Cloud console
Requires familiarity with Google Cloud console
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Save Monitoring and Managing Bigtable Health and Performance to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Monitoring and Managing Bigtable Health and Performance with these
activities:
Review relational database models
Show steps
Review relational database models prior to taking the course to ensure foundational knowledge is up-to-date.
Browse courses on
Relational Databases
Show steps
-
Review key concepts like tables, rows, columns, and primary keys
-
Describe different types of relationships between tables
-
Explain the concept of normalization
Follow tutorials on Bigtable architecture
Show steps
Explore tutorials to gain a deeper understanding of Bigtable's architecture and underlying concepts.
Show steps
-
Find tutorials on Bigtable architecture and implementation
-
Follow the tutorials and take notes on key concepts
Practice SQL queries
Show steps
Practice writing SQL queries to reinforce understanding of data retrieval and manipulation.
Show steps
-
Write queries to select data from a table
-
Write queries to filter data using WHERE clauses
-
Write queries to join tables
Five other activities
Expand to see all activities and additional details
Show all eight activities
Monitor Instance Metrics
Show steps
Monitor the performance of your Bigtable instances by reviewing key metrics like disk usage and CPU usage.
Browse courses on
Monitoring
Show steps
-
Log in to the Google Cloud console.
-
Open the Bigtable instance.
-
Go to the "Metrics Explorer" tab.
-
Select the relevant metrics to monitor.
-
Analyze the data and identify any potential issues.
Create a data model for a sample application
Show steps
Design and create a data model for a sample application to apply knowledge of Bigtable concepts.
Show steps
-
Identify the entities and relationships in the sample application
-
Create a table schema for each entity
-
Define primary keys and column families
Implement Autoscaling
Show steps
Improve the scalability and cost-effectiveness of your Bigtable instance by implementing autoscaling, which automatically adjusts the number of nodes based on demand.
Browse courses on
Autoscaling
Show steps
-
Log in to the Google Cloud console.
-
Open the Bigtable instance.
-
Follow the official documentation to enable autoscaling.
-
Configure the autoscaling parameters according to your requirements.
-
Monitor the performance of the instance and adjust the autoscaling parameters as needed.
Replicate Data in an Instance
Show steps
Enhance data reliability and reduce the risk of data loss by implementing replication in your Bigtable instance, which creates redundant copies of data across multiple zones or regions.
Browse courses on
Data Replication
Show steps
-
Log in to the Google Cloud console.
-
Open the Bigtable instance.
-
Follow the official documentation to create a cluster in a different zone or region.
-
Enable replication between the clusters.
-
Monitor the data replication status and ensure that data is consistently replicated across all clusters.
Backup and Restore Data
Show steps
Safeguard your data and ensure its recoverability in case of unexpected events or data corruption by creating backups of your Bigtable instance and learning how to restore data from these backups.
Browse courses on
Data Backup
Show steps
-
Log in to the Google Cloud console.
-
Open the Bigtable instance.
-
Follow the official documentation to create a backup of the instance.
-
Test the restore process by creating a new instance and restoring data from the backup.
-
Develop a backup and recovery plan to ensure that data is regularly backed up and can be restored quickly in case of need.
Review relational database models
Show steps
Review relational database models prior to taking the course to ensure foundational knowledge is up-to-date.
Browse courses on
Relational Databases
Show steps
Show steps
Show steps
- Review key concepts like tables, rows, columns, and primary keys
- Describe different types of relationships between tables
- Explain the concept of normalization
Follow tutorials on Bigtable architecture
Show steps
Explore tutorials to gain a deeper understanding of Bigtable's architecture and underlying concepts.
Show steps
Show steps
Show steps
- Find tutorials on Bigtable architecture and implementation
- Follow the tutorials and take notes on key concepts
Practice SQL queries
Show steps
Practice writing SQL queries to reinforce understanding of data retrieval and manipulation.
Show steps
Show steps
Show steps
- Write queries to select data from a table
- Write queries to filter data using WHERE clauses
- Write queries to join tables
Five other activities
Expand to see all activities and additional details
Show all eight activities
Monitor Instance Metrics
Show steps
Monitor the performance of your Bigtable instances by reviewing key metrics like disk usage and CPU usage.
Browse courses on
Monitoring
Show steps
Show steps
Show steps
- Log in to the Google Cloud console.
- Open the Bigtable instance.
- Go to the "Metrics Explorer" tab.
- Select the relevant metrics to monitor.
- Analyze the data and identify any potential issues.
Create a data model for a sample application
Show steps
Design and create a data model for a sample application to apply knowledge of Bigtable concepts.
Show steps
Show steps
Show steps
- Identify the entities and relationships in the sample application
- Create a table schema for each entity
- Define primary keys and column families
Implement Autoscaling
Show steps
Improve the scalability and cost-effectiveness of your Bigtable instance by implementing autoscaling, which automatically adjusts the number of nodes based on demand.
Browse courses on
Autoscaling
Show steps
Show steps
Show steps
- Log in to the Google Cloud console.
- Open the Bigtable instance.
- Follow the official documentation to enable autoscaling.
- Configure the autoscaling parameters according to your requirements.
- Monitor the performance of the instance and adjust the autoscaling parameters as needed.
Replicate Data in an Instance
Show steps
Enhance data reliability and reduce the risk of data loss by implementing replication in your Bigtable instance, which creates redundant copies of data across multiple zones or regions.
Browse courses on
Data Replication
Show steps
Show steps
Show steps
- Log in to the Google Cloud console.
- Open the Bigtable instance.
- Follow the official documentation to create a cluster in a different zone or region.
- Enable replication between the clusters.
- Monitor the data replication status and ensure that data is consistently replicated across all clusters.
Backup and Restore Data
Show steps
Safeguard your data and ensure its recoverability in case of unexpected events or data corruption by creating backups of your Bigtable instance and learning how to restore data from these backups.
Browse courses on
Data Backup
Show steps
Show steps
Show steps
- Log in to the Google Cloud console.
- Open the Bigtable instance.
- Follow the official documentation to create a backup of the instance.
- Test the restore process by creating a new instance and restoring data from the backup.
- Develop a backup and recovery plan to ensure that data is regularly backed up and can be restored quickly in case of need.
Career center
Learners who complete Monitoring and Managing Bigtable Health and Performance will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design and build systems that collect, store, and process data. They also work with Data Scientists and other stakeholders to develop and implement data-driven solutions. This course can help Data Engineers build a foundation for using Bigtable to store and process large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Data Engineers who want to use Bigtable effectively.
Data Analyst
Data Analyst
Data Analysts work with business stakeholders to understand their information needs. They then mine, transform, and model data in a way that helps stakeholders make informed decisions. This course can help Data Analysts build a foundation for using Bigtable to store and analyze large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Data Analysts who want to use Bigtable effectively.
Database Administrator
Database Administrator
Database Administrators are responsible for the day-to-day operation and maintenance of databases. They also work with database developers to design and implement new database systems. This course can help Database Administrators build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Database Administrators who want to use Bigtable effectively.
Cloud Architect
Cloud Architect
Cloud Architects design and build cloud-based solutions. They also work with customers to migrate their applications and data to the cloud. This course can help Cloud Architects build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Cloud Architects who want to use Bigtable effectively.
DevOps Engineer
DevOps Engineer
DevOps Engineers work with developers and operations teams to build and maintain software systems. They also work to improve the efficiency and reliability of software development and deployment processes. This course can help DevOps Engineers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for DevOps Engineers who want to use Bigtable effectively.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They also work with customers to gather requirements and develop solutions. This course can help Software Engineers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Software Engineers who want to use Bigtable effectively.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. They also work with stakeholders to develop and implement data-driven solutions. This course can help Data Scientists build a foundation for using Bigtable to store and analyze large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Data Scientists who want to use Bigtable effectively.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use data to develop and deploy machine learning models. They also work with stakeholders to understand their business needs and develop solutions. This course can help Machine Learning Engineers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Machine Learning Engineers who want to use Bigtable effectively.
Systems Engineer
Systems Engineer
Systems Engineers design, build, and maintain computer systems. They also work with customers to gather requirements and develop solutions. This course can help Systems Engineers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Systems Engineers who want to use Bigtable effectively.
Database Developer
Database Developer
Database Developers design and build databases. They also work with Database Administrators to maintain and optimize databases. This course can help Database Developers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Database Developers who want to use Bigtable effectively.
Network Engineer
Network Engineer
Network Engineers design, build, and maintain computer networks. They also work with customers to gather requirements and develop solutions. This course can help Network Engineers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Network Engineers who want to use Bigtable effectively.
Cloud Security Engineer
Cloud Security Engineer
Cloud Security Engineers design, build, and maintain cloud-based security systems. They also work with customers to gather requirements and develop solutions. This course can help Cloud Security Engineers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Cloud Security Engineers who want to use Bigtable effectively.
Security Engineer
Security Engineer
Security Engineers design, build, and maintain computer security systems. They also work with customers to gather requirements and develop solutions. This course can help Security Engineers build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Security Engineers who want to use Bigtable effectively.
Data Architect
Data Architect
Data Architects design and build data management systems. They also work with stakeholders to understand their business needs and develop solutions. This course can help Data Architects build a foundation for using Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance. These topics are all essential for Data Architects who want to use Bigtable effectively.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies. They also work with stakeholders to ensure that data is used in a consistent and ethical manner. This course may be useful for Data Governance Analysts who want to learn how to use Bigtable to store and manage large amounts of data. The course covers topics such as monitoring disk and CPU usage, updating clusters to apply node autoscaling, and implementing replication in an instance.
For more career information including salaries, visit:
OpenCourser.com/course/tsvkgh/monitoring
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Monitoring and Managing Bigtable Health and Performance.
Discusses the principles behind designing data-intensive applications, including those using Bigtable. It valuable reference for those seeking to build robust and scalable data systems.
Provides a good overview of NoSQL databases, including Bigtable. It good resource for those who are new to NoSQL databases or who want to learn more about the different types of NoSQL databases available.
Provides deep insights on Apache Kafka, including its architecture and operational details. Although not directly about Bigtable, it valuable resource for understanding the broader ecosystem of distributed data systems.
Save
Provides a good overview of big data analytics, including Bigtable. It good resource for those who are new to big data analytics or who want to learn more about the different big data analytics tools and techniques available.
Provides a good overview of data science, but does not cover Bigtable. It good resource for those who are new to data science or who want to learn more about the different data science tools and techniques available.
Provides a good overview of big data analytics, but does not cover Bigtable. It good resource for those who are new to big data analytics or who want to learn more about the different big data analytics tools and techniques available.
Provides a good overview of Hadoop, but does not cover Bigtable. It good resource for those who are new to Hadoop or who want to learn more about the different Hadoop tools and techniques available.
Provides a good overview of Spark, but does not cover Bigtable. It good resource for those who are new to Spark or who want to learn more about the different Spark tools and techniques available.
Provides a good overview of machine learning, but does not cover Bigtable. It good resource for those who are new to machine learning or who want to learn more about the different machine learning tools and techniques available.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/tsvkgh/monitoring
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Time
1 hours
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
This course belongs to a
collection
called
Google Cloud Database Engineer. It's comprised of 16 courses:
- Migrating to Cloud SQL from Amazon RDS for MySQL Using Database Migration Service
- Designing and Querying Bigtable Schemas
- Monitoring and Managing Bigtable Health and Performance (viewing)
- Enterprise Database Migration
- Cloud Spanner - Loading Data and Performing Backups
- Configure Replication and Enable Point-in-Time-Recovery for Cloud SQL for PostgreSQL
- Streaming Data to Bigtable
- Migrating On-premises MySQL Using a Continuous Database Migration Service Job
- Securing a Cloud SQL for PostgreSQL Instance
- Connect an App to a Cloud SQL for PostgreSQL Instance
- Migrate to Cloud SQL for PostgreSQL using Database Migration Service
- Deploy a Modern Web App connected to a Cloud Spanner Instance
- Creating and Populating a Bigtable Instance
- Cloud Spanner - Defining Schemas and Understanding Query Plans
- Cloud SQL for MySQL: Qwik Start
- A Tour of Google Cloud Hands-on Labs
Good to know
Teaches Bigtable administration in a hands-on manner
Suitable for those wanting to manage a Bigtable instance
Covers core Bigtable administration tasks
Taught by Google Cloud engineers
Taught through Google Cloud console
Requires familiarity with Google Cloud console
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